Design Informed: Driving Innovation with Evidence-Based Design

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design informed DRIVING INNOVATION WITH

EVIDENCE-BASED DESIGN

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ROBERT M. BRANDT GORDON

H. CHONG

W. M I K E M A R T I N

design informed design informed DRIVING DRIVING INNOVATION INNOVATION

WITH

WITH

EVIDENCE EVIDENCEBASED

BASED

DESIGN

DESIGN

ROBERT M. BRANDT, AIA GORDON H. CHONG, FAIA W. MIKE MARTIN, FAIA, PhD

John Wiley & Sons, Inc.

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This book is printed on acid-free paper. o Copyright © 2010 by John Wiley & Sons, Inc. All rights reserved. Published by John Wiley & Sons, Inc., Hoboken, New Jersey Published simultaneously in Canada No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 646-8600, or on the web at www. copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at www.wiley.com/go/permissions. Limit of Liability/Disclaimer of Warranty: While the publisher and the author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor the author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. For general information about our other products and services, please contact our Customer Care Department within the United States at (800) 762-2974, outside the United States at (317) 572-3993 or fax (317) 572-4002. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books. For more information about Wiley products, visit our web site at www.wiley.com. Library of Congress Cataloging-in-Publication Data Brandt, Robert, 1948– Evidence-based architectural design : case studies of applied evidence / Robert Brandt, Gordon H. Chong, W. Mike Martin. p. cm. Includes index. ISBN 978-0-470-39562-2 (cloth) 1. Evidence-based design. I. Chong, Gordon H. II. Martin, W. Mike. III. Title. IV. Title: Case studies of applied evidence. NA2750.B65 2010 720.1—dc22 2009049257 Printed in the United States of America 10 9 8 7 6 5 4 3 2 1

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Contents Preface

vii

Acknowledgments

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Chapter 1 Transformation

1

Chapter 2 Models, Simulation, and Data Mining Background and Context

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Interviews of Experts and Case Studies William Mitchell, MIT Media Lab

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17

Susan Ubbelohde and George Loisos

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William Sharples and Christopher Sharples, SHoP Tom Wiscombe, EMERGENT Chris Luebkeman, ARUP

11

70

93

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Phillip Bernstein, Autodesk

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John Kouletsis and Barbara Denton, Kaiser Permanente 139 Martin Fischer, Stanford University CIFE

Lessons Learned

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Chapter 3 The Social Sciences Background and Context

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Interviews of Experts and Case Studies Andrew Laing and David Craig, DEGW Joyce Bromberg, Steelcase Kevin Powell, GSA

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Paco Underhill, Envirosell

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John Zeisel, The HearthStone

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Sherry Ahrentzen, Arizona State University

Lessons Learned

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228

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CONTENTS

Chapter 4 The Natural and Physical Sciences Background and Context

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Interviews of Experts and Case Studies Sheila Kennedy, Kennedy and Violich

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James Timberlake, Kieran Timberlake

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Vivian Loftness, Carnegie Mellon University Edward Arens, University of California Gail Brager, University of California Fred Gage, Salk Institute

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261

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272

Esther Sternberg, National Institute of Mental Health

Lessons Learned

276

281

Chapter 5 Putting It All Together

293

Chapter 6 The 2005 Latrobe Fellowship

307

Chapter 7: Applying What We’ve Learned

321

Index

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Preface

A QUIET REVOLUTION IS UNDERWAY, one that could change the practice of architecture for years to come. It isn’t being trumpeted at the design awards ceremonies, yet it is about design excellence. It hasn’t been widely embraced by the profession but it is relevant to all design professionals who wish to remain relevant. Corporate and institutional architects and interior designers will only thrive if they know how to create places of long-standing value to their clients and communities. This revolution in the way design is practiced is the means to ensure that level of design quality.

The time has come to move on from this self-limiting approach. Picture this instead:

The genius of architects is their ability to imagine building form and then give physical structure to their musings. Architects should never relinquish this mastery of art and technology; it defines them as professionals. The question is how even greater and more sustainable beauty and utility can be created. The revolution that is gently but inexorably changing architecture looks to science as the means to better design outcomes. Architects and other design professionals typically depend on intuition and personal project experience to make design choices. That works at some level but is limited by the self and the past. New things might be tried but there’s no basis to predict how well they’ll work, if the only criteria come from the designer’s prior experience.



Using a computer simulation, you discover a way to reduce your client’s space program by 30%. They reinvest part of the capital budget in an upgraded design and use the rest of the savings to do a project they otherwise couldn’t afford.



You’ve claimed that you can help your client increase productivity through some creative new design ideas, but they need data to convince their stakeholders to change what they’re used to. By providing compelling evidence to back up your claims, you succeed in getting approvals and move forward with some breakthrough design concepts.



Bio-medical research connecting daylight and health convinces your client, a hospital administrator, to build a narrower footprint building. You design a place that is enlivened by light and views, instead of an artificially lit, enclosed space. Patients and staff thrive and you’ve aided the healing.



Prototyping demonstrates innovative ways to use a metal skin. You use the test data to design a unique building form with extraordinary beauty and free expression.

The vision of what might be seems unlimited. Aesthetics, experience, sustainability, cost reduction, improved

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P R E FA C E

operations, well being….Designers can break through and do great work. All that’s needed is evidence to understand how specific design strategies might affect building performance. With evidence, we can predict and convince. Evidence-based design (EBD) is slowly changing how the design is practiced by design professionals and valued by their clients. It can improve the quality of design, especially in ways that benefit clients. However, EBD is also often misunderstood. Many architects think it will be overly prescriptive, rather than informative. Others who like the notion don’t fully grasp how to assess if evidence is strong or weak, and in what contexts the evidence is valid. This book is about the authors’ journey to find an approach to EBD that will co-exist with design creativity, increase innovation, and lead to improved building performance. Think of this as “Informed Intuition”—a healthy mix of the professional’s instincts and a broad, deep knowledge base from many sources. Along this journey, the authors encountered a number of experts and asked them to share their experiences and perceptions related to EBD. 1. Is the use of empirical evidence appropriate to design? If yes, under what circumstances and to what benefit? How does the use of evidence in design differ from that in other professions? 2. What constitutes evidence for design? How much is enough and how rigorous does it need to be? What methodologies—qualitative or quantitative—are required for it to be credible and defensible in informing design decisions? 3. What are the appropriate types of evidence and how might they be obtained? Are there successful precedents? What architects are doing it with great outcomes and can others also succeed in spite of time and budget constraints? Does the search for evidence, in lieu of pure instinct, diminish creativity?

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4. Will my practice improve if I adopt an evidencebased design approach to my projects? Is it for all types of firms? Several major themes emerged from this dialogue. Considered together, they describe an approach to EBD that’s both broader and more demanding than much of what’s in the current literature. There are many sources of data that might serve as evidence of design impacts. Post-occupancy evaluation surveys, often cited in discussions of EBD, is only one method for seeking evidence. Computational, social and natural sciences are rich resources. This book addresses all three. Strength of evidence (i.e., how much you can rely on the data to predict design impacts on your projects) is often not understood by designers, yet it is critical to applying evidence reasonably. Architecture lacks the research standards and protocols necessary for widespread development, application, and dissemination of research that could serve as evidence. As EBD develops, design education will need to better prepare professionals to appreciate research quality standards and all practitioners will need to hone their capabilities to assess what evidence might be used in making better design choices. Knowledge gained from an assessment of one project’s performance outcomes might have great potential value for other projects. However, without shared research standards, we can’t tell if that knowledge is of good quality nor if it can be generalized from one project context to another. The design professions also must support knowledge sharing far better. Our current systems to categorize, store, and retrieve data/ knowledge are few and far between. As our concerns for human response, behavior, and performance become more complex; environmental impacts more important; and fiscal resources more constrained, clients and communities are demanding

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more understanding of the value of design. Will design professionals be able to make a strong case for highperforming buildings and the ability to use design as a lever to achieve high performance? To remain relevant, architects must…and can with the right evidence to back up these assertions of added value. This book, one in a series by John Wiley & Sons that explores the concept of evidence-based design, is not about being a researcher; it is about being a better designer and a better architect who uses evidence as one approach to informing design. The book raises as many questions as it answers but it reveals sources of evidence both internal and external to architectural practice, and addresses how and why to apply them. You won’t find the ten steps to developing an evidenced design practice but you will find ideas that will stimulate your own thinking about the use of evidence in your design practice. The revolution won’t stop but every practitioner can have a voice in shaping how the design professions evolve. In this book, the authors share some ideas about what the use of evidence might mean for a design practice…how evidence-based design might expand your horizons, bolster innovation, and reposition you to become your client’s trusted advisor. Simply, the book is about where we might take the journey from here with a somewhat different dialogue than we’ve heard before.

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This book will help the practicing architect, client, and students of architecture through three types of learning. 1. Background on research methodologies: Intended to help you decide what is most appropriate for your application. Discussion of these methodologies is intended to be absolute but rather provides a broad context of possibilities for your consideration, as you consider your own needs. Our book does not support a single, prescriptive approach. 2. Application examples: Interviews and case studies are intentionally diverse in scale, approach, and research methodology so that you can learn, analyze, pick and choose, and envision how they may apply to your design question, skill, and resource. There is not a case of “one size fits all,” but rather, many approaches from which to choose the most appropriate. The examples illustrate actual use in current project work and specific types of research being conducted for application. 3. Thoughts about the future: When speaking about the use of evidence, many architects are fearful that the process will inhibit creativity. Our observations challenge that fear and open a dialogue about expanded possibilities as architecture joins other valued professions by integrating the best of the traditional intuitive approach with an empiricism that enhances design outcomes.

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Acknowledgments With thanks!

Special Thanks

We wish to thank The American Institute of Architects, College of Fellows for awarding the 2005 Latrobe Fellowship to Chong Partners Architecture, the University of California, Berkeley, and Kaiser Permanente. This two-year study formed the genesis of our thinking and permitted the research for this publication to ask a higher level of questions in our search for innovation and excellence.

With special thanks to Professor Michael Bednar, of The University of Virginia, who encouraged me to believe that Design and Behavior really can be One; Michael Gulash and our colleagues at Intuit, who patiently supported my Work: Book Balance; and my sister, Pamela Robin, who told me I could write, before I could. ROBERT BRANDT, AIA

With appreciation to John P. Eberhard, FAIA, for introducing me to the possibilities of neuro-architecture as a means to inform design; to The Academy of Neuroscience for Architecture for sustaining that interest and to my wife, Dorian, for encouraging my intellectual curiosity.

We also wish to thank the many brilliant individuals who generously shared their thoughts, time, and experiences with us. This publication is a reflection of their many great ideas and thoughts. Lastly, we thank John Wiley & Sons for inviting us to do this work, which we believe will add to a greater body of professional knowledge for the betterment of the profession and the public we serve.

GORDON H. CHONG, FAIA

I dedicate this book to my wife, Pat, and our two daughters, Brandi and Cally, for offering hope, encouragement, caring, and love for all things that matter. W. MIKE MARTIN, FAIA, PHD

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1

Transformation

ARCHITECTURE STARTS WITH VISION AND PASSION—VISION OF A PLACE THAT WILL INSPIRE OUR SENSES AND A PASSION Practice Today

Practice Near Future

Practice Far Future

TO CREATE IT. THIS BOOK IS ABOUT TAKING THAT SPATIAL, GEOMETRIC, AND AESTHETIC STARTING POINT AND EXPANDING IT TO EMBRACE BUILDING AND HUMAN PERFORMANCE.

Formalistic Attributes

Building Performance

Human Performance

Education Today

Education Near Future

Education Far Future

Evidence

Evidence

Evidence

Form/Geometry Intuitive/Experience Qualitative Spatial Language

Sustainability Quantitative Model, Simulation Data Mining

Human Experience Qualitative Quantitative Neuroscience Social Science

Figure 1.1 Evidence Development and Application

The agenda is a TRANSFORMATIVE one. It builds on what architects do best—make form. Our education as architects is dominated by a language of spatial principles: shape, scale, color, texture, pattern, symmetry, balance, accent. These are the things we are taught and should always be central to what we design. The question is “Are they enough?” Our answer is “No!” This is a very exciting time for our profession. Every day, more evidence is being created that demonstrates the power of architecture to affect human experience and environmental outcomes. Extraordinary innovations in building performance and materials science are now also possible due to evidence-producing processes. Today’s technologies and challenges feed opportunities to refine, expand, and improve our abilities to make form. In the transformation we envision (see Figure 1.1), professional practice will still be based on our values and traditions as architects; yet our aspirations and capabilities will go beyond designing only spatially inspirational buildings. In this future, in addition to form-making, design professionals will positively influence human well-being and effectiveness and will contribute to the health of our planet. For this to be our future, our profession must acknowledge

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that the means to this end is being able to predict design outcomes. We must be able to rely on evidence to anticipate the effects of our work. In order for this information to help us make a high impact, positive design choices must be transparent, accessible, understandable, and applicable. What follows in this book is a journey to define what such evidence might be and how we might develop and apply it.

“Evidence for Design” or “Evidence or Design?” During a 2008 interview on National Public Radio, New York Times political commentator David Brooks referred to some of the people being considered for his administration by then President-Elect Barack Obama as being “evidence-based.” This characteristic, according to Brooks, created potential bridges between Obama and people with sometimes divergent opinions. Disciplined consideration of the facts (evidence) enabled them to make reasoned decisions, with the advantage being that they would bring multiple perspectives into consideration to make better choices. Since his election, President Obama has often referred to his reliance on knowing the facts before he makes decisions. While it remains to be seen if an evidential process or blind ideology will prevail in our political system, we’ve seen the power of evidence to break down inertia and enable new ideas to advance. If it plays on Pennsylvania Avenue, why not in Architecture and other design professions? Design is often cast as an act of intuitive creativity, uniquely owned by the designer and set in a context of ambiguity and uncertainty. Many architects shroud their decisions under a cloak of mystery, inaccessible even to their clients, who are expected to approve their designers’ recommendations through acts of faith. The idea of making transparent the basis on which design decisions are made is unsettling to many designers. They don’t think of evidence as a freeing agent.

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Instead it’s considered an obstacle to simplifying an essential design parti. With this mindset, rather than “evidence for design,” there is seemingly a choice between “evidence or design.” Fear of evidence isn’t because designers haven’t used it before. Every design decision, no matter how small or complex, is informed by evidence found in experience, drawn from intuition, or (less often) based on rigorous processes of inquiry. THE CONTINUUM OF EVIDENCE, WEAK AND STRONG, SURROUNDS US. Architects are used to materials performance specifications, codes that were developed based on testing and performance history, and equally comfortable drawing upon their knowledge of their own previous work. The issue is that most architects don’t think of the current design process as being evidential, whether it is or not. Yes, they use technical data and reflect on other projects; but they feel in control of the process. When that sense of control is lost, such as when a program is very complex and constraining, or a client doesn’t accept the designer’s preferred concept, the work seems less creative and personally satisfying. Even more troublesome, when the evidence comes from disciplines beyond architecture, it might be fascinating, but there’s no clear way to directly apply it. Once again, a choice is set up between evidence and design. SIMPLY PUT, MANY DESIGNERS FEEL THAT THE NOTION OF “EVIDENCE” IS FOREIGN TO THE DESIGN PROCESS THEY KNOW. Over several years of looking at attitudes about evidence-based design (EBD), the authors have found a number of consistent concerns (and myths). 

EBD is too scientific. Creativity is not all about facts. The process of creating is subjective and inductive. It starts with a spark of inspiration. Science is deductive and all rational.  EBD is reminiscent of a legal process. There are rules about how to consider evidence and decisions must follow the rules. It’s about right and wrong. Personal judgment is diminished.

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EBD is prescriptive. It limits options and stifles innovation.  EBD is too expensive and time-consuming for most practitioners.  EBD requires sharing of knowledge that is better kept proprietary for marketing purposes.  EBD uses facts to evaluate design success. This exposes our work to criticism and could harm our relationships with our clients or even expose us to legal problems. To what extent are these concerns based in truth? Are there benefits to EBD that make it worthwhile, even if it demands a new mindset? Is there a model for evidence-based practice that is specifically right for the design professions?

Not As It Seems The first step in getting past the myths and fears is deciding if EBD would be of value. Is there even a good reason to rethink how we design? THE VALUE OF EBD CAN ONLY BE UNDERSTOOD IN THE CONTEXT OF THE VALUE OF DESIGN AS A CONTRIBUTOR TO SOCIETY.

Architectural form that delights has great value. But more is possible. The public may be enamored by a structural tour de force or a landmark design that captures their spirit, but when they put on their client hat, they know they are responsible for delivering value to their organization or institution. Rarely will a new design for a hospital, school, or office building be judged by the client on the basis of aesthetics alone. The value of the facility will be attributed to how well it helps attract and motivate talent, support the needs of customers, and achieve financial targets. Will the design foster healing, learning, collaboration, creativity, productivity, or profitability? Will performance outcomes be enhanced by the design or is it merely a beautiful expense? WITH THE RIGHT EVIDENCE, DESIGN CAN DELIGHT AND SERVE.

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Intuitively, many designers and their clients sense that students learn better, patients heal faster, and office workers produce more in certain types of environments; or, in fact, that the physical environment can influence human well-being and performance. There is mounting evidence that we can influence organizational performance through design but rarely is evidence used to guarantee those outcomes. Why? In part, we don’t have access to credible, applicable evidence, or we aren’t aware of how to find it. Most of us aren’t educated as researchers and can’t tell whether what we read is good evidence or misinformation. (There’s no TRANSPARENCY about how it was developed and the qualifications of the person who developed it.) Research takes time. If a client doesn’t demand it, why do it? Then there are the fears: loss of control and creativity. THINGS ARE NOT AS THEY SEEM, IF ONE THINKS THAT THE PROFESSION CAN CONTINUE AS IT IS WITHOUT CHANGE. Clients do expect more than traditional form-

making. They are accountable to their organizations to provide more. Designers who offer more are hired; those who deliver more are hired more than once. Designers who don’t accept their clients’ mandate to deliver functional and financial value have been finding their roles diminished. We must reevaluate how we design and change the tide of how we are perceived. If we can back up our design recommendations with credible evidence, our judgment will appear more dependable and our recommendations will more likely produce the results we’ve promised. Whether that’s merely fulfilling our professional obligations or enhancing our relationships and quality of work is an interesting argument. However we view it, for the design professions to remain viable, the use of evidence that will help us satisfy our clients’ needs on their terms and create places that really work well for people is inevitable.

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Things are also not as they seem in terms of the fears we discussed previously. Creativity does exist in science. Intuition plays an important role. Professional judgment will always be needed. Our past proves that we can incorporate evidence without the design process becoming prescriptive. That’s because evidence is not prescriptive. Just as in the legal context, evidence only informs judgment, making it better. Anyone who has served on a jury knows that deliberations are anything but black and white. Lastly, sharing knowledge and learning by doing are ways we can access more evidence, which is indeed sometimes hard to find without great time and effort.

Time for a Makeover In recent years, a number of design professionals have embraced the notion of evidence-based design practice, as a model for rigorously seeking or conducting research to predict how well specific design proposals will support desired performance outcomes or conversely, inadvertently cause harm. We’ve tried to learn from similar movements in other professions (i.e., medicine, education, engineering) and we’ve questioned the relevance of lessons from those fields to the architectural profession. We’ve challenged both the quality of nonscientific evidence and the applicability of scientific method. THE HEALTH OF OUR PROFESSION, MEASURED BY THE PERCEIVED AND DELIVERED VALUE OF OUR SERVICES, DEPENDS ON OUR EMBRACING OUR CLIENTS’ MANDATES TO PROVIDE PHYSICAL ENVIRONMENTS THAT SUPPORT ORGANIZATIONAL PERFORMANCE OBJECTIVES. IN THIS WORLD, THE IMPACTS OF DESIGN ON THE PEOPLE WHO USE THE ENVIRONMENTS MUST BE ANTICIPATED AND RESOLUTIONS PROPOSED THAT INCLUDE VALIDATION THAT DESIGN WILL FACILITATE PROMISED OUTCOMES.

and share what we learn across the profession, just as we have traditionally worked together to create and document technical data in codes and standards that provide performance standards for determining appropriate action. Much can be learned from program analysis, client web surveys, and other techniques that are project-specific based. But evidence-based practice must ground itself in broader, deeper data, feasible only from a system that enables us to draw evidence from sources beyond the individual project. PREVAILING LACK OF KNOWLEDGE OF RESEARCH METHODS IS ANOTHER HURDLE TO JUMP. Few design professionals are trained as researchers or even sensitized to critically evaluate research quality. Our academic settings and professional practice rarely place value on rigorous methodologies for creating and interpreting the information used to inform design. Even the basic steps of scientific method—define the problem, create a hypothesis, test, and document—are seldom followed by designers. Hopefully, the profession will make clear to our educational system that we demand some level of research knowledge as part of basic design education, because it will be as important to our professional success as design and technical capability. In the interim, we can share experience to establish a baseline of professional credibility in EBD. All of this dialogue (with and without agreement) makes this an exciting time to develop a forward-thinking approach for evidence-based practice, including creating the infrastructure to produce and archive evidence. The profession has progressed to a point where there is interest and awareness of its potential, despite the hesitancy as to how these future opportunities will influence practice. There have been some successes that have established a foundation for additional research. AHEAD OF US AS A PROFESSION IS THE NEED

EBD CAN DO THIS.

TO ESTABLISH A SET OF STANDARDS AND GUIDELINES

Many proponents of evidenced-based practice agree that we need to look beyond our individual practices

SYSTEM FOR CREATING, ARCHIVING, AND DISSEMINATING

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TO ASSURE HIGH-QUALITY EVIDENCE AND AN EFFECTIVE THIS EVIDENCE.

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It is our judgment that this will be the next major transformation of our profession. It will create a context for significant multidisciplinary dialogue and collaborative work between the academies and the profession. These opportunities will excite the research-oriented professionals more than others but we will share the benefits of transformation. But it is a time for our total profession to engage its future.

What Will It Look Like? William Sackett, a proponent of evidence-based medicine, identifies a core principle of evidence-based medicine as “the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients.” The practice of evidencebased medicine, according to Sackett, “integrates individual clinical experience with the best available external clinical evidence from systematic research.” A similar definition of EBD has been proposed by Kirk Hamilton. “Evidence-Based Design is the process of basing decisions about the built environment on credible research to achieve the best possible outcomes.” (The Center for Health Design.) Conceptually, EBD advocates a balanced integration of the skills and experience of the design practitioner, the client’s needs, and critically assessed evidence of various types. THESE INCLUDE EVIDENCE GROUNDED IN RIGOROUS SCIENTIFIC METHODOLOGY AS WELL AS A CONTINUUM OF LEVELS OF EVIDENCE INCLUDING PERSONAL EXPERIENCE AND INTUITION. Art and science

of designing are both respected but interpreted each according to its strengths and weaknesses as predictors of design impacts on human outcomes. Both are central to making these outcomes transparent to all of the stakeholders. Perhaps the most important lesson for EBD from evidence-based medicine is the notion of “strength of evidence.” By definition, architects integrate various

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types of evidence—cultural, technical, and artistic. In the practice of architecture, it’s unlikely that the act of designing would deliberately avoid valuable inputs, or at least so it would seem. To the contrary, architects and other designers frequently claim to care about the outcomes of their work. They say they create hospitals that heal, schools that help students learn, and offices that enhance productivity. Standards vary across and within disciplines. Some give credibility to multiple types of evidence, developed with various methods. Others show a bias for rigorous, systematic, and objective methods, such as randomized experiments—the “gold standard” of scientific research. Lastly, the practice of EBD must be based on transparency. Design practices often try to use what we learn for competitive advantage. They are reluctant to be scrutinized. In contrast, the culture of peer review that science embraces ensures quality improvement. Selfconducted research is sometimes publicized but the methods by which data was collected, variables controlled, results analyzed, and findings interpreted are seldom fully revealed. Without transparent, clear, and complete communication, it’s inevitable that findings will be taken out of context, misapplied, and overgeneralized. All of these ultimately serve clients badly and discredit the process of using evidence. Designers don’t have to become researchers but they do need to understand the basics of how to use research correctly. With greater transparency, practitioners will have greater access to useful knowledge and the ability to effectively judge if the knowledge applies to their project.

The Authors’ Journey We set out on a journey to explore our theories about evidence-based design in the context of work being

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done by leading experts. We started with some assumptions and questions: 









Many research methodologies have merit in their respective disciplines. Our assumption is that design can be informed by many of these. The work discussed in the following chapters explores how different methodologies can be used effectively to address different types of design questions. We need to go beyond only postoccupancy evaluations of our own projects to achieve the richness of the examples covered in this book. Are some methodologies better suited to most questions that typical design practitioners confront? Some research requires depth of knowledge, time, and funding that most projects can’t sustain. The work in the following chapters makes evident that we can develop some useful evidence during projects that will be sufficient to spark an innovation or provide assurance that client needs are being addressed. Other research, also of value, will have to be conducted outside of project timelines and fees but can then be applied to great benefit. We’ve observed a disconnect between some research and the evidence designers need. We’ve presented examples of architectural research that was focused on application and also were reliable in predicting how specific design elements might impact outcomes. There is a need to expand beyond our associations with architects, engineers, and contractors to interdisciplinary collaborations that would bring new research methods to the production and translation of evidence for application in design. The work in the following chapters illustrates the benefits of collaboration across disciplines. Our premise is that it’s fallacious to depend upon intuition and experience alone. Doing so does not serve our profession well, especially because few architects obtain systematic feedback on actual

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performance outcomes. There is limited systematic knowledge transfer from project to project or from project to generalized knowledge into the intellectual capital of the profession. We’ve sought and found examples of other ways to develop the knowledge base.  Once validated evidence is developed, there needs to be an organizational and systematic infrastructure created to store, archive, and provide openaccess to individuals, firms, and the profession as a whole. This issue is discussed by experts in the interviews that follow.  There is a need to establish clear and accepted standards and guidelines for what constitutes “credible evidence,” how it is nested in terms of other related evidence, and what are the methods and processes for its creation and application. The work we found on our journey loosely falls into three large categories as a framework for discussion. The focus here is how these three categories of evidence could enhance building performance and human experience, as well as enrich the formal process of designing and making physical environments. Some subcomponents of each of these categories have evidence that is robust and is already used regularly. Others are quite new and are only beginning to have an impact on design decision-making as guarantors of performance outcomes. Still others are only in the incubator stage but show great promise. 1. MODELING, SIMULATION, AND DATA MINING Modeling is a set of activities that structures innovation, collaboration, and creativity in design by creating physical and virtual models of objects under investigation by designers. This activity is guided by a hypothesis or question that enables the designer to test components or systems as a thinking-by-doing activity. It is an iterative process that provides the framework for testing performance of materials, construction strategies, and other physical phenomena at various scales including

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scaled models to full-size representations. This process is sometimes referred to as reflective practice—the working through of a design question by making artifacts that represent the intended outcomes, rather than just thinking about the challenge. This approach points out that physical action and cognition are interconnected. Successful designs result from a series of conversations with various phenomena, with the conversation being between the designer and the medium of design, virtual drawings and models, paper, clay, chipboard, and real materials, constantly making and testing the outcomes to observe performance indicators. Simulation is a process for understanding the interactions of the parts of a system and the system as a whole. A system is an entity, which maintains its existence through the interactions of its parts or components. A model is a simplified representation of the actual system to promote the understanding of the performance of the parts in the context of the whole system. Since all models are simplifications of reality, there is always a trade-off as to what level of detail is included in the model. Too little detail risks missing relevant interactions. Too much detail may overcomplicate the model, making it difficult to understand the nature of the interactions. Simulation is generally referred to as a computational version of a model. Simulations are generally iterative. One develops a model, simulates it, learns from the simulation, revisits the model, and resimulates the condition until an adequate level of understanding of the relationships of the parts to the whole is reached. Critical to both of these technologies is the willingness of the designer to create a hypothesis about an artifact to be tested, either physically or virtually, knowing the perception of the artifact is incomplete or maybe even wrong. The iterative process of testing and evaluation, modeling, or simulating transforms an artifact toward some specific articulated performance outcome, use/ activity, light, behavior, etc. This process is not about rationalizing an idea or a vision, but one of transforma-

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tion of ideas and visions to meet specific performance outcomes. The more rigorous and transparent the performance outcomes, the more transparent the design process will become connecting the artifact to evidence that supports increases in performance. Data mining is the extraction of hidden relationships from large databases. This is a powerful new technology with great potential in helping organizations focus on the most important information in their data warehouses—their organization’s intellectual capital. The literature refers to this process as “super crunching.” The data used to capture and record these found relationships comes from many diverse sources (i.e., personal experience, completed projects records and documentation, and other artifacts developed to support organizational activity). This process of data crunching can suggest predictive future trends and behaviors, and the identification of important questions or hypotheses about future activities and directions within a project or organizational setting. This process of mining data allows organizations and individuals to make proactive and evidence-based, knowledge-driven decisions rooted on these predictive futures. Designers and their associated professions—engineering, construction, planning, and other design entities—have large sets of data, usually project-specific, but what is missing is the infrastructure to access and utilize this data in a longitudinal sense. Data mining and its associated tools provide a platform for creating this new infrastructure with the capacity to capture, share, understand, and utilize the existing data across and within our professions. 2. SOCIAL SCIENCES The use of evidence gained through study of the social sciences provides understanding of human behavior through scientific explanation. The process explores human desires, preferences, attitudes, perceptions, and motivations. Of most relevance to design are sociology and psychology. The discipline of environmental

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psychology specifically addresses the convergence of the two fields but other social science research, such as developmental and cognitive psychology, can enrich a designer’s understanding of the behaviors to be supported—or transformed—by the environment. Social science contributes to informed design by providing methodologies with which place-behavior relationships can be studied, as well as knowledge about why people behave as they do and why they might respond to physical surroundings in predictable ways.

The natural sciences, with a foundation in biology, have had less of a direct impact on architecture than have the physical sciences. However, that’s about to change! Within the past 25 to 30 years, the field of Neuroscience has blossomed and has stimulated an interest by neuroscientists in understanding how, why, and what parts of the brain respond to environmental stimuli and experiences, including light, sound, scale, proportion, perspective, and the like—all tools used by architects in design.

3. THE PHYSICAL AND NATURAL SCIENCES

The focus of neuroscience and the cognitive sciences has unlocked a new domain for understanding human performance in physical settings. The research that is emerging from the disciplines of neuroscience and the cognitive sciences is providing new directions for developing and utilizing research evidence for use in an evidence-based design practice. By capturing the mental processes from scans of the brain, as a person moves, sees, hears, and experiences motion in space, one can correlate physiological measures with issues of stress, satisfaction, and emotion. This understanding can then be used as evidence to predict the impact of physical spatial attributes on human performance. This is a new arena for both the production and utilization of evidence; and it holds great promise for the future of the design professions.

Within the sciences, the physical and natural sciences are often seen as a single category that is contrasted to the social sciences. While the physical and natural are considered to be “hard sciences,” using similar research bases and methodologies, they are in fact two very distinct sciences when related to architecture. The physical sciences, especially physics, have a long history that provides a foundation for architectural design of structures, mechanical and electrical systems, and the process of “making.” Today, the physical sciences continue to provide a rich area of research in issues related to building performance. In many instances, the incentive for this research is being driven by a global commitment to the design of more sustainable buildings that reflect energy-conserving approaches to design, improved building systems, and creation of new and innovative sustainable materials. On a global scale, research and advances in building sciences are being driven by a need for more advanced technologies to build taller structures with new systems and materials or new environmental technologies to respond to harsh geographic conditions. Sources for both of these advances come from research groups related to academic institutions, private industry manufacturers, and architectural practitioners seeking more responsive design approaches.

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If an understanding and collaboration with physical science represents the sophistication of tools available to us today, then neuroscience represents an equally sophisticated but yet untapped future for collaboration.

The Road Well Taken THE DIALOGUE THAT WILL CLARIFY A DIRECTION FOR THIS NEW INNOVATIVE AND FORWARD-THINKING FUTURE IS CRITICAL, AS IT WILL DEFINE OUR ROLES AS DESIGN PROFESSIONALS. IT WILL ALSO SET THE AGENDAS FOR OUR ACADEMIES, WITH WHICH THEY WILL ESTABLISH

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GUIDELINES FOR THE NEXT GENERATION OF EVIDENCEBASED PROFESSIONALS.

The primary goal of this book is to focus on the future of evidence-based practice and the mechanisms that would produce a new direction for the future of design professionals. The book does not look back at where we have been, but intentionally looks forward to help chart a map that moves into that future. The chapters that follow document the richness of work currently being undertaken by researchers and practitioners in a variety of fields that are establishing that new future. The people that were selected are individuals who focus on innovation by utilizing twenty-first-century technologies, methods, and disciplinary content to explore this new frontier. The questions they are asking, the methods they are utilizing, and the outcomes they are producing, are making major contributions to redefining the landscape of design, architecture, and construction. In the majority of cases these are people who are working on projects that are organized around interdisciplinary teams or are creating new transdisciplinary organizations. They are applying new computational technologies, scientific discoveries, and organizational agendas to resolve the challenges of the day—sustainability, human performance, environmental degradation, and transportation alternatives; at the same time as they are developing new models of work—innovative research methods, fabrication technologies, and performance-predictive tools. The next three chapters document the interviews with the selected individuals. Each interview was guided by a set of eight questions. These questions represented only the beginning points of the dynamic process of engaging each of the interviewees in a dialogue about their work and how evidence is a major component of their process of working on critical design issues. These base questions helped facilitate further discussion about the interviewees’ contributions to specific projects and to an infrastructure for producing evidence.

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The base questions listed below were only launching points and the detailed questions in each interview were a means to bore deeper into the interviewees’ work and process.   

    

How do you use research in your work and how does it inform design? How is evidence produced and how does evidence influence your work? What are the core methods, skills, and values needed to do evidence-based design or to produce evidence in your practice or institutional setting? Does the use of evidence inhibit or enhance the nature of your work? How does interdisciplinary collaboration play a part in your work? How much evidence is enough and what makes it credible? How are the outcomes of your work translated so that they can be generalized and used by others? From your perspective what should be the future models of education and practice to support an evidence-based practice?

In some cases the interviews are followed by case studies that address four important questions: 

What was the research question? What was the research method?  What were the research outcomes?  How did they inform design? 

Following the three chapters about the three categories of evidence-based design are two major case studies. One is of the new California Academy of Science and the second is a summary of the outcomes from the 2005 College of Fellows of American Institute of Architects Latrobe Fellowship. The first case study documents an important new building where formal visions and ideas are supported, refined, and strengthened by bringing evidence from other disciplines to increase

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building and human performance, and enhance the human experience through architecture. The second case study, The 2005 Latrobe Fellowship, was awarded to Chong Partners Architecture (now Stantec Architecture), Kaiser Permanente, and the University of California, Berkeley, to explore the use of evidence from the social and physiological sciences to better understand human response to design, and thereby make better design decisions. The research focused specifically on health-care environments and the question of whether design can aid healing. (Reduced “time to heal” and medical errors, in turn, increase hospital financial performance.) Credible evidence of design impacts on healing and errors does exist; but so do assertions based on very weak indica-

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tors. The Latrobe research sought a model for creating evidence that would be reliably strong. Chapter 6 summarizes the processes and outcomes of that research effort conducted in a collaborative format. IT IS CLEAR THAT INNOVATION IS ALL AROUND US. EXTRAORDINARY EFFORTS TO BETTER DESCRIBE AND APPLY EVIDENCE ABOUT THE RELATIONSHIPS BETWEEN DESIGN AND HUMAN PERFORMANCE ARE BEING UNDERTAKEN BY PEOPLE FROM VARIOUS DISCIPLINES AND WITH DIFFERING PERSPECTIVES AS ILLUSTRATED IN THE INTERVIEWS.

THESE EFFORTS WILL MOVE FORWARD THE ACCEPTANCE OF EBD AS A PROCESS; WILL ENLARGE THE BODY OF KNOWLEDGE AVAILABLE TO THE PROFESSION; AND WILL IMPROVE OUR ABILITY TO ANTICIPATE, IF NOT PREDICT, WAYS TO USE DESIGN TO ENRICH LIVES.

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Models, Simulation, and Data Mining Background and Context Introduction PHYSICAL MODELS, PROTOTYPES, AND TESTING HAVE LONG TRADITIONS IN THE DESIGN PROFESSIONS. They have been pivotal activities in innovation, collaboration, and creativity when creating design outcomes, and testing performance capacities. Our first evidence of this type of formal design activity was in the PHYSICAL MODELS BUILT AT FULL SCALE AND TESTED TO FAILURE—A PROCESS OF TRIAL AND ERROR UNTIL FAILURE DID NOT RESULT. The great pyramids, the Roman coliseums, temples, as well as many of the wonderful Gothic cathedrals were designed and built this way.

Overview of Models, Simulation, and Data Mining Over the past centuries, this process of designing changed based on advances in technology, new building materials and construction methods, and major changes in how designers organized their work processes. The introduction of new tools, such as parametric drawing and perspective and physical scaled models, influenced these changes. In recent years, however, the use of physical models and prototypes has taken on new meaning and now represents a source of many research investigations that are either project-specific

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or focused on the larger agendas of understanding either subsystems or whole building performance. Historically, modeling and prototyping has been carried out using physical artifacts that could be tested by external processes, stress, heat transfer, lighting levels, etc. However, in recent years innovations in digital technologies have transformed this process. Now digital simulations are the primary medium for representing and testing design intent and design performance expectations. SIMULATION IS A TWENTY-FIRST-CENTURY TECHNOLOGY FOR UNDERSTANDING THE INTERACTIONS OF THE PARTS OF A SYSTEM, AS WELL AS THE SYSTEM AS A WHOLE, THROUGH DIGITAL REPRESENTATIONS OF THE DESIGN ELEMENTS IN QUESTION AND THE RESULTING PERFOR-

being primarily related to building technology. In some cases, it is apparent that the professionals involved resist acknowledging any value to using data/evidence to inform their design activities, as they feel it gets in the way of their creativity. In a recent interview with Phil Bernstein, Vice President of Autodesk and a faculty member at Yale University, he noted that “it is clear that the development of new technologies for organizing, representing, and analyzing data will continue to outpace the availability of data.” This presents us with a significant challenge. Our challenge in the AEC industry is not the availability of data, but to have an infrastructure that creates access to data that designers can understand, interpret, and act on to inform design and construction.

MANCE UNDER SPECIFIC TESTING SCENARIOS. Simulation

technology is a computational version of a model that has been created to study the implications of the defined interactions over time and in various contextual conditions. Simulations are generally iterative. First, a computational model is represented in an appropriate form—2D or 3D. Then, a model is run with simulated conditions that emulate real life forces to which the actual building might be exposed. Performance outcomes are established and evaluated; and the model is revised and other simulations run until an adequate level of performance outcome has been reached, based on the understanding of the relationships of the parts to the whole of the system under consideration. In the past, it was believed that one could get by with intuition and experience. The information age we now live in has substantially changed that view. Today the name of the game is “data.” Data-driven decisionmaking is central not only to our everyday lives, but to the future of most, if not all, professional activities. The architecture, engineering, and construction industries (AEC) are struggling to engage this agenda. Each of these professions has relied heavily on experience as the primary source of knowledge, skills, and values to inform their decision-making process; the exceptions

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The Influences of Physical Models, Prototyping, Testing, and Simulation on Architecture PHYSICAL MODELS AND PROTOTYPES ARE GROUNDED IN EXPLICIT OR IMPLICIT HYPOTHESES ABOUT DESIGN PERFORMANCE, ENABLING THE DESIGNER TO TEST THE RELATIONSHIPS BETWEEN DESIGN INTENT AND DESIGNOUTCOME PERFORMANCE. THE PROCESS OF THINKINGBY-DOING THROUGH A SET OF ITERATIONS IS HIGHLY RELEVANT TO CREATING ARCHITECTURE. The design studio, either in practice or in the academy, is the armature for establishing this type of culture for the process of making physical environments. Donald A. Schon (1983) referred to this type of thinking-by-doing as “reflective practice.” This form of practice frames a set of design conditions and evaluates the outcomes through “conversation” between the designer and the artifact that is being created. These informative interchange is facilitated by various media—paper, clay, sketches, physical systems, 2D or 3D simulation, and other representations by stimulating the designer’s thoughts with evidence extracted from the physical models or prototypes.. This evidence can be tacit and

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personal or have strong analytical foundations through rigorous scientific research. In either case, the physical models and prototypes reveal to the designer potential outcomes that could not have been understood without testing a physical or virtual representation of the built form being considered. Armed with this knowledge, the designer can make better decisions about the design. THIS PROCESS OF DESIGN AND EVIDENCE APPLICATION REQUIRES ITERATIVE CYCLES OF FRAMING A CHALLENGE—A HYPOTHESIS—AND MEASURING THE PERFORMANCE OUTCOMES RESULTING FROM SPECIFIC DESIGN INTENTIONS AND ACTIONS. The challenge of this

approach is that it is expensive and time-consuming to use, build, test, and modify physical models. The digital world has a solution for at least some contexts. Virtual models using simulation technologies are replacing some physical material models in the making of prototypes. The introduction of the digital 3D printer and laser technologies also has changed how physical models provide new and creative interests in prototypes as an outcome of design. NEW METHODS OF MODELING AND SIMULATION HAVE REVOLUTIONIZED THE AEC PROFESSIONS. This revolution

has changed the way we work and even the nature of the work we do. New simulation and modeling tools have changed roles, organizational boundaries, and work processes for architects, engineers and contractors. The infrastructure of the industry itself is shifting. With the adaptation of these new modeling and simulation tools, traditional inefficiencies and adversarial relationships are yielding to a redefined practice model grounded in multidisciplinary collaboration and information sharing among and across project and disciplinary team members. This new framework has been referred to as integrated practice delivery (IPD). Building information modeling (BIM) is a major element of this IPD practice model. BIM is a parametric, objectbased software, which simulates and models a three-di-

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mensional representation of virtual buildings, drawing from complex databases that include information about use, material, structure, energy usage, cost, scheduling, fabrication details, and formal and spatial conditions. At the present time, the technology of BIM is outstripping the availability of quality database information to inform the simulation and modeling outcomes (Bernstein interview, 2009). Much of this challenge is connected to the lack of an infrastructure within the design and construction disciplines and professions for creating, archiving, and sharing data. Put more simply, it is the lack of a research tradition in both the academy and in practice that underpins this challenge. BIM will fall short of its full potential to predict performance outcomes until evidential data becomes readily available to inform the models. Data mining and its associated tools provide a platform from which to construct a new infrastructure for capturing, sharing, understanding, and using existing data across our professions. Three major constructs must be clearly differentiated to understand the data mining process. Data is defined as any fact, number, illustration, or text that can be represented so it can be processed by computational methods. Information is the patterns, associations, or relationships among data points. Knowledge, on the other hand, is the acknowledgment of patterns and trends in informationinsightful data.

Models, Simulation, and Data Mining Modeling is a simplified representation of the actual system to promote the understanding of the parts to the whole system. A good model depends on how well it represents the relationship and understanding of the parts to the whole and the whole to the parts. Since all models are a SIMPLIFICATION OF REALITY, there is always a trade-off as to what level of detail is included in the model. Too little detail risks missing relevant interactions. Too much detail may overcomplicate the

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model, making it difficult to understand the nature of the interactions.

in having access to large sets of data. What is missing is the infrastructure to access and use this data.

Simulation is a computational version of a model; and, like a physical model, it’s a mechanism to represent the implications of the defined interactions under specific conditions. Simulations are generally iterative. One develops a model, simulates it, learns from simulation, revisits the model, and resimulates the condition until an adequate level of understanding of the relationships of the parts to the whole is reached.

The concept of data mining is relatively new, but the technology to do it is not. For many years businesses and governments have used computational methods to study volumes of data to reveal trends and relationships. The continual increase in computational power has only accelerated this effort; with two phenomena – both related to computational capacity being key to the increasing use of data mining. The first is Moore’s Law, which notes that computational processing power doubles every two years. The second, Kryder’s law, is the doubling of the storage capacity of hard drives every two years.

Prototyping is an early approximation of system or product that is being designed through testing and being reworked until it reaches desired performance levels; the prototype helps set the standards for the eventual system or object (e.g., element of a building). This process works best when not all of the project requirements are known in detail ahead of time and it is an ITERATIVE PROCESS between the designers and the users and the artifact under consideration. Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help organizations focus on the most important information in their data warehouses—THE ORGANIZATION’S INTELLECTUAL CAPITAL. This includes personal experience data from surveys and evaluations; financial, audit, and compliance data; outcome data, such as energy utilization records, structural loading conditions, employees comfort ratings, and assessments of completed projects; and many of records of organizational activities. Data mining tools can find new relationships between individual data points, establishing predictions of behavioral outcomes, and forecasting trends that can help organizations and individuals make proactive, knowledgedriven decisions. Most organizations and/or professions have massive quantities of data. Architecture and its associated professions—engineering, construction, planning, and other design entities—are no exception

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The Research Methods of Modeling, Simulation, and Data Mining WHETHER ONE USES VIRTUAL OR PHYSICAL MODELS, THERE ARE SEVERAL CRITERIA THAT CONTRIBUTE TO MAKING THIS PROCESS BENEFICIAL TO DESIGN AND TO ESTABLISHING A FOUNDATION FOR RESEARCH ACTIVITY.

The primary value of these tools is the creation of the databases used to inform the models, simulations, and prototypes. If the modeling process is digital, then a rich database provides the opportunity to analyze design: performance relationships across many projects, thereby enabling inferences about project types. Nondigital (physical) models or prototypes provide similar opportunities to inform and predict, but additional data coding is required so that objective interpretations can be made. In both cases, the designer must make clear the analysis methods used to predict outcome performance. The assumptions that were used in the model, as well as the methods and standards used to analyze and interpret the data, must be transparent to designers who will use the test results to make design decisions. Without clarity about the process, the designer won’t

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be able to use professional judgment about the meaning and applicability of the findings. Finally, there must be solid peer acceptance of the analytical methods, so outcomes will have credibility in the larger context of practice. Physical models and prototypes are used to simulate and analyze material properties, as part of systems development and integration and to detect and resolve conflicts within complex systems. Physical models are typically used to test and calibrate performance metrics, such as pressure flow, stress, strain, vibration, or other forces that influence a system. In most cases today, physical models, virtual simulations, and analysis tools are used simultaneously to explore and understand the performance and to provide data warehouses for data mining research efforts.

Physical Modeling, Prototyping, Testing, and Simulation Research Opportunities for Use, Best Practices, and Best Context VIRTUAL MODELS AND PROTOTYPES ARE EXCELLENT TOOLS FOR TESTING THE FORM, FIT, AND FUNCTION OF ELEMENT. AT THE SAME TIME, THEY PROVIDE AN IDEAL FRAMEWORK FOR INTEGRATING ELEMENTS AND SUBSYSTEMS TOGETHER AND EVALUATING WHOLE-SYSTEM (AND EVEN MULTI-SYSTEM) PERFORMANCE. Virtual models and prototypes have capacity to optimize and validate the impact of this, integrating many building elements and complex building systems. Nevertheless, in most cases it is still necessary to use non-digital, physical models to explicitly illustrate the performance of real materials and construction processes in a way that’s credible to the design, construction, and client team. The most effective and informed decisions from the evidence developed by both modeling methods. The relationship of virtual prototypes and physical models have become much more coordinated, due to new digital tools, including 3D printing, rapid proto-

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typing, and fabrication technologies. There are numerous examples of this project design, as well as full-scale fabrication and construction. The use of these tools allows the designer to answer a set of very important questions: How do the pieces fit together? How will they be used and perform…and does that satisfy project goals? Will the design have the desired aesthetic impact? Will it be cost effective? By providing evidence by which performance can be predicted and making transparent the degree of relevance of that evidence, virtual and physical modeling enable good decisions about complex design issues. Data mining links transactional and analytical systems. The software analyzes relational patterns in stored transaction data based on open-ended user queries. Several types of software are available: statistical, machine learning, and neural networks. Usually, any one of the four types of relationships are sought (Frand 1996): 

Classes: Searching stored data located in predetermined groups (i.e., medical patients’ personal characteristics)  Clusters: Data items are grouped according to logical relationships (i.e., consumer satisfaction outcomes)  Associations: Data identified by associations (i.e., color and human response) 

Sequential patterns: Data that anticipates behavioral patterns or trends (i.e., automobile preference based on income status)

The methods of data mining involve five major components: 

Extracting, transforming, and representing the transactional data.  Establishing, storing, and managing the data in a multidimensional database system.  Providing access to analyst specialists and informational technology professionals.

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Analyzing the data by select application software.



Representing the outcomes—patterns, trends, and relationships—in transparent forms of user applications.

There are several types of analysis that are available to investigate the structures of database data mining. They include: 







 

Artificial neural networks: Nonlinear predictive models that learn through training and resemble biological neural network structures. Genetic algorithms: Optimization techniques that use processes such as genetic combination, mutation, and natural selection in a design based on the concepts of natural evolution. Decision trees: Tree-shaped structures that represent sets of decisions. These decisions generate rules for the classification of a dataset. Nearest neighbor methods: A technique that classifies each data record in a dataset based on a combination of the classes. Rule induction: The extraction of useful “if-then” rules from data based on statistical significance. Data visualization: The visual interpretation and representation of complex relationships in multidimensional data records (Frand 2003 UCLA).

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In research, data mining tools can resolve specific case questions. The data mining process also creates an archive of the data from each case, resulting in a composite database that can help us understand new performance dimensions, interrelated outcomes and processes, and relationships among outcomes over multiple cases. As the database grows, there is greater validation and reliability of the evidence and therefore higher value design decisions that are made using it. THE INTERVIEWS AND CASE STUDIES THAT FOLLOW ARE EXAMPLES OF HOW THIS RAPIDLY DEVELOPING SET OF TOOLS FOR SIMULATING, MODELING, AND CREATING PHYSICAL MODELS AND PROTOTYPES ARE RESHAPING THE WAY WE DESIGN, CONSTRUCT, AND EVALUATE PERFORMANCE OVER THE LIFECYCLE OF PROJECTS. This work

shows how these technologies create and consume evidence as the foundation for decision-making by designers, clients, and others who have a vested interest in the projects. The range of examples stretches over the full spectrum of design activity from understanding basic performance criteria, to exploring conceptual design alternatives, and continuing through the detailed development of integrated building systems, construction, and post-occupancy evaluation and management over time.

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MITCHELL INTERVIEW

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Interviews of Experts and Case Studies MITCHELL INTERVIEW William (Bill) J. Mitchell The notion of evidence is a very hierarchical situation. I come to this in a very pragmatic way. For the designer you do not have the luxury to not take action, so you do the best you can. You find or produce evidence in the most rigorous form possible. If you can get hard scientific evidence, great, but if not, then you have to use the best evidence you can find in the hierarchy of the situation.

RESEARCH BACKGROUND

Figure 2.1 William J. Mitchell

William J. Mitchell, Professor of Architecture and Media Arts and Sciences at MIT, holds the Alexander W. Dreyfoos, Jr. (1954) Professorship and directs the Media Lab’s Smart Cities research group. He was formerly Dean of the School of Architecture and Planning and Head of the Program in Media Arts and Sciences, both at MIT.

He holds a BArch from the University of Melbourne, MED from Yale University, and MA from Cambridge. He is a Fellow of the Royal Australian Institute of Architects and the American Academy of Arts and Sciences, and a recipient of honorary doctorates from the University of Melbourne and the New Jersey Institute of Technology. In 1997 he was awarded the annual Appreciation Prize of the Architectural Institute of Japan for his “achievements in the development of architectural design theory in the information age as well as worldwide promotion of CAD education.” Mitchell is currently chair of the National Academies Committee on Information Technology and Creativity.

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WILLIAM J. MITCHELL INTERVIEW

Before coming to MIT, he was the G. Ware and Edythe M. Travelstead Professor of Architecture and Director of the Master in Design Studies Program at the Harvard Graduate School of Design. He previously served as Head of the Architecture/Urban Design Program at UCLA’s Graduate School of Architecture and Urban Planning, and he has also taught at Yale, Carnegie-Mellon, and Cambridge universities. In spring 1999 he was at the University of Virginia as Thomas Jefferson Professor.

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How do you use research in your work and how does it inform design? The group I direct is part of the larger strategy of the Media Lab at MIT, where there is deliberate organizational structure to be trans-disciplinary. We recognize design challenges do not fit nicely into single disciplines like sociology, economics, architecture, urban design, business management, etc. My group specifically brings together architects, urban designers, electrical and mechanical engineers, business management people, and medical staff. We work very much like the historical atelier—working together on a common project that we find interesting and important. We take full responsibility for the project and have very open boundaries regarding disciplinary experts. Unlike the traditional atelier, we work as an interdisciplinary team with a lot of peer-to-peer learning within the group, usually resulting in a transdisciplinary organization.

WILLIAM J. MITCHELL INTERVIEW

Part of our strategy is to build up the intellectual capital within the group regarding what the challenges are and what needs to be done to address them as designers and researchers. We move very quickly into building prototypes of these projects such as lightweight automobiles so we can test the performance of the outcomes. The strategy is based on speculation and critique. For us the starting point for design and research is a concrete proposition—the more radical the better—and subject to our process of inquiry and action.

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This process begins with a critical discussion usually around a prototype. We spend a lot of time building prototypes as we find this is the best way to engage the transdisciplinary partners in the process as well as industry partners. We have a great deal of respect for the domain knowledge of our industry partners, architects, construction people, automobile experts, etc. The best way to access this domain knowledge is to put a concrete proposal in front of them and continue this process by building prototypes around which critical dialogue can take place to inform the strategy for making a new prototype version. This process is continued until there is agreement that an appropriate solution has been found, and then if the need exists, production is begun. We are always open to multisolutions to these projects that build on different disciplinary expertise and values. One example of this is a project where we are dealing with giving individuals personal mobility in the city using small-scale electric cars. One solution is to provide automatic recharge stations in parking spaces providing limited range, but frequent recharges. Another solution is based on nano-technology using carbon tubes to redesign the battery capacity and weight, giving extended range to the car.

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What constitutes evidence and how much is enough in your process of research? There are two levels. There is an infinite amount of evidence related to any challenge. Our attitude is grounded in the belief that you must first get a concrete proposal of an idea, create a prototype, simulate a model, etc. This will tell you what are the critical questions. From these critical questions, you can now know what type of evidence is needed to move the process forward. It is hopeless to try and collect all the necessary evidence first and then act, as you really do not know what you need until you take some kind of action. This is fundamental to how designers think and work. You need to speculate first. This will then lead to several approaches—either build a prototype, construct an experiment, do a literature review, etc., to move the process forward.

The notion of evidence is a very hierarchical situation. I come to this in a very pragmatic way. For the designer you do not have the luxury to not take action, so you do the best you can. You find or produce evidence in the most rigorous form possible. If you can get hard scientific evidence, it’s great, but if not, then you have to use the best evidence you can find in the hierarchy of the situation. Another dimension of this concern about evidence is its level of credibility so we try to be as straightforward and clear as possible about what we are basing our decision-making process in. We normally have to say we wished we had more evidence, but that is the nature of design. The designer is always working with incomplete information. The important part here is to make the evidence as transparent and legible as possible and be honest about its source. Evidence-based medicine, the precedent for this kind of process, is a good example. The doctor, if he has solid scientific clinical evidence for a diagnosis or a treatment plan for a patient, that is what will be used. If not, then it is not an option to not diagnose or treat a patient so they use the best evidence available and sometimes that is from experience and intuition.

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WILLIAM J. MITCHELL INTERVIEW

The second level is the critical debate from multiperspectives. An example of this is the idea of making a fold-up car to minimize parking space in the city. The mechanical engineers will immediately think this is insanity. They will argue that this will create very difficult outcomes, complexity of the mechanics, increased cost, and additional weight. The urban designer, however, will note what parking spaces cost in the city. It is a completely different way of looking at the project. This is when the critical debate comes into play. These debates happen when the different participants have to bring their evidence to substantiate their position. This evidence must be transparent and understandable to all who are stakeholders in the project. This then provides the opportunity to discuss the trade-offs. The important thing is to create these moments when the evidence can be brought to bear.

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Do you think that putting forward a hypothesis or critical question as a starting point in research enhances or inhibits creative action? No question! Putting forth a critical question or hypothesis enormously enhances the creative action. You can always tell the designer in the room. As soon as someone says, “Well, what can we do,” the designer stands up and says, “This is exactly what we should do,” by making a sketch or some other representation to make the point. This will set in motion a critical dialogue about how to proceed. It is critical in this process to have an atmosphere that insures there are no stupid propositions or questions. The important part, however, is to keep the dialogue open and inclusive so that all perspectives are heard. This process elicits a productive process for getting the best ideas out and critiqued. This, however, does require a particular type of attitude, which designers are trained to have—that is, the ability to put something out there without having any assurance that it is appropriate or not, but out there so the critical engagement can take place. I have noticed that many of our engineering students will not put anything out there until they think it is all figured out. We know having it all figured out never happens.

WILLIAM J. MITCHELL INTERVIEW

In your work how do you make sure that the people engaged in the research represent the appropriate mix and backgrounds?

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First, the fact that the group is within the context of MIT makes it relatively easy to find experts in just about any subject you need, but, of course, there are limitations. As always, we do the best we can. However, there is a core structure that provides continuity to the effort. We always have a group of PhD research students who are around for four or five years, a couple new ones each year so the group is always stable and provides the institutional memory. In addition, there are one or two master students who are involved for at least a year and then a small group of undergraduate students who are involved for a semester, in most cases. This structure provides a built-in self-renewal situation. Of course, when we need a specific expertise we bring it in. The key is a diversity within the group—age, ethnicity, and disciplinary expertise—the more diverse the better.

How do you translate your research outcomes into practice settings? Most of our research efforts result in published documents, technical papers, journal articles, working papers, etc. We put a lot of effort into making prototypes and pilot projects that can actively engage other designers and the general public in what we are doing. To do this, we must create outcomes that are transparent and legible to

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a diverse population, meaning we use a lot of photo realistic representations, animations, and other forms of media that are a part of the everyday life of the stakeholders. This is where the making of prototypes really helps because being able to touch, see, and maybe operate the outcomes is the best communicator.

Could you explain the nature of the prototyping process you use in the lab? We use a hierarchy of prototypes, starting usually with rough sketches that become quick nonfunctional plywood or foam-core models. We then make 3D digital models of these objects where some forms of analytical analysis and testing can take place. Then, using innovative rapid prototyping tools like 3D printing and laser cutting, we make additional physical prototypes starting with simple and inexpensive materials to highly complex working physical models of the specific materials and processes. The data files from these are sent to a fabricator, many times in China. They send back parts for the larger prototype, which are assembled and tested in the lab. This is an amazing process that we now have in today’s world. E-bay has become the global parts bin. Prototyping is a great way to get all of the team members involved in the process. Everyone understands physical prototypes. You can prototype key details and key technologies from concept to production. Some would say that we start prototyping much too early, but we feel just the opposite. We have a lot of early failures, but that is when you want failure because there is less invested and change is generally relatively easy. When you do not know what you are doing is when prototyping and simulation are most valuable.

I will start with practice. What I think needs to happen is firms need to build a network of consultants, researchers, and others with a vested interest in research to work in an interdisciplinary form around important questions facing practice. This cannot be done in a typical small firm so collaborative and joint ventures are necessary. It takes a new attitude within practice that values both the creation of new knowledge—evidence—and its application in their practice activities. It is also important to build bridges to academic communities that are actively involved in research. There is a real problem in the standard accredited architecture program as many schools in this country limit their educational goals to meeting these criteria. To have

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WILLIAM J. MITCHELL INTERVIEW

How would you change the current curriculums in schools of architecture and what types of practice models are needed to address the kinds of research processes you are using in the Media Lab at MIT?

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a viable research program takes a specific effort and commitment. In the typical accredited program too many of their resources are dedicated to teaching the narrowly defined requirements for accreditation. What needs to happen is the creation of a “playpen” somewhere outside the accredited program where radical and more forward-thinking ideas can be addressed. The Media Lab at MIT is an example at a very complex scale, but this is scalable within the constraints of the individual school. As a part of this, however, it is critical to create ways for students from the standard degree programs to participate in these playpen activities. This can also be the bridge to collaboration with practice and industry. If one wants to be involved in innovative research work it is not possible to accumulate the knowledge, skills, and values and then go out there and do the work. The context of the research moves too fast so what one has learned probably will not be relevant. What one needs is a system that is fast learning, nimble, and can move quickly into new domains. This suggests transient groups of expertise around a core agenda and a process for working in this way. This doesn’t fit well into a framework with standard criteria for outcomes like the NAAB approach.

WILLIAM J. MITCHELL INTERVIEW

Today, the setting of the classical “post-doc” after completing the formal training and education for a career is even more important. This would be an excellent way to provide intellectual capital to these playpen structures. As you are aware, there is a model in your backyard—the Silicon Valley—that is built on the social networking model. There are many small start-up companies as well as larger mature companies that operate in this model. People move freely between these organizations using their expertise to contribute. When they have a problem they can’t solve, they go out to lunch and exchange knowledge in an informal manner.

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It is also important to note that what we think of protecting and regulating our profession and its role in society may not be as important as we think it is. In today’s world we could design an air-traffic control system that would be dangerous, but the risk is managed without licensing and regulation. The point here is that these regulatory constraints also limit how we approach innovation and research.

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M ITCHELL C ASE S TUDY Mobility-on-Demand Smart Cities Project MIT Media Lab

What was the research question or hypothesis? This research is grounded in a very pragmatic approach, where transparent evidence is critical. There is no question from our perspective that putting forth a critical question or hypothesis enormously enhances the creative potential and action. For this project the starting point was an observation that in the twenty-first century 90 percent of the population growth will be in urban areas. Hence, the pattern of future energy demand will be determined by urban networks. The central research question was how to develop transportation technologies that would reduce the demand for energy in support of transportation systems in urban centers.

MITCHELL CASE CASE STUDY STUDY / Mobility / Mobility on Demand—Smart on Demand—Smart Cities Cities Project Project MITMIT Media Media Lab Lab

M I T C H E L L C A S E S T U D Y : M O B I L I T Y- O N - D E M A N D

What methodologies of research were used? Why did you select this approach? The group that I direct is part of the larger strategy of the Media Lab at MIT where there is deliberate organizational structure to be trans-disciplinary in terms of organization structure that works together on a common project that we find interesting and important. The strategy is based on speculation and critique. The process

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DESIGN INFORMED

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utilizes a hierarchy of prototypes, starting usually with rough sketches that then become quick nonfunctional plywood or foam-core models. We then make 3D digital models of these objects, where some forms of analytical analysis and testing can take place. Then, using innovative rapid prototyping tools like 3D printing and laser cutting, we make additional physical prototypes starting with simple and inexpensive materials to highly complex working physical models of the specific materials and processes. The data files from those are sent to a fabricator, to fabricate parts for the larger prototype, which is then assembled and tested in the lab. This research approach led to the development of the CityCar and RoboScooter, part of an integrated study utilizing virtual and physical modeling, simulation, and prototyping technologies to investigate the alternative scenarios for smart city development grounded in electric transportation vehicles for urban movement systems. Modeling, simulation, and rapid prototyping technologies allowed for the interdisciplinary research team to establish clear goals, communication protocols, and produce representations of each phase of the development of the CityCar and RoboScooter through a learn-by-making approach. This process began with a critical discussion around a prototype. A lot of time is spent building prototypes as we found that this is the best way to engage the trans-disciplinary partners in the process as well as industry partners.

Why were the metrics effective, efficient, credible, and doable? The computational tools used in this study allowed for the minimizing of risk of failure by using the immediate feedback loops that informed each stage of design decisions from initial concepts to operational prototypes utilizing evidence to move the project to the next level. The concern about the level of credibility of evidence for us is to be as straightforward and clear as possible about what evidence we are basing our decision-making process on. The important part here is to make the evidence as transparent and legible as possible and be honest about its source so that all of the stakeholders understand the basis for critical decisions. The best way to access the domain knowledge of a project is to put a concrete proposal in front of the research team and continue this process by building prototypes around which critical dialogue can take place and inform the strategy for making a new prototypical version. This process is continued until there is agreement that an appropriate solution has been found and then, if the need exists, production is begun.

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What were the outcomes? The outcome of this research was the creation of a prototype CityCar and RoboScooter now under consideration in the private sector for future production in the marketplace of transportation vehicles to address urban movement patterns by people. The CityCar and RoboScooter are not intended to replace existing transportation networks, but to add an additional component to the system. The two major benefits for the CityCar and RoboScooter are energy and space savings (parking) in the urban core. This project has contributed to the larger agenda of the Smart Cities Project Group including the Zero Car project that is developing electric motor wheel modules (wheel robots), and material ecologies exploring the design generation and production for material and fabrication-informed processes.

How were the outcomes applied or linked to help inform design? The power of these computational tools were central to the design and development process in that they provided direct outcomes in the form of measurable performance parameters critical to the development of the parts and whole system of the CityCar. As in this project, most of our research efforts result in published documents, technical papers, journal articles, working papers, etc. Also, we put a lot of effort into making prototypes and pilot projects that can actively engage other designers and the general public in what we are doing. To do this we must create outcomes that are transparent and legible to a diverse population, meaning we use a lot of photorealistic representation, animations, and other forms of media that are part of the everyday life of the stakeholders. This is where the making of prototypes really helps, because being able to touch, see, and maybe operate the outcomes is the best communicator.

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MITCHELL CASE CASE STUDY STUDY / Mobility / Mobility on Demand—Smart on Demand—Smart Cities Cities Project Project MITMIT Media Media Lab Lab

M I T C H E L L C A S E S T U D Y : M O B I L I T Y- O N - D E M A N D

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DESIGN INFORMED

CASE STUDY PROJECT / Mobility-on-Demand CityCAR

C ASE S TUDY P ROJECT Mobility-on-Demand Mobility-On-Demand—CityCAR CityCAR

 Figure 2.3 Big Problem: Buildings and Transport Energy and Space Consumption

Mobility-on-demand systems may use a single vehicle type. However, a more attractive option in larger and more sophisticated systems is to employ multiple vehicle types providing users with choices among combinations of cost, comfort, and functionality.

 Figure 2.4 World Population Estimates Provided by the United Nations

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1. 50 percent of the global population currently live in dense urban areas (noted by the red line in the figure). 2. There is increased urban densification. This urbanization trend will continue for the foreseeable future (rural populations will flatten and decrease). 3. The increased inefficient energy use could lead to climate change.

Figure 2.5 The CityCar—A Solution to Transportationon-Demand

The CityCar is a stackable, electric two-passenger city vehicle. The one-way sharable user model is designed to be used in dense urban areas. Vehicle “stacks” will be placed throughout the city to create an urban transportation network that takes advantage of existing infrastructure such as subway and bus lines. By placing stacks in urban

CASE STUDY PROJECT: Mobility-on-Demand CityCAR

As can be seen in Figure 2.4:

 Figure 2.6 The CityCar Unfolding Sequence to Save Space in the City

 Figure 2.7 Energy- and Space-Efficient Comparisons with Other Transportation Options

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DESIGN INFORMED

spaces and key points of convergence, the vehicle allows citizens the flexibility to combine mass transit effectively with individualized mobility. The CityCar is not a replacement for personal vehicles, taxis, buses, or trucks; it is a new vehicle type that promotes a socially responsible and more effective means of urban mobility.

Figure 2.8 Full-Scale Prototype of the CityCar

The CityCar utilizes fully integrated in-wheel electric motors and suspension systems called “Wheel Robots.” The wheel robots eliminate the need for traditional drive train configurations like engine blocks, gear boxes, and differentials because they are self-contained, digitally controlled, and reconfigurable. Additionally, the wheel robot provides allwheel power and steering capability of 360 degrees of movement, thus allowing for omni-directional movement. The vehicle can maneuver in tight urban spaces and park by sideways translation. This technology is patented-pending and under design development at the MIT Media Lab. Mobility-on-demand systems generally are not replacements for transit systems. Instead, they operate effectively as partners of transit systems, and enhance the efficiency and attractiveness of these systems by solving the “first kilometer” and “last kilometer” problems. The use of electric vehicles and bicycles eliminates tailpipe emissions, local pollution, and traffic noise. However, this does not necessarily reduce dependency upon nonrenewable energy sources. This depends upon the source of electricity. If the source of electricity is old-fashioned coal-burning power plants, for example, then the shift to electric vehicles merely displaces (though maybe with at least some advantage) carbon emissions. But if the source is hydro, then carbon emissions are eliminated. A general problem with today’s electric grids is that they lack storage capacity. This makes it difficult for them to respond effectively to demand spikes, and it makes

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them unfriendly to clean, renewable but intermittent sources such as solar, wind, and wave. However, since electric-powered mobility-on-demand vehicles are always connected to the grid when parked in stacks and racks, they throw a large amount of battery storage capacity into the grid. This opens up the possibility of vehicles buying and selling electricity—much as has been proposed for plug-in hybrids. Trading strategy would respond to current electricity prices and expectation that they would need electricity for travel in the near future. Increasing political and economic pressure related to the geopolitics of energy supply, the need to reduce carbon emissions and global warming (to which gasoline-powered urban mobility is a major contributor), and the need to shift to clean, renewable energy systems, will create increasingly powerful incentives for local and national governments to support mobility-on-demand systems.

C ASE S TUDY P ROJECT Mobility-on-Demand Roboscooter

CASE STUDY PROJECT / Mobility-on-Demand Roboscooter

C A S E S T U D Y P R O J E C T: M O B I L I T Y- O N - D E M A N D R O B O S C O O T E R

Figure 2.9 SharedUse Model in an Urban Setting

The RoboScooter is a lightweight, folding, electric motor scooter. It is designed to provide convenient, inexpensive mobility in urban areas while radically reducing the negative effects of extensive vehicle use—road congestion, excessive consumption of space for parking, traffic noise, air pollution, carbon emissions that exacerbate global warming, and energy use. It is clean, green, silent, and compact.

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DESIGN INFORMED

The RoboScooter is designed to be effective in one-way, shared-use mobility systems, similar to the one-way bicycle rental system that has been successfully implemented, on a large scale, in Paris. The robot wheel architecture enables the RoboScooter to be produced in both one-wheel-drive and two-wheel-drive versions. Two-wheel drive, which is complex and difficult with a more traditional location of motor, offers many potential performance advantages. Figure 2.10 The RoboScooter 4. Battery Vending Machine 1. RoboScooter

Figure 2.11 RoboScooter Components Storage, Battery Recharging, and Folding

3. Inductive Charging Rack 2. Removable Battery

Figure 2.12 Availability of RoboScooter at a Convenience Store

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CASE STUDY PROJECT / Mobility-on-Demand Roboscooter

Figure 2.13 Robot Wheel— The Power Mechanism of the RoboScooter

ROBOSCOOTER PERFORMANCE SPECIFICATIONS

Figure 2.14 The RoboScooter Folding Sequence 1

Production Model Performance (Estimate) Battery Life: 45 Kilometers per Charge (minimum) Motor: 1000-Watt Brushless Motor (2) Controller: 3-Phase, 36V Brushless Motor Controller with Regenerative Braking and Reverse

Prototype Performance (Conservative Estimate) Battery Life: 45 Kilometers per Charge Battery Type: Li-Ion Polymer (2 packs) 36V, 10Ah, 3-Hour Charging Time Motor: 600-Watt Brushless Motor (2) Controller: 3-Phase, 36V Brushless Motor Controller with Reverse Capability

Folding is accomplished by means of a special central pivot, which shifts the wheels in and out of alignment as required. Folding is automatic and powered by the wheel motors. It does not require manual effort by the user. Figure 2.15 The RoboScooter Folding Sequence 2

Fig 2.16 The RoboScooter Charging Station

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UBBELOHDE / LOISOS INTERVIEW Susan Ubbelohde / George Loisos It is our view that once you understand the phenomenon that you are working with, the application of knowledge or evidence clearly helps the designer understand and act on the situation in creative and innovative ways.

RESEARCH BACKGROUND

UBBELOHDE/LOISOS INTERVIEW

Figure 2.16a Susan Ubbelohde

Figure 2.16b George Loisos

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Susan Ubbelohde is a Professor in the Architecture Department at the University of California, Berkeley, and a LEED Accredited Professional, with more than 25 years of experience in building energy-efficient use, daylighting design and climate-responsive design and performance. She teaches graduate design studios and seminars in sustainable and high-performance design and technology. Ms. Ubbelohde has directed projects for the U.S. Department of Energy, the State of Minnesota, the National Science Foundation, the University of California Energy Institute, and the California Institute for Energy Efficiency. Ms. Ubbelohde is a frequent lecturer at professional conferences, and has published numerous articles on daylighting, solar access and energy efficiency, and design procedures for passive environmental technologies. George Loisos is a licensed architect and LEED Accredited Professional who has practiced in Europe and the United States since 1980. He holds architectural degrees from Tulane University, the University of Oregon, and Plymouth Polytechnic in England. His design work has ranged from large to small and public to private, including a teaching observatory in the Oregon mountains, resort facilities in northern Greece, and renovation of early industrial buildings and new community college facilities in Minneapolis. As the architectural program consultant for the Pacific Energy Center in San Francisco from 1994 to 2000, Mr. Loisos created and administered research and public programs on daylighting, energy conservation, and sustainable practices in design. Mr. Loisos has led major research programs in building energy use at the University of California, San Diego, at the University of Minnesota, Minneapolis, and for the Cali-

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fornia Institute for Energy Efficiency. Mr. Loisos lectures extensively on environmental design issues at universities and professional conferences and also presents specialized workshops on related topics for architectural and engineering firms.

How do you see evidence playing a role in your practice? Our practice is based on a model of providing clients, primarily architects, rapid response to project-specific challenges. Our goal is to make the buildings these designers are involved with better. As a firm we have 15 years of data on building performance, both modeled and real-time performance of completed and occupied buildings. The two of us together have over 60 years of experience in energy and daylighting consulting and research. Our philosophy is to use publicly available tools and materials by going directly to the source—the national laboratories like LBNL (Lawrence Berkeley National Laboratory) and the Department of Energy. We use their light simulation software and energy simulation combined with visual simulation tools to cut through the mountain of data that we produce in our consulting work.

The tools we use from the national laboratories have been and continue to be presented by the developers at conferences and in peer-reviewed journals. We follow this dialogue closely, and it gives us an understanding of what is good and not so good. DOE2, for example, is useful for daylighting energy analysis when the light is from the ceiling, but not so accurate for daylight from the side. So we know when and when not to use this tool. We also do testing of our own in our offices and by using the artificial sky at Berkeley. Thermal simulation is a little more complex. For energy we can go back to first principles as noted. Human comfort, on the other hand, is much more complex and because we have access to the Center for the Built Environment at Berkeley, we can

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UBBELOHDE/LOISOS INTERVIEW

We use these tools because they are open-source and validated and give us the opportunity to have direct feedback from the tools and our data, rather than relying on research studies and data. Our practice produces a lot of data and by using these open-source tools we can have a much better understanding of how the tools are impacting the data and versa visa. This allows us to go back to first principles. This also gives us the opportunity to go back to the research teams that develop the tools when we find things that do not seem to be working appropriately. This is very different than the commercially based programs where it is much more “black box” because we do not have access to the code. This process provides interesting loops in terms of evidence-based design in that by understanding the ins and outs of the tools we are able to better interpret and communicate to our clients the nature of our recommendations and findings and to also help in the further development of the tools.

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use their research efforts to help us understand our performance outcomes. The critical thing here is that we do not take outcomes at face value. We continually challenge and test the performance outcomes to make them as accurate as possible. This is the only way to get quality evidence to inform design.

UBBELOHDE/LOISOS INTERVIEW

We also regularly attend conferences with our peers who are doing research, giving us an opportunity to have direct access to the most current work in the field. This allows us to confirm what we are doing using the tools. This is much different than reading about building performance in a trade magazine or newspaper where, in most cases, there is a commercial interest and no real access to the principles underlying the performance metrics and tools, etc.

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As noted, we do create an enormous amount of data, but because we are always working on a specific project we have not mined data from other projects, as reference to what we are doing. It has not been practical for us in our practice. Obviously we have a lot of experience with this data, and it helps us in the interpretation and representation of the outcomes. An example would be using what we have done on a building in Pasadena, California, and if we were asked to do another building in Pasadena we would go back and look at the data that represents the similar context conditions (i.e., climate, building type, etc.) and use the parts that are appropriate as a part of our analysis. Daylighting is a bit different than energy use and climate response, in that we do keep in mind data from previous projects when we evaluate simulation results on a new project. We, however, do not have enough projects to have any energy use benchmarks within our practice for comparisons. We have used the Building Energy Performance Data Standards developed by the RIBA in England to look at projects by building type. This effort by the RIBA is to establish baselines and benchmarks by building type. It is something that is needed badly, but the infrastructure is not there yet to support the establishment of these types of data warehouses, but it will come as more and more people use simulation and modeling totals to produce data that is easily accessed and shared. At the present time, both the Department of Energy and the GSA (Government Service Authority) have similar databases that we sometimes review and compare when appropriate. An example of this, which by the way we would like to replicate, was based on our involvement in a project that designed and monitored compressive cooling in two demonstration houses with the agenda to reduce or eliminate AC all together. Because of our involvement in one other house in Pasadena, we were able to present evidence that completely changed the design strategy for the project in terms of

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thermal mass, building envelope, and reduction of AC strategies. This happened, however, only because we were involved in the research projects. The second effort is that we have done a number of daylight simulation studies for projects, and we have gone back to the completed projects and monitored the actual performance to validate that what we are simulating is actually how the building performs. Because of this, we are really confident about our accuracy of the predictions of performance outcomes in this area. In reality it is not a feasible option for most consultancies or practices to get involved in validating models and actual performance outcomes of buildings. The technical skills and equipment alone present major overhead issues to begin with, and then there are the issues of access and sensory capacity. The real problem is the complexity of controlling the design of the process. If you have one variable to monitor, okay; two is a bit more complex, but doable. In a building you have several variables to control and that is where the difficulty arises. It is almost impossible to have enough control to get accurate data and when it does happen, it takes a major organization to make it work appropriately. It is not something that can be done in a consultancy or architectural practice. There will have to be major advances in new technology and computational tools to make this feasible at the scale of the individual practice.

Another aspect of this issue of accuracy of the models to simulated building performance is what you are trying to measure. The researchers at LBNL several years ago asked the basic question: That being the case, how accurate are the models in predicting actual building performance? They hired a set of energy modelers and had them model the buildings and compare this to the actual performance of the buildings. They found the models were at least 30 to 35 percent off. The more interesting thing, however, was when they modeled for types of energy systems and compared that to actual systems in the buildings, the models were only 12 percent off. It is our view that the tools for measuring energy use work better when you use them to design systems rather than focus on just measuring energy use. This is not true, however, in daylighting. We have found that models are so accurate that we can predict down to one footcandle. In terms of human comfort, which is more complex to get meaningful outcomes, you have to focus on a specific population rather than

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UBBELOHDE/LOISOS INTERVIEW

We tend to borrow most of the technology we use from other disciplines. This is the case here as well and much of what is being developed in terms of pure research in places like mathematic and physics is not yet ready for “primetime” in architecture. There are lots of people talking about doing this, but it is mostly hype rather than actual performance.

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individuals. In most cases, if you do this, you will generally have 10 to 20 percent of the population dissatisfied and the others satisfied. Clearly the accuracy depends on what you are measuring, the sophistication of the technology, and the tools. Based on this as a consultancy or practice, you need to know when to use specific tools and modeling technologies. For example, we would not do a comfort study on a residential house, but we do them regularly on large office and laboratory buildings. We did a consulting project on a large office building in San Francisco where we were able to present evidence that by spending an additional $400,000 on a high-performance skin, there was a 30 percent increase in usable space in the building that provided appropriate levels of comfort. It also substantially reduced the cost of perimeter heating.

In your practice does the use of evidence enhance or inhibit creativity?

UBBELOHDE/LOISOS INTERVIEW

When we first work with a client it seems as if they think that what we will do will constrain and limit their options in terms of creative or innovative responses to a project. They generally come to us when they have a problem to solve that they seem unable to resolve. We are careful to respond to them in a manner that tries to give them a ground to work from that frees options. This takes the form of questions and alternatives to open up a dialogue about what the opportunities are. Once we get through this process then, in most cases, the clients see the challenges and the opportunities and work with us to maximize the creative potential. The evidence really becomes a way of opening up possibilities rather than limiting them.

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Projects come to us in many forms. Some have conditions and constraints that the limits of physics cannot solve. Others come to us with an open mind about what is needed and a clear understanding of the limits, and then we can work with them to find the potential in terms of performance outcomes, whether it be energy, light, comfort, etc. The reason why this works is less about process and evidence, but about the attitude of what is to be accomplished. We approach our work as designers so aesthetic consideration is always important to us. We want the designers of the building to do a good building. The best architects we work with seem to want a process that gets them to use, first, principles and then to use these to challenge the accepted wisdom about how to respond to some design situation, and use these principles to explore creative and innovative options to make a better building. So they see this evidence as helpful, not as a deterrent. It is our view that once you understand the phenomenon that you are working with, the application of knowledge or evidence clearly helps the designer understand and act on the situation in creative and innovative ways.

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You describe your practice as requiring a rapid practical response to projects. Would you say architects need metrics and measures to justify performance outcomes? We have found out that numbers are important at specific points in the process of working with designers, clients, and other consultants, but the part that is most important is the judgment and interruption that we provide based on the 60 years of experience represented between the two of us. We can normally, within two hours of working on the schematic design of a project with the architect, establish a strong concept for resolving the energy and lighting challenges. In this phase the hard numbers as evidence are not so important.

We have a project now for a client who is asking us to show how a specific building would change if it were built in Phoenix, Hawaii, and New York to produce a highperformance building in terms of energy, human comfort, and financial impact issues. We are modeling each of these locations and comparing them around sets of variables: set one—heat coefficient, U value, and orientation; set two—roof insulation, wall insulation, and U value. Then we integrate these sets to find a resolution that best fits each set of conditions. It is this type of numerical evidence that is very helpful when it is used around comparative situations. We have discovered through our work that numbers are just another part of the set of tools we use to make predictions about performance outcomes. They are useful in the sense that they support our larger efforts to model and simulate alternative outcomes, and the numbers help us focus the work and to interpret the outcomes in a context of the specific project and from our experience on other projects. The reality: The numbers are only as good as the questions they address. If you ask bad questions, the numbers are useless. If you ask good questions, they are extremely helpful

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We do create hard numbers, however, to provide evidence for understanding the financial implications of alternative strategies, rebates, and standard and code requirements. Even here it is important to have a soft approach in helping the stakeholders understand the numbers. It is really a dialogue of exploring and understanding the relationship between the numbers, evidence, and the design solution and performance outcomes. The hard numbers are most helpful to the other consultants (i.e., mechanical and electrical engineers). They need scientific data to be comfortable with the outcomes of our recommendations on energy, lighting, and human comfort. The bottom line for us is that hard numbers or evidence is important from getting the interview for the job all the way through the commissioning of the building.

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in the larger array of our consulting recommendations. From this perspective, we try to focus the use of numbers on those issues that will be most helpful, either in providing evidence for design decisions or evidence to communicate to stakeholders the grounds of our recommendations.

How does interdisciplinary collaboration play a part in your practice?

UBBELOHDE/LOISOS INTERVIEW

As a consulting practice we tend to work directly with and are contracted by the architecture. In most cases, we have significant interaction with all of the other consultants on the team. In our best projects we are at the table from the very beginning. Our role in many cases is one of coordination around issues of form, building envelope, plan and section development, and building orientation. Because we are architects first and consultants second, we tend to work very closely with the design architects. In terms of collaboration, we work closely with the mechanical and electrical engineers in systems design, and with the structural engineer to coordinate structure so that we maximize things like daylighting and energy issues with structural details. We also work with the interior designers on most projects as interior materials and furnishings have a significant impact on daylighting and thermal venting opportunities.

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With the introduction of LEED the consultant group has expanded to include horticulturalists, hydrologists, environmental experts—water, waste, recycling—which has complicated the task of the architect to use the limited-fee base on any project in the most effective manner. We talk a lot about integrated design, but there is much work still to be done. The concept of doing high-performance buildings is being promoted by many organizations, but the task of getting people to work together effectively is still a very big challenge. There are language issues, scope and schedule issues, fees and remuneration issues. We all know of the difficulty of architects and engineers working together as they speak a different language, but when you add some of these other disciplines who work at an even more abstract level, the interactions become even more of a challenge. We don’t recall in our history of practice having the current number and diversity of consultants involved in projects. It is clearly enriching the process, but at the same time it is challenging the organization and management of the process to get the most effective outcomes from the array of consultant possibilities. Traditionally we have relied in architecture on intuition and experience as the primary guarantors for what we do. As such we don’t have good feedback loops to share what we know with the others in the office nor with the rest of the profession. How, as a practice, do you deal with these issues?

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UBBELOHDE / LOISOS INTERVIEW

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We have struggled with this issue in our practice both in terms of sharing our 60 years of experience and trying to address the frustration of those who work with us about their desire to know more about what we do and how we do it. Our practice is built on the traditional apprenticeship model, but we intentionally create formal and informal feedback loops so our employees have the opportunity to be reflective about the work we do. We go back to our projects, both the simulations and to real buildings, to evaluate the relationships of intentions to real outcomes. This lets all of us have a better understanding of what we have done and what was the validity of the outcomes. This is really hard to do, but critical if you want to have a practice that learns—a smart practice. In terms of providing generalizable outcomes, what we do to other projects and firms and specifically the profession, we are not a good entity to ask as we find guidelines to be the bane of our existence. We are interested in the particular conditions of specific projects and positioning them in a larger framework, but not to make guidelines. We believe that the “case study” approach is much more valuable when it includes both processes and outcomes of particular projects. We can then make comparisons both within and across projects. We also have difficulty with the notion of “best practices.” To us that means, “I do not have time to think about this situation, so tell me what to do.” For us it is finding the different conditions in a project that provide the opportunity to make something better.

How do you feel about performance-based codes versus Prescriptive-based codes and how does this differ from guidelines? Guidelines are basically telling what specific action to take to get a certain outcome. Do these ten things, and you will have an appropriate outcome or solution. It is a checklist. An example is something we all learned in school—use horizontal louvers on the south elevations of buildings and vertical louvers on the east and west elevations of buildings. We know this is not always true, but it is a clear guideline. We are very much proponents of performance-based codes. Our practice is based on the concept of being a performance-based outcome practice. This is one of the best

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In terms of disseminating outcomes, we think that the model that the AIA Committee on the Environment uses to showcase the “Ten Best Projects” each year is excellent. They require that the technical information and performance outcomes be included in each building selected. Over ten years, this gives you a hundred projects in case-study form that are available on the web for practices and individuals to compare and study.

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ways to encourage innovation and creative responses. Now with the simulation and modeling technologies available, we have the capacity to find accurate performance outcomes to meet the performance expectations of a specific project. An example of the difference between prescriptive codes and performance-based codes shows how this works. If we take Title 24, it has both performance and prescriptive components. Title 24 is the “building energy efficiency standards” set by the State of California for energy building performance. If we study energy performance, the prescriptive code would require a 30 percent ratio of wall-to-window and a Uvalue of X and an R-value of Y. You would then have to design to these requirements and probably get a not-so-interesting outcome. If you use the performance-based code, the requirement would be that the building would have to use X number of Kaiser Permanente DU’s per year. Then you can do whatever is necessary to meet this performance outcome—all-glass with a high-performance mechanical system, etc. The outcome at least provides the opportunity to do a creative and innovative resolution.

UBBELOHDE/LOISOS INTERVIEW

Do you see a need to change the education or the practice model to meet the challenges of this evidence-based type of practice and consulting?

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We have spent a fair amount of time thinking about how education could change to better prepare students to understand and use the tools and processes necessary to utilize an evidence-based performance outcome design process in practice. I am teaching a seminar course this semester which exposes students, through a set of practice exercises, to a performance-based method of working. This is done in teams, where the team is composed of both building science and design students. They are designing a set of facades for a zero-energy small building in Oakland. The program of the course is divided into phases, with each phase being based on a careful performance evaluation of outcomes at the end of each phase. The course brings in several experts from LBNL (Lawrence Berkeley National Laboratory), visiting scholars connected to the CBE (Center for the Built Environment University of California Berkeley), and from industry to give lectures and to serve as jury members at the review of the performance-based outcome proposals at the end of each phase. This comes very close to providing the students the exposure and experience they would get in real-world practice. Their response to the course is very positive, and it is clear that the notion of evidence-based evaluation performance outcomes is an important component of their preparation for practice. This may not be the total answer, but I am convinced that these types of exposure and practice sessions are better strategies than a comprehensive curriculum that tries to incrementally address these issues over several courses or years of study.

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C ASE S TUDY P ROJECT Susan Ubbelohde and George Loisos Loisos + Ubbelohde Architecture—Energy

CASE STUDY PROJECT / Frog Zero

Frog Zero

Figure 2.17 Green Building Frog Zero Test Example of Modeling Technologies

Looking to a larger field of operations than single custom structures, the architect asked us to find a method to identify the smallest number of design options required to provide full comfort at net-zero energy throughout an entire region characterized by varied climate.

What was the research or critical question in this project? Project Frog came to Loisos + Ubbelohde with a deceptively straightforward research question: How do we take our prefabricated classroom characterized by quick construction, lower costs, high-quality control, and basic green performance and achieve net-zero energy, net-zero carbon emissions, and high-quality interior space efficiently and appropriately for any given site and climate? This research is conceived as being broadly open-ended for product development applicable to many locations, but also informed by ongoing specific project opportunities for defined sites and clients.

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CASE STUDY PROJECT / Frog Zero

As we develop more detailed and sophisticated methodologies for identifying the optimal configuration, envelope design, and mechanical system, we work iteratively with the product development team to ensure that all design options we identify are realistic from a manufacturing and cost standpoint.

What were the research or investigative methods used in this project? To date, four phases of the ongoing research can be described. In Phase I we took a proof of concept approach to see if the regular Frog classroom could become a Frog Zero for a real project and real client in Hawaii. Succeeding at this, we developed an optimal Frog Zero design for three more climates (San Francisco, Boston, and Los Angeles). Phase III focused on the design and performance of three custom Frog Zero projects for specific clients and site locations: the 2008 Greenbuild Frog Zero Demonstration Classroom in Boston; the Watkinson School in Hartford, Connecticut; and the temporary Crissy Field Center in San Francisco. In parallel, Phase IV developed a methodology to identify the smallest number of design options required to provide full comfort at net-zero energy throughout an entire region characterized by varied climate conditions.

What evidence was created in the investigation to inform the design process?

PHASE I: PROOF OF CONCEPT FROG TO FROG ZERO—THE HAWAII NET-ZERO CLASSROOM We began investigating whether net-zero energy and carbon emissions were actually possible with a Frog platform by modeling design alternatives for a single classroom in Hawaii to meet energy use, daylighting, and thermal comfort standards set forth in a State of Hawaii competition. Energy Plus modeling software and Radiance daylighting software were used parametrically to optimize the design and for low-energy performance, high-quality interior daylight, and air movement and thermal comfort. A wide range of alternatives was modeled to determine the envelope characteristics, including aperture sizes, shading and overhangs, insulation levels, glazing specifications, natural ventilation rates, operable window areas and locations, daylighting illumination levels, and distribution and luminous maps for contrast ratios. Once the classroom was performing passively, we designed an added radiant cooling system and sized a photovoltaic array to bring the performance to 100 percent thermal comfort throughout the school year and net-zero carbon emissions. The research results were part of the competition submission and included:

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C A S E S T U D Y P R O J E C T: F R O G Z E R O

Figure 2.18 Model of Interior Daylight in Frog Zero

Figure 2.19 Indoor Air Movement and Thermal Comfort Frog Zero

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 Thermal comfort is provided for all but 13 hours of the 200-day school year using

shading and natural ventilation with no mechanical cooling.  Thermal comfort can be provided for 100 percent of school year hours with the

CASE STUDY PROJECT / Frog Zero

use of an inexpensive radiant cooling system in the floor slab.  The classroom is 100 percent daylighted for all the days of the school year, under

all sky conditions, with the exception of 218 hours in the early morning hours of winter when the classroom regularly delivers over 60 footcandles of daylight on all the teaching surfaces and delivers to an average high of over 80 footcandles.  To achieve net-zero energy use will require between 7 and 23 roof-mounted PV

panels depending on hours of use of the mechanical cooling.

PHASE II: ANALYSIS METHODOLOGY APPLIED TO MULTIPLE CLIMATES In Fall 2008 we developed our previous research methods to produce optimized designs and performance analyses for four climates: Boston, Honolulu, Los Angeles, and San Francisco. The first step was to use parametric simulations to optimize the daylighting performance of the classroom in each climate, working with design alternatives in building orientation, aperture size and location, glazing specifications, shading strategies, interior finishes, and space planning. Once the daylight was performing as well as possible for each climate, elimination parametrics were run in Energy Plus to determine the building factors (envelope, mechanical, and operational) that were most effective in reducing energy use and increasing comfort. With the design factors identified in the elimination parametrics, a suite of building design options was developed specific to each climate. The energy analysis was run to quantify the additive energy reduction produced with the addition of each design alternative, producing an optimized Frog classroom for each climate. Every Frog option, from baseline to optimized, is a Frog Zero, but the size of the PV array required to achieve netzero changes significantly as a measure of the effective performance of the design. To convey the increasing performance of each Frog option as the suite of sustainable features was put into play, we developed two graphical series of data charts as shown in Figures 2.20 and 2.21: 1. Full graphical dashboards—As one moves through the recommended design options in the suites, the successive charts visibly change, demonstrating

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CASE STUDY PROJECT / Frog Zero

Figure 2.20 Frog Zero Elimination Parameters of Boston

Figure 2.21 Frog Zero Elimination Parameters of Honolulu

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CASE STUDY PROJECT / Frog Zero

Figure 2.22 Frog Zero Building Options— Optimized Shading in Boston

Figure 2.23 Frog Zero Building Options—Exterior Active Shades in Honolulu

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the effect of each additional alternative. The design options are identified by icons along the bottom. The annual hourly graph illustrates hours of cooling (blue dots), hours of heating (orange dots), and hours of passive mode (white dots). The overall bars of energy use are highlighted for that option and the cooling and heating energy have labeled dashboards. Additionally, as a quick visual metric, the birds-eye view of the PV array decreases in size as the energy demand decreases. 2. Annual hourly performance—The annual hourly heating (orange) and cooling (blue) demand are graphed as dots of energy intensity. As one moves successively through the added design options, the passive performance of the building increases—read in the amount of black space in the chart—and the amount of heating and cooling demand is visibly sequentially reduced.

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C A S E S T U D Y P R O J E C T: F R O G Z E R O

Figure 2.24 Annual Energy in Boston—Building Options Plus Floor Insulation

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CASE STUDY PROJECT / Frog Zero

PHASE III: CUSTOM ZERO FROGS FOR SPECIFIC SITES AND CLIENTS Turning from broader analytical techniques, we worked with the Project Frog team to optimize the design and performance of three Zero Frog projects: the 2008 Greenbuild Frog Zero Demonstration Classroom in Boston; the Watkinson School in Hartford, Connecticut; and the temporary Crissy Field Center in San Francisco. Greenbuild. Based on the Boston analytical work, the Greenbuild demonstration building was designed to operate as a temporary demonstration building located at the entrance to the Boston Convention and Exhibition Center. Under a giant overhang on the northeast terrace, the Frog Zero was constructed and furnished in one week and served as a seminar and presentation venue open to the 30,000 people who attended the 2008 conference. Watkinson School. A new Center for Science and Global Citizenship at the Watkinson School in Hartford, Connecticut, is the first Frog classroom in a cold climate. The 4,000-square-foot school will feature three flexible classrooms that can morph into lecture, seminar, or lab instruction spaces. The project, slated for LEED silver or better, includes a ground source heat pump, abundant daylight, and a photovoltaic array. It is designed to reduce energy demand by 75 percent over a base-building design. Crissy Field. The interpretive center for a National Conservancy, the Crissy Field Center requires a temporary facility while state construction impacts the current center. We worked with Project Frog to develop the off-the-grid Frog Zero to house this center in the San Francisco shoreline climate. Figure 2.25 Daylighting Simulation—Crissy Field Center Frog Zero

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Looking to a larger field of operations than single custom structures, the architect asked us to find a method to identify the smallest number of design options required to provide full comfort at net-zero energy throughout an entire region characterized by varied climate. Building on Phase I, we selected a test region in which the regional climate variation could be characterized by four locations and developed an optimal design for each climate using the following methodology: Figure 2.26 Crissy Field—Weather Data Frog Zero

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The energy consumption and occupant comfort were parametrically modeled and then a deterministic, quantitative multi-criteria decision model (MCDM) algorithm was constructed to weigh the relative importance of cost-effectiveness, energy use, and occupant comfort. Cost-effectiveness was used as a primary variable because for

CASE STUDY PROJECT / Frog Zero

PHASE IV: REGIONAL VARIATION IN FROG ZERO SOLUTIONS

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an energy-generating facility it is an excellent proxy for energy efficiency without diminishing returns. Based on these criteria, a series of components and systems were remodeled in order to engineer an optimized configuration for each climate.

CASE STUDY PROJECT / Frog Zero

What were the outcomes of the investigation? The process included modeling of each viable structural or material passive design strategy. Nine primary parameters were varied, including: orientation, wall insulation, roof insulation, thermal mass, shading, three areas of glazing, and a ventilation area. The first step in the two-part process is to narrow the options for the nine parameters considered as selectable in the suite of options for the configuration of the structure.

Figure 2.27 Mass Ventilation, Shading Data Frog Zero

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C A S E S T U D Y P R O J E C T: F R O G Z E R O

Figure 2.28 Optimized Rankings

In the 3D graph mass, ventilation and glazing options were run for one climate. Larger bubbles indicate greater cost-effectiveness. Red bubbles are more energy intensive while green bubbles are less energy intensive. This 2D graphs are slices of the 3D analysis shown in Figure 2.27, and compare two of the three variables at a time (mass and ventilation, shading and mass, and ventilation and shading) focusing on cost. Darker green indicates greater cost savings. The areas in red indicate the best choices. The second step in the two-part process is to complete a final set of simulations in a 9D matrix of all of the top combinations of options from the analysis in step one. This data is presented in a simple scatter chart plotting energy use against costeffectiveness (defined as the total construction cost increase from baseline, less the cost savings due to a reduction in the size of the required PV plant). The optimal choice is indicated by the brown square marked 1. Green indicates highly suitable; yellow is less suitable.

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CASE STUDY PROJECT / Alternatives of Compressive Cooling

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C ASE S TUDY P ROJECT Art Center College of Design Alternatives of Compressive Cooling Susan Ubbelohde and George Loisos Loisos + Ubbelohde Architecture—Energy DalyGenik Architects

Figure 2.29 Massing Model Student Housing Art Center College of Design— Pasadena, California

If the building is a thermos bottle, no matter how efficient, every variation in interior and exterior climate must be handled by an active use of energy. If the system fails, the building rapidly loses its ability to provide comfort, exceeding comfortable temperature ranges and having stifling, unfresh air.

What was the research or critical question in this project? In the hot summers of Pasadena, to build without air conditioning, still provide comfort to the residents, and to express the climate response in the building envelope developed as the appropriate sustainable performance goal—challenging but maybe achievable. The resulting design approach considered the programmatic, architectural, structural, daylighting, solar control, and thermal performance issues together as generative issues rather than treating them as isolated engineering problems to be solved later in the design process.

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Figure 2.30 Student Housing Facade Study 1: Art Center College of Design— Pasadena, California

Figure 2.31 Student Housing Facade Study 2: Art Center College of Design—Pasadena, California

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C A S E S T U D Y P R O J E C T: A LT E R N A T I V E S O F C O M P R E S S I V E C O O L I N G

Figure 2.32 Student Housing Facade Study 3: Art Center College of Design—Pasadena, California

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The program for student housing for Art Center College of Design students provided for a flexible living environment with flow-through ventilation, daylight, and balconies. There were layers of occupant control of daylight, air, and sun; 11 live-work studios and retail on the first floor and 211 single units on the above six floors, each open-plan, 10-foot x 26-foot with prefabricated service core. This student housing project reaches into a funded research program for the basis of the sustainable design approach. The initial research program produced marketfriendly demonstration houses that lowered energy performance by reducing or eliminating air conditioning. For this student housing project, the architects were interested in developing an approach to sustainability that would capture the students’ imagination and deliver a memorable and adventurous building for the college. Site planning and campus planning concerns generated an organization with the long axis of the housing running north-south with rooms facing east-west, the most difficult orientations for solar control and thermal comfort. While not ideal, this provided an opportunity to rethink the units as well as the building structure and envelope, generating a far more creative and integrated approach to what the housing units might be.

What were the research or investigative methods used in this project? The research for this project began nearly a decade earlier with a multiphase, multiteam program titled “Alternatives to Compressor Cooling for California Transitional Climates” (the ACC Project). Developed and funded initially by the California Institute for Energy Efficiency, the ACC project was conceived to offer an alternative house design to the residential building industry of California.

Figure 2.33 Energy and Daylighting Demonstration House—Pasadena, California

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For the ACC project, a design workshop produced an initial set of house designs and cost estimates which were then reviewed by developers and builders. Comfort and energy use simulations were used to optimize building technologies and to define the climatic range of application. The design most representative of market trends was taken through design development, including complete mechanical and structural design. Phase V was completed in 2003 producing two California demonstration houses based on Phases I through IV of the research built by residential developers: a house in Watsonville and one in Livermore. The houses were fully monitored and perform in line with, and at times significantly better than, the simulation predictions.

Figure 2.34 Massing/Circulation Model: Student Housing Art Center College of Design—Pasadena, California

The performance simulations and the subsequent monitored performance of the ACC demonstration houses in Livermore and Watsonville helped us to conceptualize a design approach and then to model the performance of the Art Center College of Design Student Housing project which relies on high mass, natural ventilation, adequate shading, and night ventilation to avoid air conditioning in the dorm rooms. The sustainability of the Student Housing design is integral to the architectural massing and orientation of the complex, which depend on the unit design.

CASE STUDY PROJECT / Alternatives of Compressive Cooling

C A S E S T U D Y P R O J E C T: A LT E R N A T I V E S O F C O M P R E S S I V E C O O L I N G

The concrete frame and sheer walls provide interior, shaded thermal mass critical to maintaining comfort during summer days. Crucial to the entire sustainable performance is the decision to use the single loaded corridor, with exterior circulation access on one side of the unit and an exterior balcony on the other side. The required shading on the west balconies is also the lateral bracing for seismic loads, ensuring that the thermal performance of the building will survive value engineering and remain visible to the campus.

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CASE STUDY PROJECT / Alternatives of Compressive Cooling

What evidence was created in the investigation to inform the design process? The Path Not Taken: Technological Sustainability In a normative student housing complex, the double loaded corridor provides each unit with only one exterior wall. To deliver energy efficiency, this configuration requires a suite of design strategies that separate the interior from the exterior world. These strategies:  Minimize the connection between inside and outside for minimal heat transfer  Minimize the volume of the units  Make the use of natural ventilation very difficult  Minimize the introduction of daylight and sunshine  Require mechanical conditioning (air conditioning and heating)  Use efficient mechanical conditioning to keep the unit within a static comfort range  Orient each unit to a singular quality and rhythm of light: morning sun, afternoon

sun, winter sun, or north diffuse light

Figure 2.35 First Floor Plan: Student Housing Art Center College of Design— Pasadena, California

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The resulting housing unit delivers a quality of life more typical of Chicago or Toronto than of Pasadena: a contained and controlled interior that acts as a refuge from the outdoors and the outside world. The energy efficiency and sustainable performance are achieved invisibly and by disconnecting the unit and the occupants from the aspects of the design that are working: insulation in the walls, the high EER air conditioning, and solar control in the glazing. As David Orr 1992 describes in Ecological Literacy, this approach of relying on technology may achieve measurable sustainable performance, but does so without educating those involved and without connecting them to place or their behavior to environmental consequences.

What were the outcomes of the investigation? The Design Concept: Ecological Sustainability The single loaded corridor gives each unit two exterior walls and the design concentrates the dense services and utilities into an efficient core providing separation of the living areas, one unit from another. With two exterior walls, the energy-conserving strategies can emphasize a controlled and variable connection between the inside and the outside, utilizing the natural site energies.

CASE STUDY PROJECT / Alternatives of Compressive Cooling

C A S E S T U D Y P R O J E C T: A LT E R N A T I V E S O F C O M P R E S S I V E C O O L I N G

Figure 2.36 Axonimetric Unit Plan of Art Center: Student Housing Art Center College of Design—Pasadena, California

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Figure 2.37 Section Axonimetric Plan of Student Housing Art Center College of Design—Pasadena, California

These strategies include:  Ceiling height for admitting daylight deep into the unit and optimal air movement  A concrete floor with thermal mass and radiant heating/cooling that keeps the

interior cool in the summer and warm in the winter  Interior ceiling fans to create air movement for summer comfort  An operable first skin, the glazed weather skin between inside and out, to admit

daylight and enable cross-ventilation  A second skin at the edge of the balcony that controls daylight and sun penetration  Green roofs for lower blocks and PV shaded roofs for high blocks

The resulting units are connected to the exterior world and have layers of control that are operated by the occupants. The width of the balcony provides an outdoor room as an amenity, presenting a screened and identifiable public face to the street while still admitting filtered sun and daylight to the interior of the unit. The student can close up the layers and retreat to the interior or open up to the outside as desired. The orientation of the units is based on an equality of access to sun. Units that face only north or south deny half the occupants access to sun, while units that face east and west reconnect everyone to the daily cycles of morning and afternoon, sunrise and sunset. The combination of the first and second skins, as well as the cross-ventilation and radiant floors, enable the occupant to control the hot sun of the summer afternoon and maintain a comfortable interior.

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Equally as important, the design makes sustainability a rhythmical and conscious part of life, not a matter of deprivation and dislocation. The balcony, the large windows, the operable windows, and the ceiling fan all serve to make the architecture and the occupant the agents of sustainable performance rather than hidden technological fixes and machines. As David Orr describes, with an ecological sustainable approach, nature is used as a model and architecture becomes complicit with its cycles and conditions. Building occupants become responsible agents of sustainability in their behavior and understanding of place.

BUILDING PERFORMANCE: ENERGY EFFICIENCY Figure 2.38 EnergyPerformance Data: Student Housing Art Center College of Design—Pasadena, California

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In comparison to current Title 24 student housing, the Concept Design significantly reduces energy use due to the carefully orchestrated climate-responsive architectural strategies described above and the efficient ground source conditioning system. By providing thermal mass, radiant floors, cross-ventilation, shading, and daylighting, the units require minimal heating and no air conditioning.

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In a climate such as Pasadena, it is not immediately evident that a typical student housing scheme would require air conditioning, but once the units are organized in a double loaded corridor, cross-ventilation is difficult to provide and occupant comfort is hard to achieve through passive design and climate response. A documented case is the Stanford Graduate Housing complex, in which the units were neither cross-ventilated nor air conditioned, and were poorly shaded, resulting in uninhabitable conditions for the students. We have developed a comparison of the thermal performance and energy use of a current Title 24–compliant student housing complex of equal size and number of units with the Concept Design. DOE 2 was used for an hour-by-hour annual simulation. The concept design reduces the annual energy cost by approximately $33,000 per year, which represents a savings of 49 percent over the standard (base) design.

BUILDING PERFORMANCE: OCCUPANT COMFORT AND THE CONCEPT OF GENTLE FAILURE The typical conception of an energy-efficient building is based on the behavior of a thermos bottle, in which a well-insulated envelope creates a barrier to heat transfer between inside and outside. This allows the interior to be kept at a comfortable condition with a small amount of energy used to heat and cool the bubble of air trapped inside the thermos. The concept design, in contrast, is based on an approach to occupant comfort more like that of an Italian villa. The interior surfaces (especially the floor) are thermally massive and provide a dampening to the outside temperature swings over the course of a day, remaining warm or cool in relation to the air temperature as desired. By providing a warmed or cooled surface area, comfort is delivered through the Mean Radiant Temperature (MRT) of the surrounding surfaces, rather than primarily through the air temperature. The occupants will be equally comfortable at lower air temperatures and the radiant floors are heated and cooled by a highly efficient ground coupled system. The thermal mass is the main thermal battery that provides comfort while the lightweight exterior walls admit sun, air, and daylight as desired. Cross-ventilation achieved through operable windows effectively introduces fresh air and exhausts heated air, keeping the units cool in the summer. Ceiling fans introduce air movement, expanding the comfort zone as high as 82 degrees Fahrenheit.

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Figure 2.39 Axonimetric Model: Student Housing Art Center College of Design—Pasadena, California

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If the building is a thermos bottle, no matter how efficient, every variation in interior and exterior climate must be handled by an active use of energy. If the system fails, the building rapidly loses its ability to provide comfort, exceeding comfortable temperature ranges and having stifling, unrefreshed air. If a student leaves the window open in a “thermos bottle building,” energy must be used to overcome the unplanned and detrimental thermal connection to the outdoors, whether it is winter or summer.

CASE STUDY PROJECT / Alternatives of Compressive Cooling

C A S E S T U D Y P R O J E C T: A LT E R N A T I V E S O F C O M P R E S S I V E C O O L I N G

However, because comfort is delivered through the architectural elements of the unit, the unintended connection of inside to out will affect only the comfort of that unit and not the energy use of the building overall. Similarly, the building can perform through blackouts or other mechanical failures with a very slow decline in occupant comfort. This is what we mean by a “gentle failure.” Other than during periods of outright failure, this approach allows the mechanical systems to affect the interior spaces slowly, working less often and less strenuously when they do so. This prolongs the life of the system while delivering increased comfort.

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CASE STUDY PROJECT / Apple Store Fifth Avenue—Daylighting Simulation Research

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C ASE S TUDY P ROJECT Let There Be Light and Energy Apple Store Fifth Avenue—Daylighting Simulation Research Susan Ubbelohde and George Loisos Loisos + Ubbelohde Architecture—Energy

Figure 2.40 Glass Box Lobby—Apple Fifth Avenue, NY

A glass cube poses significant thermal and luminous performance challenges. Using site analysis and daylight simulation tools, we help architects to understand the performance of their design proposal and to fine-tune the initial design without substantially altering the overall design direction.

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What was the research or critical question in this project? This case study presents the use of advanced daylight simulations in the design of the glass cube Apple Store located on Fifth Avenue in Manhattan. A glass cube poses significant thermal and luminous performance challenges.

What were the research or investigative methods used in this project? Using site analysis and daylight simulation tools, we helped the architects to understand the performance of the design proposal and to fine-tune the initial design without substantially altering the overall design direction.

What evidence was created in the investigation to inform the design process? The glass cube proposed in this project suggested that there would be a significant amount of solar radiation, glare, and daylighting control issues, which could potentially impact the visual and thermal comfort of the retail floor. Evidence was created through simulation and modeling technologies allowed for understanding the performance outcomes in various proposed design solutions within these specific environmental conditions.

What were the outcomes of the investigation? The simulations helped establish the relative freedom for the design to go forward and helped to inform the glazing specifications and the thermal and luminous design strategies for the store.

CASE STUDY PROJECT / Apple Store Fifth Avenue—Daylighting Simulation Research

C A S E S T U D Y P R O J E C T: D A Y L I G H T I N G S I M U L A T I O N R E S E A R C H

How should education change to better serve both the students’ professional goals and the goals of the profession? I teach a course that provides the students the exposure and experience they would get in real-world practice. Their response to the course is very positive and it is clear that the notion of evidence-based evaluation performance outcomes is an important component of their preparation for practice. This may not be the total answer, but I am convinced that these types of exposure and practice sessions are better strategies than a comprehensive curriculum that tries to incrementally address these issues teaching evidence-based practice as it integrates the experience into their normal design agendas of making enriching, beautiful spaces and environments for people to inhabit and experience.

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CASE STUDY PROJECT / Apple Store Fifth Avenue—Daylighting Simulation Research

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In 1998 Susan Ubbelohde and Christian Humann, both now at Loisos + Ubbelohde, completed a funded research project through the University of California, Berkeley, that developed a comparative evaluation of daylighting predictive software from the perspective of architectural and daylighting design practice. A contemporary building completed in 1993 by the Office of Stanley Saitowitz was used as a base case for evaluation. Field measurements, software predictions, and physical modeling were used as a basis for asking: To what extent can a designer successfully predict the quantity and distribution of daylight in an unbuilt design and see what the daylighted space will look like? Of the four simulation packages investigated, the Radiance software developed by Lawrence Berkeley National Lab proved to be the most accurate in predicting illumination levels and in producing accurate renderings of the daylighting conditions in the space. With a steep learning curve and input protocols that require significant commitment to learn, this software is generally not possible to run in-house by any but the largest design firms that can afford specialized personnel. However, we have demonstrated that the Radiance software has a strong record in predicting performance outcomes on large and small projects.

Figure 2.41 Saitowitz Office—Real Building Radiance Condition in San Francisco

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Figure 2.42 Saitowitz Office—Model of Building Radiance Condition in San Francisco

CASE STUDY PROJECT / Apple Store Fifth Avenue—Daylighting Simulation Research

C A S E S T U D Y P R O J E C T: D A Y L I G H T I N G S I M U L A T I O N R E S E A R C H

Figure 2.43 Saitowitz Office— Lumen Study in San Francisco

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CASE STUDY PROJECT / Apple Store Fifth Avenue—Daylighting Simulation Research

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Figure 2.44 Facade Glass Cube—Apple Store on Fifth Avenue, NY

A follow-on research study shared between Karen Carrier, a graduate student at Berkeley, and our practice further calibrated the Radiance software onsite measurements and physical models tested in a mirror-box artificial sky. The design used for comparison was an earlier Apple store in Los Angeles featuring a south-facing curtain wall and a large structural-glass skylight. Apple was interested in an elegant and visually striking design for the landmark store on Fifth Avenue—New York’s answer to the Louvre pyramid. The retail area of the store is located underground, beneath the redesigned plaza. The glass cube was proposed as an entryway that connects the plaza to the retail area below with a spiraling glass stair and a cylindrical glass elevator. As noted earlier, a 10-m x 10-m glass cube can gather significant amounts of solar radiation and daylight, both of which could potentially impact the visual and thermal comfort of the retail floor. These performance issues, coupled with concerns about potential glare conditions, prompted a careful examination of the performance of the glass cube.

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Figure 2.45 Interior Stair—Apple Store on Fifth Avenue, NY

We began by examining the solar impact on the selected site using a fisheye photograph overlaid with a sun path for that specific latitude and longitude. This indicated that direct sun will enter the cube during noon (lunchtime) hours from March through September and for a few hours in the summer afternoons.

CASE STUDY PROJECT / Apple Store Fifth Avenue—Daylighting Simulation Research

C A S E S T U D Y P R O J E C T: D A Y L I G H T I N G S I M U L A T I O N R E S E A R C H

Crucially, the canyon conditions of the site protect the cube from many hours of direct solar radiation throughout the year, which helps keep it from being simply a greenhouse collecting solar energy. We also used the fisheye photographs to check the accuracy of the 3D Radiance model. Radiance simulations were used to characterize both the levels and distribution of daylight illumination in the retail level under extreme sunny and overcast conditions. Noting the patch of direct sun that falls under the glass stair, the store was organized to use that area as a circulation and social area. Products for demonstration and sale are appropriately located in the less-daylighted areas of the store, enabling comfortable visual inspection while shoppers and employees can still sense that the sky is nearby.

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CASE STUDY PROJECT / Apple Store Fifth Avenue—Daylighting Simulation Research

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When we first work with a client it seems as if they think that what we will do will constrain and limit their options in terms of creative or innovative responses to a project. They generally come to us when they have a problem to solve that they seem not able to resolve. We are careful to respond to them in a manner that tries to give them a ground to work from that frees options. This takes the form of questions and alternatives which open up a dialogue about what the opportunities are. Once we get through this process then, in most cases, the clients see the challenges and the opportunities and work with us to maximize the creative potential. The evidence really becomes a way of opening up possibilities rather than limiting them. Figure 2.46 Fifth Avenue Sun Study for the Apple Store, NY

Figure 2.47 Radiance Sky Study for the Apple Store, NY

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Projects come to us in many forms. Some have conditions and constraints that the limits of physics cannot solve. Others come to us with an open mind about what is needed and a clear understanding of the limits and then we can work with them to find the potential in terms of performance outcomes, whether it be energy, light, comfort, etc. The reason why this works is less about process and evidence, but about the attitude of what is to be accomplished. We approach our work as designers so aesthetic consideration is always important to us. The Apple store is a daylighted space with the variation of sun movement and weather that creates delight for building occupants. The high, luminous gradient between the daylighted area and the back of the store is mediated with a continuous luminous “clerestory” that alleviates the sense of being in a cave by lighting the back wall.

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 Figure 2.48 Radiance stair model overcast sky Apple Store NY

 Figure 2.49 Radiance Stair Model Simulation Clear Sky Apple Store NY

 Figure 2.50 Radiance Stair Plan clear sky Apple Store NY

With the results from the site analysis and radiance simulations coupled with a strategy developed for local conditioning of the entryway, the glazing of the cube did not have to be spectrally selective—the default advance glazing for admitting daylight while minimizing heat gain. The structural glazing for the cube could then be specified as extremely clear, low-iron glass in order to achieve the transparency originally desired by the design team.

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CASE STUDY PROJECT / Apple Store Fifth Avenue—Daylighting Simulation Research

C A S E S T U D Y P R O J E C T: D A Y L I G H T I N G S I M U L A T I O N R E S E A R C H

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SHoP INTERVIEW William Sharples / Christopher Sharples Use technology to build practice; see practice as technology. Make the office a lab, a boardroom, theater, and a classroom. Make concepts buildable, make buildings conceptual. How it’s built doesn’t matter except when it is the only thing that does matter. Push design, embrace responsibility.

RESEARCH BACKGROUND

SHoP INTERVIEW

Figure 2.51a William Sharples

Figure 2.51b Christopher Sharples

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SHoP Architects, a 60-person practice, was founded by its five principals in 1996. SHoP has been a leader in the transformation of intricate theoretical design into easily understood construction models by rethinking architectural practice. This think tank has pushed the designer’s realm past form-making and into software design, branding, real estate development, construction, and the co-development of new sustainable technologies. As both practitioners and educators, their commitment to challenging the entire process of building has proven to a generation of architects that beauty and technological proficiency are not mutually exclusive. Their current work includes a two-mile waterfront park along New York’s East River; several projects for the Fashion Institute of Technology in Midtown Manhattan; a major bank near “Ground Zero”; and for Google in Mountain View, California. Recently completed projects include Garden Street Lofts in Hoboken, New Jersey; Hangil Book House in Seoul, South Korea; The Porter House in New York City; and SanLiTun in Beijing.

What makes computational technology unique in your practice today? “Use technology to build practice; see practice as technology.” There are a couple of ways to look at this question. Digital technology was first introduced into architectural practices as a substitute for other means of representing mostly 2D information, not much different than

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when we used drafting machines and other manual tools to make drawings and other documents. Our take on this was that the use of digital technology in the early phases was not moving our practice forward in a direction that interested us. We seemed to just use more paper, but recorded the same information. How we did find it helpful was in supporting our efforts to use a 3D format to coordinate with other consultants and entities with a vested interest in the project. The documents could be transported and visually communicated much more effectively. As we explored this more, we discovered that there were a number of types of software in the marketplace that could help us not only manage complex forms using parametric modeling but that could also play an important part in coordinating the process with the people who were going to build what we designed. This whole concept of a building information model (BIM) became a means for us to share information, both 2D and 3D, with the client, builder, and other stakeholders in the project. It really allowed us to take back an important role that had traditionally belonged to the architect, that being managing the process for translating the design to make it buildable. It allowed us to develop a collaborative and social environment in which there was a sense of multiple ownership for what we were working on around the issues related to how can we get this built, get regulatory approval, etc.

Our workflow processes take a project from conceptual design sketches to the physical models, translating these outcomes into digital data, and creating a file that can be tracked and shared as the project evolves. We do not conduct just one exploration or approach, but several alternative approaches taking place in parallel using different parameters, drivers, methods, and directions. It is a little like how “new math” is now taught in elementary schools where there are multiple ways to solve a mathematical situation. This is how we see our practice working, seeking multiple ways to resolve our design and construction challenges and problems. If we look at the applied technology group in our office, we find they use multiple platforms to create feedback loops about the design. They might start with Rhino and AutoCAD to explore a basic schematic program layout and spatial configurations. Then they move to Digital Project, Generative Components, Ecotech, and Revit

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SHoP INTERVIEW

We are a practice-based office and not committed to any one design method, process, style, or system of operating, including tools and software. We approach each project with fresh eyes. We seek to have each of our projects evolve in its unique form through a dialogue with others so that there is an open feedback mechanism that keeps all of the people with a stake in the project actively involved, sharing and improving the design and how to build the outcome.

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to explore specific complex geometric conditions to set spatial design parameters— the amount of material it takes to build it so they can be tested and performance outcomes can be evaluated. Fundamentally this is a process that has constant feedback loops within multiple software programs informing and checking outcomes across these different platforms. We spend a fair amount of time working with Autodesk because they seem to be leading this approach by integrating various software components into a more comprehensive modeling and simulation software referred to as building information modeling (BIM). At the same time, we are concerned with finding ways to archive the outcome data not only for ourselves, but also so that our clients and consultants have access to using and understanding how the project is evolving. We want the archiving to have the ability to adapt and evolve as the project moves forward through each of its phases. The way we work seems different when we talk to others who are involved in the A & E professions where a single approach is the standard. We want to have a fluid approach and an open frame of reference for all of our projects. This presents significant challenges in the normal process of our practice because we do have to deal with contracts, issues of liability and risk, and means and methods of construction that require very specific and focused responses. The important thing that we are finding through our process, however, is that we are reaching into areas of service for the architect that have not been under the profession’s control for 40 or 50 years. This makes practice really exciting and at the same time challenging for us.

How does this approach impact the role of creativity in your work? “Make the office a lab, a boardroom, theater, and a classroom.”

SHoP INTERVIEW

In the traditional model we found that we were spending 5 to 10 percent of our time on creative agendas and 90 to 95 percent of our time on managing the workflow between owner, builder, and our own consultants. We are looking for ways that technology can streamline this process and let us spend more time on creative efforts.

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Our practice is not a top-down model. We have a mix of very experienced architects and younger designers just out of school with little practical experience. We find these younger staff members bring many new skill sets to our design process, and we see this impact specifically in the computational technology arena. It is not unusual to have a person feel quite comfortable and be proficient in 10 or 12 different software programs and to have very strong design process and problem-solving skills. What we normally do is match these new people with one of the more expe-

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rienced people in the office, which almost immediately creates a dynamic, collaborative, and transparent work process. This helps foster an environment that seeks innovation and creative ways to integrate and utilize new skills and knowledge throughout the design process, and increases not only the time spent in creative thinking and acting, but also in producing innovative results in most cases. This way of working and its associated process of interactions is critical to the practice and business model of the firm. An example for us is that using software like Revit early in the design process allows us, almost from the beginning, to do quantity take-offs for costing on the project. This gives us a lot of information to control and direction on how to move along the design process and project. We have a sense of control knowing the implications of the cost of specific design strategies and decisions. When this approach is framed in a culture of problem-solving that is parameter-based and metric-driven, we are able to have solid evidence to guide each of the parameters embedded in the project and the outcome implications in each of our solutions.

It appears that software plays an important role in your office. How do you keep the software from taking control of the design? This is a concern, but what we have learned is that there is a range of interests in the use of the various software programs by individuals in the firm. Some are challenged by very specific project needs or aspects—the details or components—while others want to use the software to explore the broader concepts of the projects.

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SHoP INTERVIEW

In general, about one in ten designed projects actually gets built. When a project is stopped at Schematic or Design Development stage, it is disappointing, particularly for younger staff who are eager for construction experience. With BIM, we can do virtual and physical prototyping at any point in a project, exploring in a rigorous manner not only the details but also the means and methods for building. This iterative process not only allows for evolution of the design but allows us to continually critique that design against the proposed criteria. Because we are using 3D visualization we can address conflicts and resolve detail conditions prior to construction. This approach, as a result, provides important building experiences and design knowledge for both the newer and older members of the firm. It also allows us, even if the project is not built, to have an archive of data and documents that can be used in one of our next projects. The capacity of these live models to inform design decisions on current and future projects is exciting. This process has established a way that the design knowledge of the office is captured, archived, and reused.

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Several are interested in the research and development potentials of how the software can be used and improved. We try to let the staff gravitate to their areas of interest, but, of course, we do have to get the work done so there is some specific focus on the primary task of architecting. Our basic approach is one of learning by doing rather than formal training programs or just a menu or manual-driven learning process. We typically test new software to address some specific type of task in the office or on a specific project. If it works, we adopt the application as part of the process. If not, it is discarded, and we look for new ways and processes to do what is needed.

How has the use of these computational technologies impacted what you think of the standard stages of project delivery—schematic design, design development, construction documents, construction administration, etc.?

SHoP INTERVIEW

This has been a very interesting process for us. As we all know, the Integrated Project Delivery methods are slowly becoming the standard in the profession. As such, there is an expectation through this new delivery process that there will be overlaps in the phases of a project. For us this type of compression is very real. We are always doing design, no matter what phase the project might be in. After preliminary sketching and diagramming to define the primary design constraints we begin to model the project in a digital format. This is typically done first in a “sketch” model (such as Rhino). When the design criteria are more fully established, we will transfer into one or more parametric modeling platforms (such as Revit and Digital Project), which allow us to address issues of constructability, cost, and performance. The simulations and virtual models used in our process are shared with the other disciplines involved in the project. An immediate dialogue begins with the contractors, clients, consultants, and regulators who then have an opportunity, early in the project, to challenge proposals and make recommendations in all of the delivery phases. This tendency to draw issues like constructability into a schematic design can now be modeled and tested, providing valuable performance outcomes that influence the direction of the design.

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There are two areas where using these live models grounded in BIM are really useful and exciting. Both are client-based. First, because models are more visually accessible and comprehensible to the layperson than technical drawings, it is easier for the client to grasp the performance and cost implications of specific design strategies and proposals. This is critical not only to getting the client’s approval of specific proposals, but it also allows the client to have direct dialogue with the other stakeholders in how to resolve specific needs and requirements, set performance limits where needed, and have a much clearer image of what the physical nature of the project will be when

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constructed. The second area that is just now becoming a part of the BIM process is the facility management service potentials available after the project has been commissioned. An “as-built” digital model gives owners direct access to how each of the systems in the building performs, how to operate each of these systems, and what needs to be done to maintain the systems. In the big picture, the BIM system is the archive where all the data is warehoused from the beginning of the project through the lifespan of the building. If the data is archived properly, this design knowledge becomes an opportunity for all types of data mining that can inform our design processes on future work. We can create a continuous feedback loop, adding critical knowledge and experience to SHoP’s working methodology. It will also impact the way the larger industry of design, construction, and operation of buildings is handled in the future. This means there is a potential here for a building to get better over time by renewing its uses, systems, and other components based on solid performance of Building Monitoring Systems, producing critical data that allows the owner to see how the building is performing over time and to make changes when necessary to maintain optimum programmatic and environmental performance. The advantage of utilizing the BIM’s open architecture for facilities management will allow owners to incorporate future upgrades, creating a more sustainable form of building for a ever-changing demands.

In the traditional model, the architect of record owns the design data and associated risk, and the contractor and subs own the shop drawing data, means and methods, and that associated risk. A lot of energy goes into delineating and limiting those risk boundaries. Because the integrated delivery approach is collaborative from the beginning, all the stakeholders hold responsibility for all the data in the model and share in the risks resulting from the project. These relationships are based on trust built up over time by engaging in a collaborative and socially constructed set of decisions shared by all. We know that this represents a big change in the way most practices operate. It is a very big landscape we are working within and it is sometimes scary, but it is our experience that if the process is open, shared, and documented, making it increasingly transparent over time, trust will be developed through the social process of interaction, and everyone will understand the prime objects of the design and construction process and will be able to share in the risks. We think, “If you drink the ‘Kool-aid,’ you will become by this highly interactive and collaborative process even more responsible.”

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SHoP INTERVIEW

It is clear that you have redefined the nature of the practice model, one that is a much more open and shared process, raising questions about who owns the data and the resulting risk.

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SHoP INTERVIEW

We use a story, which I think demonstrates what we mean. It is based on putting together a piece of IKEA furniture. In the United States you would put the piece together yourself using the instructions and accepting the outcome. In Germany you would get a neighbor to help you put it together, and you both would share the risk. In Scandinavia, however, you would have a party and have all of the people attending put the piece together and then no one would remember who was responsible for the risk, so everyone would share in it equally. This change in attitude about risk is really about shifting a cultural attitude about collective, shared risk for our actions in a collaborative process that is socially constructed.

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This is a complex matter in terms of defining the business model of our firm. We still, from an internal business management perspective, monitor our services around the typical phases of a project—schematic design, design development, etc., but what is different for us is how we define the scope of services within each of these phases. By using the integrated project delivery model connected to the use of computational tools to define, explore, document, and measure performance and prototype outcomes, we are able to define the scope of services within each phase, allowing us, from a business operations standpoint, to transfer resources across phases, either to earlier phases or later phases in the project, where the work needs to be done at a particular moment based on the particular needs of that project and not where it traditionally has been done. For example, using resources to explore detail development, costing, and constructability issues in earlier phases, rather than waiting for a later phase of the project where it would normally take place. We have had to work hard to educate our clients about the value added by this strategy. We refined this approach by working closely with developers on several projects where we took equity as part of our fee structure. This gave us much more flexibility where we expended the fees in the different phases because it was really our own money we were investing and using. It is clear, by this approach, that the architects are taking on much more responsibility for the leadership and management of project delivery and, as a result, retaining more fees for these value-added services. Construction companies are beginning to realize this change and are now coming on board earlier, recognizing the advantage of a collaborative approach as an effective business model. We estimate that we spend approximately 25 percent of our net income on research and development work, which is critical in supporting the valueadded argument. Obviously there are risks involved in how we approach our practice, but we have found that there is an understanding by most of the real players in the industry that in this new model of practice based on shared risk, shared resources, and shared trust,

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most everyone is engaged and committed to making the very best project possible. It is still important to have clear statements about the scope of work and level of responsibility that each participant has. This is implemented by sharing technologies, learning from each other, building transparent relationships, and understanding that conflicts will still happen, but that a team equipped with the necessary diverse skill sets will be able to resolve them in an equitable manner. It is our view that firms who embrace this approach are the ones who will succeed in the new environment of design and construction. Those that do not change will probably not exist ten years from now.

You have a very interdisciplinary practice. It appears that all five of you came to architecture from different disciplinary backgrounds. How does that influence the way the firm works and operates the practice? From the partners’ perspective this is a family affair. We have two husband-and-wife teams and a set of twins as partners. We all bring undergraduate and previous work experiences that are very diverse—construction, political science, art history, studio arts, business and marketing. What brought us together initially was our experience as architecture students at Columbia University. We all had similar professors, were exposed to similar theory and technology courses, and share many hours in the studio together. But because of our varied backgrounds, we each had our own perspective and interpretation on what this educational experience meant and what we learned that now informs our practice. It is this diversity of experience that shaped our practice. We play to each other’s strengths and perspectives, engaging parallel viewpoints based on different experiences and beliefs. It is not about egos but about how each of us can contribute to make the very best project possible.

How would you change education to prepare people to enter this new world of practice as you have described? One of the critical problems in schools of architecture is that they tend to be insular and don’t import knowledge and skills from other disciplines. The model does not seem to work. Students need to be more active in the processes of problem formation and critical thinking. For SHoP, we begin our design process by asking a series

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SHoP INTERVIEW

As the office has grown, we have made a conscious effort in our hiring practices to maintain this type of diversity. About half the people who work in our office have undergraduate degrees in one of the liberal arts or humanities disciplines—history, social science, political science, anthropology, fine arts, mathematics, etc., prior to obtaining their master’s degree in architecture.

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of questions that respond to particular desires or effects we would like to achieve for a particular project. For example, “How can one maximize an office space’s flexibility while providing for maximum daylight?” or “How can the form of a building be tied to its environmental performance?” What several programs are now doing is creating new centers and institutes that bring individuals from multiple disciplines to work on common problems and research, facing the practice of architecture, building industry, and environment from a diverse series of perspectives. This appears to be the model of the future, and it is where the funding is being directed by universities and other external private and public agencies.

SHoP INTERVIEW

For architecture schools, there needs to be a major investment in computation technologies, rapid prototyping tools, simulation, and modeling platforms. It is as critical to carefully investigate the pedagogy of the studio. The studio today still remains a subjective setting—guided primarily by intuition and experience. These are limited and narrow metrics for evaluating performance. They have no effective way to help students find their strengths and channel their interests and capacities into meaningful roles in our industry. An architectural education could prepare one to do many things, but we do not celebrate this potential. The curricular structure also needs to be examined so that there is a clear set of foundation experiences that introduce students to the fundamentals, knowledge, skills, and values of the discipline and profession. There is a need to establish rational and critical feedback mechanisms that evaluate how each experience in the student’s education provides valuable learning, that is process-based and has the capacity of continual renewal as new knowledge and skills are developed. It is also critical to give students the means to position their work in a broader social, economic, and political context to help them not only understand how to build but also, know what to build in a responsible manner. One of the things that is very important to realize is that an architectural education prepares individuals to do much more than generate form. Students have many talents that could be applied in this new practice model. From our perspective, the diversity of experience and preparation is the real intellectual capital of the future of practice.

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C ASE S TUDIES Architectural Practice—A Dialogue with Research SHoP Architects William Sharples / Christopher Sharples

We are a practice-based office and not committed to any one design method, process, style, or system of operating, including tools and software. We approach each project with fresh eyes. We seek to have each of our projects evolve in its unique form through a dialogue with others so that there is an open feedback mechanism that keeps all of the people with a stake in the project actively involved, sharing and improving the design and how to build the outcome.

C ASE S TUDY P ROJECT The Fashion Institute of Technology (FIT)

CASE STUDIES / Architectural Practice—A Dialogue with Research

C A S E S T U D Y P R O J E C T: T H E FA S H I O N I N S T I T U T E O F T E C H N O L O G Y ( F I T )

Figure 2.52 Addition to the FIT Academic Building, NY

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CASE STUDY PROJECT / The Fashion Institute of Technology (FIT)

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What was the context of the FIT project? FIT is the preeminent institution of fashion and design education in the country. FIT is unique in the fact that it is located directly in the heart of the industry that it teaches, using its physical environment as an integral support system for its intellectual agenda.

What was the primary research/design question in this project? The proposed addition is highlighted by a multilayered glass and metal facade. Contained within this thickened facade are nested the primary circulation, review, and exhibition spaces connecting the design studios with the sky-lit student quad on the fifth floor.

Figure 2.53 Student Life Hall —FIT Academic Building, NY

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Figure 2.54 Facade Line Drawing and Glazing Detail, FIT

CASE STUDY PROJECT / The Fashion Institute of Technology (FIT)

C A S E S T U D Y P R O J E C T: T H E FA S H I O N I N S T I T U T E O F T E C H N O L O G Y ( F I T )

Just as a loom builds form and structure simultaneously, this new kind of building will allow structural systems, environmental technologies, and visual permeability to be interwoven and constructed simultaneously.

What were the major outcomes of this project in terms of addressing the research/design questions? The proposed building is seen as a proto-form—components of ideas and elements that have the ability to adjust as the program is developed with the faculty and administration. Flexibility, communication, and leading-edge technology are the underpinnings of this design, which we believe will be a unique and inspiring example of future possibilities for design and technology for FIT’s students, faculty, administration, alumni, and the people of New York.

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CASE STUDY PROJECT / The Fashion Institute of Technology (FIT)

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PROJECT FACTS AND CREDITS Location of Project: New York, NY Phase: Winning Design—Invited Competition Design Development Client/Owner/Developer: Fashion Institute of Technology Type of Project: Academic Building Total Square Footage: 97,400 sf building, 1,300,000 sf master plan Consultants Structure/MEP Engineer: Buro Happold Electrical Engineer: A.G. Consulting Landscape Architect: Matthews Nielson Lighting Consultant: Focus Lighting Inc. Facade Consultant: Front AV, IT and Acoustical Consultant: SM&W Acoustical Consultant: Akustics Vertical Transport Consultant: Iros Elevator Design Services Code & Fire: CCI Expediters: Municipal Expediting Cost Estimators: VJ Associates

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C ASE S TUDY P ROJECT The Camera Obscura—Mitchell Park

Figure 2.55 Camera Obscura Exterior Model

CASE STUDY PROJECT / The Camera Obscura—Mitchell Park

C A S E S T U D Y P R O J E C T: T H E C A M E R A O B S C U R A — M I T C H E L L P A R K

What was the context of the Camera Obscura project? An apparatus that has fascinated people since the fourteenth century, the camera obscura (Latin for “dark room”) is a novelty in today’s world. Through an optical lens and a mirror, a live image of the camera’s surroundings is projected down onto a flat, circular table that is raised or lowered to adjust focal depth

What was the primary research/design question in this project? As such, the building is conceived of and operates as a camera. This notion manifests itself through the camera’s architecture, from its movable components and material properties, to its sublime form and strategic situation in Mitchell Park East. The camera’s lens can focus on all buildings and elements in Mitchell Park (carousel house, amphitheater, ice rink, Mister plaza, ferry terminal building, etc.) or out to the marina and beyond to Shelter Island, across the bay. Furthermore, given the

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CASE STUDY PROJECT / The Camera Obscura—Mitchell Park

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scale and scope of the building, this project was driven by a “Research and Development” attitude, in an attempt to tie the nostalgic program of the camera obscura with today’s cutting-edge technology in terms of both design and construction process.

What were the major methods and outcomes of this project in terms of addressing the research/design questions? Designed entirely as a 3D computer model, the construction of the Camera was communicated as a kit of custom parts accompanied by a set of instructions much like those that one finds with a model airplane kit. Primary aluminum and steel components were laser-cut using digital files directly extracted from the computer

Figure 2.56 Camera Obscura Interior Model

Figure 2.57 Camera Obscura Kit of Parts

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85 CASE STUDY PROJECT / The Camera Obscura—Mitchell Park

C A S E S T U D Y P R O J E C T: T H E C A M E R A O B S C U R A — M I T C H E L L P A R K

Figure 2.58 Camera Obscura Construction Matrix

model, with crucial information etched into the components for ease of fabrication. Full-scale templates were provided for wall and roof sheathing, which are made of a black paper-resin board called SkatelitePro®—produced for use primarily in skateboard/BMX freestyle parks, and noted for its ability to accept a high degree of curvature. Much of the fabrication took place offsite; prefabricated panels were bolted into the concrete foundation and to each other, ensuring the required level of precision for the rest of the Camera’s structure and elements to bolt and screw onto. The subtly warped exterior skin is comprised of milled Ipe hardwood planks, the same wood that is deployed throughout all of Mitchell Park.

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CASE STUDY PROJECT / The Camera Obscura—Mitchell Park

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PROJECT FACTS AND CREDITS Location of Project: Village of Greenport, Greenport, NY Phase: Completed August 2005 Type of Project: Camera Obscura Client/Owner/Developer: Village of Greenport Total Square Footage: 350 sf Project Cost: $170,000 Consultants Structural Engineer: Buro Happold MEP Engineer: H2M Group General Contractor: Loduca Associates, Inc. Electrical Contractor: Johnson Electric Construction Corp. Photographer: Seong Kwon

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87 CASE STUDY PROJECT / The theSea Port Tower Project—Pier 17

C A S E S T U D Y P R O J E C T: T H E S E A P O R T T O W E R P R O J E C T — P I E R 1 7

C ASE S TUDY P ROJECT The Sea Port Tower Project—Pier 17

Figure 2.59 The Sea Port Tower View from the River

What was the context of the Sea Port Tower—Pier 17 project? In a proposal that envisions the rebirth of the historic South Street Seaport as a vibrant part of Lower Manhattan, SHoP’s designs for the mixed-use complexes and open spaces along Pier 17 combine the density needed to support active street life on the waterfront with intimately scaled retail corridors, in keeping with the historic context of the area, and a wide piazza for live performances, local marketplaces, community fairs, and other cultural events.

What was the primary research/design question in this project? The redevelopment of Pier 17 will reinforce the identity of the South Street Seaport by highlighting the maritime location’s unique architecture through the restoration and relocation of the Tin Building at the harbor’s edge; reestablishing the Seaport’s reputation as a marketplace by restoring and converting old and abandoned fish stalls to local food merchant and retail use.

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CASE STUDY PROJECT / The theSea Port Tower Project—Pier 17

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What were the major methods and outcomes of this project in terms of addressing the research/design questions? Through a partnership with the city’s East River Waterfront project (also by SHoP), which unveils riverscape views by transforming the dark caverns underneath the FDR highway into bright pavilions for waterfront promenades. By renewing and rebuilding an area that has lost its historical identity in relation to the whole of New York—the redevelopment of Pier 17. The East River Waterfront project will once again link the harbor’s edge to the fabric of New York City and revitalize Lower Manhattan’s identity as a mainstay for diverse cultural experiences.

 Figure 2.60 The Sea Port Tower from the Street

 Figure 2.61 The Sea Port Tower Facade Detail

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PROJECT FACTS AND CREDITS Location of Project: New York, NY Phase: Schematic Design Type of Project: Mixed-use waterfront project Client/Owner/Developer: General Growth Properties Total Square Footage: 860,000 sf (approx) Project Cost: $1 billion (approx) Name of Firm: SHoP Architects, PC Location of Firm: New York, NY Consultants Structural Engineer: Severud Associates MEP Engineer: AKF Engineers Civil Engineer: Langan Engineers Landscape Architect: Field Operations Lighting Consultant: Fisher Marantz Stone Elevator Consultant: Van Deusen General Contractor: Turner Construction Project Credits Principals: Kimberly J. Holden, Gregg A. Pasquarelli, Christopher R. Sharples,

89 CASE STUDY PROJECT / The theSea Port Tower Project—Pier 17

C A S E S T U D Y P R O J E C T: T H E S E A P O R T T O W E R P R O J E C T — P I E R 1 7

Coren D. Sharples, William W. Sharples Project Architect: Thorsten Kiefer Designers: Angelica Trevino, Jan Leenknegt, Ayumi Sugiyama, Lisa Schwert, Nathan Rich, Claire Shafer

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CASE STUDY PROJECT / The West Jsmes Street Pedestrian Bridge

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C ASE S TUDY P ROJECT The West Thames Street Pedestrian Bridge

Figure 2.62 The West Thames Street Pedestrian Bridge—A View from the Street

What was the context of the West Thames Street Pedestrian Bridge project? The West Thames Street Pedestrian Bridge is a permanent replacement for the temporary Rector Street Pedestrian Bridge, which was designed by SHoP immediately after the attacks of 9/11. Located at the entrance to the Brooklyn Battery Tunnel, the West Thames Street Bridge spans diagonally over 9A/West Street and provides a direct pedestrian connection to Battery Park City from Lower Manhattan’s financial district.

What was the primary research/design question in this project? The bridge consists of a pair of symmetrical Lenticular trusses, a form most commonly associated with late-nineteenth-century railroad bridges and known for a highly efficient structural profile. The project was an opportunity to explore the capacity and nature of the structural principles of the Lenticular Truss.

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Figure 2.63 A Walkover of the West Thames Street Pedestrian Bridge

91 CASE STUDY PROJECT / The West Jsmes Street Pedestrian Bridge

C A S E S T U D Y P R O J E C T: T H E W E S T T H A M E S S T R E E T P E D E S T R I A N B R I D G E

Figure 2.64 West Thames Street Pedestrian Bridge— Investigation of the Lenticular Truss

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CASE STUDY PROJECT / The West Jsmes Street Pedestrian Bridge

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Figure 2.65 West Thames Street Pedestrian Bridge Section Axonmetric

What were the major methods and outcomes of this project in terms of addressing the research/design questions? Unlike most arched structures, no net horizontal forces are transferred through the truss. The top and bottom chords of the truss balance out the horizontal forces, enabling a much lighter profile for the supporting structure, ideal for this dense urban site condition. An Ipe wooden deck is alternately connected to the top and bottom chords of the truss, creating a flowing formal gesture that frames the bridge deck and buffers the path from the highway below. A metal mesh screen forms a second system, connecting the same truss chords with the required 8-foot-high pedestrian guard. The flowing forms are enabled by geometric modifications to the Lenticular. PROJECT FACTS AND CREDITS Client: New York State Department of Transportation and Battery Park City Authority Location: New York, NY Phase: Schematic Design Area: 200 linear feet Project Cost: N/A Nature: Renovation of Existing Academic Building Structural Engineer: Buro Happold

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WISCOMBE INTERVIEW

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WISCOMBE INTERVIEW Tom Wiscombe I have based my practice on this premise: that forma and performance can be interwoven in ways which produce things that are beautiful, exotic even, but things which still perform work. Now, since my work has to date been very conceptual, the analytical component has often been lived and a kind of “intuitive analysis” of performance rather than finely-tuned engineering testing, but again, that’s only because I am not operating on the scale where I can follow through with those things the way I would like; the software and technical skill required to be consequent is becoming increasingly technically challenging at the same time it is becoming more powerful. Figure 2.66 Tom Wiscombe

RESEARCH BACKGROUND

In 1999 he founded EMERGENT, an architectural firm dedicated to researching issues of structure, tectonics, and materiality through built work. EMERGENT is a platform for experimentation, leveraging techniques and logics from fields outside architecture including biology, complexity science, aerospace engineering, and computation. EMERGENT’s directive is to move beyond categorical thinking in architecture and the stratification of building systems. This involves a reexamination of hierarchies and discreetness of systems toward coherent but differentiated constructions. Ultimately, the results are understood both in terms of performance and spatial and atmospheric effects.

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WISCOMBE INTERVIEW

Born in 1970 in La Jolla, California, Tom Wiscombe is an architectural designer based in Los Angeles. In 1999, he founded EMERGENT, a platform for researching contemporary models of biology, engineering, and computation to produce architecture characterized by formal variability, high performance, and atmospherics. Wiscombe started his current career trajectory in 1992, when he graduated with a B.Arch. from the University of California, Berkeley, and more or less stumbled into a job at the Los Angeles office of Coop Himmelblau.

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How does evidence play a role in informing your work? My first reaction to the term “evidence” in relation to architectural design is that it is probably associated with a pseudo-scientific world view, where things can be produced and tested to determine their efficiency or value. So it makes me a bit nervous. I actually think these days that the term “research” is far too often used in architecture in a really imprecise way. I mean, in science, as Jeff Kipnis has said, there are two things that make something research: one, that results need to be repeatable, and two, that failures are as important as successes. So the argument there is that architectural research is not interested in failures or repeatability, so that means it is either not research, or that we are using the wrong word for what is being undertaken. “Experimentation” seems more appropriate, less goal-oriented, and less verifiable. And I would argue that architectural experimentation has a wide variety of types, from purely formal, to conceptual, to performative to social, all of which can be productive, but not necessarily “research” per se.

WISCOMBE INTERVIEW

So to bring this back around to evidence, I think that a better term might be “analytical.” Analytical is distinctly different than generative or experimental modes of working—it assumes that we can actually expect things to have value or agency beyond debatable cultural value, that we can use analytical methods in design to complement generative methods. I really don’t believe you can have one without the other, and in fact I have based my practice on this premise—that forma and performance can be interwoven in ways which produce things that are beautiful, exotic even, but things which still perform work. Now, since my work has to date been very conceptual, the analytical component has often been lived and a kind of “intuitive analysis” of performance rather than finely-tuned engineering testing, but again, that’s only because I am not operating on the scale where I can follow through with those things the way I would like; the software and technical skill required to be consequent is becoming increasingly technically challenging at the same time it is becoming more powerful.

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One project which may well fit into “evidence-based design” is an installation project I did in 2007 called Dragonfly. Dragonfly was a collaborative project between my office and Buro Happold Consulting Engineers with the explicit goal of finding out if the quantitative could produce the qualitative in a design process. That is, if we could use analytical tools in a generative way to produce structural heterogeneity. So evidence became not something we would explore at the back-end to judge the finished product but rather something we would use incrementally along the way, at every turn to feed back stress data and material

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distribution back onto the design object. Dragonfly was based on “beam-brane” geometry, which we invented in 2007, and is characterized by two distinct pattern formations, one which takes bending forces, and one which acts more like a membrane, similar to the way a dragonfly wing works. So we used a high-end software, ANSYS, and generated populations of versions and tested them iteratively in an evolutionary process. This is not to say that we set up conditions and then auto-generated the project, which is far from the case. There was constant feedback between qualitative and analytical assessments of the project in each generation. This dual-assessment led to unexpected developments and formations of structure which would never have come about with a singular approach. My favorite moment of that project is actually where the software generated several versions with a beam-like element running across a zone of the structure that we had assumed was operating only as a membrane. It seemed to be kind of insisting on that development, which was really interesting. It just revealed that despite our efforts to make the project heterogeneous, we had begun to fall back onto some assumptions on hierarchy, and the computer kept insisting on indeterminacy and alternative pathways. So the design of Dragonfly, one could say, was partially driven by evidence and a search for “good” outcomes. But my point is that your definition of good makes all the difference, and that’s where the conundrum of evidence-based design lies.

I really value intuitive forms of knowledge—let me just say that up front. In that way I am more of an artist although people often try to portray me as a kind of mad scientist. But, there are limits to that kind of knowledge—let’s just call it “magical thinking”—where you begin to lose touch with things like technological limits. So when I’m verging on magical thinking, I think it’s great to stop and switch hats to engineer, fabricator, politician, user, etc. In my opinion, the best creative acts in architecture are those which take all of these realms into account and still manage to come up with something that resonates on a completely abstract level. So to try to answer your question, I think that analytical processes add complexity to design, certainly. But I don’t agree that a compendium of evidence gleaned from a kind of customer satisfaction survey of all parties and interests involved in architecture will ever be a creative act. I think the moment of creativity is the moment of unexpected, nonlinear serendipity.

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Does the use of evident and/or analytical process inhibit or enhance creativity in design?

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Could you talk a bit about how you see your work fitting into an interdisciplinary model of design? Architects and designers I can relate to always bias emotional aspects, visual aspects, and atmospheric aspects over quantitative aspects and I think that’s a good thing. I do think though that projects which exceed the image toward multiple ontologies and agencies end up being more sophisticated. They can do all kinds of work—cultural, visual, structural, mechanical, etc.—rather than staying within in a single sensibility. So I would say that it is critical that architects work with other experts in their field and these days, with people from other fields. You know, innovation always happens at those intersections between forms of knowledge and techniques. I am very interested in collaborating in a kind of architectural ecology in terms of practice. For instance, I am not a computer programmer, and I never will be, but I am going to collaborate this summer with an excellent programmer who also brings to the table a different sensibility for the most productive uses of the computer than I have. I am looking forward to learning from this. Also, of course, I have a lot of engineer friends with whom I always work with collaboratively, never just as consultants. I love to send them images of impossible things just to pique their interest, and get them involved. Especially, these days, with impossible HVAC and plumbing systems because I need feedback about the logical limits of building systems integration versus discreetness. I don’t want to be a dilettante. But the key to any of these collaborative relationships is, in my opinion, not to pretend that if you put everyone in a room together that something good will come out of it. There still has to be an instigator, and as far as I can tell, this still tends to be the architect.

WISCOMBE INTERVIEW

What do you see as the core methods, values, and skills needed to do the type of work you are doing?

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Well, I hate to do this, but the more I think about evidence-based design, the more I realize that it has very little to do with my values and process. It might even be an opposing force. As far as I understand it, it infers appropriateness and aims for the “best of all possible outcomes.” That is, it implies that in order to make the perfect omelette, satisfying to everyone, you just need to find the right chef, the most palatable eggs and vegetables and cheeses, the best pan and temperature, etc., which I totally disagree with in terms of design. I just don’t think that any pool of information, no matter how important or logical, will ever beget innovative design. Now if we are not talking about innovative design, but rather the perfection of the design

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of machine-like buildings such as prisons or hospitals, I can see the value. But for the kind of architecture that I am interested in, the kind that is transformative in some way and contributes to a long history of architects and experiments, I would have to say that too much “evidence” is a killer.

What are your thoughts about the changes needed in the academy and in practice to create new models that will support the future of our profession? I think that architecture is too much of a cottage industry, especially in America. If you consider the wild aesthetic and technological leaps currently happening in automobile and aircraft design as well as in industrial design, architecture seems to be in a truly catatonic state. It’s zombified. While I’m very excited about the new developments in infrastructure that Obama is promoting, I’m afraid that we will just repeat what we know, build more freeways, more asphalt, more junk. I’d like to see some of that funding go into research on lightweight materials, mag-lev trains, shape-changing materials, technology-embedded building skins, composites, micro-solar and micro-capillary HVAC systems, etc.—things which would begin to bring architecture and cities back to life on a lot of levels. We’ll see.

One thing I think that could have a huge positive effect on learning over the next decade will be the proliferation of analytical tools that are more user-friendly and offer different ways of visualizing architecture in terms of force flows, air flows, swarms of bodies in motion rather than just external qualities. There are some interesting ones becoming available now, but there is still not enough cross-platform fluidity to make it easy to fold into design methods quickly and productively. I’m looking forward to a cascade of these tools in the near future.

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Universities have a different problem right now, and that is an obsession with pure form at the expense of any interest in teaching applied studies. On the one hand, I think that this shift away from the “technical school” model is a good one, I’m afraid that we may have gone too far in promoting conceptual agendas. I worry that the system is graduating a lot of people who are savants, versed in making forms and images but unable to be effective in the world. This predicament is certainly related to the revolution of digital design methods, which are no longer new, but thoroughly embedded in most universities that matter.

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C ASE S TUDY Wild Structures

CASE STUDY / Wild Structures

Tom Wiscombe—EMERGENT

My work is definitely interested in an analytical approach to what might be considered “high design.” It is a personal approach informed by performance issues. It is informed on two levels. First, the exploration of structure, and second, MEP performance as a means to inform a design language using tools to model and simulate outcomes about specific design proposals.

What was the research question or hypothesis? In our office, the design and evaluation of structures always occurs on a qualitative level as much as a quantitative one. This produces formal and operational elegance, but also the messy redundancies and heterogeneities we see in the wilderness. The development of projects usually occurs in leaps rather than small increments because of the conscious lack of consistency in the techniques and sensibilities of the working process. Structural wildness—as much as we can identify it from inside the jungle—occurs at moments where systems exceed type and mutate, where tension forces suddenly switch to compression forces, and where legibility melts into unpredictable formal and atmospheric effects. It is the questioning of these conditions which form the critical questions and hypothesis for our work.

What methodologies of research were utilized? Why did you select this approach? For me the term “evidence” is difficult to understand. My first reaction to it is in the context of issues of crime or mystery; that there is one right solution and everything is clear and solved. I would prefer to think of the term “analytical” as a substitute. In this regard then I see evidence as factual data or information generated through specific types of tools for model or simulating relationships. This process would apply both to the back-end of design—detail development of components or systems for constructions, structures, MEP, formal explorations, etc., as well as the front-end concerns of framing the nature of the challenge, exploring conceptual responses to these chal-

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lenges, and setting performance criteria or expectations. The data used in both of these activities could be either qualitative or quantitative depending upon the circumstance.

The work is grounded in the dialectic process of excess and efficiency in architecture, in favor of a more complex understanding of both through biological thinking. The recursive process of random mutation and natural selection in nature provides a model for how a dynamic feedback between excesses and efficiencies can create innovation and elegance. This feedback logic is executed in the office using both generative and analytical algorithms as well as hands-on design techniques. Key to the work is the phenomenon of “emergence” which offers insight into the way apparently isolated bodies, particles, or systems exhibit group behavior in coherent but unexpected patterns. The animated beauty of emergent organizations, such as in swarms or hives, points to a range of real architectural potentials where components are always linked and always exchanging information, and above all, where architectural wholes exceed the sum of their parts.

CASE STUDY / Wild Structures

Why was it effective, efficient, credible, and doable? What were the metrics?

What were the outcomes? Biological thinking has led EMERGENT toward the exploration of new methods of systems integration, construction documentation, and fabrication. Recent co-ventures with international engineering companies, including Buro Happold and DeSimone Consulting Engineers, have begun to reveal new working methods which establish active feedback loops between engineering and design disciplines, ultimately pointing to a redefinition of AEC territories. In the scientific sense, emergence refers to the process of deriving new and coherent structures, patterns, and properties in a complex system. Emergent phenomena occur due to the pattern of interactions between elements of a system over time. Emergent phenomena are often unexpected, nontrivial results of simple interactions between simple components. What distinguishes a complex system from a merely complicated one is that some behaviors and patterns emerge in complex systems as a result of the patterns of relationships between the elements.

How were the outcomes applied, linked to, or used to help inform design? Nature is filled with variation and complexity that architecture has yet to fully explore. Biology is not architecture, of course. Nature doesn’t care about form following func-

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CASE STUDY / Wild Structures

tion or function following form; it is all about iteration, mutation, and feedback through fitness testing, all of which produces species and formations which are as elegant as they are robust. The hammerhead shark did not emerge slowly, step-by-step, from small to large hammer as is commonly thought. In fact, the first hammerhead to appear was the Winghead shark, with a very wide hammer. This mutation offered no discernable advantage—it was, at that point, “ornamental.” Through the process of optimization (a.k.a. natural selection), other species have appeared with a range of hammer sizes better adapted to hunting in various environments. In the end, the hammer cannot be understood as an essentially functional development, although it has developed various unexpected functional benefits at the back end through optimization. Beyond the trappings of literal biomorphism, my office is interested in biomimetics as a way toward both formal variability and performance. Dragonfly wings, bat wings, radiolaria, corals, and jaguar patterns are all on the table as potentially relevant to new ways of thinking about structural formations in particular. We have been pursuing this with our engineering partner using digital optimization routines to refine structures, but more importantly to generate formal variation in direct response to local conditions.

“Design today must find ways to approximate … ecological forces and structures. To tap, approximate, burrow, and transform morphogenetic processes from all aspects of wild nature, to invent artificial means of creating living artificial environments.”

—SANFORD KWINTER

The history of architecture reveals a constantly shifting relation of structure to space. Structure is sometimes latent, sometimes expressed, other times dematerialized at great effort. Whatever the case, considerations of efficiency alone are never enough to explain the role of structure in architecture. In the contemporary digital environment, vital, adaptive, formative potentials of structure have begun to emerge. There is a growing acknowledgment that structure, when removed from a state of equilibrium, can become as unpredictable and varied as natural phenomena. When released from critical states of suppression and representation, structure can become fluid, color-variegated, cross-pollinated, and hybridized, in a jungle-like ecology.

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Such wildness has been theorized by Sanford Kwinter, who is a tireless promoter of the dynamics of animal packs, storms, and guerilla tactics—all that is untame—as a way out of the mechanistic dilemmas of architecture.

CASE STUDY / Wild Structures

One way to frame a discussion of wildness is through Mies van der Rohe and Pier Luigi Nervi, who offer two divergent approaches to structuration. Mies’s canonical National Gallery in Berlin (1968) appears to be about structure, with its exposed beams and fetishistic steel detailing, but it doesn’t exhibit any intensive material or structural logic per se. The project is about the universality of flat planes, and the purity of endless metric space. In this sense, it is a conceptual project. Columns are removed from the interior and dissolved with his trademark cross-section; there is no response at the location of maximum shear where column meets roof, and the roof structure is equally deep, independent of the variable bending forces at work within it. Nervi’s Giatti Wool Mill (1951), in comparison, begins to exhibit a materialist flow of forces, a proto-wildness. In this project, the structural ceiling morphology begins to organize in response to force flows along its surface. The vertical is not suppressed, but rather begins to effect transformation in the horizontal. The variability and elegance of the relief can be experienced on a conceptual level, as intensive forces at work, but also on an immediate, sensate level. Jeff Kipnis has referred to this kind of simultaneity as a “dual-ontology.” Wild structures are not simply expressive structures. The drive toward legibility, in the sense of being able to trace a genealogy of forces back to a source, is actually quite tame. Wild structures are instead a seething combination of behaviors that coalesce into an emergent whole with effects that may exceed the structural. Butterfly wing structures are wild in that sense: Their porosity is certainly related to structural lightness and aerodynamics, but it is also unpredictably related to the production of visible color effects. It turns out that color-variegated wing patterns are often not based on pigment, but on the micro-patternings of variable-depth pores modulating wavelengths of light. Structural Expressionism, as a movement in architecture, has been more about zerosum, one-to-one legibility—no doubt a late permutation of the modernist instinct toward transparency. But it also must be noted that its practitioners have often gone to great lengths to produce legible images of efficiency at the expense of actual efficiency. This drive toward excess for the sake of producing affect in terms of structure is quite interesting, and re-examined in the contemporary environment, opens up ways of thinking about legibility versus obfuscation in structural design. I would argue that engineering efficiencies do not have to exclude excesses that these territories can cross over, creating complex formations that might do unexpected work, and might be felt as well as read.

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CASE STUDY / Wild Structures

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Figure 2.67a Batwing Structural Framework

Figure 2.67b Batwing Structural Force Diagram

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While the term “wild” is easily associated with the biological, it is important to remember that in architecture, we are talking about artificial, inorganic constructions that don’t literally grow. Wild behavior can be synthesized through any number of opportunistic processes, however, wherever material logics operate within shaping environments. In a military-industrial setting, exactly where we would expect not to observe wildness, we find salient examples. The F-22A Raptor is a radically heterogeneous construction that reflects local, opportunistic thinking in terms of materials, engineering, and manufacture. Instead of one continuous material system, this aircraft was designed using several interwoven materials and structural morphologies. Boeing made the fuselage from a deep-celled aluminum and steel egg-crate system and the wing spars from cast titanium, while Lockheed Martin made the wings, fins, and duct manifolds from formed thermoplastics and carbon-fiber composites. The structural patterning that results is patchy but nonetheless coherent. This is not an “exquisite corpse” or collage of parts, but a radically responsive model for structuration that injects variable materiality into a system of variable patterning. The result is technically intelligent, but also beautiful, articulated, exotic.

CASE STUDY / Wild Structures

C A S E S T U D Y: W I L D S T R U C T U R E S

In our office, the design and evaluation of structures always occurs on a qualitative level as much as a quantitative one. This produces formal and operational elegance, but also the messy redundancies and heterogeneities we see in the wilderness. The development of projects usually occurs in leaps rather than small increments because of the conscious lack of consistency in the techniques and sensibilities of the working process. Structural wildness—as much as we can identify it from inside the jungle— occurs at moments where systems exceed type and mutate, where tension forces suddenly switch to compression forces, and where legibility melts into unpredictable formal and atmospheric effects.

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CASE STUDY PROJECT / Abu Dhabi, UAE 2008

C ASE S TUDY P ROJECT Freshwater Plaza Abu Dhabi, UAE 2008

Figure 2.68 A Birds-Eye View— Freshwater Plaza Model Abu Dhabi

Water is the oil of the twenty-first century. In the twenty-first century, water will determine new land-use for growing populations, regional political alliances, and alternative energy production. Desalinization is one important aspect of the future of water; it is already a critical social concern, particularly in arid regions. Desalinization has long been a heavy industrial undertaking, involving huge mechanical apparatuses run on fossil fuels. Recently, a reexamination of existing seawater greenhouse technologies has revealed possibilities for large-scale, sustainable desalination using deep seawater and warm sea breeze in an evaporation-condensation loop. Freshwater Plaza is a spatialization of an innovative, low-tech water desalinization process, and part of the larger sustainability initiative of Abu Dhabi. The goal is to reveal new technologies but not for the sake of the image of technology. The project is instead focused on generating technological ambience. The divisions between technology and culture—and building technology and architecture— begin to dissolve into a hybrid spatial sensibility. Fluid flows, structural patterning,

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C A S E S T U D Y P R O J E C T: A B U D H A B I , U A E 2 0 0 8

Figure 2.69 Freshwater Plaza Interior Truss— Model View

Figure 2.70 Freshwater Plaza Model—Top View

ornament, and lighting all combine into a coherent whole, generating an unexpectedly vivid and lively atmosphere. The space will generate public consciousness of the looming water crisis as well as offer a glimpse of how biological, integrative thinking may offer productive solutions to this global problem. The project is a large, partially inhabitable roof landscape characterized by two performative pattern logics.

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Figure 2.71 Inside Truss at Abu Dhabi

The first is a three-dimensional meshwork of capillaries within which cold seawater (from a local deep source) is circulated. The second is a series of air intakes which direct warm sea air over the capillaries. Seawater is sprayed into this warm air as it enters, increasing its water content. The glass roof creates additional heat in the interior space, allowing the air to take on even more airborne moisture. Then, when this super-humidified air comes into contact with the chilled pipes, it condenses. The condensate, free of salt, drips down the capillaries into pleated troughs below, which lead to underground storage tanks. The chilled pipes are organized in such a way that they operate structurally, so the construction can ultimately be understood as a structural heat-exchanger. The hydronic and structural processes will be legible, but in an ambient, atmospheric way. The aim is not the creation of a “mechanical cathedral,” à la Structural Expressionism, but rather the creation of public space defined by crossovers of technology, culture, and sensation.

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107 CASE STUDY PROJECT / Matters of Sensation—Artist Space, 2008

C A S E S T U D Y P R O J E C T: M A T T E R S O F S E N S A T I O N — A R T I S T S P A C E , 2 0 0 8

C ASE S TUDY P ROJECT Batwing Matters of Sensation—Artist Space, 2008

Figure 2.72 The Batwing Model

Batwing is part of a larger body of work concerned with creating coherent relationships between building systems through geometric and atmospheric means. The aim is to move toward a higher-order emergent wholeness in architecture while still maintaining a performative discreetness of systems. The project can be understood as an articulated manifold which incorporates structural, mechanical, envelope, and lighting system behaviors. This is not to say that any one of these systems is “optimized” in terms of any functional category—the formal and ambient spatial effects of fluidity, translucency, glow, and silhouette are all as important for the overall effect of the piece. The intent is to establish a link between the sensate realm and infrastructural flows in architecture. This is different than simply expressing structure or expressing building technology, making it legible. Batwing is not the inside-out Centre Pompidou, which represents more than it performs, and remains a difference in degree rather than a difference in

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CASE STUDY PROJECT / Matters of Sensation—Artist Space, 2008

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Figure 2.73 Batwing Cooling Mesh Model

kind. Translation (a difference in degree) of the ductwork to the exterior doesn’t produce transformation of the system, or any unexpected or crossover effects. Now, consider co-evolutionary transformation of the bloodcomb jellyfish, found in mid-water ocean depths. The bloodcomb appears to be a single organism but it is, in fact, two co-evolved organisms: the jelly and a community of bioluminescent bacteria. The bacteria live in the “paddles” of the jelly where they thrive, providing a kaleidoscopic lighting mechanism as they move. This effect makes the jelly invisible to its deep-water predators, which cannot distinguish that emergent pattern from sunlight bouncing off the surface of the water above. The two species are distinct but interwoven in such a way that they cannot be unwound, and their combination produces sophistication not possible through a single evolutionary trajectory. The design sensibility of Batwing is driven by two types of surface transformation: the pleat and the becoming-armature. Pleats operate in terms of providing structural rigidity and directed airflow across the surface while also creating a seductive ornamental patterning. The armature transforms the envelope system into a duct system which provides supply air as well as structural continuity between envelope components.

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109 CASE STUDY PROJECT / Matters of Sensation—Artist Space, 2008

C A S E S T U D Y P R O J E C T: M A T T E R S O F S E N S A T I O N — A R T I S T S P A C E , 2 0 0 8

Figure 2.74 Batwing Deep Pleats Simulation

Figure 2.75 Batwing Modeling of Surface Ducts

Deep pleats become “air diffusers,” featuring an embedded cooling meshwork of micro-capillaries used for cooling or heating of passing air. Based on the principle of water-to-air heat exchange, this cooling system heats or cools through local radiative transfer rather than relying on “central air.” The language of the piece consciously looks to automotive and aerospace design in terms of fluidity and integration of systems as well as processes of construction. These disciplines have flourished through the feedback of design sensibility and extreme shaping environments, a process which is of profound interest to our office.

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LUEBKEMAN INTERVIEW Chris Luebkeman Everything we do in design is about creating a context for people to thrive. It is this interruptive process of defining what is needed grounded in an aggregative and disaggregative set of activities that lead to understanding and agreements about how specific evidence supports specific outcomes. It is a process of bringing forth an understanding and transparency of the meaning of specific evidence.

RESEARCH BACKGROUND

LUEBKEMAN INTERVIEW

Figure 2.76 Chris Luebkeman

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Chris Luebkeman is a director and leader of ARUP’s global Foresight and Innovation initiative. Educated as a geologist, structural engineer, and architect, Chris has a background in research. Before joining ARUP, he studied in Switzerland and went on to become a faculty member of the Departments of Architecture at the University of Oregon, the Chinese University of Hong Kong, and the Massachusetts Institute of Technology. Since joining the firm he has facilitated the creation of an eCommerce strategy, initiated research projects on the “designer’s desktop of the future,” and encouraged thinking about the evolution of the firm’s skills networks into a knowledge network. Chris is currently working with some of the world’s largest companies to develop scenarios to better understand the opportunities that change is creating for them in the built environment. He is a member of the firm’s Design and Technical Executive team which promotes the highest standards of design and technical skill to ensure that ARUP is one of the world’s leading practitioners in its chosen fields. Chris has advised the UK government’s Environmental and Physical Sciences Research Council on strategic matters relating to the built environment. He sits on the Innovative Manufacturing Centres Evaluation Panel and is guiding the Five-Yearly National Research Review. He serves the UK industry directly as a member of the CRISP (Construction Research and Innovation Research Strategy Panel) Executive. In 2004 Chris was named a Senior Fellow of the Design Futures Council.

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How do you use evidence in your work and within ARUP? This is a great theme for a book. When you say “evidence design,” do you also mean performance-based design? It would be from my perspective that performance-based design is one type of evidence that supports design decision-making. I know that performance-based datasets are being created by building owners to help them understand how to operate their new complex environments. We are also using these datasets to better understand how to redesign the systems that we are creating in our work at ARUP. For us, the range of evidence spans from rather soft humanistic data to hard-core scientific data. We see this as inclusive. There are times when anecdotal evidence is as important as hard-core scientific evidence.

Let’s focus first on the work of the Foresight activities of ARUP. The primary activity is futures workshops which bring together the total supply chain to conduct a charret around a specific topic, for example, the hotel of the future based on the experience of the traveler. This is looked at as the “whole cocoon” that surrounds the traveler— the travel agent, car-rental organization, hotel staff, hotel finance manager, a banker, the architect, interior architect; normally a total of approximately 40 people. Each group of five or six people is given a suitcase, which they must unpack, and write a Performa for the traveler who owns the suitcase. The items in the suitcase become the evidence to determine the needs and desires of the traveler. The group then must take on the personality of that traveler for the rest of the day. If the group is male and they get a female’s suitcase, then they must become that female. The same is true for females becoming a male. The Performa maps the experience of the traveler based on the interruption of the evidence found in the suitcase. The map is based half on our own experience as travelers and half on the imagined experience that is created from the evidence. Most participants have never been a part of anything like this before. This mapped experience is then placed in a new work setting, normally across two dimensions creating four options: business travel increases, business travel decreases, a rich virtual experience, and an unpleasant virtual experience. The group is then asked to think of this experience 10 to 20 years into the future. How will this new world change or alter the experience? Once this is done, then the

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LUEBKEMAN INTERVIEW

It is important to put this into perspective in terms of the work at ARUP. At one end of the scale the work with Foresight focuses on trying to determine where we are going and what are the forces that are influencing this movement. On the other end is our research and development work which is monitoring, measuring, and correlating datasets from projects both modeled and operating environments to feed back into the design paradigms that are guiding our work.

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group spends the rest of the day designing a new hotel based on the projected experience of the traveler. One of the difficulties here is to get the group to focus on the evidence as it relates to the imagined experience rather than their own experience told through anecdotal stories. The resulting designs are critiqued to determine common themes and major differences—looking for basic concepts and finally picking one that is the best with the expectation that financing would be put forward for that project. The second type of exercise is based on creating scenarios from the Drivers-ofChange perspective. We ask the groups to illustrate what are the drivers of change in their work or organization. From this, we create themes in five categories: social, technological, economical, environmental, and political. We ask them to disaggregate the issues into small manageable and understandable issues. Then, based on the drivers-of-change, we ask them to re-aggregate them to see how they impact each other at a larger scale. We research these re-aggregated issues to provide a factual base to create scenarios or stories of the future. These stories or scenarios are then used to design for alterative futures based on these connections between drivers of change and their impact on specific themes of work or organizational intention. We cannot predict the future, but by using this approach of scenarios that is grounded in evidence from the re-aggregation process, the outcomes then form a foundation for understanding the implications and, in some cases, the performance outcomes of different design options or alternatives.

LUEBKEMAN INTERVIEW

These stories are powerful humanistic evidence that create conceivable and believable design outcomes allowing the stakeholders, users, and others, to move into a set of human experiences they would not be able to do without the help of this storytelling. We all know that stories are powerful tools for clarifying basic concepts and principles. This is also true in designing with scenarios. Scenarios allow designers to take people to places—environments—they would not be able to understand without the help of the stories.

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The quality and richness of the experiences of the people who participate in this work is really important. I take real care in putting these groups together. At least a third of my time is spent selecting the participants. I assure that there is a gender mix as well as a variety of life experiences represented that is appropriate to the topic under investigation. The quality of the facilitation is also very critical to having the process work effectively so a lot of time is spent designing the structure of the charette experience. It is also important to be aware of the current situation of the movement, what is in the news, and what major issues are being discussed at the global, nation-

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al, and local settings. These current situations influence how the participants in the workshops respond. What is current for them will work its way into the process and outcomes so it is important to filter this when appropriate. One of the things that we have not done is look at the resulting data across groups, which would be very informative to see what types of patterns and relationships could be found by mining the data, which now, having done several hundred of these events with small and larger groups, is a very large data warehouse to study.

I wished I had a good answer for you on this, but I don’t. The one thing I do know is that the value of evidence is dependent on where you are going to apply it. I can give you an example. I left MIT several years ago to become the director of research and development at ARUP. This seemed to be an ideal job. I got to lead a group of the very best minds within ARUP’s organizational structure. It took me about three years to figure out that what they needed was not a leader, but a manager or administrator. That was not me, so I started to work on this concept of the Foresight project. To do this I had to convince the board of directors that there was value in this effort. It was not an easy task. They wanted hard evidence on what I was going to do and how I would add value to the organization. I wrote proposal after proposal, but was making little progress. I finally went to the board and said, “Give me six months, and I will show you the evidence.” They agreed, and a year later the board member who was responsible to the whole board for the outcomes of my work called me in for an evaluation. I had very little hard evidence so I wrote and emailed to all of the people I had worked with over the past year. I got back a stack of emails detailing how I had impacted their work. I heard things I had never heard before. I went to the meeting with a stack of emails, and said, “Here, take a look at these. I will go get a cup of coffee and be back in ten minutes.” He read the first ten or so and found things like how I had helped a group within ARUP win a specific project, and how I had changed the organization structure of that subgroup so it functioned better. That was all I needed to do to continue this work for the next five years. It was clear that the evidence I presented was compelling and was the deciding factor in my future efforts. On another level I refuse to confuse the difference between measurement and evidence. In my case if you looked at how much money I lose for ARUP in my operation, there is no way they should keep me in my position. But, if you look at the evidence of what I do for the organization, I am a very valuable member of the organization.

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LUEBKEMAN INTERVIEW

How much evidence is enough and what makes it credible?

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The money issues are a measure. The value issue is a judgment of the importance of my contribution. Maybe a better way to state this is the measurement can be either from a hard or soft position. Both are measured, but the evidence takes different forms. From the hard perspective, it becomes very quantifiable, like numbers, and from the soft perspective, it becomes more qualitative and reflects outcome in nonnumerical forms, like value, appropriateness, level of contribution. I consciously try to mix the two—quantity and quality. Evidence is inclusive with both types of measurement, hard and soft.

Does your work, which is very systematic, enhance or inhibit creative thinking and design action? I think without question systematic approaches grounded in both qualitative and quantitative evidence are more liberating than restrictive to creative action. During our workshop presentations we are careful to present both qualitative and quantitative information so that the different individuals participating can find a comfortable entry point for engagement in the topics. Some people relate better to numbers and others are more responsive to descriptive stories or scenarios.

LUEBKEMAN INTERVIEW

The critical thing here is to make whatever form the presentation takes be in a language that can be understood by all levels and backgrounds. We are all aware of the situations with architects where their presentation is all “archabable.” I was recently in a conference in St. Petersburg, Russia, where I presented our Drives of Chance approach. I was careful to make sure that I was understood. A very good Danish architect who talked about the “democracy of the parti” followed me. It was a presentation full of architectural code words, and it was clear that only four people in the room understood what was going on and three of them were making the presentation.

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This brings me back to the issue of having a mixture of evidence in terms of content that will liberate those who participate. If they can find a familiar point to engage, they will relax and be more open to accepting the unfamiliar. It provides them an “anchor point” to engage the rest. This is so important in a design team so that everyone can find a way to meaningfully participate in the work of the team. An example of this is when you try to speak a foreign language with a native speaker; you will find that their comprehension of English goes up remarkably. It is also important to understand that in any design process there are constraints introduced representing either explicit or tactic rules and guidelines. When I do the Futures Workshop charettes, I am the client, and I do set forth a clear set of constraints.

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For example, I will set out a set of parameters and constraints based on the specific driver under consideration, like the power of the gray dollar—the importance of the financial base of retirees as an important user. As a previous studio instructor, it is important to me that the outcomes be rich and thought-provoking. To assure this, I have to make it clear what my goals are and provide guidance in the process to lead them to good solutions. The means of this guidance is making clear what parameters and constraints are important to me. I think this leads to more creative thought and action on the part of the participants.

When you use this large group of people—the supply chain representatives, who come from different disciplines and backgrounds—how do you find them working together to produce evidence?

I find that the visual representation of the discussions are extremely important to open up the opportunities for the diversity of participants to engage, understand, and contribute to the development of the solution as well as stimulate and support the dialogue about the issues under consideration. In another setting a very wealthy European businessman was to have participated, but could not and sent his son to represent him. It was clear that the son was very upset to be there, but it was a duty to his father. By the middle of the afternoon, however, the son had shed his fancy business suit and was there with his sleeves rolled up making objects to support the team solutions. He said, “I did not think this

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LUEBKEMAN INTERVIEW

As you know each of them has to deal with the content from the perspective of how they are most comfortable. I did a workshop in London on the “Store of the Future,” in the Great Room at the RIBA. I gave each team, four or five people, a toolkit of design supplies: foam core, paper, drawing instruments, cutting tools, etc. One of the teams, which included a board member of the company sponsoring the workshop, had a concept of the Store of the Future being like the Guggenheim Museum in New York—at the base a food court, and at the top a yoga center. All the rest of the services were located in between. As a part of this process, I always have architecture students or interns make the objects that represent what the team members are talking about. They draw and make models to simulate the discussions. They place these objects in the center of the table so that they have the potential to be a part of informing the discussion of the team. In this particular example, they cut out a spiral and held it in a location so that everyone could see it. The board member in the group immediately said, “No, no, no. That spiral is much too tight. It must be much broader and flair out at the bottom so it will be welcoming.”

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could be so fun.” His background was in finance, so his usual mode of engaging was with numbers, but this process brought him out of that way of working, at least for a while. As the time was near to make a group presentation, he worked up a quick financial analysis on the project. It was clear that these transition points were important. He was okay with working in a new way, but it was necessary for him to return to familiar territory to make sure that he was making a strong contribution to the project in hopes that it would be the best in a larger set of groups.

How do you take the evidence that is developed from your workshops and translate it into design application either in ARUP in general or to specific projects?

LUEBKEMAN INTERVIEW

Let’s take an anecdotal situation as a way of explaining. One of the privileges of my job is I get to attend a number of important conferences like the Economic Forum or the TED Conference. At one of these meetings there were a group of regulars that seem to appear at most of the conferences. One person who comes to mind is a director of a large international firm based in France. This person has a 16-year-old son. This director came up to me recently, and said, “Chris, the Drivers-of-Change cards that you distributed at the most recent conference are my son’s all-time favorite conference gift. He keeps them on his desk, and anytime he gets stumped on a project (i.e., science, social, political, economic, environmental, or technological), he goes to the cards and looks at the visual and factual information and within minutes he has a topic and is engaged in producing an outcome.” This made my day for several months, to hear that I helped someone think creatively about a topic of his or her interest. It is the personal translation of the factual, visual, or provocative information on the cards that provides the simulations for taking ownership for a direction.

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This translation process can take place in a number of ways. The first is the personal interaction with data and categorizing the data around personal interruptions. How does this impact my life? What will the future be like based on this topic? How will it impact my work or my family? This personalization is powerful in that it connects one’s personal world to a new future world, but in a way where the engagement comes from a familiar place—one’s own experience and background. Another way to make this translation is to prioritize the data. The cards are divided into a number of categories: social, technological, etc. In groups of four or five, the cards are used to provoke a dialogue about what are the most important drivers for change by category. This provides a context for a very rich discussion that normally leads to important questions about what is missing. Are these really the most impor-

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tant drivers? This allows the group to think about these issues in a larger context and then to put them back into a specific project with a new understanding. In terms of the Future Workshops, the translation process is open in terms of specific agenda, but it never fails to produce a translation. I let all the participants know that I cannot promise what they will take away, but whatever it is they will not forget it. The insight gained may not be immediate. It might come in a few days or maybe weeks, but it will reappear in one of your context situations. The primary goal of the workshop is to stretch the minds of the participants so that they can go back to where they started. They cannot know what they know. The question here is where is the translation? Is it in the delta from where they were to where they are now? It is hard to know exactly, but I know it happens, because I hear it regularly from past participants. Sometimes the value of this process is just taking the time to stop and think in a constructive way. We have so little time to do this in our everyday roles. It allows us to look at evidence from a different perspective. Making something new is expensive. It is easier to do the familiar. As I noted earlier, each individual will engage evidence in his or her context. Evidence must be excepted as you see it. This is somewhat counter to our more focused definition, which generally comes from the judicial system where evidence is factual, static, and value-free—it must be this way. This is the challenge of the word. For designers to make use of the concept, the words have to be carefully crafted to allow for the interruptive and contextual aspects of the content of the evidence to be shaped, understood, and made transparent. For designers it is not value-free and is process and context dependent. This is not like the evidence we speak of in the sciences.

Another aspect of my work at ARUP is helping in the development of our capacity to model and simulate components of building systems. We have integrated gaming software with our 3D simulation software to create the means for modeling multisystems like fire, smoke, lighting, and navigational or way-finding simulators to be able to see the impact of these multiple physics on the design of building systems. This was developed by bringing together three existing 3D software platforms and integrating them with a standard gaming software program developed by the gam-

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Everything we do in design is about creating a context for people to thrive. It is this interruptive process of defining what is needed grounded in an aggregative and disaggregative set of activities that lead to understanding and agreements about how specific evidence supports specific outcomes. It is a process of bringing forth an understanding and transparency of the meaning of specific evidence.

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ing industry. This is just another way we produce evidence to inform our work as designers. This bringing together of multiple systems is a great way to engage more people in the dialogue and to achieve greater understanding of the process and basis for specific design actions. This provides the opportunity for people to have a conversation about a specific topic or project, rather than simply having it come from the design expert. This is terrifying to those design experts who are interested in keeping the process a mystery and proprietary.

From your perspective what should be the future models of education and practice that would support this concept of using evidence to inform design?

LUEBKEMAN INTERVIEW

I am a huge proponent of a project-based and human-centered design perspective. Much of my thinking on this in regard to education is shaped by my personal experience in teaching at four different academic institutions—ETH in Switzerland, the Chinese University in Hong Gong, the University of Oregon, and MIT. It was Oregon that seemed to me to best represent my perspective. Oregon was a school that celebrated the diversity of the faculty and centered their teaching around the studio. Each studio was grounded in the expertise and interest of an individual faculty member giving the program this rich and diverse set of offerings, providing the students with a perspective that having open and multiple perspectives on design was critical. This established a set of values for students that made them recognize they needed to stay open and flexible and bring multiple perspectives to their design work.

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In terms of an organizational model, the ETH had what I think was a good model for bridging the gap between education and practice. They had a two-year “boot camp” that taught the basic skills and knowledge, giving the students a vocabulary for understanding architecture. Then students had to take a year out and work as an intern in an office. This did two things: It gave the office a cheap labor force to do things they could not afford otherwise like participating in competitions and to also investigate new territory; research if you will. This gave the student a new perspective on what architectural practice was about. Some students did not return. They changed their career path, realizing that architecture was not for them. Those who did return were then required to take a series of courses ranging in scale from urban design, to buildings, to details of buildings. It was about the big questions facing the world today. I also wished that we had a way to connect the passion and energy of architecture students to places that do not have access to these types of knowledge and skill, by working in communities to help people have better lives and places to live, work, and play.

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C ASE S TUDY P ROJECT Computational Design and Optimization (CDO) Chris Luebkeman—ARUP

Figure 2.77 Setting of the Proposed Bishopsgate Tower for DIFA in the City of London

Imagine a team working on a large-scale building project with complex geometry. Many design parameters can be varied, and their impact on balancing different design performances is not always predictable. Using a new approach to design, the team creates an optimization model that computationally encodes client, architectural, engineering, fabrication, and construction-related parameters and desired performances.

CASE STUDY PROJECT / Computational Design and Optimization (CDO)

C A S E S T U D Y P R O J E C T: C O M P U T A T I O N A L D E S I G N A N D O P T I M I Z A T I O N ( C D O )

What is “evidence” in this case study? We investigate relationships between different targets. For instance when we are considering the geometrical configuration for a new development (urban planning) we need to assess the sunlight and daylight performance and how this impacts other existing buildings. Secondly, the development volume (or floor area) is a key parameter. Other disciplines can enter the equation; for instance, the ratio of surface versus volume can be used as a preliminary indicator of thermal performance. All these elements and others are linked together by the actual configuration of the develop-

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ment. There is not a right solution, rather a set of solutions that demonstrate how the different performance indicators are related. This approach allows us to select the final configuration with the client as multiple solutions can be seen and scored.

What methodologies of research were utilized? Why did you select this approach? Navigating the performance space promotes lateral thinking among designers and illustrates the relation between design variations and complex performance tradeoffs. The optimization model can then be adjusted and the process rerun with little extra effort to study impacts of parameter changes. Such studies can help designers to determine the best trade-off among performance and cost regions for the design as well as aiding multidisciplinary negotiations. This new design process enables improved design quality in less time with reduced cost, and can make new levels of complexity and new aesthetics possible. To move toward this future design process scenario, ARUP is incubating expertise in computational design and optimization (CDO) within its Foresight, Innovation, and Incubation (FII) group in London. CDO is about formalizing aspects of design tasks as computational models so that iterative computation, both interactive and automated, can be used to find feasible and performance-driven design alternatives that would be difficult to arrive at using conventional computing and design processes alone. CDO builds on and incorporates other emerging design computing technologies, including algorithmic design, 3D parametric and associative geometry, performance-based design, integrated design tools, and design automation. CDO is a great tool with clients as they can understand implication of certain design choices and the impact of performance quickly and interactively. The client does not need to wait days to see the implication of a change as the change has been already tested in advance.

Why was it effective, efficient, credible, and doable? What were the metrics? The CDO field is vast and comprises research in mathematics, operations research, architecture, aerospace, mechanical engineering, and civil engineering. However, a large gap still exists between research and practice in CDO, especially within the building industry. The reasons for this relate to methods, tools, and people. First, optimization methods are often only tested on small-scale benchmark tasks and do not often include practical design considerations and constraints, some of which can be difficult to model

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and are project-specific. Potential optimization tasks that could benefit from CDO generally have anything from five to 25,000 variables, from one to millions of design constraints, and from one to as many independent design performance objectives as can be incorporated. There is also often a mismatch between the areas where CDO can benefit projects most (i.e., in early design stages) and where it is straightforward to formulate computational optimization models (i.e., in detail design stages). The final reason relates to people, since CDO requires them to think and work differently. Making step changes in design processes is generally difficult. CDO requires new ways to model design tasks in terms of quantifiable design variables, constraints, and performance objectives, as well as giving up direct control of some design variables to a computational process that will determine their best values based on an optimization model formulated by the design team. CDO has been used most extensively so far on projects whose complexity has driven the need to adopt new computational processes.

What were the outcomes? A good design optimization task is one where there are design variables to work with and the designer needs to better understand the influences of their changes on one or more performances, to both meet design constraints and improve performances. The number of design variables and trade-offs among performances should be meaningful enough to justify the effort involved in creating an optimization model, finding or developing an integrated CDO tool, and carrying out optimization studies. This justification can be through sheer number of design variables, or potential gains in performance, or limited knowledge of how design variables and performances, especially multidisciplinary performances, interact. Through direct project work and many discussions about beneficial CDO applications on ARUP building projects, three areas with high potential are emerging: structures, facades, and building physics applications.

CASE STUDY PROJECT / Computational Design and Optimization (CDO)

C A S E S T U D Y P R O J E C T: C O M P U T A T I O N A L D E S I G N A N D O P T I M I Z A T I O N ( C D O

How were the outcomes applied, linked to, or used to help inform design? ARUP has used these technologies for a long time by introducing them in sensitive ways. The difference is that the new approach is more mature and can deal with a larger number of variables, parameters, and configurations. It is an evolution of our traditional approach.

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In industries like automotive, aerospace, and boating, CDO is an essential component of the design process in performance-critical applications. It has led to lighter, stronger, stiffer, and often cheaper automotive bodies, airplane wings, and ship keels. In building and infrastructure projects, however, it is only applied in small pockets and mostly for detail design tasks (e.g., automating the sizing of steel and concrete members for tall buildings), which have enabled both design cost and time savings. Drivers for increasing expertise in CDO include gaining marketing edge due to increased competition, desire for improved quality, shorter design time and cost, increased complexity (e.g., geometric) of projects, and to foster improved collaboration among multidisciplinary design teams. In addition to drivers, it is timely to expand expertise and the scope for CDO now, since it is enabled by increased computing power in both hardware and software capabilities, and increased computer fluency of young designers. Work within ARUP’s FII group is addressing these challenges to help bridge the gap between research and practice. Extending the expertise in CDO involves successfully combining modeling, methods, tools, and people. Recent progress in applying CDO in practice has extended the state-of-the-art of use in ARUP as well as contributions to academia. Benefits starting to be realized include extending what designers can currently do, enhancing design understanding, and improving design quality, time, and cost. Design time savings are often realized through the design automation component of CDO. Successful applications require designers who are willing to think outside the box in terms of both the design variants they are willing to consider and embracing new design processes that take advantage of emerging computational methods and tools. The next opportunities for CDO at ARUP, which will increase the potential benefits, include incorporating multidisciplinary viewpoints within CDO models and widening the scope to optimizing building form through collaboration with like-minded architects, and perhaps clients, to apply CDO at earlier design stages.

GENERATING OPTIMAL STRUCTURES With regard to structures, CDO has been used to generate efficient and aesthetically pleasing bracing systems for the proposed Bishopsgate Tower in London for Deutsche Immobilien-Fonds AG (DIFA), in collaboration with ARUP’s Building London Group 4 and working with architects Kohn Pedersen Fox Associates (International) PA (KPF).

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This curved tower, some 307 meters tall, required a lightly braced, randomized layout for the steel tubular stability system— “spirals” of fixed inclination wrapping around the irregular building envelope, emanating from column bases and terminating at varying heights up the building. A variable density bracing pattern was desired with more bracing elements at the bottom of the tower transitioning to fewer at the top. The optimization model for this task encoded 3 x 1,048 possible designs, a large number of design variants compared to what can be considered by hand. The objective was to minimize the number of bracing elements while meeting structural limits on maximum axial force in them, and maximum bending moment in the horizontal beams of the perimeter framework. A new CDO tool was developed initially to automate the manual, collaborative process carried out by the architects and engineers for generating, analyzing, and understanding design alternatives.

Figure 2.78 The Proposed Bishopsgate Tower Entrance Canopy— London

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CASE STUDY PROJECT / Computational Design and Optimization (CDO)

C A S E S T U D Y P R O J E C T: C O M P U T A T I O N A L D E S I G N A N D O P T I M I Z A T I O N ( C D O )

The search method employed is a variation of pattern search, originally proposed in 1961, that evolves efficient bracing patterns through iterative element removal and addition from fully braced and random starting patterns. This approach would not be possible using traditional numerical, or gradient-based, optimization methods. The “intelligent” search method, compared with basic automated iterative analysis and removal of under-utilized elements, gave improved designs in terms of reducing the number of required bracing elements for similar structural performance. It also needed substantially less computing time—three hours compared to 14 hours for basic design automation. Adding a random component to the search procedure and stochastic variation of the starting pattern enabled a wide range of

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Figure 2.79 Parametric Design Study of Bracing Patterns for the Bishopsgate Tower in London

design alternatives to be generated from the same process, all with similar structural performance. This benefits a team looking to select designs based on aesthetics, which are difficult to model explicitly within the CDO method itself. Parametric studies were carried out to explore the influence of structural limits on the minimum number of bracing elements in the system, allowing the team to make a more informed decision about which design performance region provided the best trade-off between the bracing pattern and structural limits. The Rhino CDO toolkit was motivated by an installation comprising a unique network of acrylic tubes. The approach taken combines spatial tiling, which are 3D spacefilling algorithms, with performance-driven structural erosion methods, in this case evolutionary structural optimization. Since spatial tiling does not often yield efficient structures, the aim is to find optimal networks of members within a given spatial til-

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Figure 2.80 Planning Application Bracing Schemes— Bishopsgate Tower in London

ing driven by the force or utilization in each member, while checking constraints such as strength, buckling, and displacement. The scale of the erosion takes starting designs consisting of thousands of members and erodes them down into a network of the most highly utilized of 500 to 800 members and support locations.

PANELIZING CURVY SURFACES

CASE STUDY PROJECT / Computational Design and Optimization (CDO)

C A S E S T U D Y P R O J E C T: C O M P U T A T I O N A L D E S I G N A N D O P T I M I Z A T I O N ( C D O )

Another promising area for CDO addresses the task of panelizing and rationalizing curvy surfaces. Typically, panelization of so-called “freeform” surfaces with flat or limited warp panels, triangular or rectangular, requires all the panels to be of unique dimensions. While it is possible to manufacture using state-of-the-art CAD/CAM capabilities, the fabrication and construction costs can be significant. CDO can be used to inform and negotiate building form rationalization to navigate the spectrum between extreme free-form surfaces and over-rationalization. A proof-of-concept investigation was carried out using a sample curvy surface for two scenarios: (1) panel joints allowed anywhere on the surface assuming that the outer surface is disconnected from the floor plates, and (2) panel joints required to remain at floor plate heights. The design objectives include matching the original surface within a chosen tolerance, using only flat panels and achieving some repetition in panel geometry. A purpose-built

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CDO tool was developed as a Rhino plug-in to operate on any defined surface in Rhino, given initial panelization defined as a mesh. The tool uses the stochastic optimization method of simulated annealing to carry out tens of thousands of iterations in about 15 minutes, trying to improve geometric uniformity among the panels while maintaining defined geometric constraints. CDO was successful in reducing the number of unique panels for the two scenarios described by 10 percent and 18 percent, respectively. Relaxing the tolerance on surface fit can then be used to guide surface rationalization. As architects’ desire for curvy building forms continues to grow, CDO can enable more cost-effective panelization solutions that preserve design intent.

BUILDING ENVELOPE OPTIMIZATION CDO also links with ARUP’s increasing interest and expertise in designing with building 496 panels on three surfaces—four possible panel types, 4.2 x 10,298 possible design physics. The goal here is to develop new CDO tools that facilitate the design of optimized building envelopes in response to lighting and energy criteria.

Figure 2.81 Generating an Intriguing Network of Acrylic Tubes for a Proposed Installation by Combining a Spatial Tiling with Evolutionary Structural Optimization

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Figure 2.82 Exploring the Trade-off Between Daylight Factors and Sun Hours for a Simple Two-Room Scenario

The results of this study were presented to the architects, who were enthusiastic and interested in both the bracing schemes generated and the novel design optimization process. Final bracing schemes for the planning application were submitted to the Corporation of London in June 2005. The final bracing pattern generated was modified slightly for the planning application, so as to improve the reading at the entrance to the building only. CDO tools may be used again as the design develops, both to investigate the possibility of refining the bracing pattern further and to incorporate, within the same process, parallel studies into the effects of varying individual steel member sizes on the overall efficiency of the building structure. This successful application of an established search method, tailored and extended, provides a valuable case study in applying structural optimization effectively, beyond section sizes alone, on a live building project.

CASE STUDY PROJECT / Computational Design and Optimization (CDO)

C A S E S T U D Y P R O J E C T: C O M P U T A T I O N A L D E S I G N A N D O P T I M I Z A T I O N ( C D O )

Other CDO projects in the area of structures include development of a Rhino CDO toolkit and an application to a steel space-frame stadium roof. Both involve developing automatic links between CAD tools and GSA, also called integrated design tools. The first project links Rhino and GSA to evolve novel frame structures, while the second links a parametric model in CATIA with GSA to optimize section sizes for the steel space-frame roof according to design codes. Integration of CAD tools and GSA enables automatic creation of GSA models from CAD geometry and structural attributes attached to geometry as well as the potential for gaining fast structural feedback within a CAD environment.

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BERNSTEIN INTERVIEW Phillip G. Bernstein, FAIA Without a major shift toward research that creates data for application in finding resolution to design challenges, much of the technology for modeling and simulating design performance outcomes—evidence—will be substantially under-utilized.

RESEARCH BACKGROUND

BERNSTEIN INTERVIEW

Figure 2.83 Phillip Bernstein

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Phil is a practicing architect with 25 years of experience and a vice president at Autodesk, Inc., a provider of architectural and engineering software, where he leads industry strategy and relations for the AEC Division. At Autodesk he is responsible for setting the company’s future vision and strategy for technology serving the building industry, as well as cultivating and sustaining the firm’s relationships with strategic industry leaders and associations. Prior to joining Autodesk, he was an associate principal at Pelli Clarke Pelli Architects. He is on the faculty of the Yale School of Architecture, where he teaches courses on architectural practice and management. He writes and lectures extensively about practice and technology issues and has been published in Architectural Record, Architecture, Design Intelligence, Fortune, and Perspecta. He is a trustee of the Emma Willard School of Troy, NY, a senior fellow of the Design Futures Council, a Fellow of the American Institute of Architects, and former chair of the AIA National Documents Committee. He is a leading voice advocating the adoption of innovative digital technologies in architectural practice and influencing teaching and research about these technologies in schools of architecture around the world.

How does evidence play a role in informing your work? Architects have traditionally not had systematic methods for collecting evidence or rules, nor specific knowledge from which they could consistently infer decisions in their design actions. They have relied on the other side of the brain—their intuition and experience. One of the major problems facing architects at this point is to make the design process more

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logical, supported with better representational and analysis tools. Design representation that can help evaluate systematic evaluation of a complex set of relationships must be supported by data which is otherwise sorely missing from the design process itself. If we want to develop a more knowledge-based enterprise in practice we must develop appropriate technologies to organize and inform the design process. The current existing technologies, both 2D and 3D, have limited capacity to actively provide performance analysis of the design. At Autodesk we have a different perspective—we want to develop a technology that will support the design process and systematically categorize information, and, secondly, provide iterations of ideas for logical analysis. We are trying to transition from technology that is primarily a presentation platform to one that can utilize parametric algorithms allowing designers to explore a design challenge such that the outcomes of design decisions are transparent and supported by factual evidence.

Can you give us a sense of kind of information (data) you need to make this technology effective?

At the present time the existing technologies for modeling and simulating buildings are primarily focused on form generation. When we move beyond form generation, the problem set is three orders of magnitude more complex. As such, to address types of building performance issues like water use, energy, lighting, structure, etc., not only are the issues more complex, but the analysis algorithms are much more difficult to construct. Getting performance outcomes that are grounded in a transparent process, and providing evidence from the modeling and simulation that allow the designer to make better informed decisions that reflect the value added by the design itself, is the real goal we’re working toward.

Will the use of these types of technologies inhibit or enhance creativity? In my judgment, use of these modeling and simulation tools will undoubtedly enhance creativity—assuming they are easy to apply and the results are transparent

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BERNSTEIN INTERVIEW

Let’s take sustainability, for example. We know that sustainability as a design objective is comprised of a complex set of issues and the interaction of many variables like energy optimization, enclosure systems, building orientation, heating and cooling systems, alternative energy generation, etc. We need to be able to isolate these variables so they can be modeled individually as well as be integrated into a larger framework and their interrelationship with other variables determined when individual subcomponents are varied. In both cases, the underpinnings are to understand the impact on specific performance expectations and outcomes.

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for the stakeholders. Modeling and analysis tools will allow the designer to explore a broader range of options based on objective results rather than mere intuition. In fact, the inherent danger of using generative technologies will be that they create so many alternatives that it’s difficult for the designer to manage and use the outcomes, particularly when they’re buried in options. It will still be critical to use the innate sensibility of the designer to sort through these alternatives and options and make a final judgment, but the tools can provide factual feedback as options are generated, and perhaps even sort the viable from the untenable. Cesar Pelli used to caution us about using the computer for the “systematic generation of useless alternatives,” which I think is an excellent word to the wise.

BERNSTEIN INTERVIEW

In the aerospace industry there are a group of designers who are interested in multidisciplinary design optimization. They develop algorithms for outcomes for each single discipline and then model those outcomes simultaneously to determine the whole system impacts and performance. This works well to design an aircraft wing, but in architecture there are sets of decisions that don’t lend themselves to this type of process because of the need to mix the practical and the aesthetic. Both filters are needed to wend through this thicket of options, and that will differentiate the talented from the nontalented. There is no “evidence-based process” to find beauty, so there will always be a need for the designer to create or discover it.

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Further, an explicit process design is as important as final design outcomes. Defining such a process with evidence-based generation and sortation of alternatives is one of the primary values of the use of model-based design technology. Rather than create or evaluate alternatives based purely on the designer’s judgment, why evaluate computationally, based on data and established rules? Two years from now there will be no excuse for a building not to properly utilize sunlight for lighting because we can simulate this information so accurately. You can take a Revit model, connect it to a 3DS Max model, and it will tell you the lighting level on every surface of a building for every day of the year. So there’s really no excuse for not mastering that characteristic of your design. If this approach is expanded to accommodate other constraints we can create the basis for other design processes that will generate taxonomies that frame the problem-solving objectives. At Autodesk we are examining some key issues in this regard, including geometry generation, sustainability, cost estimating, and structural engineering. As you can imagine, however, these problem sets are very lengthy, complex, and costly to develop.

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Historically industry professionals have been good at collecting evidence to address questions of how to build, but very weak when it comes to doing so about what to build. Consider three avenues of design investigation: First, the nonrationalized approach—“I am the architect. I know what to build, so trust me”; second, the postrationalized approach—“I have a cool idea, but I do not know how to build it so I’ll use lots of sophisticated digital tools to understand it, engineer it, and then finally represent how to build it”; and finally, a prerationalized approach—“Here are rules describing the expected performance outcomes of what I want to build, and the computer can find the solution.” It is the prerationalized approach that is the future of design activity. It is, however, not enough to have an algorithm to drive the process. There is a critical need for an open knowledge base from which the algorithm can draw a range of overlapping answers from which the field of possible solutions can be found. Historically, architecture has been an “old person’s” profession, where years of experience were considered necessary to become a seasoned designer. This experience, however, is not transferable because it is person-specific, and this is not going to change. But is it possible for one person to absorb and integrate all the current performance demands, new innovative building systems, design theory, not to mention all the new insight into architecture from the neurosciences and behavioral sciences necessary to design today? Probably not, but the modeling and analysis technologies will not “catch up” in the near term. So architecture will need experienced leaders to help find the appropriate possible solution sets to specific problems and this means that the “old person’s” profession will persist—but supported by new tools.

One of the challenges here is to create a knowledge foundation for prerationalized exploration. If you look at the current sociology of information in AEC, you’ll find that it is broad-based and poorly organized. This will continue, particularly with the expansion of the Internet, and so what’s needed is data mining structures that are very smart at looking at very messy information. This is basically what Google has done but at a limited scale, far short of what’s necessary in the building enterprise. It is critical for our profession to create infrastructure so that our data—our collective wisdom—can be shared. We need the equivalent of a social network, or perhaps crowd-sourcing. All the data must be warehoused so everyone has access—“building performance data on Facebook,” for example. If one looks at the

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BERNSTEIN INTERVIEW

Do you see information/data utilized by these technologies as being ubiquitous and shared or limited and proprietary?

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struggles to establish standards for this type of data sharing, the solutions that are vaguely disorganized, organic, and market-sensitive are the most successful. Those that attempt to articulate a set of standards and regulate use in a highly structured way have mostly failed.

BERNSTEIN INTERVIEW

The two primary constraints of access to knowledge are storage capacity and processing speed which today are unconstrained—so store as much data as you can get your hands on and use the brute force of processing capacity to organize the data into new structures that provides new insights. So what I’m suggesting here is the need for an open-source database of accumulated knowledge about buildings. Let individuals mine that vast storehouse of the data to determine relationships which can inform their decision-making process—this is “evidence.” That sort of data should always be open, but the interactions with the data can be proprietary. For example, the data in a Revit model is rather uninteresting in and of itself, but the technology to structure, organize, and interact with it and use it costs hundreds of millions of dollars to develop and progress. The two concepts—data structure and means of interaction—are deeply connected.

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The lack of a research tradition in the AEC industry is a major barrier to the creation of data necessary to drive current practice. We don’t have a knowledge-transfer platform in our professions. At one level we lack the intellectual infrastructure for this process to become meaningful. Renee Chang from the University of Minnesota and Laura Lee from Carnegie Mellon University are working on this challenge. They basically say, “In architecture we do not have the systemic infrastructure to generate our own knowledge or to provide meaningful input to encourage researchers from other disciplines to undertake research related to our design concerns.” If I were to ask one of the people in an office to research a specific subject, that person would probably not know what to do other than “Google it.” There is no real comparison between how design practitioners define research in architecture and what most scientists think of research. We have no similar structures that provide that rigor—ranging from literature search to peer review of the outcomes of our research efforts. We lack the foundations of things like extensive PhD programs, research laboratories, and institutes that provide the vehicles for this type of knowledge creation. For a country that spends a trillion dollars annually on construction, the AEC industry is a “cottage industry” that is very disorganized and fragmented and unfortunately adversarial. This concept of evidence-based design is going to be limited not because there is not a need for the process, but because of the lack of knowledge structures to drive the analysis processes to produce evidence. We have developed very sophisticated tools

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to model and simulate complicated building systems, but what is lacking is the content or data to populate these tools.

What are your thoughts on the changes needed in architectural education and/or the practice model of our profession to meet these challenges? To make meaningful change in our educational and professional enterprises there is a need to look carefully at the infrastructure of professions or industries that are knowledge-intensive—like law, medicine, pharmacology, biochemistry, computer science, and organizational management. This challenge needs to be addressed as a design problem—build an infrastructure for architectural research and practice that produces and disseminates useful knowledge about outcomes that are open, shared, and easily accessible. As part of this review, it is important to address the following questions: What are the sources of knowledge? What is the culture of the operational components for research and the application of knowledge in practice? How is knowledge archived and shared? What types of new tools and other resources need to be developed to support this type of research in the academy and in practice? What is the education model for making this research strategy operational?

BERNSTEIN INTERVIEW

In the professions with intensive knowledge demands, there is a culture of knowledge interdependence, where one piece of research is nested in a larger structure of exploration that is open, shared, and dependent on the critical review and elaboration of an outcome by peers. The pipeline of this knowledge is a mechanism for sharing outcomes through written papers, conferences, peer review, institutes and centers for collaborative research efforts, and networks of organizations that provide resources.

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C ASE S TUDY P ROJECT CASE STUDY PROJECT / The Chicago Project

Research in Architecture Phillip Bernstein, Vice President Autodesk The Chicago Project

Figure 2.84 Observing Designer Interactions in a Collaborative Setting

The research methodology is to simulate the convergence of three currently parallel design techniques through the production of a demonstration video and to observe the reactions of those interacting with the system, and those viewing the demonstration video.

What is the research question? Hypothesis: That a technology, which supports the convergence, or sequential experience, of currently parallel design processes required for sustainable design would improve sustainable design outcomes.

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The research methodology is to simulate the convergence of three currently parallel design techniques through the production of a demonstration video and to observe the reactions of those interacting with the system, and those viewing the demonstration video.

Figure 2.85 Exploring the Alternatives with Multiple Discipline Interactions

CASE STUDY PROJECT / The Chicago Project

What is the research methodology and which aspects are useful for architects?

The movie portrays designers interacting in a simulation which links visualization of a proposed design, analysis of sustainable characteristics of the design, and an assessment process of evaluating design effectiveness for the purpose of achieving a sustainable design rating, such as LEED™.

What are the anticipated outcomes and how can they be useful for clients and architects? By observing the interactions of designers during the process, and observing reactions to those who are seeing others interact through a simulation, we anticipate a positive reaction to the vision and an awareness of the opportunities, which would be represented by a convergent system. We anticipate that designers will describe how a hypothetical system might impact their design process and improve their understanding of sustainable design decision making.

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CASE STUDY PROJECT / The Chicago Project

How does this research help architects envision the link between architecture and research?

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This project provides architects with insight into the ways that research can expand the definition and the capabilities of the profession.  Figure 2.86 Systems Impacts on Decision-Making and Modeling

 Figure 2.87 Process in Action in a Collabortive Setting Using Simulation and Modeling Computation Technologies

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C ASE S TUDY P ROJECT CASE STUDY PROJECT / 1560 Trapelo Road

1560 Trapelo Road

Figure 2.88 The Trapelo Road Interior ©Jeff Goldberg /Esto

This project demonstrates how a well-documented process can yield insights to improve future projects in cases when traditional contract mechanisms are employed, and also in cases where innovative methods are implemented. What is the research question? Hypothesis: That a joint contractual relationship which links owner to architect to contractor will improve design outcomes by eliminating waste and liability-avoidance which firms experience when working as separate entities.

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What is the research methodology and which aspects are useful for architects? CASE STUDY PROJECT / 1560 Trapelo Road

The research methodology is to conduct a real project using a new contract mechanism, and to document project process and outcomes.

What are the anticipated outcomes and how can they be useful for clients and architects? The anticipated outcomes are to achieve a project within the established timeframe and budget, but with a higher level of satisfaction among team members, and a higher quality project. The outcomes are incredibly useful if this method can be extended to improve project quality and efficiency and satisfaction on other AEC projects.

How does this research help architects envision the link between architecture and research? This project demonstrates how a well-documented process can yield insights to improve future projects in cases when traditional contract mechanisms are employed, and also in cases where innovative methods are implemented.

Figure 2.89 The Trapelo Road— A Place to Work ©Jeff Goldberg /Esto

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KAISER INTERVIEW John Kouletsis and Barbara Denton National Facilities Service Division, Kaiser Permanente We are committed to applying the best evidence we can find—learnby-doing if you will. The Garfield Center, which is a facility for mocking-up solutions to design problems, is a major contributor to increasing our creative outcomes. It is a setting where proposals can be tested and evaluated before going live at a health-care facility.

Figure 2.90a John Kouletsis

Figure 2.90b Barbara Denton

John Kouletsis is the Executive Director of Strategy, Planning, and Design with Kaiser Permanente’s National Facilities Services. He joined Kaiser Foundation Health Plan, Inc., in 1991. During his tenure at National Facilities Services, Kouletsis was responsible for developing the Kaiser Permanente Standards Program. He served as the Program Director for Templates 2000, an initiative to research all of the clinical spaces Kaiser Permanente builds and tests with front-line physicians and staff in terms of function and workflow. Extensive internal and external benchmarking, as well as design sessions with more than 1,000 clinicians and support staff over a period of 18 months, built the basis for the Standards Program. Kouletsis is also the Executive Director for both the Template Hospital Project, Kaiser Permanente’s hospital of the future, and Kaiser Permanente’s High Performance Buildings Initiative. His department is responsible for developing and improving the Kaiser Permanente Standards Program and he is one of the sponsors of the Sidney R. Garfield Centers for Health Care Innovation. Prior to joining the National Facilities Services Core Group, Kouletsis worked as a Project Manager at Kaiser Permanente’s Vallejo Medical Center. Barbara Denton is Team Manager of the Environmental Design and Research Team of Kaiser Permanente’s National Facilities Services, Strategy Planning and Design group. Her team is dedicated to design innovation in the health-care environment, and focuses on sustainable building

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RESEARCH BACKGROUND

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strategies including environmental toxics reduction and energy efficiency, safety by design, and integration of the brand into the built environment. This work also includes signage and wayfinding systems, diversity issues related to implementation, and organizing multidisciplinary teams to create evidence that informs design for health-care environments. Denton is the Project Director of the Total Health Environment Initiative. This initiative is a partnership between Brand, Service, Information Technology, Clinical Delivery, and Facilities to align the Kaiser Permanente Brand with the built environment. Consumer-based research conducted in all Kaiser Permanente regions across the country informs design solutions for this important initiative.

KAISER INTERVIEW

Could you describe the range of activity that Kaiser Permanente has in research related to facility design and construction?

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Kaiser Permanente has been involved in the evidence-based process for decades, first as a major contributor in establishing the concept of evidence-based medicine. For two decades Kasier Permanente has been developing design and construction standards to guide our facility development programs. The concept of evidence for Kaiser Permanente is a comfortable notion. We have become a believer in using a wide range of evidence; evidence developed by the “Gold Standard” of research—the double blind study, to direct observational studies of existing and proposed facility conditions. The goal is not only to make our facilities better for our patients and staff, but to also increase the capacity of our facility planning and design staff to respond to ever-changing facility challenges. As an insurance and health-care provider as well as facility owner, Kaiser Permanente is faced with a set of complex demands—longterm agendas of new and innovative facilities to accommodate the rapidly changing context of health-care delivery, and, at the same time, address immediate challenges of renovation, retrofitting existing facilities, and building new hospitals and other health-care facilities to meet today’s current demands. We have the whole spectrum of research at work—rigorous scientifically grounded studies through short-term critical research questions that are connected to a specific project that needs an immediate response. Most of the scientific research completed is undertaken under contract with an outside research agency or consultant, however, Kaiser Permanente does have a substantial in-house research group working on a range of studies. In-house research relies heavily on going through existing data (i.e., patient health records and satisfaction outcomes) as well as working with an expert panel of users, doctors, nurses, technicians, patients, research specialists, and other service staff. The primary reason for

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this approach is not only does it involve the end-users who have a major stake in the outcomes, but it allows Kaiser Permanente to be fast in producing performance outcomes that can immediately guide our design and planning agendas. All of our decisions are grounded in some type of evidence that is transparent and ranges from the most rigorous possible, to the observations of a limited number of users and experts. The backbone of this process is the use of diverse content expert panels guided by a nine-step process that produces transparent methods and performance outcomes: 1. Frame a critical question, create a hypothesis 2. Extensive literature review about the question 3. Review findings from the literature by an expert panel 4. Expert panel finds a potential solution or solution set 5. Recheck the appropriateness of the solutions with end-users and experts 6. Mock-up the standard at the Garfield Center 7. Run simulations and other exercises at the Garfield Center to test the appropriateness of the solution 8. Create a standard to guide the execution on project 9. Conduct postoccupancy evaluations; a lifecycle approach—cradle to grave. Communication is obviously an important part of this content expert panel approach; however, it is made easier because we are a one-parent organization, who owns 100 percent of the information and data—the evidence. As such, we must take responsibility for framing the outcomes, the information, and data in a language form that is understandable and will create buy-in by the stakeholders of the outcomes, either the evidence or project proposal.

We have three ways to determine this. First, we have situations where we have to undertake a specific research study, like the Latrobe, with the agenda to create new knowledge or evidence. Most of our work, however, is grounded in confirming existing evidence that has been produced by other research studies, and evaluating this evidence in terms of its appropriateness for application to our specific design challenges. Finally, when time or resources are a major constraint, we use what we call “precautionary principle.” If there is a panel of experts who think that what we are

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How do you determine that the evidence you use to make specific design and planning decisions is rigorous enough?

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proposing is appropriate and will not cause harm, we accept the available evidence as the basis for moving the project forward. Another major influence of our work is the size and scale of our operation. We have more than 4,000 projects underway in any given year. They range from quite small to enormous—reroofing to major new hospitals. This volume of work requires the creation of about 400 project teams, working on a variety of projects. This makes it easy to find a project somewhere or an individual within Kaiser Permanente who is an expert on most any situation we might encounter. When this does not happen, then we seek help from external experts and consultants. Kaiser Permanente has several suborganizational parts with specific agendas in terms of the delivery of some form of health-care service connected to patient safety, workplace safety, or environmental safety. We try to leverage each of our research efforts to engage as many of these other suborganizations in the projects of Kaiser Permanente’s National Facilities Services. This not only provides better buy-in on implementation, but also provides a rich and diverse set of experts to support and review our work. We also have developed a strong network of agencies and research institutes (CDC, NIOSH, EPA, DOE, DOD) that do research related to health-care concerns. We partner with them regularly to either assist us with our research or use their outcomes to inform what we are doing on a specific topic or project. We are a hierarchically structured organization, so most everything we do gets several levels of reviews from the immediate staff and end-users to Kaiser Permanente senior management.

KAISER INTERVIEW

How does this process of using expert panels grounded in evidence generation and application enhance or inhibit creativity?

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Without question this way of working enhances creativity at Kasier Permanente. Kaiser Permanente staff want to participate on a content expert panel so they can contribute to find a resolution to a challenge. Kaiser Permanente is committed to implementing and applying the evidence we find—learn-by-doing, if you will. The Sidney R. Garfield Health Care Innovation Center, which is a facility for mocking up solutions to design problems, is a major platform we use to test and confirm our creative outcomes. It is basically a setting where rapid physical prototyping takes place so that proposals can be realized and evaluated before taken to real-time in a health-care facility. This facility lets us test design proposals and their performance outcomes on some dimension of service delivery, patient safety, staff productivity, and environmental risk reduction in a low-risk environment.

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It is clear within National Facilities Services there are several methods of approaching the creation or establishment of evidence and its application. How would you describe this array of methods and approaches?

What would be an example of a research project that was directed at creating a set of standards to guide design efforts within National Facilities Services? About 75 percent of our research is focused on developing standards to guide our design and construction efforts. A good example of this process was our recent commitment to reduce toxic materials in our furnishings used within our facilities as a part of our larger concerns with addressing sustainability. Due to Kaiser Permanente’s buying power—purchasing $40 million of furniture each year which includes a large amount of fabric—we felt we could influence fabric manufactur-

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The majority of our research and evidence construction is attached to immediate projects, and needs implementation strategies as quickly as possible, but are grounded in the best evidence available at the time. There are a number of examples drawn from what we refer to as the Total Health Environment Initiative. The goal of this initiative is to establish how Kaiser Permanente can make the experience of patients, physicians, and staff better by creating better settings for those experiences. We also have an initiative to create better, greener, and safer work and treatment places, a major effort to recycle construction waste, to use fabrics with fewer toxic chemicals in and on our furnishings in our health-care settings, and better facility lighting conditions. Each of these projects has a range of methods, metrics, and performance outcomes. Some, like the Total Health Environment Initiative, was a major study conducted with external consultants working with internal content experts and comes close for us in National Facilities Services to being the “Gold Standard” for doing research using scientific methods. At the other end of the research spectrum is a construction-recycling project done internally by a limited number of our staff at one Kaiser Permanente hospital. Staff developed the strategy, standard, and guidelines so implementation could be used throughout Kaiser Permanente. Due to this project, Kaiser Permanente now recycles almost 100 percent of its construction waste. The measure of what evidence we need, what methods are needed to create it, and how to measure performance outcomes is based on the simple criteria of what, how, and when can we get the best evidence within the constraints of the existing project schedule and budget. It is critical to know that most of this work is a bottom-up approach rather than a top-down effort. Efforts start with end-users and are implemented by professional staff with strong management support from the top.

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KAISER INTERVIEW

ers to respond to a new set of low- or no-toxic chemical fabric standards. The basic approach was to ask an outside chemical expert firm to provide us with a list of toxic chemicals that are used in the production and/or finishing of fabrics used in furniture and other building furnishings (i.e., drapery, floor covers, etc.). With this list in hand, we created a Content Expert Panel (15 people) with both internal and external experts to review and evaluate the list of chemicals and develop a strategy to approach fabric manufacturers to see how their production process and fabrics rated in terms of this list. Kaiser Permanente sent a questionnaire to major fabric manufacturers requesting responses and notified them of Kaiser Permanente’s attempt to create a new design standard for fabrics that would be used within the organization. Kaiser Permanente took the questionnaire results and created criteria to set tiers for sustainability in fabrics. This resulted in a three-tier structure: Tier One—limited or no toxins; Tier Two—acceptable levels of toxins; and Tier Three— unacceptably high levels of toxins. Kaiser Permanente set a standard that resulted in: Tier One—the most acceptable fabric; Tier Two—could be acceptable under certain circumstances; and Tier Three—fabrics would not be purchased or used. Evaluating fabric manufacturers using these criteria, we found only three manufacturers who met Tier One and Tier Two standards. Kaiser Permanente made agreements and partnerships with these manufacturers to supply the materials for our furnishings and facilities. It is our hope that Kaiser Permanente’s buying power will encourage other manufacturers to make changes; change the approach of the whole industry to increase the number of manufacturers who are operating more sustainably; and increase the range of fabric products. We have shared our process and outcomes openly so that other organizations could use our findings to inform their projects as well and hopefully encourage other changes that are more in line with current attitudes about being green. (See the Case Study for more detail.)

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The second project is the “Total Health Environment Initiative.” This project aligns our patients’ facility experiences with our brand strategy—“Total Health” —and the messages in Kaiser Permanente’s advertisements. An outside consultant was hired to undertake the project. An 18-month study using multiple research methods resulted in what is referred to as the emotional journey of a patient. This emotional journey was translated into 21 key experiences, and design criteria and solutions were established for each of the zones, based on member-focused research. These criteria have now become a standard that defines the acceptable performance outcomes in these 21 key experiences in Kaiser Permanente facilities that designers and architects must meet in their project proposals, both in new and renovated Kaiser Permanente facilities.

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This is a project that was resource-intensive both in terms of expertise, but also in financial and management support. For us it is at the upper end of our standard for doing research in the facilities area. It was a critical study to provide evidence for future organizational planning as well as guiding Kaiser Permanente’s design and construction efforts. (See Case Study for more detail.)

Do you think it is possible for an individual architect or firm to undertake these types of research efforts? Our immediate response is yes, but qualified by the level of resources required. It is true that our size and buying power has leverage, but the types of questions we asked about toxic materials, or human experience and performance could be asked by any designer or architect. The first example would take moderate resources to structure and implement the methodology of the research, but there are a number of organizations, like the Center for Health Design, that one could partner with to get the support of a critical mass of service organizations, architects, interior designers, product designers, etc., to get manufacturers to respond. It is not likely an individual firm will get a manufacturer to change its product line, but toxins are toxins, so if the outcomes are transparent and designers are responsible by specifying sustainable products, the level of influence could expand significantly and should and probably would bring about change.

KAISER INTERVIEW

In the case of the Total Health Environment Initiative it is not likely that an individual or firm could undertake such an effort unless, like in this case, the consultant was an architectural firm with a research division with internal resources. The resources and expertise required in this type of project limits who and how this type of study could be undertaken. The important points here, however, are how the critical question or research study is framed, how the strategy for creating the network of interest is established, what level of financial support is available, and is there a capacity to establish a collaborative and interdisciplinary team of experts to address the research question.

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C ASE S TUDY P ROJECT Creating a Sustainable Fabric Alliance Program for Kaiser Permanente John Kouletsis and Barbara Denton National Facilities Services—Strategy Planning and Design

Figure 2.91 Sustainable Fabrics Used in a Kaiser Permanete Hospital Patient Lobby

Our mission is and always has been to improve the health of the communities we serve, and that includes an emphasis on environmental stewardship. What’s good for our environment is going to be good for our members, our staff, and the community as a whole. George Halvorson, CEO, President, and Chairman of the Board, Kaiser Foundation Health Plan, Inc

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Examples of Kaiser Permanente’s Sustainable Interior Creation of the Sustainable Fabric Alliance provided the following benefits to Kaiser Permanente and the communities that Kaiser Permanente serves:  Sustainable fabrics included as part of the Sustainable Fabric Alliance do not

cost more than other products on the market and in most cases represent a cost reduction.  Sustainable fabrics perform as well as the nonsustainable products previously

purchased.  Adoption speeds a general movement in the textile industry toward

sustainability: 

Use of recycled materials reduces the amount of waste in landfills.



Eliminating heavy metal dyes in the manufacturing process reduces contaminates in the water supply.



Removing PVC, mercury, and other dangerous chemicals in the nonwoven fabric products decreases the amount of harmful toxins in Kaiser Permanente facilities.

OVERVIEW In November 2007, after a rigorous selection process, Procurement and Supply and National Facilities Services (NFS) completed formal pricing agreements with three fabric vendors—Designtex, Maharam, and LDI Corporation—resulting in the creation of the new Sustainable Fabric Alliance Program. With the reduction from four to three fabric vendors in the Alliance program, the three vendors will obtain increased volumes. Kaiser Permanente will use only sustainable fabrics at a substantial savings, compared to the fabrics in the current alliance program. Through extensive communication and sharing of its findings, Kaiser Permanente leveraged the fabric industry to move toward more sustainable products. Kaiser Permanente will also continue to study and bring attention to important environmental, health, and safety issues, and will use its purchasing power to transform the industry. Ultimately, the extent to which these changes affect our choices as designers, architects, and health-care professionals is determined by our willingness to meet and share our concerns with market leaders and our resolve to make changes individually and within our own organizations.

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PROBLEM STATEMENT  Incorporate environmentally sustainable products into the Fabric Alliance  Establish cost control/cost savings for the new sustainable fabrics  Reinforce the Kaiser Permanente brand position of “Total Health” in all its physical

environments

FINDINGS For many of the Content Expert Panel participants and stakeholders, environmental considerations had never played a key role in their decision-making processes beyond considering recycled content. While some were aware of Kaiser Permanente’s Environmentally Preferable (or Preferred) Purchasing (EPP), most had not been provided with the scientific support or rationale behind the policy, particularly with the human health concerns underlying the chemicals and materials to avoid. Performance, customer service, and aesthetic issues were the primary considerations when choosing fabric and fabric vendors. Environmental issues were either undervalued or not considered at all. The importance of the educational process provided cannot be overemphasized. Rather than asking the team to accept Kaiser Permanente’s environmental concerns without question, Kaiser Permanente staff and consultants invested time and resources into bringing pertinent environmental information and considerations to all the participants and stakeholders. Ultimately, everyone was equipped to consider the variety of fabric offerings provided by the fabric vendors in the context of human and environmental health concerns. The new Sustainable Fabric Alliance Program categorized fabrics into three categories:  Category I—Fabrics that do not contain any chemicals of concern as outlined in

the EPP. In addition, no antimicrobial treatments are used and no finishes utilizing bio-accumulative toxins are applied.  Category II—Fabrics that avoid at least three (3) chemicals of concern as outlined

in the EPP. Kaiser Permanente notified all three vendors that Category II could only be specified over the course of the initial contract, and that Kaiser Permanente expected all vendors to develop new lines of fabric that would meet the standards of Category I by the end of the first contract period.  Category III—Fabrics that currently do not meet any of the sustainable requirements

listed in categories I or II but do meet the performance criteria established in Kaiser Permanente’s Furniture Standards Program. Kaiser Permanente notified all three

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vendors that Category III fabrics would be phased out at the end of the initial contract period. Significantly, Kaiser Permanente asked each vendor to commit to reducing or eliminating fabrics and finishes that contain PVC, HFRs, VOCs, PFCs, heavy metals, and antimicrobials; and all four vendors agreed.

THE PROCESS TO CREATE A NEW FABRIC ALLIANCE PROGRAM In 1996, Kaiser Permanente developed the Fabric Alliance Program to ensure a uniform quality level for fabrics, and to consolidate the volume of fabric purchased annually to a small group of fabric vendors. It also established a per-yard cost cap for all upholstery, cubicle curtains, and draperies used in Kaiser Permanente facilities, and established criteria for fabric selection including performance criteria, fabric content, and maintenance. Additionally, the program created informal relationships with a limited number of nationally recognized fabric vendors. The original Fabric Alliance Partners were Architex, Design Tex, Maharam, and Momentum Fabrics. The Fabric Alliance relationships were informal because most fabric at Kaiser Permanente was purchased through third parties. For example, upholstery fabric is purchased through furniture manufacturers, and cubicle and drapery fabrics are purchased through general contractors and their subcontractors or through the Materials Management or Environmental Services departments at local medical centers.

Figure 2.92 Clinic Waiting Room—Kaiser Permanente Sustainable Interior

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C A S E S T U D Y P R O J E C T: C R E A T I N G A S U S T A I N A B L E FA B R I C A L L I A N C E P R O G R A M

The Fabric Alliance Program is still in effect today. However, in the summer of 2006 a group of core team members from the National Facilities Services, Strategy Planning and Design team realized that significant improvements were needed in order to incorporate environmentally sustainable products into the alliance. Furthermore, Procurement and Supply recognized the

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importance of establishing cost control/cost savings for the new sustainable fabrics, compared to the current fabric line. Moreover, it was anticipated that the new sustainable fabric selections and cost reductions would be a perfect opportunity to reinforce the Kaiser Permanente brand position of “Total Health” in all its physical environments. National Facilities Services leadership asked the Furniture SST to convene a Content Expert Panel, made up of in-house content experts and interior design consultants to redefine the Fabric Alliance Program. Procurement and Supply aimed to formalize the relationship with the Fabric Alliance vendors through pricing agreements while National Facilities Services wanted to incorporate sustainable practices and fabrics into the program. As a diverse group of multidisciplinary stakeholders were participating in the process, Kaiser Permanente staff recognized that to achieve the desired goals, the CEP needed to have a common understanding of the environmental issues involved in sourcing fabrics. NFS staff and consultants introduced Kaiser Permanente’s history on environmental issues and shared Kaiser Permanente’s Environmentally Preferable (or Preferred) Purchasing (EPP) policy. Information about the key toxicants that are found in fabrics was discussed and a background on the current state of recycled content and fabric recyclability was provided. In turn, the CEP more readily identified challenges within the industry (as well as within Kaiser Permanente) that needed to be addressed in order to source more environmentally responsible fabrics.

RESEARCH AND DATA GATHERING The research and data gathering process was a four-step process. The first step in the process was to create a list of fabric vendors recommended by Kaiser Permanente interior design consultants. The second step was designed to gather information from these fabric vendors on the environmental attributes of health-care fabric. In order to achieve this, Kaiser Permanente and its consultants sent a prequalifying survey, or Request for Information, to the list of vendors. This prequalifying survey was sent to 17 fabric vendors, including many of the largest contract fabric vendors in the country. In the end, only 12 of the 17 vendors responded to the survey. The prequalifying survey asked a number of questions about sustainable product practices and fabrics, including:  What percentage of the company’s entire offering the sustainable products

represented  Whether those product lines included key chemicals and/or materials of concern

as stipulated in the EPP  Whether the products had received any indoor air quality (IAQ) certification for

low Volatile Organic Compound (VOC) emissions

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 The percentage of recycled content in their sustainable products  Whether products were recyclable or compostable  General questions about the corporations’ environmental policies and plans for

sustainability into the future In summary, all but one company offered limited products free of PVC and HFRs. Most companies offered recycled or bio-based content products or recyclable or compostable products, and about 75 percent of respondents had (limited) products tested for indoor air quality. Environmental policies ranged from those companies having no environmental policy in place (“Goal is to make money”), to those companies that are making broad commitments to being “leader[s] in sustainable materials…..we’ve adopted environmentally sound practices.” A few companies stated that they had very rigorous protocols in place to evaluate the use or nonuse of PBTs. Some are not using them at all. A few companies identified tough benchmarks to mark their environmental progress. At the end of Step Two, it was determined that while the information from the 12 companies was valuable to understand the commitments each was making, it did not provide enough detail to enable the CEP to narrow the number of vendors for the next stage of inquiry. As a result, 11 of the 12 responding vendors were asked to continue to the third step—the detailed survey.

CASE STUDY PROJECT / Creating a Sustainable Fabric Alliance Program for Kaiser Permanente

C A S E S T U D Y P R O J E C T: C R E A T I N G A S U S T A I N A B L E FA B R I C A L L I A N C E P R O G R A M

Figure 2.93 The Raw Materials of Sustainable Fabrics

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The third step was rigorous in that it required the vendors to complete a full survey for each individual family of fabrics for consideration, which for some companies required more than ten different detailed responses. Moreover, the fabric vendors were asked to provide a list of their sustainable products as well as extensive questions regarding their commitment to sustainability. Finally, they were asked to include any information on additional environmental issues for health-care fabrics not yet identified by the survey. The survey required manufacturers to identify:  The full material content of the fabrics and any treatments, including whether

the products contained polyvinyl chloride (PVC), halogenated compounds or flame retardants (HFRs), perfluorochemicals (PFCs), volatile organic compounds (such as formaldehyde), and other chemicals of concern (fiberglass, heavy metals, antimicrobials, fungicides, and other persistent bio-accumulative toxicants)1  Any indoor air quality emission tests the fabrics had passed2  Recycled fabric content, specifically preconsumer and postconsumer recycled content  Performance results for standardized test data developed by the Association for

Contract Textiles (ACT)  Recyclability and other end-of-life issues, including identifying leaching or off-

gassing issues at end of life of the product  Product transportation and packaging information

Throughout Steps Two and Three, the prequalification and detailed survey processes, and prior to in-person meetings with vendors, not one fabric vendor required Kaiser Permanente to sign a nondisclosure agreement regarding the information that they provided to the CEP.3 The consultants then accumulated and analyzed the responses for the CEP. They reviewed each family of fabrics focusing on key toxicants, indoor air quality issues, and recycled content, and separately on the fabric finishes.4 1. For a detailed description of the chemicals and materials of concern associated with fabrics, read “Future of Fabric: Health Care” from Health Care without Harm and the Healthy Building Network, October 2007. 2. For a detailed description of the indoor air quality emissions standards and certifications relevant to fabrics, read “Future of Fabric: Health Care” from Health Care without Harm and the Healthy Building Network, October 2007. 3. Some of the finish and/or treatment manufacturers did require nondisclosure agreements prior to the inperson meetings. 4. As the process unfolded, the team identified the need to question directly the finish manufacturers about the environmental issues associated with their products. As a result, Kaiser Permanente developed a short survey for finish manufacturers in anticipation of the in-person meetings and created a scorecard for their materials as well.

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Based on the survey responses, the team developed the criteria and a scorecard to evaluate the vendors. Additional information on the major fabric finishes and treatments used in the industry was critical to understanding the full health and environmental impact of the fabrics presented to the Content Expert Panel. The CEP team analyzed and evaluated the manufacturer responses while the consultants identified key issues for future in-person meetings with each of the vendors. The CEP also chose which vendors would be invited to continue to Step Four, which was a presentation of their fabric lines.

NARROWING THE FIELD In spite of the fact that 12 vendors had been invited to respond to the second detailed survey, the original Fabric Alliance partners had clear advantages over the other candidates due to their long history with Kaiser Permanente. CEP members recognized that sustainable issues negatively impacted a few of the vendors, but a history of excellent product quality and customer service weighed heavily in the decision to bring the vendors in for face-to-face presentations. As a result, all four original Fabric Alliance partners were invited to continue to Step Four—a presentation before the CEP. In addition, four small to medium-sized companies, well known for their commitment to design excellence and sustainable attributes, were invited. To provide a complete picture of the market, four companies that manufacture treatments or finishes which add stain resistance, ease of maintenance, and/or moisture resistance to fabrics, were asked to team up with fabric vendors who offered these treatments and finishes as a part of their fabric lines. One additional manufacturer indicated that they were close to making a major technological breakthrough in nonpetroleum-based synthetic leather fabrics. As a result, the CEP asked this manufacturer to continue in the selection process.

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C A S E S T U D Y P R O J E C T: C R E A T I N G A S U S T A I N A B L E FA B R I C A L L I A N C E P R O G R A M

VENDOR PRESENTATIONS Prior to inviting the vendors to present their product lines to the Content Expert Panel, the team grouped the vendors into three separate categories. Group One vendors were those that integrated sustainability into their fabric program by creating a program and a timeline for implementation. These vendors worked directly with fabric and treatment manufacturers to introduce sustainable practices into

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Figure 2.94 Sustainable Fabrics Used in a Kaiser Permanente Hospital Patient Lobby

the fabric industry, and they diverted a portion of their revenues back into research and development, and had research professionals on their staff. Category I vendors were active in identifying new issues and solutions as opposed to waiting for market trends to dictate action, and they are successful at providing well-designed fabrics that are sustainable as well. Group Two vendors were small and medium-sized “boutique” vendors that typically had owner representation at the meeting and superior design lines and quality. These vendors were highly driven entrepreneurs who were committed to sustainability, and were limited to the type and amount of research and development. Group Three vendors were those that were service and price-value leaders, and they utilized third-party consultants or programs (such as LEED)5 to represent environmen5. Leadership for Energy and Environmental Design.

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tal standards. They primarily associated sustainability with recycled content, and they often lacked a clear vision of complex environmental issues. These vendors could not justify investment into sustainability without a guaranteed Return on Investment (ROI) and they appeared not to have a research and development program.

FINISH AND TREATMENT MANUFACTURERS During this phase of the project, the Content Expert Panel also interviewed fabric finish and treatment manufacturers. The companies interviewed focused on the stain resistance and moisture blocking capabilities that are so important to the health-care industry. Two general categories for fabric treatments and finishes manufacturers appeared. The first category of fabric treatments and finishes was those that used Teflon® or Teflon-like finishes. Typically, these chemicals are persistent, bio-accumulative toxicants (PBTs), which means that they are chemicals that persist in the environment, they bio-accumulate up the food chain, and are toxic to animals and/or humans. These finishes are perfluorocarbons (PFCs), related to the chlorofluorocarbons (CFCs) that have been banned because of their ozone-depleting effects. They can pass from a mother to the fetus through umbilical cord blood, are found in human breast milk, and some are suspected carcinogens. The second finish and treatment category focused on nanotechnologies. “Nanotechnology” is defined as the study and use of structures between 1 nanometer and 100 nanometers in size.6 As a new technology that covers a myriad of chemicals and processes, the information presented suggested that there are a number of additional issues that need to be studied. The one company stated that “the polymers used are too large to be absorbed into the skin or inhaled and...do not utilize nanochemicals that could be ingested or inhaled.”

CASE STUDY PROJECT / Creating a Sustainable Fabric Alliance Program for Kaiser Permanente

C A S E S T U D Y P R O J E C T: C R E A T I N G A S U S T A I N A B L E FA B R I C A L L I A N C E P R O G R A M

DECISIONS AND RECOMMENDATIONS The CEP recommended four vendors: Carnegie, Designtex, Maharam, and LDI Corporation. As a result, Procurement and Supply sent out a Request for Proposal (RFP) to these vendors to complete a further review of their product quality, product cost, 6. To provide a visual comparison, it would take eight hundred 100 nanometer particles, side by side, to equal the width of a human hair. A nanometer is one-billionth of a meter.

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and business partnering with Kaiser Permanente. Based on their RFP response, the selected vendors were invited into contract negotiations with Kaiser Permanente. Prior to negotiations, each vendor was asked to catalog their fabrics into three groups. Using the Sourcing and Standards Team (SST) and Content Expert Panel (CEP) processes, Kaiser Permanente National Facilities Services, in partnership with Procurement and Supply, created a Sustainable Fabric Alliance Program. The process to create this program was rigorous. It included continuous research and data gathering, narrowing the field of vendors using two fabrics industry surveys; presentations; and interviews.

NEXT STEPS Communication and implementation tools will be developed by the Furniture Sourcing and Standards Team in partnership with Procurement and Supply. In addition, the team will work with Kaiser Permanente stakeholders to ensure that the decisions made by the CEP are incorporated into the Kaiser Permanente Standards Program. Members of the Strategy Planning, and Design team will also work to ensure that the Category I and II woven fabrics and synthetic leather fabrics are graded into the Kaiser Permanente Furniture Standards Program. A transition period will ensure that program implementation will not adversely impact current project schedules and budgets. Through extensive communication and sharing of its findings, Kaiser Permanente will leverage the fabric industry to move toward more sustainable products. Kaiser Permanente will also continue to study and bring attention to important environmental, health, and safety issues, and will use its purchasing power to transform the industry. Ultimately, the extent to which these changes affect our choices as designers, architects, and health-care professionals is determined by our willingness to meet and share our concerns with market leaders and our resolve to make changes individually and within our own organizations.

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FISCHER INTERVIEW Martin Fischer This notion of interdisciplinary or cross-disciplinary teamwork and the use of evidence go hand-in-hand for me. I am sure this is influenced by my background as a Swiss engineer. If you are working in a multidisciplinary team, it is mandatory that each of the people that represent different disciplines be able to present evidence to illustrate how the disciplinary processes influence performance outcomes. Without this type of approach of using evidence as the language of discourse, the setting then just becomes a power struggle of personalities.

Figure 2.95 Martin Fischer

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Martin Fischer is a Professor of Civil and Environmental Engineering and Director of the Center for Integrated Facility Engineering (CIFE) at Stanford University. He holds a Diploma in Civil Engineering (Ingenieur Civil Diplomé), January 1984, Swiss Federal Institute of Technology (École Polytechnique Federale, EPFL), Lausanne, Switzerland; M.S. in Industrial Engineering: Engineering Management, June 1987, Stanford University; PhD in Civil Engineering: Construction Engineering and Management, June 1991, Stanford University. Fischer is passionate about improving the sustainability of the built environment: “For me, this means that buildings do more for their users—we make the best use possible of the energy, materials, and efforts that create a building—and that they are built productively and with environmental and social sensitivity. This can only happen if everybody involved in making and using a building participates when their input is most useful and if the whole process is managed well. Therefore, I am teaching undergraduate and graduate courses on how to design a building’s life cycle and how to manage projects using traditional and modern management approaches and information technologies.

FISCHER INTERVIEW

RESEARCH BACKGROUND

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“Today’s construction management tools do not represent and communicate the spatial and temporal, or four-dimensional, aspects of construction schedules effectively. They do not allow project managers to create schedule alternatives rapidly to find the best way to build a particular design. We lack a formal, computer-interpretable representation of construction knowledge and its relationships to a 3D design representation. My research group formalizes this knowledge within a 4D (3D plus time) framework. This formalized knowledge enables project managers to create and update schedules rapidly and to integrate the temporal and spatial aspects of a schedule as 4D models. These intelligent 4D models support computer-based analysis of schedules with respect to cost, interference, safety, etc., and improve communication of design and schedule information.”

How do you see evidence playing a role in your work and how is this evidence used to inform design?

FISCHER INTERVIEW

There are three ways in which I produce and use evidence in my work. First is the use of computational modeling tools to simulate potential design and construction conditions for the purpose of evaluating specific performance outcomes. The second is data mining from existing real-world projects to establish relationships for understanding the influence of parameters and constraints on building performance. The third way is an old standard, that being a social process with peers and experts, to confirm outcomes as being appropriate and grounded in industry standards and processes (i.e., peer review panels, expert panels, or just normal meetings of parties with a vested interest in the project).

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One of the projects we are currently doing is looking at the energy performance of the building we have just moved into on the Stanford campus. The purpose of this study is to compare the simulation models used in design building with the actual performance of the building in use. I think this would be what might be considered a postoccupancy evaluation. So far it has been difficult to collect really good data, let alone match up the models used to design the building with actual performance. The study will verify whether the models used to design reflect anything to do with actual performance. This has raised several interesting questions for us like: How do we actually use the building? How does that type of use match with the designer’s description of use when employing the models to simulate use in the design process? We have 2,300 sensors in the building that collect data every minute, giving 3 million data points a day. We thought that should be pretty good evidence; however, what we have found is very interesting. The collected data after one month suggests that

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we use 1,300 units of energy per day; we are billed for 500 units. If you use a simple energy calculator, it should be 300 units, and the model used to design using a more complex calculator, Energy Plus, predicts 400 units. We are now wondering whether this represents an aberration or is it common to have this wide variation between actual and modeled performance outcomes. It appears from a discussion that this is not an uncommon relationship which suggests that there needs to be great efforts to calibrate the models with real data so that the prediction becomes more accurate.

How much evidence is enough and how rigorous should it be? This is a difficult thing to know. It raises questions of: How much data to collect? How often to collect the data? How long the data needs to be kept? If one just looks at a limited area like issues of sustainability and energy use, there does not seem to be any standards or guidelines for determining the answers to these questions. Is more, better than less? It is hard to tell. On the engineering side in areas like structure, acoustics, cost, and scheduling, I would think that in 2009 you would expect good evidence from computational models that are based on the reality of current projects (i.e., quantity take-offs, structural performance data, allowing good calibration, and validation foundations). We are not there yet, but getting closer.

One of the major challenges in understanding building performance is the relation of parts to the whole of a project. Most of the research is about parts, as such what does the future hold in terms of an integrated whole? This notion of the relationship of the parts to whole systems is critical to me. We have all kinds of examples, both with students and practitioners, where we give the impression that if we measure one key-performance indicator, like BTUs per square foot, then we have a high-performance building. This is all wrong. We may have a good building in terms of energy, but what about all the other components that make up the building?

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On the architecture side, issues of space and use, it might be awhile before we have the performance indicators represented in computational tools. As such, this means that we will have to continue to rely on a social process for validation. This process, however, needs to become much more rigorous with transparent strategies and evaluation tools so that the stakeholders in any project can track and understand the implications of design choices on building performance. For this to work effectively there will have to be a clearer representation of the project and the computational technologies for representation of architectural space are now rather robust.

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The problem here has to do with the impact of what we choose to measure and how that begins to define the nature in the larger sense of what we design. For example, if, in the Olympics from the beginning, discus throwing was the indicator of high human performance, then we would have developed physically very different than, as is of course the case, if there are multiple indicators of high performance in other events like running, jumping, etc. I would hope that we would begin to see the importance of having multiple performance indicators that would define a highperformance building. Maybe we need a “Building Olympics” to challenge the development of the performance outcome parts, into multiple performance indicators that relate to an integrated building model.

Do you think that having more rigorous evidence inhibits or enhances creative thought and action? If you are working alone and you are faced with evidence, it may constrain and limit the ability to be creative. It is, however, very different if this evidence is introduced in a setting where there is a collaborative process which is represented by multiple disciplines and perspectives. This type of evidence can become the stimulus for exploring more creative thought, innovative strategies, and alternative directions in the project.

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This notion of interdisciplinary or cross-disciplinary teamwork and the use of evidence go hand-in-hand for me. I am sure this is influenced by my background as a Swiss engineer. If you are working in a multidisciplinary team, it is mandatory that each of the people representing different disciplines be able to present evidence to illustrate how the disciplinary processes influence performance outcomes. Without this type of approach of using evidence as the language of discourse, the setting then just becomes a power struggle of personalities.

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The methods I use to make this effective to make clear how the system boundaries for the design are framed include physical scope and scale, temporal scope and scale, disciplinary scope and scale. In addition, it is critical to determine at several levels the details of the performance criteria that really matter and then work at increasing levels of detail. With this established, it is also very important to respect the differences across the disciplines, as each discipline will have slightly different formulations of system boundaries, performance criteria, etc. This diversity of perspective is instrumental in creating opportunities for innovation and new directions. One important aspect here is to have a process that is grounded in a common understanding of the important question or questions: How will this change over time, and what is (are) the design solution or solutions. It is evidence that will link this understanding

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between question and solution. Its form will vary, but it must be transparent to the stakeholders. It is also important not to get side-tracked by unimportant details. The example that comes to mind is a recent meeting on a new building here on campus. We got into a discussion almost at the beginning of the meeting, whether the building should have uni-sex restrooms. We spent over 30 minutes talking about this, and we had not even decided that we were going to do a building. One must be careful to establish a set of issues and work at several levels of detail (e.g., the ten most important issues, the next ten, and so forth). This will keep the process and outcome in a productive mode and not get limited too early by unimportant constraints like cost and aesthetics which so often happens.

How important are metrics or measures when creating and using evidence?

Without this type of data from metrics that connect modeled expectation to actual performance outcomes it becomes very difficult to prioritize and improve what is influencing specific performance outcomes and how to improve them in the process of designing or operating the buildings. There is an example in our new building where in one of the stairwells there is a list from the top floor to bottom floor of all of the things that were done to make the building more sustainable. But nowhere do we have any data that shows what each of these things cost, and how much value was added to the building performance. Without evidence, it is impossible to make real

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At CIFE this has been our major soapbox for the decade, and it is finally starting to resonate with our industry partners. We just met with a group of 30 members last week on a large project, and it was them who suggested how important it was that we establish metrics or measures to tell us if we are making appropriate progress. The normal situation is, however, that we typically measure at the end rather than the beginning of and throughout a project. Unfortunately, the outcomes from this measurement process at the end do not help us during the project, but they do give us data that could be mined for future projects if we would do it. Somehow it tends to take a lower priority when we get going on a new project. Of course it will inform us if there are connections, but the agenda is not formal. What we really need are metrics that can inform us in real time, answering the question: Are we on track and making appropriate progress? This is critical today where the complexity of the types of projects we work on is so great and multidimensional that metrics become our guides and evidence to understanding and appreciating the expected performance outcomes.

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informed decisions about actions and value added or, more basic, how to learn from what you are doing now, and how it will influence the next project. There are many examples of where organizations have set an agenda to establish metrics on how the entity performs. No matter what the metrics showed—positive or negative outcomes—the overall process was extremely valuable to the performance of individuals, groups, and the whole organization.

How do you take the evidence from a context-specific project to a generalized way in the next project? This is very hard to do in our industry. There really is not an infrastructure for the purpose of cross-project data archiving and mining. All of our projects create a lot of data that are used during the project, but when the job is completed, the data are discarded. Because of this, there is very little opportunity to mine across projects and learn from the bigger patterns and relationships that could be in the data. One of the largest building monitoring and operators in this country contacted us to see if we could provide them with building performance data. They have thousands of buildings that they oversee, but have not collected any of the data on a longitudinal basis. They throw building data away after ten days.

FISCHER INTERVIEW

One of the problems here is that we do not have agreements on how to slice/dice the performance outcomes so that categories are established so that meaningful metrics can be used to make comparisons. I have a sport analogy that might help: Let’s say that someone is the best pitcher in the Bay Area based on the number of strikeouts per game pitched. Then you could compare this data from California, with other states to understand just how good this particular individual is. We don’t have first an agreement of what performance indicators or metrics are—strikeouts—nor how to define the best pitcher. Without these two fundamental aspects, it is difficult to have meaningful data mining across projects.

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The notion of data mining brings up a number of interesting issues. Before the mining can be useful, we must have some structure that allows us to ask important questions. Again an analogy is helpful here. If you want minor league performance in baseball, there are expectations of what the qualities are of the person who will play. The same is true if you want major league performance. This can be transferred to architecture. If you want a major league building, how does that get defined and what are the characteristics of these types? By data mining over a number of projects these characteristics can be articulated, as we have a way of defining what is minor and major in terms of buildings. Again, it is about using existing data in a new way

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to create new data that defines evidence for justifying specific kinds of outcomes. One of the challenges is getting organizations to share the data, and also, the issue of the performance of individual systems to the whole system. Also, every building has a context that defines its many constraints and parameters that are unique, making it difficult to make comparisons.

How successful have you found it to make the transition from research outcomes to having them adapted into the professional practice setting? Not as successful as we would like, but it is improving. We have had a number of extremely successful projects with our partners. It takes about ten years from a pilot research study to having an organization adopt and utilize research outcomes. This does not count about five years of development work on the technology before it is ready to test in a practice setting. The key is to have top management support the research effort and endorse it at each of the stages. This will then allow the substructure of the organization the opportunity to take the risk of adoption. Our success includes both 3D and 4D applications—not what I would call real Building Information Modeling; it is much too early yet. It has been the integrated, concurrent engineering method that involves multidisciplinary shared simulation models that has been the big traction during the last 18 months. I would refer to this as an example of an evidence-based, multidisciplinary design process. All of the organizations that have adopted this strategy have found it very beneficial and much easier to integrate into their organization than they thought. Paul Saffo from the Institute for the Future says that it takes 20 years to have an idea move from an idea to application in the profession.

The first thing is to have at least a couple of respected project managers willing to get behind and utilize the new methods or tools in their work. For this to work, however, it takes top management to give strong support for the efforts to make change. It also takes the commitment of enough resources (i.e., time, training, money etc.), so that the implementation is seen by the other employees as not adding to their already busy and important activities, or it will be seen as an unfunded mandate. Metrics of progress are also important. There must be evidence that the adoption is producing value, great productivity, more efficient work processes, more innovation, etc. The final thing that helps is to pay attention to and nurture the change agents or

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What are the characteristics of those projects that were successful into practice?

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champions of the new change activities. It takes about four generations of champions to sustain change and make it permanent. An example of evidence-based change at a large building owner was when top management had concerns about the cost overruns on projects. They thought it was the designers and users changing their minds that was the big problem. They developed 12 categories for why change was introduced in projects. They then took six years of projects done by the organization and categorized the changes and how they affected cost. We found that yes, about a quarter of the cost overruns were caused by the designers and users changing their minds. However, what was a big surprise was the finding that project managers were responsible for two and a half times more changes through their work practices than the designers. This evidence then made the organization refocus where they needed to change the policies and methods for controlling cost overruns.

What are your thoughts about using data that already exists versus creating new data in every project as the evidence for action?

FISCHER INTERVIEW

I am very much in favor of finding out how to use existing data as the foundation for providing evidence for a specific project. By using existing data, we not only find what is there but also what is missing. I make a parallel with this issue of using drawings or documents as the starting point of a project (i.e., plans, sections, schedules, cost estimates, etc.), versus using an integrated shared model to create the documents. At the present time most of the industry works from a document level and then infers the underlying model. This creates numerous coordination challenges, as a change to one document does not necessarily coordinate other documents that depend on the same data. If the shared model is used, a change in the model updates all the integrated documents so coordination becomes less of a challenge.

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What this means to data is that we tend to see data in the form of reports, losing sight of where the data comes from. It is hard to track data from reports over time. This is why using data that exists to create data for the specific project makes sense. Developing a process for mining these data to create new data is critical.

What changes would you recommend to education or to practice models to make this evidence-based process more effective? This is a difficult question, but I do think there is a need for some changes in our educational approaches. Students must learn the methods and tools for validating

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data and then trust the data and outcomes. We currently do not do a very good job of this. It is also critical to teach in a much more organized manner the new technologies for modeling, simulation, representation of projects as well as tools and strategies for data mining and production. I think also that there are changes needed in how we teach design where the process becomes much more introspective in terms of informing the outcomes from evidence and create young professionals with an open attitude toward the constraints and contributions of the other disciplines. This should then make it more likely that more buildings respond better to the challenges building owners and users face while also meeting the global environmental challenges of reducing the environmental footprint of the built environment or having the built environment even have a positive environmental footprint.

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In terms of changes to the practice model, I will have to give this a bit more thought, but do recognize that change is not only needed, but is happening as we speak. I see owners, architects, engineers, fabricators, and builders see opportunities for themselves and for their customers through evidence-based, integrated design. I see many project teams working hard at changing the culture on projects to be more open and proactive and to be more rigorous in management of the information basis that informs design, project management, and life-cycle performance. These are very significant changes, but all project teams I work with are striving toward more productive and effective collaboration, design, and construction processes.

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CASE STUDY / CIFE Technical Report Number 143

C ASE S TUDY CIFE Technical Report Number 143 Product Model 4D CAD IFCVR-EVE—Executive Summary Martin Fischer and Calvin Kam October 2002 INTRODUCTION This Product Model and Fourth Dimension (PM4D) report presents the findings from the design and construction of the Helsinki University of Technology Auditorium Hall 600 (HUT-600) in Finland. Running simultaneously with the design and construction of the HUT-600 project, an international research partnership extensively applied the product modeling approach, tested the Industry Foundation Classes’ (IFC) interoperability standards, and employed an array of design visualization, simulation, and analysis tools on the 17-month, U.S.$5 million capital project. Through our dissemination of project experiences and analytical results, we hope that building owners, end-users, and project teams will take advantage of the current capabilities and benefits of the PM4D Approach, which leverages commercially available state-of-the-art analytical and visualization tools to optimize the design, construction, and operation of a proposed facility during early project phases. Figure 2.96 shows the software tools that were used by the project participants involved in this research and shows the information that was exchanged between these tools via product models based on open (IFC) and proprietary standards. In this research, we have documented cultural, technological, and business barriers to the PM4D Approach.

PM4D APPROACH The HUT-600 project team used the following PM4D Approach: They constructed and maintained object-oriented product models with explicit knowledge of building components, spatial definitions, material composition, and other parametric properties. Only with this product modeling approach could the team leverage the object intelligence from the 3D models for data interoperability. These product modeling and interoperability approaches eliminated the inefficiency and risks of data reentry in conventional practice. The PM4D Approach was crucial for generating reliable and

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quick cost estimates, construction schedules, comfort designs, energy analyses, environmental reports, and life-cycle cost studies. Furthermore, the approach allowed the project team to utilize visualization tools to review spatial designs in virtual walkthrough, compare lighting schemes in photo-realistic renderings, and comprehend construction sequences in 4D animations, all leveraging the same electronic design information.

MAJOR BENEFITS During the early schematic phase, object-oriented modeling software and IFC’s allowed the project team to shorten the time for design iteration, develop a reliable budget for effective cost control, and eliminate the need to reenter geometric data, thermal values, and material properties as different disciplines contributed to the design progress. Additionally, visualization tools such as photo-realistic rendering software, Virtual Reality-Experimental Virtual Environment (VR-EVE) fostered early communication among the end-users, owners, and the project team, who then captured valuable inputs and effectively translated the client’s intent into long-term values. Building on the resulting efficiency and time-savings, the project team was able to conduct a variety of in-depth life-cycle studies and alternative comparisons on thermal performance, operation costs, energy consumption, and environmental impacts. Compared to a conventional approach, these relatively seamless data exchange and technology tools substantially expedited design and improved the quality of interdisciplinary collaboration. The PM4D Approach empowered the building owners to better align the long-term facility values with their strategic plans.

CASE STUDY / CIFE Technical Report Number 143

C A S E S T U D Y: C I F E T E C H N I C A L R E P O R T N U M B E R 1 4 3

MAJOR BARRIERS TO EXTENDING PM4D BENEFITS As desired, most PM4D benefits occurred during the early design phase. Even though the PM4D approach improved upon conventional practices in terms of design quality, project risks, and life-cycle values, we encountered technological, cultural, and business barriers to extending the benefits of PM4D Approach. Project participants in the HUT-600 project could have enjoyed further benefits if product modeling tools supported revision-handling, two-way exchanges, simpler mapping of data formats from exporting to importing applications, and if IFC-compliant software tools were extensible and robust. Culturally, 4D technology could have introduced additional analytical benefits beyond its current utilization if it had been conducted earlier during the

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preconstruction phase. The online project extranet (also called “project databank” in this report), if developed optimally, would have made information exchanges more efficient during the construction documentation phase. At the same time, building owners and designers could have exploited business opportunities for the architects’ role in developing and coordinating a sharable product model.

CONCLUSIONS AND RECOMMENDATIONS Based on experiences from the HUT-600 project, we conclude that the PM4D Approach helps expedite conventional design practices and promote life-cycle approaches. Project examples demonstrate that owners could choose among comprehensive life-cycle alternatives, end-users could provide input to the facility design in a timely manner, and project team members could differentiate themselves from their competitors with higher efficiency, quality, and more effective application of their expertise. Most participants in this project were surprised by the large number of design, engineering, and analysis tasks that can be supported productively with product models today. Figure 2.96 shows that many software tools were able to import IFC-based and/or non-IFC-based product models for many different disciplines and diverse criteria. However, Figure 2.96 also shows that the exchange of product model information based on an open standard like IFC is not yet as mature and widespread as needed in practice. One should also note that the use of IFC-based product models worked quite well in the schematic design phase of the project. However, in the later project phases, IFC-based product models were not as effective a means as proprietary information formats to exchange data between software tools. On this project, the IFC Standard 1.5.1 was used; recently published Standards 2.0 and 2.x address some of the shortcomings of IFC-based product models found in this research. One would also expect that some of the software-based limitations have been ironed out by the vendors by now. The product modeling and information standards community has long touted the advantages of supporting the many software Figure 2.96 Snapshot of major product model applications used by the project team in the PM4D approach (middleware and internal database are omitted). The figure shows how the project team exchanged product model data between these applications. The figure illustrates clearly the need for the exchange of product model information to support the design of many aspects of a project for many different disciplines and criteria. Note that some of the links that existed at the time of the project (e.g., between ArchiCAD and MagiCAD) were not used by the project team. Furthermore, today some of the links (e.g., between RIUSKA and CFX) are IFC-compliant.

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tools used on projects with a common core model. However, we are still lacking a validated specification for the content of such a core model. Therefore, one of the specific goals of the research was to study whether such a core model exists, i.e., emerges through the team’s experience in using product models to share data, and if it exists, what type of information is part of the core model. Figure 2.96 and the experience from this research show that the building geometry, material types, and space identifier (or ID) are part of a core model. On the other hand, the architect had to expend significant effort to adjust the “core” model to support the different needs of the various disciplines. Furthermore, Figure 2.96 also shows that, in addition to the 3D core model, there appear to exist discipline-specific models, such as the thermal model. To exploit the potential benefits of the PM4D Approach further, we recommend that researchers and software developers focus their efforts on partial model exchanges, product model servers, better defining “core” versus “discipline-specific” product models, and developing more reliable and extensible tools. Copyright © 2002 by Center for Integrated Facility Engineering

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M O D E L S, S I M U L AT I O N, A N D D ATA M I N I N G

Lessons Learned: Models, Simulation, and Data Mining Overview We are now very much aware when someone makes reference to the “information age,” they are referring to a new form of capital sometimes noted as “intellectual capital.” The game is no longer just about access to information but what one does with the information that is critical. INFORMATION IS THE SOURCE OF INNOVATION, INVESTMENT, CONTROL, POWER, AND CREATIVITY. Computational tools allow us to use data to establish, understand complex relationships, interpret and transform the information, and optimally communicate performance outcomes. THESE COMPUTATIONAL TOOLS ARE RESHAPING THE LANDSCAPE OF DESIGN, ARCHITECTURE, AND CONSTRUCTION. THEY ARE AT THE CENTER OF A MAJOR EVOLUTION, AND MAYBE REVOLUTION, IN HOW WE WORK, WHAT WE WORK ON, WHO WE WORK WITH, AND HOW WE MEASURE THE VALUE WE CONTRIBUTE. Tools for modeling, simulating, prototyping, and mining data, create evidence of predictable performance outcomes that is used to inform design decisions, and justify the quality rationale for design actions to all stakeholders.

These computational tools give us the capacity to organize and search data and to create virtual models, simulate performance, and fabricate physical prototypes. In the hands of skilled and innovative practitioners and researchers, these tools are establishing a new model for conducting research and producing evidence to inform the art of design. As is the case with most developments in architecture, change results by importing new technologies, scientific findings, and other inter-disciplinary knowledge. The change does not come without a struggle. Clearly,

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this has been the case with bringing computational modeling, simulation, and data mining tools into architecture. The underlying need for these tools has long been a part of architecture. Physical models, as well as manual representation methods and drawing, have been at the center of exploring and communicating the art of design for centuries. Data mining has also been a part of the design process, although primarily to rationalize already determined design solutions, rather than to discover evidence of fresh design strategies to improve building performance. The interviews in this chapter make apparent two phases of evolution in the use of computational tools in architecture: The first phase represented substitution processes, in which the tools replaced existing manual ones to perform existing tasks. For example, 2D drawing and 3D physical modeling were used primarily for documenting and recording traditional design deliverables— sketches, schematic design drawings, construction documents, etc. The second phase in happening now. This is about a fundamental change in how these technologies have changed the nature of how we work as well as what we work on. These new tools represent design elements and systems as parts and wholes, and measure their impacts in active, iterative, real-time settings.

General Observations About Modeling, Simulation, and Data Mining These new computational tools and their support devices are rapidly reshaping the way we think of the value of data across disciplines and professions where performance metrics and outcomes are critical. We are learning to interact differently, whenever there is a benefit from coordinating parts and whole systems across disciplinary and professional boundaries. IT IS COMMON TO SEE THESE TOOLS USED IN TANDEM AND IN AN ITERATIVE PROCESS. Simulated outcomes from one tool are used to inform the next iteration

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of inquiry by the same tool or as data to inform another computational tool to further explore the design situation. These iterations intake new data, creating alternative outcomes which take the form of virtual models that over time become physical models or prototypes produced with 3D printers, laser cutters, and other automated computational base fabrication tools. This process is continued until it is determined that an appropriate level of performance outcome has been established. The ever-increasing computational speeds and storage capacities of these technologies have been central to providing the platform for evidence-based practice and the production of evidence both in terms of its development and its application. The interviews in this chapter illustrate that these tools are producing powerful evidence to inform design. The potential applications are many—new transportation prototypes, integrated building systems, lighting and energy, and life cycle management…. For all of their current uses and those drivers of change yet to be modeled, these tools will be a critical part of the way architecture is practiced in the future.

The Challenges On the surface there seems to be NO LIMIT TO HOW THESE COMPUTATIONAL TOOLS will support innovation in design practice. A closer look, however, uncovers some major challenges if we are to accomplish those opportunities. ONE OF THE BIGGEST CHALLENGES IS THAT THE CAPACITY OF THE COMPUTATIONAL TECHNOLOGIES IS ADVANCING MORE RAPIDLY THAN OUR ABILITY TO CREATE THE DATABASE INFRASTRUCTURE NEEDED TO INFORM TECHNOLOGIES. We are missing a warehouse for the collection, archiving, and sharing of the multitude of data produced in projects. This void limits the impact of these technologies on the performance outcomes of projects and the profession’s ability to adapt

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to the demands of our increasingly complex design challenges. A major effort needs to be made to create ways for firms to capture proprietary information and to share data with other professionals concerned with design, construction, and operation of physical environments. This is critical if these tools are to become a major component of the arsenal of research and evidence-based practice processes. Another significant challenge is the reliability and validity of the models to simulate real-world performance. Many of the computational tools used to predict outcome performance seem to have significant metric variation between the predicted performance outcomes in the simulation phase when compared to the actual performance outcomes once the environment has been commissioned. There are several reasons for this, but ONE OF THE MAJOR FACTORS IS THAT THERE IS VERY LITTLE EFFORT TO CALIBRATE THESE MODELS IN REAL-WORLD SETTINGS. This is due to the dearth of available real-world data. In many cases, there are not the resources available to instrument the building to collect the real-world data. Another challenge: In most cases, these tools are currently used to simulate single variable performance outcomes, i.e., energy consumption, daylighting, structural capacity—parts, or subsystems, rather than whole systems with multivariable performance outcomes. The major reason for this is the lack of compatibility of various modeling and simulation technologies. They can’t share data and findings without recoding. Some disciplines develop and use computational software and hardware that works for their specialized uses but can’t communicate with tools used in the design process. Evidence of this problem can be seen in the language we use to describe the outcome of performance-based design. We typically talk about high-performance buildings in terms of the single dimensional of energy efficiency. (Sometimes, lighting and other sustainable design

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M O D E L S, S I M U L AT I O N, A N D D ATA M I N I N G

factors are be included, but rarely do we see reference to functional, spatial, or experiential performance parameters. In many cases we just don’t have the performance indicators and metrics to model and measure design outcomes holistically in data-driven simulations. TO BE EXTREMELY USEFUL, THE APPLICATION OF MODELING, SIMULATION, AND DATA MINING TOOLS NEEDS TO COVER A WIDE RANGE OF DESIGN ATTRIBUTES— human use and human experience; energy; structural performance; human comfort, activity, and function accommodation, just to name a few. Some of these attributes have well-defined metrics while others have very soft metrics. Depending upon which attributes one is exploring, the understanding of the performance outcomes might be high (as is the case with energy or structural performance) or low (as when predicting human experience For the latter, intuition tends to trump evidence. This raises the complicated question of what is enough evidence and how strong does it have to be. The basic question is: What is the difference between measurement and evidence? There is no one answer that fits all conditions. It’s generally supported that quantitative measurements are strongest and most easy to interpret. However, it isn’t always possible to have reliable metrics. As architects and designers, we must make decisions with the best evidence available, whether it is solidly grounded in research or more loosely derived from our personal experience or intuition. Whichever it is, we need to make that evidence externalized, documented, and understood by others. As architects we have reasonably good evidence on how to build, but very weak evidence when it comes to what to build. IT IS CRITICAL THAT WE MAKE BOTH THE HOW AND WHAT OF BUILDING TRANSPARENT BY CREATING AND APPLYING EVIDENCE WITH CLARITY, HONESTY, AND INTEGRITY.

How well the evidence is understood will establish

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the value of what we contribute and the new computational tools give us methods to help accomplish that clarity. There ARE three distinct ways to think about how these computational tools and evidence can be used in designing: A nonrationalized approach—“I am the architect. I know what to build, trust me.” A postrationalized approach—“I have a cool idea, but I do not know how to build it so by using tools, nondigital and digital, I can understand and represent the how to build.” Finally, a prerationalized approach— “Here are rules describing the expected performance outcomes required of what I want to build. Find the solution.” It is this prerationalized approach that is the future of evidence-based practice (Bernstein Interview 2009).

The Summary In summary, the eight interviews in this section have described an exciting future for the use of evidence and the establishment of a model for evidencebased practice. It is clear that each of the individuals interviewed is APPROACHING THEIR DESIGN WORK UTILIZING THE MOST ADVANCED COMPUTATIONAL TOOLS available today. Whether they are doing research or practicing, all eight interviews illustrate a commitment to using the best evidence they can generate to inform their practice or research outcomes. They all recognize that they must act whether they are a designer or researcher using the best evidence they have to move their agendas to a resolution. Simulations provide means of presenting and evaluating articulated conditions. Data mining provides the foundation and content to inform iterative simulations. Models provide mechanism for testing using specific metrics to document and understand the level of performance outcomes on selected subsystems or whole system attributes. The models then become the means for fabricating prototypes,

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either virtual or physical, to explore and understand the real-world performance of the outcomes and, in some cases, move into commercial production. At the core of this work is A NEW MODEL FOR RESEARCH AND PRACTICE in architecture and its related disciplines. There is still much to be done, but the computational innovations that have put this in motion have created a level of momentum that will sustain the effort for years to come. At the center of these revolutionary computational tools are opportunities and challenges for both practice and education to embrace a new form of RESEARCH THAT VALUES UNDERSTANDING HOW WHAT WE DESIGN ACTUALLY PERFORMS. The real question for many designers is:

Do they want to be a part of this new and exciting future and embrace the fact that transparent evidence is central to what we do or, do they want to hold onto the tried and true practices of where they have been—trusting our intuition and experience? We say it is time to embrace evidence in a new form, not as proof or truth, but as transparent documentation that allows all stakeholders to understand and assign value to the nature of the performance outcomes we produce as architects and designers. THE FUTURE IS NOW USING THESE INNOVATIVE COMPUTATIONAL TOOLS AS OUR ARSENAL.

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REFERENCES 1. Physical Prototypes: A Necessary Step or Needless Bottleneck, 3D Vision Technologies, a White Paper, 2008. 2. Wikipedia, the free encyclopedia: Simulation, 2009. 3. Gene Bellinger, Modeling and Simulation: An Introduction, The Way of Systems, System Thinking, Manchester England, 2004. www.systems-thinking.org/modism/modism.htm 4. Wikipedia, the free encyclopedia: “Data Mining,” 2009. 5. Michael Berry and Gordon Linoff, Data Mining Techniques, John Wiley & Sons, New York, NY, 1997. 6. Todd Grimm, Users Guide to Rapid Prototyping, Society of Manufacturing Engineers, Dearborn, MI, 2004. 7. “An Introduction to Data Mining, Thearling.com, 2008. 8. Bjorn Hartmann and Scott Klemmer, “Reflective Physical Prototyping through Integrated Design, Test, and Analysis,” HCI Group, Stanford University, 2006. 9. S. Denning, The Springboard, Boston: Butterworth-Heinemann, 2001. 10. M. Gibbons, C. Limoges, H. Nowotny, S. Schwartzman, P. Scott, and M. Trow. The New Production of Knowledge: The Dynamics of Science and Research in Contemporary Societies. London: Sage, 1994. 11. Helga Nowotny, Peter Scott, and Michael Gibbons, ReThinking Science: Knowledge and the Public in an Age of Uncertainty, Blackwell Publishers Inc, Malden MA, 2001. 12. Donald A. Schon, The Reflective Practitioner: How Professionals Think in Action, Basic Books Inc. Publishers, New York, 1983. 13. Jason Frand, Data Mining: What is Data Mining?, Anderson School of Management, UCLA, 1996.

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3

The Social Sciences

Background and Context Overview of the Social Sciences Design matters. What architect or other design professional doesn’t believe that? We only have to listen to friends and co-workers to know how much people care about the places where they live, work, and play. Many, if not most, of us also believe that design matters tangibly by affecting health, learning, retail sales, athletic performance, productivity, and other aspects of our lives. THE ENVIRONMENTS DESIGNERS CREATE ARE THE SETTINGS THAT ENABLE OR INHIBIT HUMAN INTERACTION; PROMOTE OR STIFLE HUMAN DEVELOPMENT; AND FOSTER OR HARM HUMAN WELL-BEING.

Architects’ clients often want design to matter beyond its artfulness. The people who hire designers are responsible for providing places that will help their companies or institutions excel. They seek design that will enhance performance, whatever the measure of that is within their work context. Designers know this intuitively. Many even market the notion of design that matters in terms of organizational outcome. “If you hire us, we will help your organization achieve….” Yet few architects understand specifically what aspects of design relate to their clients’ needs; nor can they quantify that impact in a believable way that will help

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their client justify the cost. Often there’s no basis for their assertions about organizational performance enhancement other than professional intuition. So, the question isn’t if design matters; rather its “in what way, how much, why, and to what effect” do people respond to the environments around them? IF ARCHITECTS AND INTERIOR DESIGNERS COULD ANSWER THOSE

SOCIAL SCIENCES, PARTICULARLY SOCIOLOGY AND PSYCHOLOGY, AND DESIGN HAVE BEEN MARRIED FOR OVER

50 YEARS. IN SOME WAYS, IT’S BEEN A ROCKY MARRIAGE BUT ONE WITH MANY MORE HIGHS THAN LOWS. AFTER THESE MANY YEARS, THESE DISCIPLINES TOGETHER PROFFER EXTRAORDINARY PROMISE FOR INFORMED DESIGN. INNOVATION IS OCCURRING ON TWO FRONTS.

QUESTIONS, THEY WOULD HAVE KNOWLEDGE TO CREATE

THE FIRST IS THE USE OF SOCIAL SCIENCE METHODOL-

HIGHER VALUE PLACES AND GAIN GREATER CREDIBILITY

OGY TO CREATE EVIDENCE THAT WILL HELP US BETTER

WITH CLIENTS.

PREDICT OUTCOMES OF DESIGN DECISIONS. THE SECOND IS ABOUT THE APPLICATION OF KNOWLEDGE ABOUT THE

To succeed, the model for evidence-based design practice must embrace creativity and avoid dictating cookie-cutter design solutions. Good architecture is more than rote application of rules. It is innovative problem-solving at its best, wholly addressing needs, including the human need for delight and invention. Prior experience and intuition serve their purpose in design, as they do in all the decisions we make in life. Yet when we are faced with making major life decisions, people will most often do some research and seek advice to be well-informed. We’re not enslaved to that information but we consider it. Making the best design recommendations we can, respectful of clients’ value systems, is a responsibility of design professionals who wish to be treated as trusted advisors. That demands both being informed with transparent knowledge and being creative. Lessons from the social sciences can help. Much social science research occurs in complex real-life settings and uses disciplined methods to sort through the messiness and come to a valid understanding of causes and effects. Other social science research is laboratorybased but also links human behavior with environmental influences. Most importantly, because it’s about people and what affects their perceptions and actions, social science research can help designers understand how to manipulate physical environmental attributes to support the outcomes sought by their clients and to do more interesting work.

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CAUSES OF HUMAN BEHAVIOR, E.G., HOW PEOPLE LEARN (COGNITIVE SCIENCE) AND HOW PHYSICAL SETTINGS AFFECT LEARNING (ENVIRONMENTAL PSYCHOLOGY).

Methods (to study behavior) and knowledge (about behavior)—both can inform the creation of places where people can thrive. Data-hungry clients can gain confidence in design recommendations when they’re backed up by performance metrics or even just a thorough needs assessment. Social science methods can be used to create business value by linking a design choice—say color or access to daylight—with a desired behavioral outcome, such as healing in the context of a health-care client. Some such research already exists and the challenge for the average design practitioner is to access it. In his interview in this chapter, John Zeisel, PhD, claimed that some research exists on virtually any design question. Therefore, it could be claimed that there is always an opportunity for informed design. However, the amount of information may not always be enough, depending on the risks and costs associated with the decision being made. As the stakes become higher, the data must be more compelling to be an effective decision tool. WHEN EXISTING RESEARCH IS NOT SUFFICIENT FOR THE QUESTION AT HAND, THE PROCESS BECOMES USING THE BEST AVAILABLE INFORMATION, WHILE APPLYING THE TOOLS AND METHODS OF SOCIAL SCIENCE TO AUGMENT EXISTING DATA WITH NEW INFORMATION DEMANDED BY THE SITUATION.

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THE SOCIAL SCIENCES

Frequently, project fees and timetables won’t support original research (although some practices have done well in finding clients who will fund it). When practical constraints limit research, the predesign planning process itself may provide an opportunity to systematically study the issue using internal client data, i.e., programming on steroids intended to reveal the potential to impact organizational behavior through design; not just a room list. Project-centric research may not apply broadly beyond the project, as it might reflect a specific client’s idiosyncratic context, but many researchers will claim that patterns very frequently recur across organizations that allow generalizations from one project to many. Further, as Andrew Laing and David Craig point out in their interview, even when the results can’t be generalized, systematic analysis of client needs provides a type of evidence—information about that client that can help that client understand how a design change could affect their organization’s performance. The work highlighted in this chapter addresses both methods and behavioral knowledge. Several themes emerge. 



THERE ARE MANY RESEARCH METHODS THAT APPLY TO DESIGN. THE USE OF SEVERAL, RATHER THAN ONE, ENHANCES RESULTS. One can even cross the lines of this book’s chapters and mix data mining, prototyping, and social and natural sciences! There are many research approaches that may be used. For example, if your goal is to zero in on one very specific design attribute, it might be best to use highly controlled protocols in a laboratory setting. However, other questions may be better researched in complex environments with multiple variables at play, if it’s how the influences come together as a system that most interests you.

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REGARDLESS OF THE SPECIFIC METHODS OR SETTINGS YOU CHOOSE, THE RELIABILITY OF THE RESULTS WILL DEPEND ON USING RIGOROUS METHODS.

Architects are seldom trained researchers. Often even PhD students in Architecture have no prior exposure to research methods. Because design professionals as a group haven’t been sensitized to valid research practices, there is much poorly done research resulting in misleading information. Though well-intended, this work can lead to false expectations and failure of the resulting designs to yield positive results. Such information is also readily available to the profession through conferences and publications, so it is adopted as truth and the damage spreads. We can do better by engaging people with research skills whenever possible, either as collaborators or in-house experts. Multidisciplinary collaboration is an ever-present concept advocated by proponents of evidence-based practice. Innovative designers are forging external relationships with consultants and academia; or they’re hiring people with diverse backgrounds who understand the social sciences. 

EVEN WITH THE RIGHT SKILL SETS INVOLVED, IT’S ESSENTIAL TO CLEARLY COMMUNICATE THE RESEARCH CONTEXT—THE HYPOTHESIS, SETTING, SUBJECT POPULATION, CONTROLS, AND MEASURES—ALONG WITH THE FINDINGS. That way, clients and other

designers can make their own judgments about how much weight to put on the data in their decisions, on their projects. How we communicate the evidence is as important as the evidence itself. Fortunately, over many years of environmental design research, a strong foundation has been developed from which design practice can move forward. Social science methods and knowledge—both are there to enhance evidence-based design practice, as long as the designers understand where to find them and how to use them.

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The Influence of Social Science and Environmental Psychology on Architecture Environmental psychology is arguably the social science discipline most directly related to evidence-based design. The mid-twentieth century witnessed an intersection of design—largely of urban and interior spaces— and social scientists. Although not a social scientist by her early training, Jane Jacobs (1916–2006) addressed social issues in her advocacy of more humane urban development; one of which emphasized the importance of enhancing existing urban neighborhood patterns. Her theory of neighbors having “eyes on the street” emphasized citizen engagement and encouraged a redefinition of neighborhoods. Linking socioeconomic, political, and cultural anthropology to the history of urban growth patterns, she advocated for denser, higher-quality urban economic policies rather than suburban developments. “Eyes on the street,” as Sherry Ahrentzen, PhD, argues in her interview, has been too often lifted out of context by architects who thereby use evidence to misinform design. However, Jacobs’s work resonated with architects and helped bridge the gap between design intent and outcome, if not connecting design and scientific methodology. Another urban theorist, William H. Whyte, introduced many designers to a social science method. In his Street Life project, Whyte conducted over 16 years worth of observational studies of pedestrians in Manhattan and patterns of human behavior—walking patterns, use of open space, points of gathering, and interaction. Everyday people were observed and photographed by still and movie cameras, and interviews were undertaken, interpreted and analyzed. Whyte was an advocate of field observations of people in natural conditions rather than in laboratory, experimental states of being.

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Much of the early focus of environmental psychology was on interior environments. Robert Sommer (Personal Space), a social psychologist, studied how people alter their space to meet their needs and how, in turn, those spaces affected their behavior. Edward Hall (The Hidden Dimension), an anthropologist, identified how different cultures interpreted space in social relations. A number of behavioralists believed that design would control behavior and their work on office environments is credited by many to be a precursor to the discipline of architectural programming. Once it was recognized that space could influence behavior, the logical next step was a systematic inquiry process to articulate the design problem. In 1968, the Environmental Design Research Association (EDRA) was established by social scientists, design and facilities professionals, students, and educators. It remains committed to the development and dissemination of research to improve understanding of the interrelationships between people and their surroundings, and thereby help to create environments responsive to human needs.

Primary Areas of Investigation A review of environmental psychology literature reveals six primary areas of investigation. (Garling and Golledge 1993, Kaplan and Kaplan 1982) 

Attention: Understanding how people notice the environment; either by stimuli which are (1) involuntary (distracting) and command notice, or (2) voluntary, requiring some effort, often resulting in fatigue. Understanding “attention” is the starting point of designing to enhance human behavior.



Perception and cognitive maps: The ability of people to imagine the natural and built environment, retain these images in the brain as spatial networks, and remember and recall these images

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THE SOCIAL SCIENCES

called “cognitive maps.” These neural networks enhance the ability to recall images that in turn influence new perceptions and understanding of new experiences. 

Preferred environments: People seek environments that are most comfortable, that build confidence and the ability to engage others. Research is in areas that provide coherence (order), legibility (understanding), complexity (stimulating variety), and mystery (the prospect of gaining more information).



Environmental stress and coping: In addition to the study of environmental stressors such as acoustics and temperature change, other cognitive stressors such as prolonged uncertainty, lack of predictability, and stimulus overload are common points of study.



Participation: Much research is oriented toward enhancing citizen participation in environmental design, management, and restoration.



Conservation behavior: Studies explore environmental attitudes, perceptions, and values as well as devising intervention techniques for promoting environmentally appropriate behavior.

In addition to research that attempts to establish direct links between environmental variables and behavioral responses, there’s a rich resource for designers in the form of related research fields; such as developmental and cognitive psychology. For example, how people learn, concentrate, and create is well researched and can provide the designer of educational settings with deep understanding of the behavioral characteristics that the space is intended to support for optimal human function. This type of “hypothesis-based design” does have an element of inference but it is informed design at the least and, in the best circumstances, can then be directly tested and measured for outcomes to confirm the hypothesis. Did this setting indeed influence the desired result?

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John Zeisel’s work with people living with Alzheimer’s Disease is an excellent example of evidence-based process that starts with knowledge about behavior: People rely on natural mapping and mental cues to find their way and brain deterioration can impair these processes; which informs a hypothesized relationship to specific design elements (e.g., mementos); and ultimately is measured in a research-based assessment of the outcomes of design intervention.

Methods The body of knowledge is rich and relevant to designers who want to positively affect human behavior. Social science research methods are relevant to complex environmental settings. Two of these—survey and observation—may be the most commonly used tools for assessing design performance, particularly in postoccupancy evaluations (POEs). These therefore have the dubious distinction of being both very powerful and very dangerous. RESEARCH DESIGN IS AS IMPORTANT WHEN USING SOCIAL SCIENCE METHODS AS IT IS IN OTHER SCIENCES. Most designers wouldn’t presume to venture into a lab setting and hook up electrodes to experimental subjects. How many, on the other hand, would see no problem with writing a survey, even if they have no training in how to do that? And this is the tip of the iceberg. THERE IS A SYSTEM OF STEPS. THERE ARE SAMPLING PROTOCOLS TO AVOID BIASED RESULTS. PROCEDURES ARE NEEDED TO KNOW WHICH OF MANY CO-PRESENT VARIABLES IS THE CAUSE—OR ARE THE CAUSES—OF THE OUTCOME. EXPERIMENTAL DESIGN NEEDS TO ANTICIPATE AND CONTROL FOR CONFOUNDING VARIABLES WHEN APPROPRIATE AND/OR NEUTRALIZE THEM IN THE ANALYSIS OF THE DATA. CHOICE OF RESEARCH INSTRUMENT ITSELF MUST BE KEYED TO THE QUESTIONS BEING QUERIED AND THE SPECIFIC DESIGN OF THE TOOLS

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IS CRITICAL. STATISTICS HELP CLEANSE DATA SO THAT

9. Data Analysis

ANOMALIES DON’T CREATE MISLEADING RESULTS. LAST-

 What combination of analytical and statistical

LY, ONCE THE MEANING OF THE DATA IS UNDERSTOOD,

processes will be applied to data? What level of numerical differences is significant?

THE COMMUNICATION MUST BE CLEAR TO AVOID IT BEING USED OUT OF CONTEXT BY ANOTHER DESIGNER.

10. Conclusions, Interpretations, Recommendations:  Was my initial hypothesis supported? What if my

Here are ten typical steps in the process and some questions one would answer before moving on to the next step.

findings are negative? What are the implications of the findings for the theory base? What representations can be reliably made to the public and other researchers?

1. Problem Statement  What are the obstacles in terms of knowledge,

data availability, time, resources, and cost/benefit?

Tools

2. Theory Assumption, Background Literature  Is there relevant literature to address my issue?

Any prior failures? Why? 3. Variables and Hypothesis  Can we define the independent, dependent,

and control variables? Can we define the relationships between the variables? 4. Operational Definitions and Measurements  What is the level of aggregation? Unit of Mea-

sure? What degree of error will be tolerable? Will others agree? 5. Research Design and Methodology  What are the threats to internal or external va-

lidity? 6. Sampling  How will I choose my samples? Is it important to

be representative? 7. Instrumentation  Are valid and reliable instruments available or

must I construct my own? 8. Data Collection and Ethical Considerations  How much training will be required of interview-

ers, observers, and analysts? What level of interrater reliability is acceptable? Do subjects’ rights need to be preserved?

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This brief discussion of tools is an overview of some frequently used methods. It’s less a “do it yourself at your own risk” guide than a way to raise awareness of the variety of tools available for different situations. Ask 

Nondirective and Structured Interviews: These are an excellent way to uncover drivers and needs, of which the subject is aware, as well as their perceptions and preferences. Structure enables consistent analysis of data from more than one subject or project; and works well when the questions have been framed. Less structure provides greater opportunity for the subject to raise unexpected issues. (Picture the psychoanalyst encouraging the patient to talk about a deepseated issue: “I see…and you’re saying that made you feel…? ) Active listening techniques apply to ensure that needs and perceptions are raised and not shut down by narrow lines of questioning.

One-on-one interviews provide a safe context for the subject to openly share feelings. Small group interviews are often intended to provide peer support for raising controversial topics and may also be used to develop ideas and themes.

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THE SOCIAL SCIENCES



Focus Groups: One of the earliest methods used in design inquiry, focus groups are an efficient way to poll representative options and to provide context for diverse opinions. Good for information gathering, the social dynamics make closure less likely than raising issues. Skilled facilitation is critical.



Surveys/Questionnaires: These are very powerful for developing large data sets of well-controlled specific data and demographics controls. Traditionally, questionnaires enable high participation, good for both learning about needs from the perspectives of multiple users and engaging many people as part of the change management process. Web surveys have become particularly useful for reaching large populations of subjects. Their limitations are that the questions should be narrow and few, if you want a good return rate.

Observe 



Trace Observation: How we actually use space and how we manipulate it to overcome shortcomings often reveals truths about needs and behaviors that are unconscious or not socially comfortable to discuss when asked. Trace observation documents the artifacts we leave in our surroundings. Behavioral Mapping: Space use is dynamic. People move from setting to setting. Their perceptions are often different from what really happens in the real world of varied, sometimes random actions. But it can be visually documented to reveal repeated patterns and anomalies. The map will document movement for Point A to B, most likely places for interaction or congregation, and sources of delay and conflicting behaviors.

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Ethnography: Observing a person going about their daily lives provides an objective perspective on what actually is happening as compared to what people say is happening. There are many tools used in ethnographic studies: shadowing, in which the researcher is actually present and following the subject; activity logs and photo ethnography, where the subject documents his or her own behaviors but in a rigorous format to help get beyond perception; video, which may be less intrusive than shadowing but subject to its own regulatory concerns about protecting privacy and participant well-being; and “bed checks,” in which behavior is documented at set time segments and places.

How to write an effective survey, facilitate a focus group, or control an observational study is the topic of many other books. This book’s purpose is to illustrate through example, the work of people who are using social science methods and integrating knowledge from sociology, psychology, and anthropology in design application. Despite the long history of environmental psychology and the rich data it has produced, hurdles still need to be overcome. What are best practices in using the information and skills from the social sciences? Or is the better question: “WHAT CAN WE LEARN FROM THE BEST PRACTICES OF TODAY TO TRANSFORM DESIGN PRACTICE TOMORROW?”

REFERENCES Garling, T. and R. Golledge (eds.) (1993). Behavior and Environment: Psychological and Geographical Approaches. Amsterdam: North Holland. Kaplan, S. and R. Kaplan (1982). Cognition and Environment. New York: Praeger.

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Interviews of Experts and Case Studies LAING AND CRAIG INTERVIEW Andrew Laing and David Craig “It’s a complicated problem we typically deal with. We do use data a lot to understand how people currently work. We also use that data to understand how the current pattern could change. You can often better support how they currently work but can get more by changing the work pattern.”

RESEARCH BACKGROUND

LAING AND CRAIG INTERVIEW

Figure 3.1 Andrew Laing, PhD

Figure 3.2 David Craig, PhD

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Andrew Laing is Managing Director, DEGW North America. With 19 years of experience with DEGW in London and New York, Laing combines an interest in research into the design and use of the workplace, with active involvement in leading client services. Since establishing the North American business in 1998, Laing has worked with many significant clients including Accenture, Fidelity Investments, Google, JWT, Microsoft, GSK, Nike, and the United Nations. Laing is the co-author of New Environments for Working and The Responsible Workplace. He has published many articles and speaks regularly at conferences. He is a visiting lecturer in the School of Architecture at Princeton University and received his PhD from MIT. David Craig is a Director of DEGW North America in New York, where he contributes to global workplace strategy projects and oversees the development and application of DEGW’s methods and tools in North America. Craig has focused on developing innovative approaches for measuring the impact of the workplace on businesses, including most recently impacts on employee productivity and workplace culture. He has also pioneered methods for developing distributed workplace practices for organizations seeking to enhance and capitalize on increasing employee mobility. Recently he led a global company-wide effort on tools and methods. Craig’s recent clients include Capital One, Fidelity Investments, Marsh & McLennan Companies, Microsoft, and Pfizer.

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He speaks regularly at industry conferences and has taught at Harvard’s Executive Education program and at Georgia Tech.

How do you use evidence in your work? DEGW has been very focused for a long time on how we work with clients to capture what they need in the design of their workplaces; how we collect information or evidence to support the briefing for these design projects; and also how we use that information as a means of measuring the success of those environments once they are implemented. The real focus for us has been a very user-centric approach. We’re interested in understanding the user perspective at different levels—a senior leadership level, where we learn about the corporate (or government or institutional) direction for moving organizational intent and strategy, in parallel with the user perspective across the organization about their own participation in that environment and the ability of that environment to support their success.

We’ve developed a series of tools that are quantitative and qualitative. Qualitative: High-level discussions with leadership and staff about objectives (what they’re trying to achieve) and metrics that might relate to that. Quantitative: Observational techniques and workplace performance surveys that capture critical qualities of the environment that relate to how people get their work done. We also use this data to benchmark “before” and “after” a design implementation. With our clients, we try to estimate the impact of the changed environment on their productivity. We look at the whole environment, not just the physical design but also technology, the way they manage their time, and the whole host of factors that contribute to workplace performance and user satisfaction. We do social network analysis, drawn from sociology. We employ some ethnographic methods but these are qualitative in nature. The point of it is to understand where the business wants to go and how people should be working to go there. Different sorts of data, often direct interaction with business leaders, comes into play. It’s difficult to get people to think about not just more conference rooms or whatever other physical changes they have in mind that might impact work, but instead to think more abstractly about the way people interact with each other.

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What types of methods do you use to develop information to inform that understanding?

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Are the questions you ask centered around facilities? We’re pretty careful to make sure the questions we ask are not only about facilitiesbased issues. Our strategy is often not about facility-based issues but about the organizational change they’re trying to create or the business direction they want to move in. Our approach is related to an historical change in the nature of the workplace, especially with new technologies of the last 15 years, which challenges what the “office” is—where people get their work done and how they collaborate and communicate. The facility is no longer the container of the organization. We have to ask questions that are more about how people work and what they want to achieve. These questions enable us to think about the response of the workplace to help them achieve our clients’ goals, with workplace considered in a very broad sense—work from home, how you use space over time, and the way you use technology.

Does the process you use to understand new workplaces inhibit or enhance design creativity?

LAING AND CRAIG INTERVIEW

The work we do is driven primarily by our research and consulting—the urge to understand how organizations behave and the requirements they have for the environment. In terms of creativity, we’re finding a paradox. As work becomes less place-dependent—as we work in many different ways, virtually and otherwise—the value of the design of the place itself actually becomes more important. There is an interesting value-inflation. It emphasizes the role of design.

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We develop concepts, always partner with an architect, and usually hand off the project after a transition period. The research findings will reveal opportunities and import areas where a client should focus but really there’s a big step between that and actually creating designs. Therefore, solutions we come up with often do involve design concepts. We often think about the physical design as well as the needs; and we’re very creative with space, especially because we’re also thinking of new work styles, new policies, and new ways of using technology that organizations haven’t seen before. The creative side of it is much broader than just thinking about space. We think of ourselves as designers of work, more than anything, tying together space, technology, policies, that sort of thing.

What types of measurements and metrics do you use in data development and analysis? Our 2004 project with Capital One may be the best example. We started working with the executives, group by group, to determine what they believed

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drove productivity in their group. We also explored their metrics, formal and not, such as milestones, pipeline, etc.—all the usual business metrics—and then we worked back from those to define actual, observable behaviors which affect the metrics. For us, the further back you go into the details of how people actually work, the more easily measured these things are. It’s more difficult with the aggregate business metrics we started with because these are going to be influenced by different variables. So we developed a constellation of things that drove business performance. We came up with a consensus set (12 to 20 metrics in total), such as “amount of time waiting for a colleague” and “time answering an email.” Our job was to measure, before and after the design change, those things the business leaders thought were valid indicators of what made people more innovative. This is far from scientific. The goal is to capture how the client defines productivity, measure it with reliable methods, and bring them back to the appropriate level. We developed a series of hypotheses (e.g., how the new workplace would address an identified issue), which all together contributed to defining a new workplace environment we could then measure. There are many tools for measuring, among them electronic surveys, comprehensive observations before and after, tracking average time with different behaviors, among others.

The work you address involves a number of variables. Can you isolate the impact of each of those; or is it even important to do that?

When you do interviews, focus groups, and surveys of large populations, you get very strong indications of what issues are important and how well these are performing in current conditions, even without doing the postoccupancy. We can take that as a leading indicator of what needs to be provided in a new environment. The perspective we have is that this kind of measurement is “intentional”; it’s not like a laboratory study. The metrics are driven by those intentions of the organization. One of the things we all have to think about here is the validity of different types of measurement. Which types of measures are in a sense more independent or more objective than others which are more driven by perception? The combination of

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We don’t ever try to separate the effect of different changes from one another. The client organization doesn’t have that luxury of trying many different things and putting together what they learned. It has a relatively short time for the study and it’s banking on the analysis succeeding. You do as much as you can to get it right the first time. We look at the total impact.

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methods we use varies. For example, “time in a meeting room” is independent of user perception of how well the environment is supporting them as users; but our position is that the user’s perspective is also a valid measure because they think and believe they have seen changes in how the environment supports them. Therefore the change is having a result that’s part of the intention.

How about the use of statistics? We rely heavily on descriptive statistics but it’s partly to demonstrate to the corporate organization that there is a demand for something. We have a very rigorous way to use observation to measure how space is being used over time. For example, we know how many observations over how much time would lead you to relevant conclusions. We don’t typically use any type of reliability statistics, although we typically do work to get the right samples based on the probabilities. That’s to ensure we have a decent representation over all the subgroups we’re cutting the data by; but we’re not looking for stability within work patterns or other types of responses. We take individual responses as meaningful; we’re not always just seeking the averages or aggregate statistic. There is consistency over time of work patterns we’ve observed across similar organizations that has given us a fair amount of confidence about them. There is a difference between what people report about use of space and what rigorous observational studies over a decade reveal. (We see less occupancy than what people report.) That difference is pretty consistent, so we’ve explored what the drivers of it are. Our goal is to provide enough credibility to convince managers—it’s not necessarily to draw firm conclusions from, at least that would convince a researcher outside the organization.

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Do you use an interdisciplinary research approach?

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Yes, both internal and external. Within the firm, we employ quite a varied set of expertise in various social sciences—people with some kind of social science and some design training as well. We’ve found that mix of disciplines to be quite valuable. We also often collaborate with others, depending on the assignment, and are most likely to partner with psychologists and sociologists. We probably talk more in a design language than in anything else. I’m aware there’s a lot of workplace research but a lot takes an individual employee level perspective—how productive an individual is. The data on teams and organizations as a whole is somewhat sparser and usually more qualitative. So we really invented our

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own analysis and process for developing data that’s not done by anyone else. It’s a relatively small market we work in.

How much of your research is project-centric versus contributory to a broader knowledge base? We collect a similar set of data across clients. We’re looking at mining data across organizations. There’s also some limit to the extent to which the data can reliably be generalized in terms of performance because we’re often trying to be very specific to the business and what their particular metrics are. In that sense, it isn’t completely standardized. It is driven by organizational objectives. Most of the data is before conditions and often about dated facilities. We do postoccupancy evaluations maybe a quarter of the time. Often organizations are onto something new and different. We are sitting on a mountain of data (10,000 survey responses every month; observe 50,000 employees a year).

How would you change the curriculum or practice model to encourage use of evidence to enhance creativity? It does seem to us there are big gaps in architectural design training where this kind of approach is largely absent from the curriculum. I don’t see many schools that are developing a rigorous understanding of the social science tools and methods that architects could be using in programming efforts. I think programming is seen as a kind of routine effort. The schools don’t spend much time on the rigorous thinking.

It would be ideal if the schools introduced that in their curriculum. It’s a huge opportunity to reinvent and add value to what the architect is offering to the client.

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I’d even be cautious about calling what we do “programming.” There is a very creative side to understanding demand—what an organization needs, how they currently work, and so forth. We have a lot of methodologies and they come together in different, very creative ways, and get expressed in unique ways, depending on what the organization is dealing with.

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C ASE S TUDY

CASE STUDY / Space Program Story

Space Program Story DEGW, April 2009 In 2003, a large financial services company was looking for alternatives to cubicles and to the long-standing assumption that people needed an assigned desk and needed to be in it to be productive. Their main research question concerned how people would work and what needed to be supported, if they didn’t have assigned space. They also asked whether the solution could be the same for everyone, or whether it would need to provide a range of options.

The company was already more progressive than most of their peers with regard to their workplace, having implemented an open work environment designed to emphasize collaboration over individual status, but they wanted to further increase the efficiency of their space, more closely co-locate staff who worked together, and improve the work experience. Several research methods were used. Because there were very few examples of the kind of workplace they were envisioning, the answers to their questions came primarily from research on how people at the company worked at that time and from how people said they would like to work, particularly when given new scenarios to consider. Data was collected through observations of behavior in existing spaces that tracked how often space was used and for what purposes; surveys that gauged work patterns and measured the importance and performance of various aspects of the existing workplace; focus groups that explored future scenarios; and interviews with managers to better understand business drivers and objectives. The research revealed some compelling information. Observations showed that assigned individual workspaces were only occupied around 35 percent of the time, indicating that their conventional space was inefficient, at least in the sense that their biggest piece of infrastructure was not well used, and that most work already took place away from an assigned desk. Low desk utilization along with high meeting room occupancy also revealed a polarized work pattern, with people commonly spending many hours in meetings every

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CASE STUDY / Space Program Story

C A S E S T U D Y: S PA C E P R O G R A M S T U D Y

Figure 3.3 Average Occupancy of Assigned Workspaces: Systematic observation reveals much less time spent at an assigned desk than self-reported. This often-repeated pattern creates an opportunity for shared spaces that will reduce occupancy costs and provide more interesting work settings.

day and then struggling to keep up with individual responsibilities in their remaining time. This finding was consistent with data showing that people desperately wanted more spontaneous interaction (versus scheduled meetings) and more accessibility with their colleagues. Finally, the research showed that there was not one universal work pattern but several different ones, ranging from extremely mobile to extremely desk-bound. Four different work-style categories were derived from the data and used for planning purposes to represent four different types of needs. Some roles predicted specific work styles, but many did not, suggesting individual differences. The research outcomes therefore led to a notably different workplace and a new way of supporting, even transforming, work patterns. Observational data showing low utilization helped confirm the hypothesis that work could be supported without assigned space. Data regarding specific performance gaps, in conjunction with manager input about what helped and hindered productivity in their teams,

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Figure 3.4, 3.5 The Workplace Performance Survey also quantified specific functional deficiencies and thereby suggested most important design interventions to improve productivity.

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C A S E S T U D Y: S PA C E P R O G R A M S T U D Y

Figure 3.6 Current Work Patterns by Job Type: Through analysis of work processes, workers were categorized by their degree of mobility. This enabled the planners to quantify an optimal mix of settings to support various needs.

led to a decision that the core work environment should be even more open than before and should have more settings designed specifically for spontaneous meetings. Since control over distractions was also an issue uncovered in the survey, quiet zones—areas of the workplace designated as distraction-free—were also added to the design. Lastly, to ensure that the right balance of settings, from very collaborative to very individual, were provided, work-style categories were used to quantify specific types of demand (e.g., such as how many meeting rooms one would use over the course of a week if one were categorized as a heavy “collaborator”), and the prevalence of different work styles were in turn used to develop a space program for the final concepts. Ultimately, the idea that every employee would have access to a range of specialized spaces rather than assigned one all-purpose space allowed the space program to be finely customized based on the activities and preferences of each team.

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Figure 3.7 Translating survey data into space concepts is a critical transition. This mixed setting concept provided places that were appropriate for different work patterns identified by the research.

 Figure 3.8 Desks are provided for mobile workers on a shared basis, substantially reducing real estate costs.  Figure 3.9 Settings other than offices and cubicles provide choices to people to work according to their preferred style. The research clarified how much collaboration and private time was actually needed to fulfill job functions.

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BROMBERG INTERVIEW Joyce Bromberg “When I discovered this practice of human-centered design, it calmed me as a designer because it allowed me to come up with solutions which, as a given, had to be aesthetically pleasing but in the best sense were more creative because they were solving an unmet need and were deeply aware of the process that was going on.”

Figure 3.10 Joyce Bromberg

Joyce Bromberg is Director of WorkSpace Futures—Research at Steelcase Inc. In this role, Bromberg is responsible for user-centered research for vertical markets and Phase 0 research for new product development. Sometimes called “pioneering research,” this activity utilizes her 25 years of industry experience in the areas of observation, synthesis, and design. Bromberg was appointed to this position in 2002. Prior to this, she was Director of Space-Planning Research and Environment Design. In these roles, she was responsible for all research and development activities related to space planning, the design of Steelcase environments, and was the lead developer of community-based planning, a space-planning methodology and web-based toolset. Bromberg joined Steelcase in 1982, as an interior designer. In 1986, she was promoted to Interior Design Project Manager, designing many award-winning showrooms and industry/trade show events. She then was appointed Manager of Strategic Planning for the architect and design market. She has also served as director of Surface Materials and Advanced Concepts. Bromberg is a graduate of the High School of Music and Art and has a BA in Art History from the State University of New York at Stony Brook.

How do you use evidence for design in your work? My team uses a human-centered design research methodology to help Steelcase identify user needs that translate into a better health-care product. In a sense, because products are always conceived in terms of

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RESEARCH BACKGROUND

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an application or the setting in which they are to be used, we use the research to develop new kinds of applications at an architectural level. We also freely share the findings from our research with our clients and anyone else who’s interested. We’re very interested in building a body of evidence and adding to that body of evidence through collaborations with health-care institutions and organizations like the Center for Health Design.

Could you talk about various methodologies you’re using to do this research? I don’t know if anyone has come up with a definitive way to conduct evidencebased design research but we’re experimenting with different approaches and hopefully adding to the body of knowledge about how one might approach such research. We have a basic six-step process that is not proprietary to Steelcase:

BROMBERG INTERVIEW

1. Understand: It’s necessary to comprehend secondary research with the goal of being as smart as we can about a topic or discipline—the vocabulary, process, roles, design precedent, and the forces impacting them today, e.g., insurance and medical error affecting health-care. We always do the reading with the physical environment in mind. For example, how might medical error be reduced by the design of an environment or the way we craft a new product?

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2. Observe: The secondary research helps us to choose observation sites but we’re always looking for a wide variety of places to observe. We spend generally a week at a time, around the clock, at any given location; and have developed a number of methods that help us observe. Part of what we do is about “asking”— using interviews, questionnaires, and focus groups. The asking reveals the explicit process; for example, what people say they do. The second part of observation allows us to understand the tacit, the unconscious—what they’re doing without even thinking about why they’re doing it. For this, we might shadow people, do time utilization studies, camera studies, video ethnography—a whole variety of techniques. The third part is Participatory Design. By engaging people, we get into their latent needs; the emotional. One of our tools is an online collage tool that allows participants to describe the existing condition and the desired or “should be” condition. It allows you to uncover deep feelings about experience. Our process is about asking, observing, and engaging: When you’re designing with intent, you have to look at not just your space but also at the people, their behavior, and how they interact with objects and each other; at their technology;

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and at their process. These have to be understood and designed for at the same time. When we observe, we look at all and how people work around deficiencies. 3. Synthesize: We’re very stringent about documenting all observations and secondary research and keeping this data separate from our opinions and the concepts that come out of it, as well. So, our third step is to state an observation and how we feel about that; and then track the concepts back to the original research source. You begin to see patterns in the data. We share observation stories and then group those stories into clusters—patterns of behavior or patterns of need—until we have gone from insights to sets of actionable design principles. 4. Realize: The next step is to use the principles, much like design criteria, to create solutions. We have charrettes and do a lot of brainstorming—considering the needs, the application context, and the aesthetics. The solutions are not developed in isolation. In conjunction with industrial designers, we consider products in context of what the new space will look like, the experience of the staff, and all the protocols and behaviors and technologies that one would need to make those spaces effective. 5. Test: Then, the product always goes into prototyping. We build full-scale models and do user testing. 6. Measure: Whenever we can, although not always possible, we measure what we’ve accomplished. Measurement for us always goes beyond only satisfaction to outcomes, such as time to treatment.

The converse is true. I think people mix up creativity and aesthetics. When I was starting as a designer, I was always worried about how something was going to look and where my next idea would come from. It was very stressful, particularly if you didn’t want to pour through design journals and rely on what was already being done. When I discovered this practice of human-centric design, it calmed me as a designer because it allowed me to come up with solutions which, as a given, had to be aesthetically pleasing but in the best sense were more creative because they were solving an unmet need and were deeply aware of the processes that were going on. Sometimes architects and designers aren’t aware that when they mess with the physical environment, they’re messing with an ecology of behaviors. If they’re not as mindful as they should be they’re going to cause harm. So for me, ours is a very affirming process that allows my whole team to be much more creative in their solutions and the solutions to be more effective for the users as well. It does anything but limit creativity.

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Might this research process inhibit creativity?

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Do you use a wide variety of interdisciplinary expertise? Not only do I believe in cross-disciplinary teams but I believe we’re creating new kinds of professions or practices. On our team, we have people with lots of different backgrounds—designers, architects, researchers, and social scientists—and we always work with doctors, nurses, and patients, and often architectural firms as well. When you’re handling complex problems, it’s very difficult to do anything alone anymore. There must be collaboration. You have to have smart, curious people who have been trained to think and solve problems. In that sense, the broader the backgrounds, the better, because you have diverse people with diverse experiences to solve a hard problem.

BROMBERG INTERVIEW

There’s a need to give people a way to understand what it is they’re designing for. That way, they can design something that will help people be more effective or have some kind of positive, measurable outcome. Design education can’t be about aesthetics alone. The curriculum will have to change dramatically. You have to give people tools to understand performance and process. For example, what can we learn from neuroscience about how the brain works that we can apply in order to design environments that essentially help the brain perform better? We’re beginning to know how people learn. Are we taking advantage of that knowledge in the design of classrooms? So, designers can not only learn a method of investigation; they can be opened up to other areas of inquiry and take that information and make it useful for the practice of architecture.

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There’s another aspect of practice that has to change. Architecture firms aren’t going to be able to do the level of research we’re talking about alone. We’ve got to come together in consortia to do it, where we share everything we learn in the spirit of furthering the science. There’s more to be gained in doing that than there is to be lost. There has to be this notion of altruism, if only to be good citizens of the world. In science, everything is shared and everything has to be peer-reviewed. The reward comes in being there first. It goes nowhere if you keep it a secret. If you don’t allow it to be scrutinized and measured, it reduces the work we do as designers to a commodity.

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C ASE S TUDY Consultation Room Design and the Clinical Encounter— The Space and Interaction Randomized Trial Julia R. Almquist1; Caroline Kelly, MID2; Joyce Bromberg2; Sandra C. Bryant, MS3; Teresa J. H. Christianson, BS3; Victor M. Montori, MSc, MD4,5,6

INTRODUCTION The design of outpatient consultation rooms has remained generally unchanged despite major changes to patient care practices, processes, and technology. A study funded by Steelcase and conducted in the Division of General Internal Medicine of the Mayo Clinic in Rochester, Minnesota, utilizes a collaborative research model and rigorous experimental controls and statistical analysis to explore the relationships between specific aspects of room design and patient outcomes. This case study, excerpted from a monograph by the research team, illustrates the explicit use of controlled research techniques to assess design impacts on a setting of great importance to quality of care.

THE RESEARCH QUESTION The exam or consultation room, in which millions of outpatient visits take place yearly, may critically impact the quality of health-care in general and of the patientclinician interaction in particular. While there has been much work examining the patient-clinician interaction, little has been done to understand the extent to which it can be affected by the design of the consultation room.

CASE STUDY / Consultation Room Design and the Clinical Encounter

C A S E S T U D Y : C O N S U LT A T I O N R O O M D E S I G N A N D T H E C L I N I C A L E N C O U N T E R

The traditional consultation room involves a desk designed for the physician’s individual use, with the clinician sitting in the primary work position on a chair with enhanced mobility. The patient and care partner (e.g., family member) sit to the side, on 1. Department of Planning, Policy, and Design, School of Social Ecology, University of California, Irvine, California 2. Research, WorkSpace Futures, Steelcase Inc, Grand Rapids, Michigan 3. Division of Biostatistics and Bioinformatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 4. Knowledge and Encounter Research Unit, Mayo Clinic, Rochester, Minnesota 5. Center for Innovation, Mayo Clinic, Rochester, Minnesota 6. Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota

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fixed chairs, and with limited access to the computer screen. Three trends in healthcare suggest the need to reconsider the design of the consultation room in terms of its potential affect on patient-clinician interaction: patient-centered care as a manifestation of high-quality care; the shift from acute-care models in the outpatient setting to relationship-based care in the context of chronic care delivery; and the evolution toward information-intensive encounters, in which the electronic medical record and health information on the Internet play key roles in supporting clinical decision-making and patient education.

METHODOLOGY The Space and Interaction Trial (SIT) was conducted to understand the extent to which a consultation room designed to support modern clinical encounters could affect the patient-clinician interaction compared to a traditional room. SIT was a pilot randomized controlled trial of real clinical encounters to measure, through participant self-report surveys, the effect of a design intervention. In particular, the study evaluated the impact of three specific design features that potentially support the evolved nature of health-care today: the placement of the computer screen, the type and position of the desk, and the arrangement of the seats. Two consultation rooms—a standard room and an experimental room—were designed. The standard room was modeled as composite using design guidelines from the Mayo Clinic, the Veterans Health Administration, and design reference books. (Figure 3.11) Key features of this room recognized the physician as the primary user and included: (a) distinct designated spaces for patients and clinicians; (b) a desk surface for clinician use; and (c) the setup of the computer monitor and input devices that favor physician use. The experimental room (Figure 3.12) was designed to enhance patient-centered care with the use of technology in the consultation. This room featured a half-round table with a computer monitor on an extendable arm mounted on the wall above the table and differs from the standard room in the following ways: (a) the desk surface is a shared space for patients and clinicians; (b) the computer monitor and input devices allow similar access for patients and clinicians; and (c) participants sat on three adjustable chairs of the same design (with glides on patient chairs for safety and casters for mobility for the clinician) set around the table. The arm-mounted monitor was in full view of everyone sitting at the table and could be adjusted as needed. The computer input devices (i.e., wireless keyboard and mouse) were similarly accessible to patient, care partner, and clinician. Otherwise, the standard and experimental rooms were identical in terms of finishes and equipment.

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199 CASE STUDY / Consultation Room Design and the Clinical Encounter

C A S E S T U D Y : C O N S U LT A T I O N R O O M D E S I G N A N D T H E C L I N I C A L E N C O U N T E R

Figure 3.11 The traditional consultation layout was designed around the physician’s access to technology.

Figure 3.12 Research findings demonstrate increased patient involvement in the consultative process was supported by a new layout.

From August until October of 2007, six physicians and 65 patients participated in the study. Sixty-three patients completed the postvisit survey and are included in the analyses. Patients had a median age of 69, and 48 percent were women. Of these, 44 (70 percent) had not had prior episodes of care with the same clinician, and 14 (22 percent) had not received care at Mayo Clinic prior to current episode of care. Table 1 describes the baseline characteristics of patients by trial arm. Table 2 describes the results of the study across the six questionnaire domains.

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Table 1. Baseline Characteristics Standard room (N = 30)

Experimental room (N = 33)

Total (N = 63)

P-value

Age, median (interquartile range)

68 (58, 74)

73 (67, 75)

69 (61, 75)

0.201

Women, n (%)

14 (47%)

16 (48%)

30 (48%)

1.02

Care partner in the room, n (%)

14 (47%)

15 (45%)

29 (46%)

1.02

New to Mayo Clinic, n (%)

5 (17%)

9 (27%)

14 (22%)

0.372

New to this clinician, n (%)

8 (27%)

11 (33%)

19 (30%)

0.602

Characteristics

1 2

Wilcoxon Rank Sum Test Fisher Exact

Table 2. Results by Domain Standard room (N = 30)

Experimental room (N = 33)

P-value†

Predefined domains, median (interquartile range)* Patient satisfaction with the visit

99.3 (97.2, 100)

100 (98.6, 100)

0.127

Mutual respect

100 (100, 100)

100 (100, 100)

0.305

Trust in physician scale

100 (100, 100)

100 (100, 100)

0.984

Communication quality

100 (92.9, 100)

100 (92.9, 100)

0.362

People-room interactions (comfort, clear where to sit and place belongings, access to the computer monitor and input devices)

81.8 (72.7, 88.6)

86.4 (77.3, 90.9)

0.140

Interpersonal-room interactions (cliniciancomputer-patient interactions)

87.5 (68.8, 100)

93.8 (81.3, 100)

0.145

* Higher scores are better † Wilcoxon Rank Sum Test

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THE MAIN FINDINGS The data indicates that redesigning the consultation room to accommodate for the nature of modern outpatient care (i.e., increased patient involvement in informationintensive encounters) has a positive impact in the way patients experience the consultation, even in environments in which satisfaction with the standard consultation room is very high. The experimental room was particularly successful in improving access to the computer display for patients and their care partners. Patients reported physicians making greater use of the electronic information (e.g., their medical record data, radiological images, health information on the Internet) to explain treatments and make decisions. Notably, patients in both rooms endorsed to a similar extent the notion that they participated in conversations about information on the computer screen, while patients in the experimental room were also able to see this information directly on the screen. This experience appears to be reliably captured in the questionnaire, as judged by the extent of interobserver agreement between patients and care partners. The ability to interact with the computer was an area of disagreement, mostly due to care partners indicating greater levels of dissatisfaction than patients with their lack of access to the computer screen in the standard room (as they were seated further away from the screen than the patients).

IMPORTANCE OF THIS RESEARCH TO THE DESIGN PROFESSIONS

CASE STUDY / Consultation Room Design and the Clinical Encounter

C A S E S T U D Y : C O N S U LT A T I O N R O O M D E S I G N A N D T H E C L I N I C A L E N C O U N T E R

Although few designers have the research expertise to conduct research of this type, the collaborative nature of this experiment can be emulated to create evidence that benefits from experience outside traditional design realms. Further, although a high level of experimental rigor was used—and that is often off-putting to designers—the applicability to design is clear. The findings point the way to design adding tangible value for the people who own and use the space and they help make a case for a new design solution, thereby enhancing innovation.

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POWELL INTERVIEW Kevin Powell People want innovation and creativity. There is no machine that manufactures that. What you need is context where you’re encouraged—even forced—to consider multiple factors.

RESEARCH BACKGROUND

Figure 3.13 Kevin Powell

Kevin Powell is the Research Director for the General Services Administration (GSA), Public Buildings Service (PBS). His group identifies new technologies and approaches needed to improve PBS’s business process. Recent research has been focused on three primary areas—sustainability and highperformance building strategies; workplace effectiveness; and optimizing energy efficiency and operations. GSA-sponsored research includes several groundbreaking studies documented in “Workplace Matters” (2006) and “Sustainability Matters” (2008), “Assessing Green Building Performance” (2008), “Energy Savings and Performance Gains in GSA Workplaces” (2009), and “The New Federal Workplace” (2009) all published by the GSA (www.gsa.gov). Prior to joining the GSA, Mr. Powell worked with the Center for Built Environment, University of California, Berkeley.

POWELL INTERVIEW

What sort of research have you been engaged in and for what reason?

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I am guided by the philosophy that the buildings we build, the places we make, need to grow out of the requirements of the people who are going to inhabit those buildings and places. The goal is to get things right and the way you get things right is to know what’s working and what’s not, and get that knowledge to the people who can act on it. We are an agency that manages over 350 million square feet of commercial space where over a million people work. We know that to make the best decisions, we need the best information. We are mindful that we are public servants, and that a key part of our mission is to deliver superior workplaces for the federal workforce, at the best value to the American taxpayer.

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In terms of researching building performance, where are we headed? Broadly, the research program is guided by a Six Sigma-structured approach—Define, Measure, Analyze, Design, and Verify. We also use the Balanced Scorecard technique, so that we’re not just looking at the financial domain, but are also looking at our customer, employee, and business process domains. We are committed to postoccupancy evaluations to complete a feedback loop. POEs help us know if we are specifying the performance our tenants need, and if we are getting the performance that we are specifying. Currently, we are developing an exciting new metric called Integrated Design Excellence Analysis (IDEA). The IDEA tool will measure the success of Design Excellence from initial concept designs through fully developed design documents. The IDEA tool will provide GSA a framework of integrated design factors to use in rating projects within a standard scale. We believe that an extension of the IDEA tool, using the same set of factors, will become the basis for future postoccupancy evaluations.

Are these tools an asset to design creativity, or conversely, do they inhibit creative thinking? I believe—strongly—that an evidence-based framework enhances creativity. A clear framework provides freedom, the spurring of thought that happens when the problem and success criteria are well-defined, and you can fully focus on pushing the envelope of the solution. People want innovation and creativity. There is no machine that manufactures that. What you need is context where you’re encouraged—even forced—to consider multiple factors.

The tools we rely on to make our decision-making stronger spur our creativity. The inception of GSA’s research program began with a series of workplace analysis tools— time utilization studies, social network analysis, end-user satisfaction surveys, and focus groups. Taken together, these tools showed that people were no longer tethered to their offices to access information. Technology enabled them to work anywhere, anytime. From this analysis, we knew we couldn’t just continue to build office space as if nothing had changed since the 1970s; we needed to creatively identify new solutions. Objective information also spurs buy-in. When we showed a customer evidence that two-thirds of the time, across multiple industries, knowledge workers are not at

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Experts bring an enormous amount of information and experience to bear. What spurs their creativity is capacity to make unexpected leaps, where the undefined becomes defined. But all of this can only happen naturally if you have a framework: Where are you starting from? Where are you going? What does success look like?

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their desk, they thought that was interesting. When we showed them that we had observed that exact pattern to be true in their particular space, a lot of conversation followed, and the designer earned a license to be creative in developing a wide range of spaces, to change the size and location of offices and cubes in a way that could never have occurred without that underlying framework of analysis.

How rigorous does evidence have to be to be credible? How much is enough to be considered “proof” and is the process scalable to all design projects? As a public institution, we are required to be both transparent and accountable. We are currently facing mandates that require us to pursue very ambitious sustainability goals—55 percent reduction in energy by 2015, carbon neutral buildings by 2030. Research implies innovation, risk, and reward. We are fortunate that our initial efforts appear to be paying off. We just completed a study that confirms that compared to national baselines, our recent buildings use 26 percent less energy, emit a third less carbon dioxide, all while costing 13 percent less to operate and having occupants that are 27 percent more satisfied. Having access to these objective facts has been important in validating—and further shaping—our approach to high-performance building. We are also fortunate at GSA that the scale of our organization—we have nearly 9,000 buildings in our inventory—allows us to research the best design, operation, and management strategies with an investment of only a small percentage of our operating revenue.

POWELL INTERVIEW

What aspects of design education and the current practice model do you think should change?

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Every assignment in the design studio begins with a program of requirements. Solving that program—with bold creativity and unexpected innovation—that is the goal of every design student, and it should be the goal of every design professional. What needs to be emphasized is that being clear, at the outset, what the criteria of success are, and being able, at the end of the day, to provide evidence that those criteria have been achieved—that is the foundation of a happy ending.

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C A S E S T U D Y: A S S E S S I N G G R E E N B U I L D I N G P E R F O R M A N C E

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Assessing Green Building Performance: A Postoccupancy Evaluation of 12 GSA Buildings U.S. General Services Administration (GSA) Kevin Powell, Don Horn, Mike Atkinson Pacific Northwest National Laboratory (PNNL) Kim M. Fowler, Emily M. Rauch

“This study breaks new ground by comparing GSA’s sustainably designed buildings against U.S. commercial buildings, using the latest performance data. Its findings will be relevant to building owners and developers, public and private, across the country.” David Winstead, Commissioner, Public Buildings Service

INTENT Being a public agency, the GSA has responsibilities to the environment and the taxpayers. Reliable measurement is key to understanding and managing the performance of its portfolio of facilities, including energy use, operating costs, and occupancy productivity. With approximately 342 million square feet of office space, housing 1.1 million workers, this is a large opportunity and challenge.

CASE STUDY / Assessing Green Building Performance

C ASE S TUDY

The foundation for sustainable design has been in place for several years, providing a number of use case opportunities. GSA has applied sustainable design principles to its building projects since 1999; and in 2003 established a target of U.S. Green Building Council (USGBC) Leadership in Energy and Environmental Design (LEED) Silver– level certification for new construction. Federal government mandates enacted in 2005 and later have raised the bar further, demanding a way to ensure that building performance is measured.

METHODOLOGY In this 2008 study, 12 GSA buildings are evaluated in a whole building performance measurement (WBPM) study to determine how well GSA’s sustainably designed buildings are performing. The study’s intent is to seek holistic evidence about the outcomes of using sustainable design approaches that will enable the GSA to make effective decisions about future design.

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CASE STUDY / Assessing Green Building Performance

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Figure 3.14 National Park Service, Omaha, Nebraska

Figure 3.15 At the Omaha Department of Homeland Security, landscaping captures stormwater runoff

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Figure 3.16 Building orientation along with horizontal and vertical fins helps to optimize the energy performance of the EPA Headquarters in Denver, Colorado

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Measures included environmental performance, financial metrics, and occupancy satisfaction. For each building in the survey, at last 12 months of data were collected, sourced from utility bills, facilities maintenance schedules and budgets, and surveys. Performance data was identified, normalized, and analyzed using the Building Cost and Performance Metrics: Data Collection Protocol of the Department of Energy Federal Energy Management Program. The performance of the GSA buildings was compared with the average performance of U.S. commercial buildings, as documented in the CBECS national survey of commercial buildings constructed between 1990 and 2003 (EUI); Energy Star (CO2); 2006/2007 IFMA and BOMA surveys (Maintenance Costs); the Federal Water Use Index (Water); and Center for the Built Environment, UC Berkeley Occupant Satisfaction Survey.

FINDINGS Overall, best performance was achieved by buildings designed with an approach integrating various aspects of sustainability, as defined by LEED. These include site development, water savings, energy efficiency, materials selection, and indoor environmental quality. The two LEED Gold–level buildings were the only ones that performed at consistently high levels, although they did not lead on every measure. Integrated sustainable design, the evidence shows, is helping the GSA to deliver buildings that use less energy, have lower operating costs, and foster occupant satisfaction (which has been linked in other research to productivity).

CASE STUDY / Assessing Green Building Performance

C A S E S T U D Y: A S S E S S I N G G R E E N B U I L D I N G P E R F O R M A N C E S

Specifically, the buildings in this study use 26 percent less energy (65 kBtu/sf/yr vs. 88 kBtu/sf/yr); have 13 percent lower aggregate maintenance costs ($2.88/sf vs. $330/sf); and have 33 percent fewer CO2 emissions (19 lbs/sf/yr vs. 29 lbs/sf/yr). Some buildings performed strongly across the board, if designed with an integrated approach, while others achieved high ratings on only certain measures. Buildings designed to the California Title 24 energy code or Energy Star had high energy performance. Operating costs were lowest when sustainability was so considered in all aspects of design, including recycling and cleaning. A frequent question of corporate real estate and facilities managers is if there is an ROI for sustainable design beyond energy savings. There are indications. A 2002 survey of 800 MBAs found that 80 percent said their motivation and company loyalty was enhanced by the company’s sustainability initiatives. In the same study, 79 percent said they would forego income to work for a company with a credible strategy for sustainability.

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CASE STUDY / Assessing Green Building Performance

This survey strengthens such evidence with higher than average satisfaction ratings for the GSA buildings on air quality, cleanliness, thermal, acoustics, and lighting. Change management and periodic fine-tuning of systems also have apparent value.

SIGNIFICANCE This research provides the GSA with data to objectively assess building performance and the return from investment in LEED and other design approaches. It demonstrated that the top performing quartile of building already meet 2015 federal mandates for reducing metered energy and water use, thus providing guidance on future building programs. Areas for improvement and questions for future research also surfaced. At a larger level, the methodology can be applied by practitioners to their own work. The full study cited here contains tools, formats, and standards that may be of use.

REFERENCES Figure 3.17 Department of Homeland Security, Omaha, Nebraska. Recycled brick mulch from local brick plant. Full cutoff light fixtures to reduce light pollution. Building is 66 percent more efficient than ASHRAE 90.1 required. Soffit overhang on western facade. White roof to reduce heat island effect.

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1. K. M. Fowler and E. M. Rauch, Assessing Green Building Performance: A Post-Occupancy Evaluation of 12 GSA Buildings, PNNL-17393, Pacific Northwest National Laboratory, Richland, WA, 2008. www.gsa.ov/applied research. 2. Survey of 800 MBAs from 11 Top International Business Schools, Stanford Graduate School of Business, 2002 GlobeScan International Survey, MORI.

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UNDERHILL INTERVIEW Paco Underhill One of the things the design professions desperately need is to become more gender integrated. The sensibility here is whereas a man goes into a hardware store and buys a hammer, a woman buys pictures on a wall. That’s part of what the transformation process is.

RESEARCH BACKGROUND

Figure 3.18 Paco Underhill

Paco Underhill has spent more than 25 years conducting research on the different aspects of shopping behavior, earning his status as a leading expert and pioneer in the field. Envirosell, the firm he founded, is the principal testing agency for prototype stores and retail bank branches in the world. Beyond retail, the firm practice includes public libraries, airports, train stations, stadiums, museums, and medical offices. His research shows how today’s world is ruled by factors such as gender, “trial and touch,” and human anatomy. His first book, Why We Buy: The Science of Shopping, has been published in 27 languages, and has sold more copies than any other retail book in history. That book was reissued in 2009 as Why We Buy for the 21st Century. His second book, titled Call of the Mall: The Geography of Shopping, was published in 2004.

I am delighted that twenty-first-century designers recognize that their responsibility isn’t the construction of monuments but is focused on being able to serve the needs of people. My job as a researcher is making frames. Let me construct the frame within which you focus your creative energies. I can make you a better designer without limiting your artistic or creative palette. The architecture profession is struggling with its relationship with financial success. An architect can design an iconic headquarters building but

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How do you use evidence, what kinds, and why is it important to your clients and your work?

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that building will have no effect on the financial health of the company. An architectural firm’s fees are based on selling hours, rather than some form of creative impact to the clients’ bottom line. In store design, there is a long history of award-winning and widely published projects that are financial disasters and are closed before the prizes are awarded, or the spread in the magazine is published.

Design desperately needs to be more answerable to its clients and evidence is one of the ways of starting that process. So, how do you do it? In 2009 it’s easy to collect data. Being able to turn that data into something that’s actionable and useful to a building operator or designer is a lot tougher. For 25 years, I’ve been using observation, interviews, mapping, and tracking systems to be able to try to understand better what happens. There is a new generation of designers that are empowered by the collaboration with researchers. Early in my career I had the opportunity to interact with a number of name-brand architects, all of them talented and driven…but breathtakingly arrogant. Over the past ten years the design profession has changed. Just the fact that you are writing your book is evidence. Some of the changes are driven by some very practical economic realities. In order to charge a premium for design services, there has to be some concrete evidence of value created—“This package did this for this brand”; “This store design increased sales”—or the perception of value—“This building or home resulted in this measurable result.” Once you start to take measurements, the design profession is no longer a strictly creative process but one that has accountability.

UNDERHILL INTERVIEW

Do you believe that being answerable to your clients will necessarily result in the best solutions for the community?

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If the only thing that you designed is what someone asked you to do, then why did they need you in the first place? Clients often don’t know what to ask for and therefore you have to be proactive in understanding their operating culture. That often involves some sort of discovery process at the front end. One of the historic problems for the design professions is whether that process happens in-house or is farmed out. If it happens in-house, it is a subservant factor to the design process itself. I think it’s better to have someone who could, if need be, turn around and yell at you for turning in preliminary design concepts that have no relationship to the fact-finding mission undertaken on the front end of the project.

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The design profession has to be a champion of the process of getting to design. Often our work with design firms is making sure we have everybody on the bus; then it’s the designer’s job to drive the bus. But getting everybody on board first is really critical.

How much evidence is enough and is it hard or transitory? Think about what made a good house in 1985 and what made one in 2009. Some things are the same and some are different. Yes there are energy management issues and advances in building technologies, but we as people have changed, too. According to the most recent census data, less than 24 percent of American households have a mother and father and dependent children living under the same roof. Yet how much of new home construction is still about one master bedroom and a bunch of smaller ones? Where is the home gym and home office? Ever tried to keep a McMansion clean?

What tools and methods do you use to create or capture evidence? We capture data in a variety of ways. For our observational data, our primary technology is humans and paper. We supplement this with video recordings using a combination of HDD and 8mm cameras. Video is analyzed by humans using video splitters to view multiple points simultaneously. For survey data, we use PDAs, mostly Palm E2 and Palm CENTRO, with wireless capabilities to transmit data. Wireless transition allows us to monitor the progress of the interviewers every few hours. The palms are used mostly for surveys but have also been used for observational data when the capture points are linear.

Maps are done using a combination of software packages from basic PowerPoint shapes, to Google SketchUp and Adobe Photoshop. Much of the mapping is done manually. Again, this is due to the unique nature of every map and the data points that are illustrated by the maps. In some cases macros are used to facilitate the process. We use technology selectively. There is so much technology out there that could make our data collection more efficient but with every piece of technology you give up something. Much of our work depends on seeing things that are not always obvious and much of this seeing needs to be done by a pair of eyes and not a CPU.

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Data is analyzed using a combination of SPSS, SPSS Desktop Reporter, MS Access, and MS Excel. While many deliverables are similar, each project requires a manual run of the data to account for the differences in each project. We use a proprietary global database to compare data points across different categories as well as countries.

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Figure 3.19 Entrance pathway mapping research reveals shoppers’ immediate directional tendencies upon entering the store. Percentages do not reflect the shopping of specific fixtures. Fixtures are included for illustration purposes only.

Figure 3.20 This store coverage map illustrates the percentage of shoppers moving from the front to the rear of the store. The stores are divided consistently into four roughly equivalent sections for this measurement.

UNDERHILL INTERVIEW

A simple example of this is something that we do routinely—a store entrance count. This is basically recording how many people enter the store and capturing some demographic information like age and gender.

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There is facial recognition software that we can use to count the number of people entering while simultaneously recording the age and gender of each person. Once you set up your parameters, the software analyzes the video and gives you your data. However, the fact that you have to set up these parameters limits what the computer sees. In contrast, when we use humans to capture these numbers, they don’t only see the parameters but the surrounding area. So in a simple entrance count, the human data capture can also note that the entrance is too narrow for two carts, or that

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Figure 3.21 First destination documents the percent that various settings are the first stop of entering shoppers.

In the world of store design, there has been an intrusion of some technologies where the fascination is with the technology, rather than the human intelligence to turn it into some sort of useful form. One of the important qualifications of a new tool is how often you can use it and still add value. How often can I go back and redo a process—and redo—and learn something new that I can apply? For example, if I have a floor plan with all the tracks of where people are walking, is it something I want every two weeks or every two years? Something might be interesting once but not as an ongoing process. As a toolmaker looking at the world of design, I often look at the least amount of technology and how little I need to get my processing engine working.

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traffic jams are common at the entrance, or that customers peek into the store but do not enter. (Maybe the Cashwrap line is visible from the entrance and it is too long.) A computer can never tell you that because you can’t anticipate what you might see; thus you can’t set the parameter. When we purchase technology, we look not only on how productive it makes us, but what we would lose and gain if we used it.

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Does evidence enrich or inhibit design creativity? As a culture that consumes culture, we can no longer tolerate a one-to-one relationship between an artist and their work. That’s an act of masturbation. It is exciting that there is a generation of designers out there now that recognizes that there are collaborative processes which are the focal point of getting desires and information out and into the design process…and that making it happen is really exciting. If we look at what’s exciting in our culture, such as making a movie, those things are not solo acts. Many of us in the twentieth century got comfortable thinking sitting down. As a testing agent for prototypes, we see the best of ideas fail for the stupidest of reasons because no one went out on the floor to take a look. If I look across my office in New York, my head salesman has an MFA for the theater; my COO has degrees in playwriting and psychology. Another person came out of elementary education. There are some business folks. There’s no profession out there that actually trains people to do what this firm does. I look for smart, willing to travel, curious people and, most importantly, people with a sense of Zen…selflessness. Only when you turn on that Zen moment do you become the conduit to the information that’s being presented to you.

What would an educational program look like to get the kind of people we need to be successful? In 1977, as an adjunct instructor in a well-known New York City design school, I put together a course on the intellectual literature on design and no one signed up. If that course were to be offered today, lots of people would sign up. That’s a statement about where this education process started and where it’s gone. A continuing sense of evolution and introspection is one that keeps the profession vital. I like the young architects I meet now much better than the architects I met 30 years ago. The process of looking at people and their patterns of movement that started with William Whyte has had a popular impact. When William Whyte wrote The Social Life of Small Urban Spaces, its print run was probably less than 5,000 copies. Now, the number of people who pick up my books at an airport and read them is remarkable. There is a broad interest in design issues and a perception that design can be a healing science or process. Thanks for talking to me.

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ZEISEL INTERVIEW

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ZEISEL INTERVIEW John Zeisel Sometimes there’s no time, money, nor client desire to go out and collect new data but you always should think about whatever data there is. Why would you not?

RESEARCH BACKGROUND

Dr. Zeisel received his PhD in sociology from Columbia University and a Loeb Fellowship from Harvard University, Graduate School of Design. He is author of Inquiry by Design, a standard reference in many architecture, design, and social science courses. Dr. Zeisel chairs the advisory board of the International Academy of Design and Health and chaired the scientific committee of the Third World Congress on Design and Health. Dr. Zeisel has taught at Harvard University’s Graduate School of Design, Yale University, and McGill University. In 1994 he served as the Cass Gilbert Visiting Professor in the Department of Architecture at the University of Minnesota. Since 2005, he has been Visiting Professor, School of the Built Environment, Salford University, in the United Kingdom. Founder of Hearthstone Alzheimer Care, Dr. Zeisel has received many awards and citations for programming and postoccupancy evaluation of health-care facilities, senior housing, family housing, offices, and schools.

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Figure 3.22 John Zeisel, PhD

Dr. Zeisel is president of Hearthstone Alzheimer Care, a company that manages assisted living treatment residences for people with Alzheimer’s Disease and related dementias. He received the 1998 EDRA/Places research award for examining the effects of the physical environment on health and well-being of people with Alzheimer’s Disease. The same year he was honored with the Environmental Design Research Association’s Career Award for his contributions to design research. In 2008, the American Society of Interior Designers (ASID) selected Dr. Zeisel to receive its Educator of Distinction Award for his book Inquiry by Design and his work linking design for Alzheimer’s with health outcomes.

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How do you use evidence in your work related to Alzheimer’s? Physical environments specially designed to reinforce the remaining abilities of people living with Alzheimer’s can effectively constitute a treatment for people living with Alzheimer’s. Treatment also includes modifying communication to respond to the reality of the person living with Alzheimer’s and pharmaceuticals that deal with the person’s health problems. The first step in evidence-based design for this group is to thoroughly understand what contextual correlates there are that relate to symptoms like anxiety, agitation, and even aggression and then determining what contextual changes need to be made to address those symptoms. Research over a number of years indicates that reduced symptoms like these, measured with the same outcome measurement tools as drug efficacy studies, are associated with specific characteristics of the physical environment. Natural mapping and memory cues have been found to be fundamental to environmental design that is correlated with reduced symptoms of Alzheimer’s Disease as well as improved function and independence.

ZEISEL INTERVIEW

 Figure 3.23 Physical environments with residential character help prompt more appropriate social behaviors for the setting.

 Figure 3.24 Research has found that people with Alzheimer’s have less anxiety and aggression in bedroom settings that provide for privacy and personalization.

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“Natural mapping” is a concept developed by Norman in 1988 to describe the intuitive ease of use in product design. It can also be used to describe environments that are self-evident, e.g., negotiable by a person without instructions. Naturally mapped gardens and residential settings, with visible destinations and place identifiers, help people with Alzheimer’s find their way, even though their cognitive mapping capabilities may have been compromised by brain dysfunction. Conversely, natural mapping promotes “walking” and avoids the symptom of “wandering”—a behavior that occurs frequently in places with layouts that are not self-evident. People living with Alzheimer’s often are unable to retrieve memories present in their brains due to hippocampus and related brain damage. That’s where “memory cues” can play a role. Memory jogging physical environments, such as the person’s own furniture, mementoes, and photos of reminiscent places or people in their lives, can serve this purpose.

 Figure 3.26 Camouflaging exits by, for example, using less visible electronic locks, is one design method linked by research with alleviating depression for people living with Alzheimer’s.

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 Figure 3.25 Healing gardens should be designed so that people can intuitively find their way around (i.e., “natural mapping”) despite a loss of cognitive ability due to brain dysfunction.

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Natural mapping and memory jogging design elements promote behaviors appropriate to specific social settings. There are numerous examples that illustrate how design can help people with Alzheimer’s live healthier, happier, and more productive lives. For example, privacy, personalization, and a sensory environment that people with Alzheimer’s can understand are correlated in our research to fewer psychotic symptoms.

Do you think that evidence inhibits or enhances creativity? Creativity shows itself best in the face of constraints, so the more evidence available, the greater the opportunity for design creativity. The more evidence available that points in a certain design direction, the more creative a designer can be because there are more tools to work with plus a framework of added information about the project’s context. Evidence enhances creativity. There’s no way it can reduce it because creativity can’t be reduced.

How rigorous does evidence have to be to be useful?

ZEISEL INTERVIEW

The higher the quality of the evidence, the more useful it is. A major problem that evidence-based designers face, however, is the confusion between research rigor and research quality. Laboratory experiments, exploratory observation, interview studies, and even an interview with a subject about how she or he feels in a given setting can yield high-quality research findings. All these different forms of research can be applied equally rigorously. Rigor and quality are independent of the datagathering approach.

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Evidence generated using participant observation as the research design or evidence from a random controlled experiment can both be of high quality and rigorous. One of the mistakes people make in judging research quality and rigor is that they equate experimental design—the research approach employed in pharmaceutical trials—with being more rigorous and of higher quality, and participant observation or anthropological methodologies as being less rigorous and of lower quality. This way of thinking is totally outside good research theory and practice. Quality of research has to do with the appropriate use of methods for the topic of study. So, if you want to find out how mice go through mazes, do an experimental study in a laboratory with mice. But if you want to find out what process people use to find their way around a hospital—way finding—an experimental study might be totally inappropriate. An observational study, possibly with interventions such as changing the colors and signs, might be more appropriate. Quality and

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rigor have to do with how carefully you apply a methodology; they are not inherent to any one methodology. Any information is better than no information at all. A little bit or a lot of data turned into relevant design information can both be extremely helpful in making good design decisions—as long as they are both applicable to the design problem. A study carried out with five subjects may be less suitable for generalization than one with 1,000 people; but the one carried out with 1,000 people may be less rigorous and of lower quality than the smaller study. In making evidence-based decisions it is essential not to overestimate the value of the evidence at hand; nor to underestimate it.

How do you take a single piece of segmented information and know how it should affect design, which by its nature is influenced by a multitude of environmental conditions? Investigators employ experimental research design to isolate causes. Participant and behavioral observation help investigators understand the interrelated parts of more global phenomena. Certain way finding research carried out in a hospital—specific research in a specific place—might well be applicable to all way finding design. Other specific research studies may only be applicable to that place. Findings can have broad applicability or not—depending on many factors. Skilled evidence-based designers know how to assess evidence, decide how best to use it, and apply it carefully. The skill of these designers lies in putting the evidence in context, together with other information, and using judgment to give it weight and priority in decisions. The same problem exists in medicine. Doctors usually have to make decisions in complex human situations.

The designer decides worth. Evidence-based design research, as opposed to other forms of design research such as postoccupancy evaluation, rests in the hands of the designer or design team. If a designer believes he or she needs information about something, several things can happen. If money is tight, he or she can employ a literature and database search. With resources, the designer might decide to carry out original research. The designer has to judge available resources and how important having the data might be to the design. Evidence-based design puts the responsibil-

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ZEISEL INTERVIEW

Is it worth it to a designer to go through an evidence-based process to develop that one piece of information if that bit needs to be combined with many others in context, as you describe?

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ity into the hands of design decision-makers to determine what’s important. That’s another form of creativity. High-quality, rigorous data informs opinion, attitudes, and decisions. I believe we should recommend to designers to use the best available data whenever possible to make a decision. Data can influence but it can never determine a decision. The more we know about the context of a design project and how it interrelates with the people, the space, and the cost, the more we are likely to make better decisions. I wouldn’t begin any design project by collecting evidence. I’d begin with context— what people say they want and what resources are available—to know what evidence to use. I don’t think you ever don’t look at the best available evidence.

Do you always want to go out and collect new data? Sometimes there’s no time, money, or client desire to go out and collect new data but designers always need to think about whatever data there are. Why would you not? When making actual decisions, you put whatever resources you have into gathering relevant evidence; that’s the best you can do. In my book Inquiry by Design, I write about design achieving “the domain of acceptable responses.” We’re not looking for the optimum environment. We can’t. We’re looking for that environment that does the job we want it to do as well as possible. You do the best you can as a designer with the resources you have. That’s the best you can do.

ZEISEL INTERVIEW

Clients assume we know how to build but they’re interested in knowing what to build. Do you believe interdisciplinary teams can help us determine what to build?

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I agree that clients believe designers know what and how to build what is needed. I’ve always assumed that the answers to these questions can be best determined by a team that includes experts with a background in the social sciences applied to design. More recently, I’ve come to realize that it’s also important to have a team member familiar with the neurosciences and design. We have to broaden the definition of the term “interdisciplinary” and raise our expectations of interdisciplinary design team members. Each scientist on such a team has to understand the design process, as well as their own discipline. Interdisciplinary design teams need to develop a common image of the building they’re working toward as a building; or the science just becomes window dressing that goes away in value engineering.

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You’re very explicit about the research team understanding the design process; how important is it for architects to understand the other people’s framework? If they want to have a dynamic team, the architect must also understand the scientists’ framework. With mutual knowledge, it’s like people playing different instruments in an orchestra; they tune to each other.

What has to happen to the practice model or educational curriculum to foster innovation in the future?

ZEISEL INTERVIEW

One barrier to moving architectural education and practice toward employing more evidence is that designers and their clients still act and relate to each other within a master builder model. There is neither a tradition in architecture of using referential knowledge nor one in education of knowing how to use evidence. There need to be core courses on research methodologies and at least one required course on research and evidence for those designers who eventually want to employ evidence-based design decisions in their practice. Even if only 5 percent of designers move in this direction, the profession must recognize as a new specialty, not design that is only visually striking, but design that works for people, with an understanding that resulting buildings will be judged based on their usefulness and quality of the design shown in postoccupancy evaluation.

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AHRENTZEN INTERVIEW Sherry Ahrentzen For this [evidence-based design practice] to happen on a large scale, the culture of architecture has to change, so the profession sees itself not just as a problem-solving culture—which it is and why we all love it—but also as a problem-defining, knowledge-seeking culture.

RESEARCH BACKGROUND

AHRENTZEN INTERVIEW

Figure 3.27 Sherry Ahrentzen, PhD

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Dr. Ahrentzen is Associate Director for Research, Policy, and Strategic Initiatives at the Stardust Center for Affordable Homes and the Family, of Arizona State University (ASU). Her efforts are directed toward producing and fostering research that acts as a catalyst for debate, action, advocacy, and innovation. The Center’s research products give constituents reliable information and new insights to inform development actions and policy decisions. For the last 25 years, Dr. Ahrentzen’s research has focused on new forms of housing to better accommodate the social and economic diversity of U.S. households and families. Her work has been published extensively in journals and magazines, such as Journal of Architectural and Planning Research, Harvard Design Magazine, Builder, Journal of Social Issues, and Progressive Architecture, and she has presented her work at the annual conferences of the American Institute of Architects, the Environmental Design Research Association, Association of Collegiate Colleges of Architecture, as well as at a number of universities and professional organizations. With Karen A. Franck, she edited the book New Households, New Housing. She has over 60 published articles, chapters, and reports, and has received more than 20 research and instructional grants from various agencies. Her research has been funded by the American Institute of Architects (AIA), National Center for Real Estate Research, Urban Land Institute, Home Depot Foundation, Local Initiatives Support Corporation, U.S. Department of Housing and Urban Development, the National Science Foundation, National Endowment for the Arts, Fannie Mae Foundation, Association of Colle-

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giate Schools of Architecture, Robert Woods Johnson Foundation, and Graham Foundation for the Study of the Arts. Professor Ahrentzen has consulted overseas, in China and Indonesia. She has also served as a member of the board of directors of the Environmental Design Research Association, of the Advisory Council for the Initiative for Architectural Research, and of the Advisory Group for the Housing and Custom Residential Knowledge Community of the AIA. She is a past associate editor for book reviews for the Journal of Architectural and Planning Research. In addition to her research and work as a consultant to architects, designers, and planners, Dr. Ahrentzen is currently Research Professor at ASU, College of Design; and from 1983 to 2003 was a professor at the University of Wisconsin-Milwaukee, Department of Architecture. In 2009, she received the Career Award from the Environmental Design Research Association.

What kind of evidence do you use in your work? I’m often in the role of developing research studies, providing the evidence and interpreting what the evidence could mean. Those studies may be directed toward a task at hand, if it is action research developed for a specific project, or they may have a more generalized direction, advancing the state of knowledge of the particular arena of study.

In recent years, my work has been mostly focused on housing. It seems that in housing, compared with health-care, office, or school design, the idea of evidence-based practice isn’t considered or practiced in large measure. There has been good research on housing design and development from academics, private homebuilding industry, even some foundations and nonprofits. But, by and large, that research is not being sought by housing design professionals at the level it is happening in other industries and by other types of clients. Also, there is not the same scope of funding sources as there are for health-care design research. I think that’s because the client in housing is not an institutional one, for the most part.

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I work with architects and planners in thinking how to translate research into something appropriate for their use. When I teach, I work with students on how one might seek out evidence and how to actually apply that in design decision-making. It’s much easier in the classroom than in the real world, where you can have all the evidence in the world but also the political and financial arenas to contend with. It is more complicated in design practice to figure out how to position the evidence so it actually can be considered and applied.

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When housing has a more therapeutic component as part of the living environments, e.g., senior housing, assisted living, and specialized housing for vulnerable populations, evidence-based design seems to operate well. There seems to be more funding and the designers are more receptive. But if it’s housing for modest- or lowincome people, even for mixed-income populations, not as much design research is being sought. There is of course structural and technical research. But, by and large, we have little evidence in knowing how housing design matters in the daily lives of residents. Architects and designers, for the most part, are basing their decisions on past practices and hunches, until someone complains or threatens a liability suit.

Given the challenges you cite, can we advance evidence-based design for housing? Much of what we’re doing at the Stardust Center is action-oriented research, where we’re working with a specific group, for a specific development. We conduct design charrettes, survey and interview residents, do site observations and walking audits, collect environmental and asset data of the site and surroundings—all evidence that’s specific to that population of residents. That seems to be something we can do well. But more generalizable research that contributes to a body of knowledge that goes beyond being place- or site-specific evidence, that’s where I’m more frustrated. But I’m not giving up!

What are the questions/key issues you address through research?

AHRENTZEN INTERVIEW

My research looks through the lens of human users and their experiences. But that perspective is coupled with other viewpoints. Financial is also a key research area of housing. Energy has its physical environmental focus, but energy in the home is also a human comfort issue.

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Good residential and housing architects strive toward quality-of-life issues like privacy, social stimulation, dignity, socializing, and neighboring. Many would like research that helps them know the extent to which the needs of their specific population might differ from those of more conventional clients. For example, I am currently researching housing for adults with autism. Is environmental stimulation, such as daylighting, going to be different for people with autism than it is for a more typical population of residents? What about privacy, socializing, or other quality-of-life issues for an autistic person? The architect wants to know: “Is the most appropriate design the same or different from one I’d conventionally use for the typical population I generally design for?”

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Are those human performance issues measurable? I don’t think architects think of them as performance issues, as opposed to more generalized quality-of-life concerns. Measurement may be more likely considered when it reduces costs, for example, when the design can reduce care provider needs in supportive housing.

Are you saying that evidence isn’t transferable from one setting to another? It can be transferable. For example, there is research from school settings about environmental stimulation for people with autism. You can think about that school context and decide how the evidence may be applied to other settings, sometimes with qualifications or conditions. In this case, the age of school students in the research has to be assessed with the age of the people in a home, for example. Or how the social stimulation at school may be substantially different from that in one’s home.

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It irks me when architects misapply or misinterpret performance measures. I think conceptual use of research is extremely valuable but sometimes the context in which it occurs is not understood well enough to determine when it can be generalized to different people or in different situations. Instead the research is applied as a design principle across-the-board but the design is erroneously said to be substantiated “because research shows that….” I’ll give you an example. Many architects may talk about their design reflecting “eyes on the street,” a concept derived from the research of Jane Jacobs, Oscar Newman, and others—when a street is lined with buildings whose windows look out onto the public street. Jacobs talked about the residents looking out their windows and knowing if there was someone lingering on the block who shouldn’t be, and the like. It is evocative, and made sense for the dense urban fabric that Jane Jacobs was talking about, where people in their homes and shops would want to look out onto the street because things were happening out there, people were moving about, there was something interesting to look at, and the like. But many architects translate that term into a completely different context, like a suburban subdivision with wide streets and no one on the street anyway so there is no reason to look out the window. Or from rooms like the living room in the front of the home which have become dead zones because the families are in the back where the kitchen is and where things are happening. “Eyes on the street” sounds like a good design concept for enhancing safety as a general quality-of-life concept. But it isn’t applicable as “research-informed” or “evidence-based” without considering whether the context of the research is applicable to the context of the setting or situation being designed for.

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If you want to be an evidence-based designer and you want to make a difference, you have to consider the relevancy of the research context as well as the research findings, and how that corresponds to the setting, people, and context you are designing for.

With institutional clients and receptive architects, is there willingness to build in metrics? Sometimes there’s interest in it, if they think it’s the first of many similar projects. There’s not a lot of interest in developing metrics for one project. Senior housing— especially assisted housing or housing for people with dementia—there is concern about performance metrics there. I’m working now with a public housing authority and they’re very interested in metrics because they see it as something applicable to other projects. Interestingly, I have been approached in the last year by two architecture firms who have spent years designing affordable and mixed-income housing. They want to know if their “hunches” work. They want to know what aspects of their design mattered, how it mattered, and to whom it mattered. There is now a significant stock of affordable and mixed-income housing that has received professional recognition and awards. Many architects recognize, though, that those awards aren’t necessarily based on evidence. In many cases, the award jurors never even visited the site or received any evidence of its effectiveness other than the stray testimonial. But I see more and more of these architects who would like to know if their collective design hunches paid off in the ways they thought.

Do you think research enhances or inhibits creativity?

AHRENTZEN INTERVIEW

The most creative research act is a good research question. If you start with a mundane question, you just gather data. If you start instead with a question that is so well crafted that it is compelling, provocative, and explanatory, then you step in an entirely new direction.

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What professions use the environment-behavior approach and what makes them successful? Product designers use a lot of anthropological, ethnographical, and historical research, and they do a lot more testing, prototyping, and repeated testing over time than architects do. Product designers are absolutely more receptive to the fundamentals of science as a component—but not the only one—in the design process, and not just physical science but also the natural and social sciences. They see de-

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sign as an informed process of inquiry, often collectively driven, and one with its moments of creativity and aesthetics. Even product design students have that inclination but not architecture students as a group.

What methods do you use? Many of my doctoral students come from design disciplines, so mine is often their first research methods course. I stress there are different paradigms underlying research but all seek two “essential qualities”: crafting a good question and research integrity. How do we judge the latter? The integrity of the research method needs to be assessed in terms of the paradigm in which it is embedded. As a class, we make those assessments not from a single point of view but from the various epistemologies researchers are coming from. My students critique research integrity. “How do you control—or should you control—the researcher’s subjective view?” “To what extent can you claim representation to others beyond the sample that you’re looking at?” “What are the strengths and shortcomings of each technique?”

What changes in practice or education need to occur to advance the appropriate use of research in the design professions?

AHRENTZEN INTERVIEW

The culture of architecture, particularly in schools, needs to embrace itself not as a problem-solving culture but as a knowledge-seeking culture as well. When I look at Engineering, I see problem-solving but I also see engineers trying to understand the nature of what’s behind the problem and how to address that in a much more systematic way than a “hunch.” This approach needs to be reinforced in schools and through our awards. Until then research classes will be more idiosyncratic than integral to what architectural education is about and those who understand and embrace research will be a subculture— like some PhD students now—not a culture.

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Lessons Learned

PERHAPS THIS WILLINGNESS TO BE PRAGMATIC, TO FOCUS ON APPROACHES THAT CAN BE REASONABLY ACHIEVED IN REAL PROJECT APPLICATIONS CONTEXTS,

The work of the experts presented in this chapter and that of others illustrates the power of using social science methodologies and knowledge to advance the practice of informed design. How can the profession realize this potential? What is preventing a wider adoption of these tools and resources? Three lessons learned emerge prominently from the discussions with our thought leaders.

ABLY ENGAGE AN EVIDENCE-BASED APPROACH. This in no way precludes systematic, rigorous methodologies. In fact, our experts’ work illustrates the value of consistent approaches. It also seeks to build the body of knowledge over time, when possible, although that isn’t its primary raison d’être.

Pragmatism

Standards

Bromberg talks about the high costs and time demanded by controlled experimental research, such as the work done with the Mayo Clinic. Despite the value of this type of in-depth research, it’s frequently not possible given timelines and budgets for design projects. Therefore, a systematic and thoughtful but less detailed “scientific” approach is more the norm for her team’s applications-oriented research.

Our experts, each in his or her way, demonstrate the importance of understanding quality research methods. Ahrentzen, an educator, is directly engaged in raising awareness of various types of research and the importance of rigor starting with framing the research question. Her students are being taught how methods can influence the outcome and the essential importance of the research context in determining which results can be generalized to which application situations.

Laing and Craig acknowledge the vast amount of data that DEGW has accumulated in systematic ways that would allow it to be coalesced to advance the body of knowledge. However, there is also a project-driven nature of much of what they do… the focus on information, e.g., company business intentions and leader perceptions, which will resonate with corporate decision-makers that might not always be transferable to other organizations. Somewhat similar to Bromberg’s work, this application orientation serves the project purpose and has the rigor needed to contribute to the body of knowledge but the driving force is answering the question at hand. Zeisel advocates enriching projects with information in large and small engagements. The sources may be secondary or primary research and the project decisions will be served by some added intelligence. Again, the principle is to seek the best available information.

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IS A WAY THE TYPICAL DESIGN PRACTICE CAN REASON-

Powell’s exploration of many tools and assessment of the usefulness of each for linking business outcome to environment is another example of critical thinking in process development. The projects that will be developed using the new planning model will benefit from this higher level of rigor. Similarly, Underhill’s highly systematic methods, well-suited to their purpose, attest to the potential to achieve highly reliable predictors of performance outcome. Regardless of specific approach, the common theme is to be aware that discipline is required in good research practice, even with methods as seemingly “soft” as interviewing and observation. This runs from the very beginning when the work of others is critically reviewed for applicability to the project context, through measurement and data quality review.

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Practitioners can improve the reliability of their own research efforts and can distinguish between any available information and appropriate information for their project.

claims by proponents of evidence-based medicine that clinician judgment is a necessary part of the process because it alone bridges between data and patient context.

THERE IS A PREVALENT ABSENCE OF KNOWLEDGE

Our experts see only greater creativity through informed design—a more inventive problem definition process, a more transformative vision of the projects’ potential to enhance the human experience, and physical solutions that are richer because they are built upon deep appreciation of the whole realm of experiencing environments.

ABOUT RESEARCH METHODS AMONG DESIGN PROFESSIONALS. AS A RESULT, THE RESEARCH IS SOMETIMES UNDERVALUED AND THEREBY NOT EVEN SOUGHT. AT OTHER TIMES, EVIDENCE IS VIEWED AS A PANACEA. WHEN THIS IS THE CASE, THE RESULT IS A DESPERATE SEARCH FOR IMMEDIATE AND ABSOLUTE ANSWERS THAT DO NOT EXIST; OVERGENERALIZATION (APPLICATION TO THE WRONG PROJECT CIRCUMSTANCES); AND ULTIMATELY DISAPPOINTMENT IN THE RESULTS AND EROSION OF CREDIBILITY. BETTER UNDERSTANDING WHAT CONTRIBUTES TO RESEARCH QUALITY WOULD HELP DESIGN PRACTITIONER’S DEVELOP HIGHER VALUE INFORMATION AND KNOW WHEN TO APPLY IT.

Creativity Our thought leaders (and this book’s authors!) passionately agree that one myth needs to be debunked. That is the rather prevalent belief that an evidence-based approach limits creativity. KNOWLEDGE FREES THE DESIGNER FROM THE STRESS OF HAVING TO INVENT WITHOUT GENUINE INSPIRATION.

IT STIMULATES WITH COMPELLING AND PROVOCATIVE HYPOTHESES ABOUT THE POWER OF THE DESIGN TO CHANGE OUTCOME. IT ENGAGES DECISION-MAKERS AND GIVES THEM THE BACKUP THEY NEED TO TRY NEW AND MORE INVENTIVE APPROACHES. IT PROVIDES INSIGHTS TO BREAK THROUGH CONSTRAINTS.

Nevertheless, many designers do not agree. They fear that an evidence-based approach will force them toward formulaic solutions; that it will prescribe rather than inspire, overcomplicate rather than enrich. A similar debate continues in medicine despite that

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Moving Forward The challenge is therefore clearly laid out. We need a mix of pragmatism and scientific rigor. The work must serve the projects’ needs and, when possible, contribute to the larger body of knowledge. And the design professions need to develop an appreciation for the value of social science methods and knowledge to the extent creativity is served and outcomes are improved. A starting point is greater collaboration between social scientists and designers. Multi-institutional research is one opportunity. Cross-disciplinary teams are another; and these may involve people within design firms, consultants and clients themselves. Increasingly, the mix of skills can be found in various places. Our thought leaders also agree that changes in curricula would help greatly. Often design schools focus on aesthetic and perhaps technical competencies to the exclusion of human performance outcome considerations. PhD programs sometimes are the first introduction to design students, albeit a self-selected subgroup of designers. This can be changed but will the impetus need to come from the profession, clients, academics, or the students themselves?

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What would future practice look like if current innovations were truly embraced and expanded? To begin: Social science methods would be used in the appropriate way and in the appropriate context to explore needs and discover the better ways to satisfy human performance demands.

To do more than either can do alone: Social scientists and designers must work collaboratively toward common ends.

Then: Human behavioral research would be understood and applied to design solutions.

HAVIORS .

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A ND WHEN WE SUCCEED: METHODS, KNOWLEDGE, AND EXPERTISE TOGETHER WILL ENABLE DESIGNERS TO CREATE ENVIRONMENTS THAT TRANSFORM BE -

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4 The Natural and Physical Sciences

The relationship between science and design has deep roots. Vitruvius defined “architecture” as “firmitas, utilitas and venusta”; often referred to as “firmness, commodity, and delight.” “Firmness,” the tectonics of architecture including structural, mechanical, electrical, and civil engineering and all facets of construction, is based on scientific principles grounded physics, chemistry, biology, and earth science research.

Background and Context Architects, engineers, and contractors depend upon the advances in natural and physical science to inform contemporary design challenges, such as building systems performance, kinetic facade systems, the composition of new materials, structural seismic design, the structural and mechanical design of super tall structures, lighting, acoustics, climate response, energy management, and many aspects of sustainability. The architect’s dependence on these sciences is deeply rooted in history and defines much of the essence of design.

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Overview Generally, the term “natural science” refers to biology and the earth sciences, while the “physical sciences” are astronomy, physics, and chemistry. This distinction between the natural and physical sciences is significant, relative to architecture. Both of these broad categories of science have many specialized areas of study, among them botany, zoology, medicine, neuroscience, geology, geophysics, hydrology, astrophysics, geophysics, physical chemistry, and biophysics; as well as many cross-disciplinary endeavors, all focused on the study of the universe and the rules or laws of natural origin. WITHIN THESE SCIENTIFIC DISCIPLINES, RESEARCH IN BOTH THE NATURAL AND PHYSICAL SCIENCES DEALS WITH THE VERY BASIS OF ELEMENTS—MATTER, MOLECULE, ATOMIC OR CELL STRUCTURE. AT THIS BASIC LEVEL, RESEARCH—COUPLED WITH THE LOGIC AND MATHEMATICS—USES A VERY STRONG FOUNDATION OF METRICS AGAINST WHICH OUTCOMES ARE EVALUATED.

The “hard sciences,” especially physics and chemistry, rely heavily on the use of objective data, experimental and controlled processes, instrumentation, quantitative measurement, and repeatable methodologies. Recent technological advances in computation enable the manipulation of massive amounts of numerical data, reinforcing the potential of the hard sciences to produce highly compelling and credible research outcomes Even so, the scientific community continually scrutinizes research results for validity and reliability, knowing that no scientific process guarantees absolute proof or results that can be generalized to all situations.

of structural interaction (forces, weight, mass, momentum, gravity, motion, energy transfer, principles of electricity and its source and properties); (2) the chemistry of material composition and material reaction; (3) the astronomy of the sun and solar system; (4) the biology and ecology of the land on which we build; and (5) the earth sciences including soil science, seismology, atmospheric pressure and winds, evaporation, condensation and humidity, hydrology, and precipitation. PHYSICAL SCIENCE RESEARCH IS INTEGRALLY LINKED TO UNDERSTANDING “BUILDING PERFORMANCE.” Not surprisingly, the greatest innovation and advances in the architectural profession have traditionally been those having to do with building performance; using objective criteria, standard protocols, and metrics which are quantitatively definable. BY CONTRAST, THE NATURAL SCIENCES PROVIDE INSIGHT FROM A BIOLOGICAL (WHOLE ORGANISM) PERSPECTIVE AND INFORM “HUMAN PERFORMANCE” IN BOTH QUALITATIVE AND QUANTITATIVE MEASURES. THESE QUALITATIVE MEASURES MAY BE MORE SUBJECTIVE BUT ARE CONSIDERED NO LESS VALID THAN THE QUANTITATIVE, OBJECTIVE MEASURES.

The Influence of Natural and Physical Science on Architecture

Specific examples of the influence of physical sciences on architecture can be seen in the work of institutes, product manufacturers, governmental testing agencies, and private testing institutions, most of which utilize instrumentation to simulate, test, and analyze issues such as natural and artificial lighting, thermal comfort; air flow; noise levels; seismic motion”; and strength of materials and product and building systems standards for fire, toxicity, and life safety performance. Historically, much of this research is oriented toward understanding the performance of building systems and materials.

The natural and physical sciences have specifically influenced architecture in terms of (1) the physics

Recently, the use of computer technology for visualization, simulation, cost and energy modeling, com-

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T H E N AT U R A L A N D P H YS I C A L S C I E N C E S

putation and integration of information has significantly advanced as a means of providing evidence in the form of building performance data for use in the design process.

Neuroscience In Chapter 1 Figure 1.1, we spoke about the importance of a future where design could positively influence human well-being and effectiveness, in addition to our current focus on the science of building performance. In this new world, we would better anticipate how people would respond to specific environmental stimuli such as lighting, spatial form, and sound; and how human behavior might be affected by environmental attributes. NEUROSCIENCE HOLDS THE KEY TO THAT UNDERSTANDING. Today we have the social sciences to understand human behaviors. Tomorrow, we will look to neuroscience to predict physiological responses to environmental stimuli and use that knowledge to design places that stimulate desired responses FOR THE NEAR FUTURE, PHYSIOLOGICAL RESEARCH RELATED TO ARCHITECTURE WILL PROBABLY BE UNDERTAKEN IN COLLABORATION WITH SCIENTISTS OR IN AN ACADEMIC SETTING, RATHER THAN WITHIN A DESIGN FIRM. Just as many firms specializing in the design of health-care facilities currently employ individuals trained as nurses, physicians, and health-care administrators, in the near term neuroscientists will become members of design teams. We’re already seeing a new generation of individuals dually educated as architects and neuroscientists entering the profession.

WHAT IS NEUROSCIENCE AND WHAT MIGHT NEUROSCIENTISTS AND ARCHITECTS HAVE AS COMMON INTERESTS? Neuroscience is rooted in the biological sciences and has recently evolved dramatically due to revolutions in molecular biology, electrophysiology, and computa-

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tional science. The discipline of neuroscience is often referred to as a study of the brain: more precisely, neurobiology is the study of the biology of the nervous system, and neuroscience is the science of mental functions that form the foundation of the constituent neural circuitries. NEUROBIOLOGISTS ARE WORKING TO GAIN A GREATER UNDERSTANDING OF HOW NETWORKS OF NEURONS PRODUCE INTELLECTUAL BEHAVIOR, COGNITION, EMOTION, AND PHYSIOLOGICAL RESPONSES. IN THE CONTEXT OF ARCHITECTURE, THAT UNDERSTANDING IS RELATED TO THE RESPONSE OF EXPERIENCES AND ENVIRONMENTAL STIMULI CAUSED BY LIGHT, ACOUSTICS, SCALE, TEXTURE, AND OTHER DESIGN ELEMENTS IN THE KIT OF PARTS USED TO CREATE PLACES.

Three significant aspects of neuroscience research make it possible to comprehend how architecture and physiology interact. 1. Anatomy of the brain: A long-standing understanding of the anatomy and function of the brain, the senses that relate to architectural stimuli such as vision, hearing, movement, and cognitive functions 2. Imaging technologies: Recent imaging technologies that permit an ability to see which portions of the brain are “firing.” 3. Neuroplasticity: Current discoveries about neuroplasticity, which examine the cause and effect of cell regeneration; their responses to environmental stimuli—such as light, noise, and vision—are of interest to both neuroscientists and architects. Anatomy of the Brain and its Functions Mapping the Mind, by Rita Carter, provides one of the best foundations for nonscientists in understanding the brain, mind, and consciousness. Carter reminds us of the relationship between the anatomy of the brain and

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particles in the body tissue by magnetism and then bombarding them with radio waves.

its functions. These functions relate to the same senses that concern architects: 

Functional MRI (fMRI): Neuronal firing is fueled by glucose and oxygen, which are carried in blood. When an area of the brain is fired up, these substances flow toward it and the fMRI shows the areas where there is most oxygen.

The temporal lobes: responsible for sound, speech, comprehension, and some memory



Positron Emission Topography (PET): Measures fuel intake

The frontal lobe: responsible for integrative functions, thinking, conceptualizing, planning, and conscious appreciation of emotion.



Near-infra-red Spectroscopy (NIRS) : Measures fuel being used at any moment by the brain



Electroencephalography (EEG): Measures brain waves—the electrical patterns created by the rhythmic oscillations of neurons



Magnetoencephalography (MEG): Similar to EEG



The occipital lobe: critical to providing visual processing



The parietal lobe: critical to movement, orientation, calculation and certain types of recognition

 

Carter emphasizes the complexity of the brain’s two hemispheres covered by a cerebral cortex; the “little brain” known as the cerebellum; the 100 billion neurons with its dendrites, axons, and synapses; and the interior corpus callosum, which shunts information between the left and right hemispheres.

ALL OF THESE TECHNOLOGIES PROVIDE IMAGES AND COMPUTATIONS OF WHAT IS HAPPENING IN THE BRAIN WHEN EXPOSED TO SPECIFIC STIMULI, IDENTIFYING WHAT

Carter also provides an understanding of the limbic system, which includes the:

PORTIONS OF THE BRAIN ARE RESPONDING AND MEA-



Neuroplasticity

Thalmus: A relay station directing incoming information to correct parts of the brain for processing



Hypothalmus: Adjusts the body to keep it optimally adapted to the environment



Hippocampus: Responsible for long-term memory



Amygdala: Where fear is regulated and generated

Imaging Technologies While the individual parts of the brain have been well documented, a greater understanding of which portions of the brain “fire” in response to environmental stimuli—has been enabled by new scanning technology. These include: 

Magnetic Resonance Imaging (MRI): MRI, in combination with a software system called a computerized tomography, works by aligning atomic

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SURING THE EXTENT OF THAT EXCITEMENT.

Norman Doidge, in his book titled The Brain that Changes Itself, speaks about recent discoveries that show that THE BRAIN’S ANATOMY IS NOT FIXED BUT IN FACT CELLS ARE CONTINUALLY CHANGEABLE, MALLEABLE, AND CAN BE MODIFIED. This concept of “neuroplasticity” has opened an entire field of study to understand what kinds of stimuli cause these changes to occur and to find practical (medical) applications for regeneration of cells. Using the scanning technologies and computational science, a fascinating field of exploration is engaged in linking stimuli to response. Because many of the stimuli such as light, sound, smell, touch, vision, and perspective are of mutual interests to neuroscientists and architects, future collaborations between the disciplines present exciting opportunities.

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T H E N AT U R A L A N D P H YS I C A L S C I E N C E S

Current Examples of Research, Hypothesis, and Work in Process In her most recent book, Healing Spaces…the Science of Place and Well-Being, Dr. Esther Sternberg explores the relationship between neuroscience and architecture through seeing, sound and silence, touch and smell. She notes: “Thus we use vision, smell, and touch to gather information about our surroundings. Each sense detects individual features of what we perceive. Our brains then integrate these features in time and space to create a three-dimensional, richly colored, stereophonic, and scanned image that tells us where we are. The sense-pictures change constantly as the world alters around us at every moment of our lives. And in response, the brain continuously uploads the new information and incorporates it into constantly revised versions of our world.” With advances in the field of neuroscience, new disciplines such as neurolaw and neuroeconomics have evolved. Many architects credit John P. Eberhard, FAIA, with being the founder of another new discipline, neuroarchitecture. A researcher, architect, and educator, Eberhard is a serious student of neuroscience and describes its relationship to architecture in his books Architecture and the Brain (2007) and Brain Landscape (2008). In addition to his role as knowledge leader and father of this new discipline, John Eberhard is the founder of the Academy of Neuroscience for Architecture (ANFA) in San Diego. To encourage neuroarchitecture research, ANFA has brought together architects and environmental psychologists, such as John Zeisel, with neuroscientists, including Drs. Fred Gage and Tom Albright of the Salk Institute; Dr. Eduardo Macagno of the University of California, San Diego; Dr. Steve Henricksen of Western University of Health Service; and Dr. Esther Sternberg of NIH; and industry leaders, such as Joyce Bromberg of Steelcase, and educators, including Gil Cooke, Dean of the New School of Architecture in San Diego.

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Through these efforts, a new generation of professionals educated in joint architectural-neuroscience programs is being developed. ANFA continues to foster research opportunities and linkages between the two disciplines of neuroscience and architecture.

The Research Methodology of Natural and Physical Science The research methodologies, protocols, and (peer review) standards used in the natural and physical sciences are similar to the traditional ten steps discussed in the previous chapter on social science. Perhaps the primary differences from the social science in methodology are: 1. Greater dependency on controlled laboratory experiments; 2. Highly specific, defined, and focused experimentation; 3. Greater use of instrumentation; 4. Consistent use of quantitative metrics;; 5. Laboratory experiments scaled to smaller samplings in “controlled and blind” settings; 6. Consistent isolation and manipulation of individual variables; and 7. Consistent ability to replicate the experimental conditions. Aided by the nature of rigorous research in laboratory settings, much of the research related to architecture is focused on singular aspects of human response to environmental stimulus within a limited contextual circumstance. For instance, for the 2005 AIA Latrobe Fellowship by Chong Partners Architecture, the University of California, Berkeley, and Kaiser Permanente, undertook a study of the effect of a very specific controlled, and defined, lighting condition on heart rate variability as an indicator of stress under a specific contextual setting.

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Natural/Physical Scientific Research Opportunities, Best Applications, and Best Context

CURRENTLY, THE MOST PROLIFIC AREA OF INNOVATIVE AND APPLICABLE RESEARCH LINKING SCIENCE AND DESIGN IS THE EXPLORATION OF DESIGN STRATEGIES TO INCREASE ENVIRONMENTAL SUSTAINABILITY.

The physical sciences provide valuable insights into design approaches for enhanced building performance and new materials to address sustainable design challenges. However, critics complain that the research is limited in design application, since the method focuses on but one piece of the solution to a whole building system. (The hard sciences are known for their reductionist approaches to research and experimentation.) A single research finding alone can rarely accurately inform applied building design, which is influenced by a confluence of issues. For example, the use of a new material developed from chemistry is highly dependent upon the physics of its application to determine true utility. Nonetheless, natural and physical science experimentation is creating highly relevant evidence of relationships between individual design elements and performance outcomes in specific contexts.

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In contrast, today there is little substantive research in neuroscience to dependably link a specific environmental stimuli to a specific human response. But we have confidence it will come and prove itself to be exceptionally compelling. As a larger database of research is developed, neuroscience will provide credible evidence of human response to environmental stimuli within a specific context. The following interviews provide insight into how scientists and architects are utilizing knowledge gained from the natural and physical sciences to inform design. Their work falls into three categories: 1. The Physical Sciences: Higher Building Performance 2. The Physical Sciences: New Material and Design System Development 3. The Natural Sciences: Neuroscience

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Interviews of Experts and Case Studies KENNEDY INTERVIEW Sheila Kennedy, Architect

Figure 4.1 Sheila Kennedy

We launched our materials research unit MATx because we saw the potential to integrate new forms of infrastructure into materials, buildings, and cities. There are many available technologies and materials that would be very beneficial for use in practice, but there is relatively little understanding of how active materials perform and how they may be integrated in the components of architecture and the organizational structure of practice. We wanted to accelerate the implementation of energy-efficient digital technologies, such as photovoltaics, sensor and light-emitting diodes, in the building industry. We realized that we needed to develop a model of practice which would allow us to research, create, and develop the building products, technologies, and services that were necessary to realize the given needs of our projects. This has led us to become the interdisciplinary organization we are today.

Sheila Kennedy is a founding Principal in the Boston firm of Kennedy and Violich Architecture, Ltd. (KVA) and Design Director of its materials research unit MATx. Designated as one of Fast Company’s Masters of Design, Kennedy is described as an insightful and original thinker, who is “designing new ways of working, competing, learning, leading and innovating.” Kennedy’s work was featured in “Design and the Elastic Mind,” MOMA’s exhibition on breakthrough designs for new technologies and she is the first woman to hold the position of Professor of the Practice of Architecture at MIT. In 2000, Kennedy established MATx, a pioneering materials research unit at KVA to engage applied creative production across the fields of electronics, architecture, design, and material science. MATx explores

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RESEARCH BACKGROUND

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how design can leverage the formal, aesthetic, and technical properties of digital technologies and new materials to accelerate their entry into the building industry and meet the needs of different cultures around the world. MATx has developed designs and technology applications for Dupont, Siemens, Osram, Herman Miller, SaintGobain, The North Face, and the United States Department of Energy. The MATx Portable Light Project, a nonprofit global initiative to create energy-harvesting textiles in the developing world, has been recognized with a 2009 Congressional Award, a 2009 Energy Globe Award, and a 2008 Tech Museum Award for technology that benefits humanity. Kennedy’s research and work in architecture has been recognized by grants from the National Endowment for the Arts and the National Academy of Sciences. She is the author of seven patents for the integration of digital technologies in architecture, building materials, and textiles, and has served as an advisor to the U.S. Department of Energy, the National Academy of Sciences’ Government-Industry Partnerships, and the Vision 2020 National Technology Roadmap. Her work has been exhibited at many international design venues and has been featured in journals of architecture, design culture, anthropology, and optoelectronics, as well as on National Public Radio, BBC World News, CBS News, CNN Principal Voices, Wired Magazine, Science News, The Economist, The Wall Street Journal, BusinessWeek, and The New York Times.

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Kennedy and her colleagues put MATx research into practice through the creation of a new model for practice which brings a digital fabrication workshop, an optoelectronics lab, and an architecture and design studio under one roof. The firm’s headquarters is located in the former Blue Bird Bottling Plant in Boston’s emerging NewMarket District. The KVA MATx studio was selected by I.D. Magazine as one of the top 40 creative global workplaces.

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Your practice is known for its integration of research and design. Can you tell us how you develop your research and how it is reflected in your design? As a design firm, we are primarily interested in creating ideas and developing processes that enable us to realize these ideas in practice. Innovation in architecture requires a reconsideration of the relationship between design and production processes. Since there are budget and schedule constants for any given project, we take on a double responsibility to create the project’s design and to design how the product will be realized.

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We launched our materials research unit MATx in 2000, because we realized that the need to design and integrate energy-efficient digital technologies in building projects places a great demand for vertical integration in architecture. We saw the potential to integrate new forms of infrastructure into materials, buildings, and cities. We realized that we needed to develop a model of practice which would allow us to organize (and often even create) the building products, technologies, and services that were necessary to realize important environmental parameters in the given needs of a project. This has led us to become the interdisciplinary organization we are today. And it has shaped the physical organization of the studio space where we work. At KVA MATx we renovated an industrial warehouse to suit our needs. We developed a stacked open studio floor plan where digital design and modeling are in close proximity to our materials library and where our optoelectronics “skunkworks” can flow into flexible project rooms and fabrication workshops. We have literally created a studio space which enables us to integrate research and design.

There is an important distinction between the meaning of “research” and “evidence.” Research is the process of looking or searching for different solutions. Evidence suggests that something is evident or obvious, that it is already seen in relation to a given problem. For us, design always begins with research, with the task of searching to define a given problem and to discover different ways that it can be addressed in design. The importance of intuition in the creative process can’t be underestimated; it is one of the major assets of architecture as a creative discipline. As a starting point, we outline hunches, then test our intuitions by working with a process of rapid prototyping and by examining the basic implications of an idea and checking it against our experience and what is already known. We often separate various strands of the problem in a series of different prototypes, one for structural functionality, for example, and one which brings a quality of space

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Our research often explores how to make the best use of young and sometimes underperforming new technologies. Our interest in making things has led us to combine new materials with familiar materials such as brick, glass, or textiles. By combining new technologies with traditional materials the fundamental nature of both “old” and “new” materials is transformed. By creating integrated, composite materials and building components—that provide new capabilities—we can move on past the modern architectural distinctions between “high” and “low” or “smart” and “dumb” technologies.

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or experience. We undertake a variety of empirical tests using both digital and physical models. Later in the design process these strands will be integrated once each is more clearly defined.

How important is it to be credible in describing value? Do you use metrics? Credibility is developed over time. But a radical idea will not be automatically accepted based on past experience or credibility. However, if people can see or touch something, and use it—live with it for awhile—changes in habits of thought and practice can happen. It is important to create a value proposition. However, value can be described in many ways—equity, political, social, and cultural. These are significant values which are often not easily monetized. Architects can emphasize value in the full terms of our discipline; by understanding the relationships between spatial, aesthetic, experiential, and technical aspects of issues such as energy conservation, life span, and efficiency. As architects we should not be attempting to promote design using metrics. It would be naïve to think that numbers and statements used in metrics are purely factual or even objective; they are created according to various perspectives. We don’t start with, nor do we focus our design process on metrics—we try to develop designs that emphasize qualities that are unique to the medium of architecture; the use of light, the sensory experience of materials, the way a material surface or a space can engage the passage of time.

KENNEDY INTERVIEW

Can you give us some examples of how your research has informed your design?

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KVA has recently completed Harvard’s new Film and Video Headquarters, RISD’s Graduate Arts Center, and the University of Pennsylvania’s Motion Capture R&D Labs. Their design of the East River Ferry Terminal Building at 34th Street in Manhattan, currently under construction, received the New York City Art Commission Award for Design Excellence, and is the first public sector project in Manhattan to be realized with digital fabrication. The 34th Street Ferry Terminal in New York is an example of how budget and site served as catalysts for innovation. A traditional steel roof structure proved too expensive, due to staging problems on a congested urban site. In collaboration with Michael Stein and our structural engineering team at SBP, our design developed a novel

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double-sided stressed skin textile roof that reduces the need for steel trusses and can be fabricated offsite, so a high degree of fabrication quality can be maintained on this public project. One of the most interesting aspects of this project involved creating a cooperative set of performative surfaces that work together in an affordable way to provide a first instance of distributed infrastructure in a public building. The lower fabric roof layer is made with a reflective metal mesh which is intersected by light wells that provide daylight to information and seating areas below. We developed a way to integrate LEDs in the light well surfaces to provide illumination and responsive signaling capabilities that monitor weather and ferry boat arrivals and departures. Using only off-the-shelf sensors, and industrial rugged foot step switches, we designed benches with energy-efficient passenger heating on demand. The design of distributed heating, artificial lighting, and daylighting in architecture is a key transition away from modern centralized building services. This strategy accelerates the use of new energy-efficient technologies and we find that our research investment returns many times over as we can apply what we’ve learned to new projects.

The solar roof panel industry is based on the use of “peak efficiency” metrics, which describe the energy generated at peak hours when sunlight is perpendicular to the panel. Solar nano-materials are a disruptive technology. The organic photovoltaic materials used in SOFT HOUSE solar textiles are very inefficient in relation to traditional glass panels. However, they are very inexpensive to manufacture, and their production process uses far less embodied energy. Their value lies in their ability to convert sunlight into energy all day long, so we need to introduce a new idea of accrued total daily energy. Though less familiar as a metric, the total energy produced is what is important and also the fact that the energy-manufacturing process is clean and it is well known that most companies don’t produce metrics on embodied energy in production.

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Since 2000, the team at KVA MATx has been working with semiconductor materials that harvest energy and emit light. In our SOFT HOUSE project, we have been working with manufacturers of solar nano-technology which can be printed on flexible, thin-film substrates using an organic dye. We are developing ways to integrate this new material into solar textiles for energy-harvesting building curtains, façade, and roof canopy systems. One of the interesting aspects which emerged in this project was the need to challenge and redefine the terms of efficiency metrics that have been used by the glass solar panel industry for the last decade.

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The work of KVA has shown that the use of research and high-quality design are not inconsistent but in fact are integrated and dependent. What changes to our academic curriculum and practice models do you think are needed to encourage comparable innovation in the future? We need to be working more with materials, (physical) models, and memory—the memory of what has already been accomplished in the discipline. Ironically, the parametric software and CAM tools that allow us to begin to consider questions of emergent digital materiality also have the potential to distance architects from the day-to-day considerations of contemporary practice. Construction in practice requires the fluid movement from the virtual 3D digital model to a projected, flat 2D drawing schedule of parts which are then assembled into a 3D physical constructed reality. Digital machine outputs in building practices require the architect to work directly with the material/machine interface and be much more adept at understanding and predicting material performance. Yet in many schools, 3D printing and the segregation of studio, classroom, and workshop are beginning to erode the architect’s ability to make things, to understand the resistance of materials.

KENNEDY INTERVIEW

Architects need to continually invent strategies for relevancy without giving up the realm of architecture’s unique areas of creative expertise. We need a formulation of research with a continuum between basic (core disciplinary) research and applied research, where one leads back to the other. Historical research and precedent are increasingly important—it is not the first time that our culture is experiencing significant changes in infrastructure and in the physical environment. This requires the architect to scrutinize the problems of the present with a better understanding of history without compromising her or his ability to imagine alternative futures. What do we want to achieve? What can we do right now, with what we already have? How can this help us create better futures? The best projects of architecture are those that have the ability to move between the future and the present to transform the discipline from within.

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K E N N E D Y C A S E S T U D Y: 3 4 T H S T R E E T F E R R Y T E R M I N A L

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34th Street Ferry Terminal KVA Architects In 2003, a large financial services company was looking for alternatives to cubicles and to the long-standing assumption that people needed an assigned desk and needed to be in it to be productive. Their main research question concerned how people would work and what needed to be supported, if they didn’t have assigned space. They also asked whether the solution could be the same for everyone, or whether it would need to provide a range of options.

KVA was commissioned by the New York City Economic Development Corporation (EDC), the New York City Department of Transportation (NYCDOT), and the New York City Parks Department (NYCDPR) to design the East River Ferry Project in Manhattan. This major urban waterfront transportation initiative includes the design of an intermodal ferry terminal at East 34th Street as well as ferry boat docking facilities, waterfront improvements, and community amenities on six sites along the East River waterfront in Manhattan. The project expands regional waterway causes by accommodating high-speed ferry service to La Guardia Airport, Staten Island, Brooklyn, Queens, and New Jersey. The design encourages public use of the waterfront through pedestrian, train, bike path, and vehicular connections from the City to the riverfront, offers commuters an alternate and sustainable means of transportation within Manhattan, and serves as a public safety corridor in times of emergency. The design of the 34th Street Ferry Terminal takes a nonnostalgic attitude toward the NYC riverfront. Pier 34 is redesigned and expanded to provide passengers with ticketing and waiting facilities and public access to three high-speed ferry berths. KVA secured grant monies from New York State agencies for offgrid sustainable energy generation including hi-torque urban wind turbines and solar-powered solid state lighting. The architecture integrates information from New York City’s existing and underutilized maritime GPS to provide electronic way finding signage, intelligent real-time transportation scheduling (ITS), wireless public messaging, and information access systems for commuters and waterfront residents.

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 Figure 4.2a 34th Model: View of 34th Street Landing from Water

 Figure 4.2b 34th Street Ferry Terminal Rendering: View from Landing toward Manhattan

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The Ferry Terminal uses an innovative tensile textile roof structure which is fabricated offsite and erected in a matter of days to provide an efficient approach to building delivery on this urban site. An upper layer of structural PTFE fabric provides 15 percent translucency and the lower layer of reflective mesh bounces light reflected off the water surface, providing a natural play of light by day and avoiding the need for costly site lighting. On-demand integrated radiant heating is provided in the passenger waiting area. Further, the area is protected from windblown rain by retractable weather screens. The 34th Street Ferry Terminal creates a public architecture which juxtaposes the natural and artificial qualities of the East River Waterfront with the project’s sustainable digital technologies. The building’s cross-section is detailed so that the terminal appears to be suspended above the water—the sound of the river and the reflective capacity of the changing water conditions at high and low tides are engaged by the surfaces of the architecture. The physical experiences of the waterfront environment are combined with the expanded virtual experiences of the working commuters: GPS, cell phone, and Internet.

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K E N N E D Y C A S E S T U D Y: 3 4 T H S T R E E T F E R R Y T E R M I N A L

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KENNEDY CASE STUDY / Soft House

Soft House KVA Architects The Soft Energy Path, presented by Amory Lovins at the Rocky Mountain Institute in 1978, outlined the value of multiple and hybrid approaches to reduce mainstream consumption of nonrenewable energy sources. Drawing upon these principles, the SOFT HOUSE research group, a team of architects, engineers, fabricators, and manufacturers organized by KVA MATx, created a prefabricated house design where the performance and material potentials of disruptive organic photovoltaic (OPV) nano-technology could succeed without having to compete with the dominant technology of the electric grid. The SOFT HOUSE by KVA MATx transforms the household curtain into a set of energyharvesting and light-emitting textiles that power solid state lighting and portable work tools such as laptops, digital cameras, and PDAs. SOFT HOUSE textiles can adapt to the changing space needs of homeowners and can be moved to follow the sun generating up to 16,000 watt-hours of electricity—more than half of the daily power needs of an average household in the United States. KVA MATx was commissioned by the Vitra Design Museum to realize full-scale prototypes of the SOFT HOUSE energy-harvesting textiles for the exhibit “Open House: Architecture and Technology for Intelligent Living.”

Figure 4.2c Soft House Model: Perimeter curtain moves outdoors to provide shade and harvest sunlight. Raised central curtain creates open floor plan.

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KVA MATx application designs for energyefficient semiconductor technologies in movable curtains, translucent textile screens, and luminous room enclosures shift the boundaries between the traditional wall and household utilities. The SOFT HOUSE distributed energy network is made of multiple, adaptable, and cooperative light-emitting

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Figure 4.2d Soft House Model: Mobile energy-harvesting curtains illuminate the SOFT HOUSE.

textiles that can be touched, moved, and used by homeowners according to their needs. Translucent movable curtains along the SOFT HOUSE perimeter convert sunlight into energy throughout the day, shading the house in summer and creating an insulating air layer in winter. A central curtain moves vertically to create an energy-harvesting chamber or a suspended soft chandelier with integral solid state lighting.

Figure 4.2e Soft House Curtain: Central energyharvesting curtain in soft chandelier mode.

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K R N N E D Y C A S E S T U D Y: S O F T H O U S E

The principles of the SOFT HOUSE energy network—simplicity, adaptability, and intelligent cooperation among individual elements—are extended into the architectural design and fabrication of the SOFT HOUSE. The grid shell plywood structure of the SOFT HOUSE can be adapted to accommodate a range of different site and solar orientations in a digital design and fabrication process. Parametric design software, developed for the SOFT HOUSE project, allows the OPV density of the energy-harvesting textiles to be mass customized on computerized lamination machines according to the homeowner’s budget and energy needs.

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TIMBERLAKE INTERVIEW James Timberlake, FAIA Partner, Kieran Timberlake Architecture is holistic alchemy…a little bit of this and a little bit of that, a little more of this and a little less of that with the emphasis on a process leading to a product that has the totality of factors—cost, scope, time, money, aesthetics, environmental responsibility—all incorporated and in balance. It is a combination of art and science, analysis and intuition—all in balance. As with any science, architecture needs data, facts and metrics to shape design in a verifiable way. As with any art, architecture cannot do without beauty.

Figure 4.3 James Timberlake, FAIA © Ed Wheeler

James Timberlake is a founding partner of KieranTimberlake, an internationally recognized architecture firm based in Philadelphia and recipient of the 2008 AIA Architecture Firm Award. He received the Rome Prize from the American Academy in Rome in1982. Kieran and Timberlake were inaugural recipients of the Benjamin Latrobe Fellowship for architectural design research from the AIA College of Fellows in 2001.

TIMBERLAKE INTERVIEW

Mr. Timberlake has taught at several universities nationwide and currently leads a design research studio at the University of Pennsylvania. He has co-authored Manual: The Architecture of Kieran Timberlake (2002), Refabricating Architecture (2004), and Loblolly House: Elements of a New Architecture (2008). Two more books are forthcoming in 2011.

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With a full-time research group within the firm, KieranTimberlake is actively engaged in inventing ways to use new materials, processes, and construction methods. Collaboration with engineers, builders, landscape architects, environmental and material scientists, clients, and representatives beyond architectural practice is essential to the firm’s holistic approach to making. Ongoing exploration of the role of design research in architectural practice has produced several leading edge provocations including SmartWrap™, a mass-customizable, energy-gathering building en-

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velope exhibited at the Cooper-Hewitt National Design Museum, and Cellophane House, a fully recyclable, off-site fabricated dwelling commissioned by the Museum of Modern Art. KieranTimberlake is a recognized leader in sustainable design, with three LEED Platinum projects built in the last three years and two buildings named “Top Ten Green” projects by the AIA Committee on the Environment. The firm has worked internationally in Calgary, Singapore, and Morocco, and recently won a competition to design the new United States Embassy in London. Recent projects include the Cornell University West Campus Residential Initiative in Ithaca, NY, Loblolly House in Taylors Island, MD, Stewart Middle School at Sidwell Friends School in Washington, DC, the Yale University Sculpture Building and Gallery in New Haven, CT, and a low-cost, LEED Platinum–rated home, for the Make It Right Foundation in New Orleans, LA.

How does the use of research and evidence play a role in design decision making and informing your work?

It has changed our product for the better; we are now more informed, and have more data to make better design decisions. The processes are not prescriptive, so we are freer as a result of having more information, along with a clear communication and design process. Our design methodology can be adapted to different circumstances, sites, clients, or programs. Our buildings all have deep intelligence as they are rooted in the same process, with the same interest in performance and outcomes. We have found that clients are receptive to art that is based upon or informed by science. It is a much more substantive approach to architecture due to the process having deep roots in research and inquiry. When a client asks for a “50-year building,” we have the metrics to substantiate what that represents. As a result, design improves because it is based on analysis and performance. It has also changed the dynamic during design with our clients and the perception of design value.

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In 2006 we became one of the few architectural firms in North America to be certified by the International Standards Organization (ISO) for the research, management and delivery of architectural services. Since then we have mapped 44 processes in the firm. We monitor, learn from, and continuously improve those processes. When we first started the ISO certification, some feared that bringing rigor to our process would limit creativity, yet we have experienced the opposite result. Incorporating these rigorous processes has allowed us to become more intuitive rather than less. Bringing deeper analysis to the science we have clearer data, information, and metrics brought to developing the art of the project.

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Do you have a predominant research methodology? Predominant, no. We want an approach that allows us to be nimble rather than beholden to a proscriptive set of rules. Research takes on many forms within the office and, of course, our research is not limited to design. We do, however, include in our initial stages of design analysis a comprehensive exploration of environmental considerations. These factors are identified as “opportunities” around which research must be applied and solutions developed. In conjunction with this, environmental constraints, social and programmatic considerations desired by the client, and regional contexts are taken into account. These considerations form a list of factors for the design to address, at which point we can begin to seek iterative opportunities and lasting solutions. Although we mine a variety of resources, past projects serve as precedents. Inherent to ISO 9001:2008 is a method of documentation which provides a knowledge database of past research. The site specific nature of architecture means that many of the opportunities encountered are likely to be unique. Past research is drawn upon for appropriation, inspiration, or evaluation as to where improvements might be made. In addition, we often employ technologies transferred from other industries which requires us to craft solutions, and think beyond the normative modes of assembly, organization, and delivery. Rather than providing a systemic path toward a solution, using technology transfer requires meshing disparate systems to address unique problems.

TIMBERLAKE INTERVIEW

Since we need to prove the viability of a system or product before it is implemented, ideas are explored through computer models, prototypes, and mockups, and vetted against past experience, cost considerations, and expert advice. These efforts serve to refine the technology and ensure that all foreseeable real world contingencies have been accounted for.

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After design and construction, we’re not done. Post occupancy analysis and monitoring helps determine if the technology achieves the desired performance, durability, and maintenance requirements. The methods for conducting this analysis are multifaceted and include user interviews, site inspections, and the deployment of monitoring technology. Information garnered at this point in the process lets us know if in situ modifications are needed to optimize function and inform subsequent designs. The countless lessons learned through the post occupancy and monitoring process are invaluable tools for avoiding future issues with deeply innovative work. To ensure this information is disseminated, the many small lessons, manipulations, discover-

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ies, and monitoring data are recorded and shared internally with circulated research documents, presentations, and online wikis. This closes the innovation loop, priming the cycle for the next project and the next analysis of site opportunities.

When integrating research into a design practice, how do you determine “how much evidence is enough?” This is a decision that has to be made based on the needs of the client, the complexity of the design challenge, the context, and of course the value of the opportunity. We look at the integrated effects of first cost, life cycle cost, performance, energy saving, constructability, and maintenance. Taking all of this into account means that aesthetics emerge later in the process than one might think, because we are confident that if we agree on certain performance criteria, that there are a thousand beautiful design solutions that we can provide. We strive for a continuous loop of improvement and reflection. This requires a ceaseless inquiry about how we can do what we have just done—better—and helps to hone the skills to frame questions and seek out measurable data that we can act upon to improve what we have done. Research is an iterative process; a process of refinement of analysis, data, information, and technology continually exploring, looking, and cross referencing. Research does not always lead to innovation or invention or, for that matter, to great design. More often it results in confirmation, but the process places us in a position, as it does in many other industries, to explore and innovate in ways we did not expect at the outset.

This arena is as yet unmined. We are at a point where I think there is some understanding to help architects learn more about human response but we need additional, continual data to help us refine that understanding. Behavioral responses to particular designs, aspects of place making, and the creation of interactive spaces all need to be gathered and mapped. White’s efforts in the 1960s, among others, that were based upon observation and intuition, still provide the profession with a basis for many design decisions. We need greater efforts in this area. Current, principal drivers are environmental ethics, building sustainably, creating new and integrated processes, and dealing with fiscal constraints. When we have the opportunity to study human response, perhaps the best way to gain information is to

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Much of your work and interest in research deal with the making of buildings. Do you think we can apply the same research rigor to understanding human response in addition to building performance?

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spend more time monitoring and cataloguing the human response to existing spaces and stimuli. Continue to monitor, observe, make hypotheses about what is seen and refine the next effort based upon what is learned. Then bring that to the next learning cycle. This is a well used and understood modeling process.

For your practice model of integrating research and design to be understood, are there any changes to our current educational model that are necessary? We have spoken quite passionately at conferences and in our writing that the nineteenth-century Beaux Arts architectural education model is no longer valid for design education. It makes little sense to assign a group of students a project, expect them to develop it utilizing singular intelligence, and then aggressively critique that work six weeks later without some substantive research and data collection, collective intelligence sharing, collaborative work models, and deeper learning methodologies during that period. It simply gives priority to art over science, and intuition over analysis with a jury responding to images rather than information. It leads to premiating form over holistic integration and surface over substance. This is a dead on delivery model of education. It perpetuates failure. It encourages lessening productivity and the arteriosclerosis of integrating design with construction. It is not assistive to us as practitioners. It is a continually “band-aided” system by those who review, advise, and accredit. Our practice system is more nimble. Our education system needs to be responsive to our need for nimbleness.

TIMBERLAKE INTERVIEW

Instead, with our MArch degree candidates at the University of Pennsylvania, we are given the latitude to work “open source” in five-year increments. Each year begins with an examination of the previous year’s inquiry and experimentation. Earlier work is dissected and critiqued. Prior work is seen as an impetus to creativity, not a limitation. It becomes grist for further questions and experiments and a guide to higher levels of inquiry and speculation.

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To promote collective intelligence the students work in collaborative teams. Everything we have learned as practitioners indicates that the most important skills we can impart are how to work together rather than alone—how to bring inevitable conflicts to solutions resulting from higher levels of creativity and productivity. The generation we now teach gathers and processes information differently. Given the complexity of the knowledge base required to make architecture today compared to one hundred years ago, new advances in architecture and construction will be best made by those who embrace the new ways of working together and sharing information.

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LOFTNESS INTERVIEW Vivian Loftness, FAIA There needs to be a stronger national mandate linking health to the built environment. NIH does not recognize in their grant priorities the critical relationship between health and buildings. If this were to change, there would be greater incentive for biomedical researchers to seek collaborations with schools of architecture and practitioners.

RESEARCH BACKGROUND

Why is the use of evidence critical in your work? What kind of research constitutes adequate evidence, and how are you developing that knowledge? Over the years, I have surveyed executives to determine their decisionmaking process when purchasing a car, a computer, or a building. Interestingly, executives can make careful value judgments, based

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LOFTNESS INTERVIEW

Figure 4.4 Vivian Loftness

Vivian Loftness is a University Professor and Head of the School of Architecture at Carnegie Mellon. In addition to her role as Senior Researcher at the Center for Building Performance and Diagnostics, Professor Loftness is a licensed architect and a Fellow in the American Institute of Architects. She is actively engaged in architectural education, research, and collaborations with building industry partners such as DOD, DOE, Department of State, GSA, NSF, and major industries such as Steelcase, United Technologies, and Johnson Controls. She has served on five National Academy of Science panels and on the Academy’s Board of Infrastructure and the Constructed Environment. She is one of a few distinguished architects truly capable of bridging applied research and practice. Her specific focus of research over the past ten years has been a critical analysis and research into the understanding of high-performing buildings. As a part of this effort, she has also gained specific insight into sustainable building design and its interrelationship with high-performing buildings.

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upon performance, when determining whether to purchase a $30,000 car over a $10,000 car, or a $3,000 laptop over a $1,000 laptop. In both instances, the buyers were able to articulate dozens of performance differences that resulted in the decision to purchase the higher-priced alternative despite the short life of a car or a laptop. By contrast, executives could barely define the quality differences of a $300-per-square-foot building over a $100-per-square-foot, opting for the leastcost solution, despite the fact that buildings should be 50-year investments. Owners and occupants were less able to evaluate building performance as a differentiator of price and value. Architects have failed to differentiate for the public an understanding of what constitutes high-performing versus low-performing buildings. Lacking that understanding, preferences for building design or purchases are made for other reasons (location, media hype, builder’s reputation) instead of the performance of the building—diminishing the value and contributions of the architect and design. This lack of differentiation has led to my commitment to provide a better understanding of what differentiates a high-performing building, system by system, and the lifecycle value of that quality to the person making the decision. This research is focused on two activities: (1) the aggregation of known or existing evidence linking buildings to high-performance outcomes such as health, productivity, retention, sales, energy, and facility savings, and (2) the creation of new evidence with the aggregation of existing knowledge, yielding research that now has critical mass to enable us to link better building components and systems with better outcomes. Those elements of a building defining high-performing buildings were identified, analyzed, sorted, and categorized. Physical attributes were linked to occupant perceptions and organizational values. In office environments, a number of attributes were found to be of great significance:  Thermal comfort: air temperature controls

LOFTNESS INTERVIEW

 Lighting quality and control

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 Ergonomics: individual and organizational  Acoustics: privacy for concentration alongside collaboration  Network access  Biophilia: access to the outdoors

This research captures hundreds of research studies into a database (both by piece as well as whole building) toward the creation of new evidence to define high-performing buildings, with the economic benefits that will ensure client buy-in.

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Armed with these databases and hypotheses, how have they been used to inform design? Utilizing the case-based BIDS™ database and the resulting building performance guidelines, we have worked to provide a quantifiable, cost-based comparison of energy and facility management savings as well as other organizational savings such as churn, turnover, absenteeism, creativity, and in repetitive jobs, worker productivity. These links of building attributes to individual and organizational benefits have often been called evidenced-based design. The creation of a case-based database, the development of a cost-based model and the basis for linking building performance with human behavior, led us to create a new research tool for decision-making support. Creating new research-based tools for the design profession is a critical responsibility of the research community.

Have you found the use of data, evidence, and research to inhibit or enhance creative thought? Have interdisciplinary collaborations played any role in your research efforts?

Architects have always collaborated with other disciplines—especially engineers and contractors—and this is a well-used and understood tradition. However, these collaborations have often been linear with few truly multidisciplinary early design decisions or iterative improvements based on diverse expertise. With the growing intention of attaining LEED (Leadership in Energy and Environmental Design) recognition, however, architects have begun to embrace interdisciplinary early design decision-making, collaborating in the conceptual design stages with geologists, hydrologists, sustainable energy engineers, transportation engineers, horticulturalists, arborists, chemists, and material manufacturers. The growing use of Building Information Modeling (BIM) is also supporting the integrated design process, and the overlaps between sustainability and BIM suggest a dramatic shift in design decision-making that will be truly creative and visionary. While these two current shifts in practice promote a greater degree of interdisciplinary collaboration, they remain focused on “how” buildings are built and their integrated performance in hard metrics. Still lacking is the interdisciplinary collaborations necessary to inform “what” we are building in response to human performance metrics—to enhance health, productivity, creativity, motivation, even collaboration. For this, we will

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Some architects fear that use of evidence-based design may inhibit creativity through prescriptive rules and prescriptive solutions. However, it is our belief that evidence provides the foundation for design theories and design hypotheses, establishing what is known, and revealing opportunities for innovation. Creativity is not invention in a vacuum, but invention from a basis of both precedents and impacts.

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need to collaborate with social scientists, anthropologists, and environmental psychologists, to explore the impact of the built environment on human performance and behavior. Not since Oscar Newman’s book Defensible Space have we investigated the link between the built environment and crime—and this study is now almost 40 years old. Interdisciplinary collaborations with social scientists, anthropologists, and environmental psychologists offer rich opportunities for creative and visionary design.

As someone who has bridged between education, research, and practice, what changes are needed to foster a culture in support of evidence-based design, creativity, and innovation?

LOFTNESS INTERVIEW

At this time education, research, and practice seem so disparate; three separate activities. This could be addressed by the coordinated efforts of all three, or catalyzed by a stronger national mandate for performance in the built environment. For example, research, education, and practice could contribute significantly to linking health to the built environment. Today, the National Institute of Health (NIH), which provides the greatest amount of money for research, does not recognize in their grant priorities the critical relationship between health and high-performing buildings. If this were to change, there would be greater incentives for the medical researchers, for example, to seek collaboration with schools of architecture and architect practitioners.

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Without national funding focused on major societal gains, from health to sustainability, the funding to bring researchers, educators, and practitioners together is inadequate. Unfortunately, the current practice model limits the amount of discretionary funds available to architectural firms for research or collaboration with universities, especially small and mid-size firms which represent 95 percent of all firms. In the face of limited resources for research and innovation, there is potentially a better model that was used by EPRI. This Electrical Power Research Institute pooled the resources from hundreds of small utilities into a substantive research budget to support studies in a broad range of subjects related to the electric power industry at a scale that could never be afforded by individual utilities. If architectural firms pooled their resources and determined the most critically needed research with university partners, the profession would gain both in significance and in compensation. It would be critical, however, to share the knowledge gained as opposed to generating proprietary information for competitive advantage. Tomorrow’s professional practice will, by necessity and by vision, be more integrative in design development and more creative in the generation and sharing of knowledge. The importance of the built environment to pressing societal issues—health, crime, water, climate change—as well as the greatest societal opportunities—community, education, and quality of life—are critically dependent on collective creativity.

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L OFTNESS C ASE S TUDY Building Investment Decision Support (BIDS) Architects have failed to differentiate for the public an understanding of what constitutes high- versus low-performing buildings. Lacking that understanding, preferences for building design or purchases are made for reasons other than the performance of the building, thus diminishing the value and contributions of the architect and design.

What was the research or critical question in this project? The goal of this project is to develop a cost-benefit analysis framework for various advanced and innovative building systems and to incorporate these within a multimedia decision support tool. The BIDS project has four specific objectives:  The development of economic language and logic whereby intelligent workplace

design can be thought of by the business investor as analogous to other emerging, strategically central investments that have different operating life cycles (economic sustainability), competitive implications (workforce impacts), and payback periods (capital market valuation criteria).

LOFTNESS CASE STUDY / Building Investment Decision Support (BIDS)

LOFTNESS CASE STUDY

 The development of a cost-benefit analysis framework for evaluating various ad-

vanced and innovative building system options in relation to a range of cost-benefit or productivity studies, to be incorporated within a multimedia decision tool.  The determination of cost centers where the benefits of high-performance ap-

proaches will be significant, and the expansion of a database relating quality indoor environments to major capital cost and benefit areas, including productivity, health, and operations costs.  The identification of laboratory and field case studies demonstrating the relation-

ship of high-performing components, flexible infrastructures, and systems integration to the range of cost-benefit or productivity indices. Investment in high-performing building solutions and technologies is limited by first cost decision-making. As a result, the development of a life-cycle tool comparing the cost-benefits of building technologies is central to the commercialization of highperformance building solutions. Examples of the life-cycle justifications include orga-

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nizational effectiveness, energy efficiency, waste management and renewability, and the productivity and health of the workforce.

What were the research or investigative methods used in this project? The primary research approach utilized an intense and thorough process of “data mining” that led to the development of the Building Investment Decision Support (BIDS) tool. Research began with a review of thousands of abstracts, analysis of hundreds of papers, and the development of hundreds of case studies related to individual topics of concern. Following this process of data mining, the researchers developed interrelationships between various attributes of the work environment utilizing complex crosssectional techniques of analysis. The process identified the relationships between design options, cost/benefit factors, and scenarios of application which is the basis for the BIDS cost-benefit analysis decision support tool. It is represented in a threedimensional matrix expressed in an X,Y, and Z axis format.

What evidence was created in the investigation to inform the design process? Design Options: For the first axis of the BIDS matrix, the researchers looked at: (A) Air Quality—Ventilation Control” through “Federal Agenda” on p. 260 (B) Air Quality—Ventilation Control (C) Thermal Control (D) Lighting Control (E) Flexible Connectivity: data, power, voice, security, environmental services (F) Privacy and Interaction (G) Ergonomics (H) Access to the Natural Environment and Environmental Finishes All of these building systems are design options that affect the quality of the individual workplace.

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Cost-Benefit Factors The second axis of the BIDS matrix captures the range of economic benefits that have been identified with high-performance building components and systems. Many of these workplace-related expenses are those which are carried annually by organizations—from energy and facility management costs to churn and health and litigation costs. The ten cost-benefit areas where annual organizational investment is significant are: (I) First Cost/Mortgage Savings through Quality Packages: Integrated system savings over individual components Quality and Modularity with JIT purchasing over redundancy (J) Facilities Management Cost Savings Energy/utilities, management, repairs (K) Individual Productivity Cost Savings Speed, accuracy, effectiveness, creativity, impairment, absenteeism (L) Organizational Productivity Cost Savings Time to market, profit, company value (present and future) (M) Attraction/Retention Cost Savings Time and quality attracted, training costs, retention rates (N) Tax/Code/Insurance/Litigation Cost Savings

LOFTNESS CASE STUDY / Building Investment Decision Support (BIDS)

LOFTNESS CASE STUDY

Tax depreciation, Code compliance, insurance and litigation costs (O) Health Cost Savings Insurance and medical costs, health litigation, Workers’ Compensation, environmental evaluation and remediation (P) Renewability Cost Savings: Organizational Reconfigurabilty/Churn (Q) Renewability Cost Savings: Technological reconfigurability (R) Salvage/Waste Cost Savings Organizational, technological, environmental modifications Aging and Wear, Obsolescence, Salvage Value

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Organizational Scenarios The third axis of the matrix relates to the economic characteristics of organizational types that may affect the cost-benefit calculation for high-performance products. The organizational types currently in BIDS are organizations characterized by: (S) Globalization (T) Collaboration (U) Technical Dynamics (V) Organizational Dynamics (W)Gold-collar Orientation (X) Environmental Agenda (Y) Federal Agenda

What were the outcomes of the investigation? Currently, work in the BIDS project is focused on five areas: (1) case study development, (2) interface and software refinement, (3) financial assumptions and calculation development, (4) linking multistudy conclusions to design guidelines related to quality, and (5) web-based commercialization of the tool with a business strategy. The real cost of doing business is realized over time, not in first construction costs. Careful bookkeeping will reveal that “cheap” buildings and infrastructure, and “cheap” building delivery processes often result in major costs over time. Source: Paper entitled “Building Investment Decision Support (BIDS)” by Vivian Loftness, FAIA, and Volker Hartkopf, PhD.

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ARENS INTERVIEW Edward Arens, PhD For the important topics of indoor environmental quality and energy efficiency, the architecture profession does not have, or even ask for, substantive feedback on how their designs perform once built. There is very little real learning going on.

Figure 4.5 Edward Arens

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Ed Arens is Professor of the Graduate School at the University of California, Berkeley (UCB), Director of the Center for Environmental Design Research (CEDR), and Director of the Center for the Built Environment (CBE). Professor Arens’s research approach is reflective of his highly interdisciplinary educational background. He earned a Bachelors in architectural history, a Masters degree in forestry, a Masters degree in urban studies—all from Yale University—and a PhD in architectural science from the University of Edinburgh, U.K. Prior to joining the University of California, Berkeley (UCB), Arens headed the Architectural Research Section at the National Bureau of Standards in Washington, DC. Having started in the Building Science Laboratory in the Department of Architecture at Berkeley in 1980, he currently serves as Director of both the CEDR and the CBE at Berkeley. Arens’s applied research interests are in energy-efficient design and operation for comfortable and productive buildings, innovative building mechanical systems and controls, building aerodynamics, and the design of spaces for pedestrians outdoors. His fundamental work has been in the modeling of comfort in conditions where air movement, temperature, and radiation are unevenly distributed across the human body. He has been active on ASHRAE standards. For his work, he has received three Progressive Architecture Research awards and three ASHRAE Best Technical Paper Awards.

ARENS INTERVIEW

RESEARCH BACKGROUND

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The work of CBE is very diverse and consistently includes evidence gained by research. Is this unusual? Is there a type of research special to architecture? Increasingly, schools of architecture and their faculty have moved away from using factual evidence in teaching. There has been a stream of fashionable topics and “theories” that are really not much more than storytelling—their short shelf-life shows that they are not contributing to accumulated knowledge. Unfortunately, the architectural press does not review these topics critically, to the detriment of the profession.

ARENS INTERVIEW

I don’t believe that there is a special type of research for architecture. If you want to do research, the physical sciences represent buildings, and the social and physiological sciences represent the occupants. The professional practice of architects (the creative activities of conceiving buildings and organizing space, and the business activities of leading teams of different disciplines) are also scientifically approachable topics; studied using psychology for the former and business school or operational research methods for the latter. The cultural and historical parts of architecture have been traditionally dealt with using longstanding scholarly techniques that are perfectly understandable and acceptable to scientists. In all these things (and I think I am including everything in architecture here) it is possible to do research, and in each case the research should meet scientific standards. Otherwise it is not worth doing; it will produce garbage.

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The lack of feedback to designers on how buildings are performing is the fundamental problem in the profession. It means that past mistakes are repeated and that positive developments are not recognized and adopted. Part of this is lack of instrumentation in buildings. Aircraft provide their designers and operators with immediate and continuous feedback on how they are performing. This capability leads to diagnoses of malfunctions; standards for improved designs; and reliable, fuel-efficient aircraft. Since buildings, like aircraft, are complex systems, they will never reach modern levels of efficiency or sustainability until they are designed with feedback instrumentation. However, there is another cause to the lack of feedback: Architects are not looking for it. A lot of them have never been trained to observe an operating building in ways that reveal how it is performing. They have not learned what to notice or measure, and how to interpret what the measurements signify in terms of improving the building’s design and operation. This needs to be changed. There have been barriers: Architectural fees haven’t traditionally paid for feedback and clients and architects are fearful to know the answer. Given a societal demand

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for higher-performing sustainable buildings, this may be changing. It helps that technology is making feedback far less expensive than it used to be. UCB’s Center for the Built Environment has developed a web-based survey of occupant satisfaction in buildings that is used to establish performance benchmarks for office buildings. With a database of 65,000 completed surveys, it is possible to quantify the characteristics of high- or low-performing buildings. The core of the survey inquires about eight primary attributes, including thermal comfort, air quality, acoustics, lighting, and space. Optional modules allow other types of buildings to be examined in more depth. Whenever a negative (unsatisfactory) rating is marked, the survey leads to a second layer, or branch, of questions that probes deeper into the source of the problem. With enough such feedback of actual performance, it is possible to review the effectiveness of design standards and codes, and to identify deficiencies requiring revision.

How should designers use your research and what are the implications for design outcomes?

Do you think that the use of this research foundation inhibits or enhances creativity? What is the role of interdisciplinary collaboration in both research and design innovation? Factual knowledge provides a vocabulary and framework for creativity. As an analogy, think about a musical composer who needs notes and scales from which to compose; these form the vocabulary and framework for music. Similarly, knowledge, standards,

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Architecture is a practical art and profession. A foundation of information developed from dependable research should be a starting point for creative thought. I suggest that architects begin to address themselves to getting proper feedback from functioning buildings. This will teach them to be more sensitive designers and also to make better products for their clients. If they did this systematically on a large scale, it would truly ennoble the profession. Some, possibly most, of the feedback and learning require nothing more than careful observation. Lighting, for example, is easily appraised with an informed eye. However, some of the feedback and learning must be based on measured data, since you cannot see energy flows or occupants’ discomfort. Having measurements, one can make really valuable scientific defensible claims. And after that, professional researchers can use such data to do even more generalized research. Fortunately, the LEED process is pushing the profession in this pragmatic direction. With increasing experience, practicing architects will in my view begin to become more scientific in attitude, without in any way diminishing their creative gifts or abilities.

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and codes are a part of our craft; even if it may provide additional challenges, the best designs are responses to complex challenges. There has long been more innovative collaboration between architects and structural engineers, simply because both produce visual results. There has been less synergistic collaboration with mechanical and lighting engineers, because on the one hand energy flows and comfort are less readily visualized, and on the other, defects in lighting are so easily concealed by the tricks of architectural photographers or computer renderings. Yet this collaboration is equally or more important in the design of quality buildings.

As someone who is part of an academic institution as well as a researcher, what changes to architectural education will help to foster an evidencebased design approach?

ARENS INTERVIEW

Academic programs in architecture would benefit from a greater mix in faculty skills; this was the great contribution of the Bauhaus teaching model. Beyond design theory, students would benefit from being exposed to those who can: build advanced buildings, teach superior building craft skills, and explain building performance and its impact on occupant performance. The latter people should also be able to teach students how to observe and measure performance in real buildings.

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A RENS C ASE S TUDY Air Quality and Thermal Comfort in Office Buildings: Results of a Large Indoor Environmental Quality Survey The University of California, Berkeley, Center for the Built Environment (CBE) has developed a web-based survey of occupant satisfaction in buildings that is used to establish performance benchmarks for office buildings. With a database of 65,000 completed surveys, it is possible to quantify the characteristics of high- or low-performing buildings. A foundation of information developed from dependable research should be a starting point for creative thought. I suggest that architects begin to address themselves to getting proper feedback from functioning buildings. Edward Arens, PhD, Director of the Center for the Built Environment

What was the research or critical question in this project? Indoor air quality and thermal comfort are two important aspects of indoor environmental quality that receive considerable attention by building designers. International and regional standards prescribe conditions intended to foster environments that are acceptable to occupants. Although there is considerable field data on air quality and thermal comfort, there is far less data that assesses occupant satisfaction across a large number of buildings using a systematic method and using occupant opinions as a measure of building performance.

ARENS CASE STUDY / Air Quality and thermal Comfort in Office Buildings

ARENS CASE STUDY

For the past several years, CBE has been conducting a web-based indoor environmental quality survey in office buildings. The anonymous, invite-style survey measures occupant satisfaction and self-reported productivity with respect to nine environmental categories: office layout, office furnishing, thermal comfort, air quality, lighting, acoustics, cleaning, maintenance, and overall satisfaction with building and workspace. The questions asked in the survey have remained consistent over time to create a standardized database for benchmarking and analysis.

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What were the research or investigative methods used in this project? The primary research methodology included the development of a social scientific questionnaire that was used to survey a large, 34,169-person sampling in a diverse number (215) of buildings. The building locations provided geographic dispersion throughout North America and Finland; 90 percent being located in the United States. Eighty percent of the buildings were owned or leased by a governmental agency and housed office workers. The questionnaire, providing self-reports of satisfaction or productivity, used a 7-point semantic differential scale with end points of “very dissatisfied to very satisfied.” The scale was assumed to be roughly linear with ordinal values assigned to each of the points along the scale. In the event where a respondent voted “dissatisfied” to a satisfaction question on the survey, they were taken to a follow-up page containing drill-down questions about the source of dissatisfaction and a text box for openended comment. If the drill-down questions and answers were inconclusive, field observation and measurements into those specific areas in question were possible as a second research methodology. The survey was taken across seasons but the majority of responses in the database were collected during the summer season. The average response rate was 46 percent.

What were the outcomes of the investigations? Thermal Comfort: Overall, more occupants were dissatisfied (42 percent) than satisfied (39 percent), with 19 percent of occupants neutral. The surveys showed that in just 11 percent of the (215) buildings, 80 percent or more of the occupants were satisfied with temperature in the workplace. Based upon diagnostic follow-up questions about the sources of dissatisfaction, the most frequently cited problem was the lack of adequate control of temperature. Of particular note is that 76 percent of all occupants with a thermostat were satisfied with the temperature in their work space as opposed to 56 percent satisfaction for those without a thermostat. Operable windows significantly increased satisfaction with temperature. One striking result is that there were approximately the same number of hot and cold complaints in warm weather. This suggests that there may be a large potential to im-

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prove comfort and reduce energy in those buildings with a significant number of cold complaints in warm weather. Air Quality: Unlike thermal comfort, 45 percent of occupants rated the air quality as satisfactory or better, and 32 percent less than satisfactory. Of those who rated the air quality as less than satisfactory, 74 percent rated the air as “stuffy/stale,” 67 percent as “air is not clean,” and 51 percent as “smelling bad” (odor). The average air quality satisfaction vote for occupants with operable windows was 0.48 compared to 0.14 for those without operable windows. Productivity: The basic question asked was: “Overall, does the air quality in your work space enhance or interfere with your ability to get your job done?” The survey found a very high correlation between satisfaction ratings and self-assessed productivity impacts. Summary Discussion: With respect to thermal comfort and air quality goals set out by standards, many buildings appear to be falling far short. ISO Standards recommends acceptable conditions in which at least 90 percent of people are satisfied with their thermal environment. ASHRAE standards define the same limits but recognize that local discomfort and asymmetries could produce an additional 10 percent dissatisfaction. The CBE survey results clearly indicate that much higher rates of dissatisfaction occur in buildings within the surveyed area with only 11 percent of the building having 80 percent or more satisfied occupants. The mean building satisfaction rate is 59 percent as compared to the ISO recommended 90 percent.

ARENS CASE STUDY / Air Quality and thermal Comfort in Office Buildings

ARENS CASE STUDY

Source of Case Study: Air Quality and Thermal Comfort in Office Buildings: Results of a Large Indoor Environmental Quality Survey.

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BRAGER INTERVIEW Gail Brager, PhD How can architects depend on intuition and experience for informed decisions since most architects don’t go back to ask questions or analyze how a building is working?

RESEARCH BACKGROUND

BRAGER INTERVIEW

Figure 4.6 Gail Brager

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Gail Brager, PhD, is a Professor at the University of California, Berkeley, Department of Architecture. She is also the Associate Director of UC Berkeley’s Center for the Built Environment, former Chair of the U.S. Green Building Council’s Research Committee, and one of 12 female ASHRAE Fellows, a distinction awarded to only about 1 percent of ASHRAE’s 49,000 members. The focus of her work involves research into thermal comfort, adaptation in naturally ventilated and air-conditioned buildings, and mixed-mode design strategies. For her work she has received: the Presidential Young Investigator Award from the National Science Foundation, a Progressive Architecture Research Award, the Ralph G. Nevins Award for general research in Thermal Comfort, the Crosby Field Award for a project on thermal adaptation, and numerous other awards. In addition to her research, she teaches courses in areas of energy and environmental management, sustainable design for hot climates, mechanical systems and architectural space-making, and research methods. Philosophically, she believes that what makes buildings memorable is less about the glossy images of their exterior but more for the experiences of people who live, work, or pass through the interior spaces. The environmental forces of sun, wind, and light have a strong influence on a building’s experiential aesthetic and the consideration of these forces should be a purposeful part of the earliest stages of design. Brager guides students to learn about principles, tools, and values that will enhance their ability to create buildings that are both beautiful and efficient, responsive to climate and people, sensitive to the environment, and a delight to be in.

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How do you use evidence in your work and what constitutes evidence? I must admit that I am amused by the notion of evidence-based design, which to me seems so obvious but the words and the semantics being used suggest that it is a new and novel concept. Design decisions should be based, in part, upon an understanding of how they affect performance, and you can describe “performance” in a very broad way. This has always required knowledge. In this regard, evidence-based design seems to be a new term for a timeless process. Even if designers base their decisions solely on intuition and experience, what do they use to inform intuition and experience? Evidence can be obtained from a wide range of sources. On the most simple level, evidence could be obtained by all members of a design team, and not just the architect, going back to a building and using a variety of means of finding out what is working and what is not. They can speak to occupants directly, or just observe and form their own opinions if they intend to inform their own intuition and experience in a very personal way. This is not research but is a very important and a useful means of gathering information or evidence which can inform personal intuition and experience. In a more detailed way, design team members can do their own physical monitoring or surveys, or review existing data gathered by others. The primary problem is that very few designers return to speak to clients or occupants to understand whether or not the building actually works as designed. Therefore, little feedback or knowledge is gained by the experience; this raises issues with depending solely on personal, yet often uninformed, intuition and experience, as is a tradition in design decision-making.

How is the evidence from research used to inform design? What are the implications of research for designers? Practitioners would like to know: What kind of evidence is needed, how much is enough, how much rigor is needed to be credible, accepted, and valued as evidence? The amount of research, or evidence, needed greatly depends on answers to: What

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BRAGER INTERVIEW

Since the concept of evidence-based design has its origins with evidence-based medicine, you might assume that the commonality of the two practice concepts is a mutual consideration of human health; in the case of evidence-based design, it is the health of the people in response to the built environment. At the Center for the Built Environment, we are concerned with understanding the impacts buildings have on both the people (health, comfort, well-being, productivity) as well as the natural environment (water, energy, climate change, resource use). The research is rigorous and provides evidence in a way that raises the bar beyond intuition and experience.

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question(s) you are trying to answer—what’s the design application? Can you take risks (hospitals must be risk-averse whereas a single-family residence may be willing to take more risk); how much time and resources are available to conduct the research? The research effort is related to the design application and occupant operational needs. Given the complexity of buildings, using a variety or broad spectrum of research approaches is often necessary:  Field studies: Provide a form of diagnostics, and can involve both physical

measurements and occupant surveys. While they are less controlled, the use of measurements and surveys in operating buildings is essential for understanding the impact of design decisions. A well-crafted study that is large in sampling includes statistical analysis, and observational techniques can provide diagnostic understanding of what is working, what is not, and the possible causes. Even a brief exploratory study can help prioritize (or narrow) the question or identify the problem for further focused study. Studies using standardized methods can establish benchmarks against which to evaluate future research outcomes for other buildings.  Laboratory experiments: Are more controlled, and are often designed to

investigate more narrowly bounded research questions where one can reduce or avoid the confounding factors. Sometimes the objective of these studies is to develop new tools and instruments which we can use in our own research, or perhaps introduce to practitioners for their own use.  Simulation and modeling: Provide feedback on very specific issues under controlled

BRAGER INTERVIEW

circumstances that can be varied. While there are limitations on being able to simulate real performance of complex buildings, the greatest value of this method is its ability to quickly compare alternative design or operating strategies while holding other factors constant.

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At the Center for the Built Environment, we like to use a combination of lab, simulation, and field studies to draw a full picture since there are pros and cons with each of the individual methodologies. Each is of value, each provides a piece of evidence, each is used to verify and question the results of the other. But in many cases, it is only the synergistic effect of using multiple methods of inquiry that gives you a complete picture.

Do you have a good model for interdisciplinary collaborations? Interdisciplinary collaborations are rich in concept but difficult in execution so you need to be specific about the context. One can be speaking about collaboration be-

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tween different professionals within the building industry, between researchers from different academic disciplines, or between researchers and practitioners. CBE is a good model of interdisciplinary collaborations at all these levels. Our industry partners include architects, engineers, contractors, developers, manufacturers, utilities, government organizations, and building owners; CBE provides a forum for their own discourse and collaboration in a noncompetitive environment when they can work with multidisciplinary researchers to identify the issues of concern to the industry. This early and open communication helps shape research projects that go beyond purely theoretical or philosophic questions, and ensures that research outcomes can get sent back to practitioners quickly. We jointly identify the low-hanging fruit and try to move quickly to meet the needs of the practitioner. In turn, the practitioners learn about research methodology and acquire tools that they can use on their own. Lastly, we exchange hats and some of our industry partners often work directly with the researchers on specific projects.

Looking forward, what changes would you make to the academic curriculum to enhance the use of evidence-based design?

BRAGER INTERVIEW

It seems that students at both the undergraduate and graduate levels are actively seeking more interdisciplinary education and understanding of sustainability, and this can simultaneously be informed by, and in turn benefit, evidence-based design thinking. It appears that interdisciplinary collaborations are best and easiest to achieve if centered around a focused topic such as sustainability, or digital media, in the case of Berkeley. At UC Berkeley, we are developing a graduate certificate program in sustainability which brings together Architecture, Engineering, Business, and Energy Resources. Interdisciplinary collaborations will provide multiple insights from varied perspectives in addressing complex issues posed by building design.

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GAGE INTERVIEW Dr. Fred (Rusty) Gage, PhD Scientists believe that evidence should be at the core of every decision we make so it is the empirical approach of collecting information that constitutes, or consolidates, evidence for a hypothesis.

For those of us who are scientists, without evidence, we are not scientists. Evidence and facts are not luxuries. You don’t know what creativity is unless you have examined the facts. Without the facts, how will you know that what you are doing hasn’t already been done by others?

RESEARCH BACKGROUND

GAGE INTERVIEW

Figure 4.7 Rusty Gage

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Rusty Gage is Professor and Vi and John Adler Chair for Research on Age-Related Neurodegenerative Diseases, Laboratory of Genetics at the Salk Institute for Biological Studies in La Jolla, California. He is a neurobiologist and neuroscientist who concentrates on the study of the adult central nervous system and the unexpected plasticity and adaptability to environmental stimulation that remains throughout the life of all mammals. His work may lead to methods of replacing or enhancing brain and spinal cord tissue lost or damaged due to neurodegenerative disease or trauma including stroke, Alzheimer’s Disease, Parkinson’s and Huntington diseases, leukemia, and lymphoma. Gage’s lab showed that, contrary to accepted dogma, human beings are capable of growing new nerve cells throughout life. Small populations of immature nerve cells are found in the adult mammalian brain, a process called “neurogenesis.” Gage is working to understand how these cells can be induced to become mature functioning nerve cells in the adult brain and spinal cord. They showed that environmental enrichment and physical exercise can enhance the growth of new brain cells and they are studying the underlying cellular and molecular mechanisms that may be harnessed to repair the aged and damaged brain and spinal cord.

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In addition to being a Fellow of: (1) The National Academy of Science, (2) The Institute of Medicine of the National Academy of Science, and (3) The American Academy of Arts and Science, Gage has been honored with numerous prizes, awards, and recognition. He is acknowledged as one of the most innovative, original-thinking, productive researchers and leaders in his field. In a 2005 article, Science Watch notes that Rusty Gage is ranked second in the Essential Science Indicators (ESI) web product listings of the hottest researchers in neuroscience and behavior, with more than 10,000 total citations. He has the single highest citation average per paper of anyone in the field as tracked by ESI—averaging some 90 citations for each of over 100 articles since 1995. Gage served as president of the Society of Neuroscience in 2001. Because of his interest in the brain’s plasticity and adaptability to environmental stimulation, he was elected to lead the Academy of Neuroscience for Architecture (ANFA) as its Chairman from 2004 to 2006. He shares with architects a keen interest in human response to environmental stimuli.

As a scientist, what constitutes evidence? How rigorous does the research have to be? How is evidence developed and how do you use it to inform issues of your concern? As a scientist, I believe that evidence should be at the core of every decision we make. It is the empirical approach to collecting information that would constitute, or consolidate, evidence for a hypothesis. For those of us who choose science as our vocation, without evidence, we are not practicing science. As a scientist, we utilize a series of research steps that are critical to gaining evidence. They are the essence of any empirical research process. These steps are at the heart of the credibility, dependability, and relevance of an empirical research finding. In general, the methodology includes:

that is existing on a subject, whether good, bad, strong, or weak. A thorough literature search is important to establish what is known, what is commonly understood to be the current state of understanding, and to identify where gaps in understanding exist.  Establish a hypothesis: For a scientist, establishing a hypothesis is perhaps one of

the most creative activities. Identifying the correct question to be asked, properly defining its boundaries, and clearly defining how testing this hypothesis will add

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 Literature search: Look at (as much of it as possible, if not all) the material

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to the larger body of knowledge. This development of a hypothesis will determine what it is that needs to be tested.  Test the hypothesis: The experiment must be doable; meaning that the test

outcomes must be measureable and the tools needed to test must either be available or able to be developed. For scientists, the ability to know what and how to measure is a great opportunity for creativity; establishing appropriate control groups and mechanisms, understanding statistical probability ratios, significant effects and reliability quotients as well as ensuring that the tests can be repeated are critical considerations in testing a hypothesis.  Interpretation of results: Again, a creative activity for scientists is the interpretation

of results, establishing the significance relative to the larger scope of issues to be studied. This process is similar to participating in finding another piece of a large puzzle.

You have described a very prescriptive process, does this empirical process enhance or inhibit creative thought? Clearly as a scientist, I am an advocate for: (1) rigorous experimental procedures, and (2) the need to measure outcomes in a quantitative manner. I believe that decisionmaking is enhanced by the creativity in defining the question, creating proper tools and measurement standards, as well as interpretation of results; all of these activities are important to creative thinking and coming up with better results. I think that “constraints” are lynchpins, or connectors, to creativity.

GAGE INTERVIEW

More evidence results in more sophisticated knowledge which in turn results in more creative solutions. Evidence and facts are not luxuries. You don’t know what creativity is unless you have all of the facts. Without the facts, how will you know that what you are doing hasn’t already been done by others? For scientists, creativity and discovery are integrally linked in both the process of exploration as well as the joy of finding an explicit outcome.

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In the process of experimentation and exploration, how much is done as interdisciplinary collaborations? As scientists, all of us have “drunk the Kool-Aid” therefore, use of the empirical research processes provides a baseline of understanding that permits interdisciplinary collaboration; each bringing his, or her, own perspective. The keys to interdisciplinary collaboration require an understanding of where differences of opinion lie, ensuring that there is consensus around a common question, and agreeing on the metrics of

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the study that would be useful to all collaborators. Attitudinally, collaborations are most successful when one model of research or measurement is not forced onto the others and when one scientist does not attempt to change the others’ behavior; rather, use the others’ skill set to serve your interests.

Given the characteristics and differences between the natural and physical (“hard”) sciences and architecture that you have described, do you see any implications of utilizing a more empirical approach to design? Use of scientific research methodologies hold great promise for architects interested in understanding how human response can inform design decisions. With current knowledge and resources available, it is possible to conduct research which will provide physiological feedback of human response to specific environmental stimuli. While the capability is here, the rigorous research has not been done at this time. Some changes in the professional and educational culture of architecture may be needed before the empirical process of decision-making begins to make sense in a way that is comparable to your current use of intuition and experience. However, this may not be a far reach since much of how architects currently develop innovative technological approaches to how you design buildings are well-researched and utilize an evidential/empirical decision-making process. My experience with some of the leading designers, like Frank Gehry, is that they currently utilize well-researched methodologies with computer modeling but don’t regard this as research.

Architects shouldn’t be concerned about losing their creativity if they add some aspects of empirical research to their intuition and experience. The added knowledge merely creates a reasonable framework, a clear definition of the question to be explored thus freeing the mind to focus creatively. This process of working within known frameworks (site topography, climate, building technologies, budget, codes, etc.) is already a part of the (informed) intuition-based architectural profession.

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The gap in the use of research and evidence lies primarily in the area of understanding human response to environmental stimuli rather than in building science and technology. This is an area of interest for the architects and scientists who are participating in the work of the Academy of Neuroscience for Architecture (ANFA).

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STERNBERG INTERVIEW Dr. Esther Sternberg, M.D., Neuroscientist All forms of evidence are valid and critical in providing yet another important perspective of the investigation. If you discount one approach as being less valid then the next, you run the risk of missing an entire body of information, especially when dealing with hypotheses of complex phenomena.

I consider architecture to include issues of complex phenomena because it is dealing with design decisions affected by multiple factors.

RESEARCH BACKGROUND

STERNBERG INTERVIEW

Figure 4.8 Esther Sternberg

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Esther Sternberg is an M.D. with a specialization in Rheumatology. She is currently Chief of the Section on Neuroendocrine Immunology and Behavior at the National Institute of Mental Health (NIH). She is also director of the Integrative Neural Immune Program, NIMH/NIH and a co-chair of the NIH Intramural Program on Research in Women’s Health. Dr. Sternberg has served as a member of the Board of Directors of the Academy of Neuroscience for Architecture (ANFA). Trained as a rheumatologist, and an expert in neuroendocrine immunology, her research focuses on studying hormones of the stress response and how they affect immune diseases like arthritis. When asked about her area of expertise, she notes: “…it is about the connection between the brain and the immune system. So basically it is about how the brain talks to the immune system and how the immune system talks to the brain, and understanding how those connections play an important role in health—in maintaining health and in preventing disease. When those connections are broken, you get disease, and when you maintain those connections, you get health.” She notes that one of the most exciting research opportunities looking forward is “the ability to link complex phenomena—like psychosocial events to molecular and cellular events—at the level of, for example, tumor biology,

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or at the level of allergic or inflammatory disease.” In her interview comments that follow, and our own interpretation of her comments, we note an attitude that does not rely on the predilection of “hard science” for stricter controls—neither in defining what constitutes evidence nor the amount of control exerted in gaining the evidence despite the fact that her own background is as a biological scientist. Dr. Sternberg believes equally in the validity of a broad spectrum of research approaches. She defines credibility of evidence in a manner that does not equate validity of outcomes to “total control” of research methodology. She is equally comfortable with standard research approaches in the psychosocial sciences, as well as with laboratory studies at the molecular and cellular level.

Unlike most natural or physical scientists, including neuroscientists, you define “evidence” much more broadly. Can you speak more about your perspective of what constitutes evidence? My background in research—linking body and mind and undertaking research to address complex phenomena—strongly influences my perspective of what constitutes evidence, how evidence is obtained, and its ultimate real-world applications.

Assuming all methodologies are undertaken utilizing established, standard, institutional protocols and addressing institutionally acceptable criteria, then all forms of evidence are valid and critical in providing yet another important perspective of the investigation. If you discount one approach as being less valid than the next, you run the risk of missing an entire body of information, especially when dealing with hypotheses of complex phenomena. I consider architecture to include issues of complex phenomena because it is dealing with design decisions affected by multiple factors—whole organism responses. I don’t believe that it is appropriate to simply use a biomedical model of research for studying the effects of architecture on health, since architectural researchers are working with total environments that are complex, multifaceted entities. My interest is in both: (1) the response of “the whole being” as well as (2) the causal effects of “the individual parts”—from the organism (a rat or human) to a molecule or cell. They reinforce an inseparable, interrelationship required of research with com-

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It is important to accept, and never denigrate, multiple research approaches in gaining evidence—including case studies (individual circumstances), surveys and questionnaires (large samplings), behavioral observations (in field, uncontrolled studies), and laboratory experiments (randomized, controlled studies).

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plex phenomena. Likewise, depending upon whether the question being asked is related to the “whole or the part,” one or another of the multiple research methodologies may be more appropriate. All evidence can be contributory and all methodologies equally relevant depending upon the question being asked, the resources and skills available to the researchers, and expectations of a real-world application. [Current panel discussions with which Dr. Sternberg is participating continue to redefine what constitutes evidence and how it is gathered in real life.]

When are interdisciplinary collaborations most appropriate within your broad spectrum of developing evidence? Inherent in my belief in gathering and using various methodologies of research to gain evidence, is the importance of interdisciplinary expertise and collaboration: their value is never in question. Gaining input from psychologists, sociologists, toxicologists, chemists, biologists, and many subspecialists is inherent in moving from “whole to part to whole” in the investigative processes of mind and body and in determining cause and effect. Using interdisciplinary collaborations is like the work of a lawyer, where there is no one piece of evidence that is strong enough but if you can piece together multiple pieces from various perspectives, you can create a story that proves or strongly supports a theory.

STERNBERG INTERVIEW

By using a broad spectrum of research approaches, what are the implications for design?

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As a past Board Member of the Academy of Neuroscience for Architecture (ANFA) and the mother of a daughter trained in architecture, I am no stranger to the profession of architecture and design innovation. I believe in the validity of the full range of research methodologies, and that architectural research may be best approached from an epidemiological* model rather than a biological model; no less rigorous in adherence to standards and criteria of methodology, similarly subject to protocols and peer review and equally valid in its credibility. * Editor’s note: A dictionary definition of epidemiology is: “The study of factors affecting the health and illness of a population, and serves as the foundation and logic of interventions made in the interest of public health and preventative medicine…including study of outbreak investigation, design of the study, establishment of a hypothesis, data collection, analysis, statistical modeling, testing of hypothesis, documentation of results and peer review for publication.”

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Epidemiologists are said “to employ a range of study designs from the observational to experimental and are generally characterized as descriptive, analytic (aiming to further examine known associations or hypothesized relationships), and experimental (a term often equated with clinical or community trials of treatments and other interventions). Epidemiological studies are aimed, where possible, at revealing unbiased relationships between exposures such as alcohol or smoking, biological agents, stress, or chemicals to mortality or morbidity. Identifying causal relationships between these exposures and outcomes are important aspects of epidemiology. Modern epidemiologists use informatics as a tool. The term “epidemiologic triad” is used to describe the intersection of “host, agent, and environment” in analyzing an outbreak. I believe that architectural research and epidemiology have similarities because of their need to look: (1) broadly at multiple affects (complex organisms), as well as (2) specifically at environmental stimuli (causal interventions) such as changes in lighting, acoustics, scale, proportion, texture, etc. within a specific setting or context. [Editor’s note: It is important to define the differences between the current state of architectural research and scientific research. The differences are as follows:]  Today, the architectural profession lacks definable standards and criteria that

 For any architectural research undertaken, there is no established methodology

or protocol, such as peer review prior to publication, to ensure that the study has been undertaken within well-defined processes. The profession does not have the equivalent of the New England Journal of Medicine or the Journal of American Medical Association (JAMA). As a result, doing a literature search, one of the first steps in scientific research, is virtually useless in architectural research since what you will find is undependable.

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must be met to be considered as valid research. In most scientific fields, the research standards and criteria are well-defined and generally understood and adhered to by all researchers, irrespective of the category of science and methodology used to undertake the research. In the sciences, there is never a question of whether the methodology is adequately rigorous as long as it meets the established standards and criteria. Thus, each piece of scientific research is “nested” into a larger body of knowledge. Lacking in standards and criteria, architectural “research” is undependable and often lacking in credibility. There is no nesting, or building upon, a prior piece of dependable architectural research.

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 Irrespective of its utility or value, most architectural research is undertaken for

competitive advantage and not shared; either between practices or between industry (manufacturers and other disciplines such as engineering or construction) collaborators. The profession’s primary source of research information is undertaken to model code compliance, material, product or system testing compliance. Other than these prescriptive requirements, there is little “lateral” knowledge gained or transferred from project to generalized knowledge that benefits the profession.  Beyond the generation of valued research, the architectural profession currently

does not have an organization or technical mechanism to categorize, store, retrieve, and mine data.

STERNBERG INTERVIEW

Dr. Sternberg’s comparison of architectural and scientific research has helped to formulate much of our own thinking about the challenges facing the use of research in an evidence-based design education and practice.

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Lessons Learned The Physical Sciences: Building Performance

personal intuition and experience as a tradition in design decision-making. (G. Brager and E. Arens) 

Evidence is gained from a wide range of sources. At the Center for the Built Environment (CBE) we like to use a combination of field observations, user surveys, laboratory experiments, computer simulation, and modeling studies to draw a full picture since there are pros and cons with each of the individual methodologies. Each is of value, each provides a piece of evidence, each is used to verify and question the results of the other; individually, each must be taken with a grain of salt and none individually gives you a complete picture. (G. Brager)



In research, the physical sciences represent the building and the social sciences represent the occupants. Architecture has a strong relationship to various forms of science and it is possible to do research that must meet a scientific standard. Otherwise it isn’t worth doing. But with increasing experience, practicing architects will be able to use scientific foundations in research without diminishing their creative gifts or abilities. (E. Arens)



It’s our belief that the use of evidence should not be used as a prescriptive rule book and that use of an evidence-based design process will not provide definitive answers. Instead evidence provides a foundation for a hypothesis; establishing what is known, what and where to explore for innovation. It is this later opportunity that adds to creativity. (V. Loftness)

Looking back, we are easily reminded of the strong influence that the physical sciences have had on the design of buildings. Evident from our interviews, that tradition continues and into the future could prove to be the source of the most powerful evidence for innovative, informed design. Research advances are being driven by a desire to define the standards for higher building performance. GIVEN THE POLITICAL, SOCIAL, FINANCIAL, AND ETHICAL SUPPORT FOR SUSTAINABLE DEVELOPMENTS, IT IS NO WONDER THAT MANY OF THE MOST INNOVATIVE BUILDING PERFORMANCE STUDIES CENTER AROUND ISSUES OF ENERGY CONSERVATION, USE OF RENEWABLE RESOURCES, AND THERMAL COMFORT.

Edward Arens and Gail Brager, from the University of California, Berkeley, Center for the Built Environment, and Vivian Loftness, from Carnegie Mellon’s Center for Building Performance and Diagnostics, provide the following key thoughts: 

Architects have failed to differentiate for the public an understanding of what constitutes high-performing versus low-performing buildings. Lacking that understanding, preferences for building design or purchases are made for reasons other than the performance of the building; thus diminishing the value and contributions of the architect and design. (V. Loftness)



The primary problem is that very few designers return to speak to clients or occupants to understand whether or not the building actually works as designed. Therefore little feedback or knowledge is gained by the experience; this raises the issue of whether it is appropriate to depend on

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The Physical Sciences: New Material Development THIS TYPE OF WORK RELATED TO THE PHYSICAL SCIENCES IS BEING STRONGLY INFLUENCED BY FIRMS COMMITTED TO INNOVATIVE DESIGN EXPRESSION. TECHNOLOGICAL

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fact, and metrics to provide proof just as you would in any scientific process. (J. Timberlake)

ADVANCES ARE ATTRIBUTABLE TO SUSTAINABLE DESIGN PRACTICES, STRUCTURAL ENGINEERING FEATS, AND NEW METHODS OF CONSTRUCTION SEQUENCING AND FAB-



There is an important distinction between the meaning of “research” and “evidence.” Research is the process of looking or searching for different solutions. Evidence suggests that something is evident or obvious, that it is already seen in relation to a given problem. For us, design always begins with research, with the task of searching to define a given problem and to discover different ways that it can be addressed in design. The importance of intuition in the creative process can’t be underestimated; it is one of the major assets of architecture as a creative discipline. As a starting point, we outline hunches then test our intuitions by working with a process of rapid prototyping and by examining the basic implications of an idea and checking it against our experience and what is already known. (S. Kennedy)



Research is an iterative process; a process of refinement of information, data, analysis, new information, looking, and exploring. (J. Timberlake)



As architects, we should not be attempting to promote design using metrics. It would be naïve to think that numbers and statements used in metrics are purely factual or even objective; they are created according to various perspectives. We don’t start with, nor do we focus our design process on metrics—we try to develop design that emphasizes qualities that are unique to the medium of architecture. (S. Kennedy)

RICATION. THESE HAVE SPARKED A SURGE IN THE CREATION OF NEW MATERIALS AND BUILDING SYSTEMS…

and more. This type of research is being pursued to attain greater architectural design freedom, invention, and innovation. New building technology and material development is the means rather than the end, and the results are often spectacular. Sheila Kennedy and James Timberlake provided these key thoughts: 

We launched our material research unit MATx in 2000, because we realized that the need to design and integrate energy-efficient digital technologies in building projects places a great demand for vertical integration in architecture… We have literally created a studio space which enables us to integrate research and design. (S. Kennedy)



We dedicate four professionals and 3 percent of our gross revenue to research. (J. Timberlake)



Our research often explores how to make the best use of young and sometimes underperforming new technologies. Our interest in making things has led us to combine new materials with familiar materials such as brick, glass, or textiles. By combining new technologies with traditional materials, the fundamental nature of both “old” and “new” materials is transformed. By creating integrated, composite materials and building components that provide new capabilities, we can move on past the modern architectural distinctions between “high” and “low” or “smart” and “dumb” technologies. (S. Kennedy)



Architecture is alchemy. It is a combination of art and science. The science portion requires data,

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Transmaterial One and Transmaterial Two by Blaine Brownell catalogs innovative materials uses, properties, and sources. Brownell highlights “composite,” “intelligent,” “multidimensional,” “recombinant,” “repurposed,” and “ultra-performing” materials. Many, such as carbon fiber, ceramic, felt, foam, polymer, and porcelain, are commonly known but are being recast for new design uses.

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“MAKE IT WORK—Engineering Possibilities,” the January 2009 exhibit at the Center for Architecture in New York, provided additional examples of current materials research and the recasting of known materials in new ways to harvest or manage energy in a world of dwindling global resources. Highlighted in this show are: 

Membrane Systems: Thin polymer membranes called ETFE (ethylene tetrafuoroethylene) used in combination with tensile or space frame structures.

 Figure 4.9 Combining Membrane System with Space Frame Structures

 Figure 4.10 Membrane Systems Provide Translucency

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Actuated tensegrity: Use of sensors and actuators in structures and surfaces to create movement in response to changing environmental conditions; not only facades that respond to sunlight but also tall buildings that bend, twist, and undulate in response to wind.

Figure 4.11 Sensors Trigger Structural Response to Changing Wind Conditions

Figure 4.12 Mock-Up of Actuated Tensegrity

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Aegis hyposurfaces: Interactive surfaces using digital processing technology to control thousands of individually actuated panels; all of which can move independently when triggered by sound or movement.



Smart Wrap Photovoltaic Panels or Soft Wrap Fiber: Use of photovoltaic or semiconductors integrated with glass or fiber curtains to provide vertical enclosure to buildings while generating and harvesting energy.

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 Figure 4.13 Example of Digitally Processed Technology to Control Actuated Panels

 Figure 4.14 Proposal by Kieran Timberlake for a Smart Wrap Building Facade

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 Figure 4.15 Proposal by Kennedy Violich/MATx for a Soft Fabric Wrap Facade.

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 Figure 4.16 Ductal Concrete Used to Provide Lightweight, High-Performance Forms

 Figure 4.17 Fiber Reinforced Polymer Providing Sheer and Tensile Strength; Proposal for the Effiel Tower  Figure 4.18 Lightweight, Long-Span Structure Using Fiber-Reinforced Polymer 

Ductal Concrete: Fabrication of walls that are lightweight, ultra-high-performance fiber-reinforced material with over ten times the strength of conventional concrete yet lightweight and comparable to steel.



Litracon: Translucent concrete made from a matrix of glass fiber as an aggregate.



Structural Glass: No longer simply structural vertical panels but now used as resin-laminated beams, columns, and tubes. The tubes are architectural needles made of borasilicate glass pipes composed of two layers of glass that have been precompressed and are able to withstand wind loads of 50 to150 square meters.



Fiber-Reinforced Polymer: A combination of resin, providing sheer strength and fiber which provides tensile strength that can be formed into any shape.

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Hydrogen-Producing Algae Glass: Used to produce solar energy harvesting by using algae to produce hydrogen through the process of photosynthesis. A fuel cell is situated on the top of each tube which connects hydrogen to electrical current.



Hybrid Structures: Figs 4.19, 4.20

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THESE INNOVATIONS ILLUSTRATE NEW MATERIALS RESEARCH AND DEVELOPMENT METHODS, NEW PROCESSES FOR DESIGN AND CONSTRUCTION. FUELING INNOVATION IS AN INCREASE IN COLLABORATIONS BETWEEN ARCHITECTURE AND DISCIPLINES NOT TRADITIONALLY PART OF DESIGN TEAMS; AS WELL AS COLLABORATIONS OF (ACADEMY) RESEARCHERS, MATERIAL MANUFACTURERS, AND PRACTITIONERS. THESE BOUNDARY CROSSINGS WILL NECESSITATE NEW SKILLS, REEDUCATION, AND NEW PRACTICE MODELS. SMALL DESIGN-ORIENTED FIRMS, RATHER THAN THE LARGER FIRMS, APPEAR TO BE LEADING THE WAY WITH THESE NEW WAYS OF WORKING: THE PRINCIPALS OF THESE FIRMS SEE THE RESEARCH AS INTEGRAL TO THEIR DESIGN EFFORTS AND THE EXPERIMENTATION IS OFTEN MADE POSSIBLE BECAUSE OF THEIR COMMITMENT TO TEACHING AND AFFILIATION TO AN ACADEMIC INSTITUTION.

 Figure 4.19 Modeling of Hybrid Structures to Produce Efficient and Environmentally Responsive Structures

 Figure 4.20 Modeling of Hybrid Structures to Permit Design Expression

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The Natural Sciences: Neuroscience Until the recent emergence of neuroscience as a source of evidence for design the natural sciences have not played a major part in informing our understanding of the human performance within our built environments. That has now changed with neuroscientists and architects seeking a biological basis to comprehend how and why design affects people. Neuroscience will help designers understand—even predict—how people will feel and behave when confronted with specific environmental characteristics. The specialized and complex nature of this type of research makes its meaning and practice beyond the reach of most practitioners in the near term. Yet, with time, when a richer database has been built, the information will be accessible and applicable to all practitioners. Then, as a profession, we will be able to SEIZE THE OPPORTUNITY TO DESIGN BUILDINGS



All forms of evidence are valid and critical in providing yet another important perspective of the investigation. If you discount one approach as being less valid than the next, you run the risk of missing an entire body of information… especially when dealing with hypotheses of complex phenomena. I consider architecture to include issues of complex phenomena because it is dealing with design decisions affected by multiple factors. (E. Sternberg)



The key to interdisciplinary collaboration requires an understanding of where differences of opinion lie, ensuring that there is consensus around a common question, and agreeing on the metrics of the study that would be useful to all collaborators. Attitudinally, collaborations are most successful when one model of research or measurement is not forced onto the others and when one scientist does not attempt to change the others’ behaviors; rather, use the others’ skill set to serve your interests. (R. Gage)



I don’t believe that it is appropriate to simply use a biomedical model of research for architecture since architectural researchers are working with total environments which are complex, multifaceted entities. I believe in the validity of the full range of research methodologies, and that architectural research may be best approached from an epidemiological model rather than a biological model; no less rigorous in adherence to standards and criteria of methodology, similarly subject to protocols and peer reviews and equally valid in its credibility. (E. Sternberg)

THAT AFFECT HUMAN PERFORMANCE AND CHANGE THE MINDSET OF “BUILDINGS AS AN END” TO “BUILDINGS AS A MEANS.” THE VALUE OF BUILDINGS WILL BE UNDERSTOOD TO ALIGN WITH THE CONTINUUM OF HUMAN OCCUPANCY, RATHER THAN THE SHORTER PERIOD OF DESIGN AND CONSTRUCTION FOCUSED ON THE BUILDING.

Interviews with leading neuroscientists Rusty Gage and Esther Sternberg provide hope that collaborative research between architects and neuroscientists is very realistic, in fact not very foreign to how architects currently design. Using information about the brain’s response will inform design decisions in a very pragmatic manner within the very near future. Some of their key thoughts: 

Evidence and facts are not a luxury. You don’t know what creativity is unless you have all of the facts. Without the facts, how will you know that what you are doing hasn’t already been done by others? For scientists, creativity and discovery are integrally linked in both process of exploration as well as the joy of finding an explicit outcome. (R. Gage)

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Other current initiatives add promise to prospects for linking neuroscience and architecture in the understanding of human performance: 

Organizations such as the Academy of Neuroscience for Architecture (ANFA) are critical in fostering collaborative research efforts between

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architects and neuroscientists. While each discipline brings traditional expectations of how their discipline operates, the new collaborative effort will result in a new set of standards, guidelines, and protocols which define how neuroarchitectural evidence is undertaken and applied to design practice. We suspect that it will be a hybrid of the social, natural, and physical scientific methodologies. The challenge for architects will be to establish a strong research culture; while neuroscientists will need encourage scientific rigor while also appreciating the importance of informed intuition and experience when applying evidence to design. 



In addition to UCSD’s educational advances, encouraging research efforts are occurring there as the result of collaboration between the Division of Biological Sciences, the Swartz Center for Computational Neuroscience, and the Calit2 Virtual Reality Group. Dr. Eduardo Macagno, PhD and 2009 Chair of ANFA, has served as the focal point of this project. A central goal of this work is to merge technologies that monitor human neurological and physiological variables (brain electrical activity, eye and body position and orientation, heart rate, skin conductivity, etc.) with cutting-edge 360-degree immersive Virtual Reality (VR) technologies. The intent of this merger of technologies is to quantitatively and objectively measure responses of people moving through and interacting with real built environments, in real time.



Dr. Magno notes: “The technical difficulties inherent in obtaining real-time measurements of neurological and physiological variables in freely behaving individuals experiencing a built environment are not trivial: it is hard to build a good EEG cap, to find a terrific VR environment, to interface the two and then to interpret the data accurately in a meaningful way, but the expertise and advanced instrumentation to do this are currently available at UCSD.”



The prototype is up and running and they are beginning to acquire baseline data. The initial stages of the project have been focused on developing a time-locked, real-time interface between the VR equipment and the neurological/physiological instruments, particularly the high–definition electroencephalographic (HDEEG) multielectrode cap with wireless telemetry, in order to correlate the recorded data on human physiological and behavioral responses to the specific VR representations that evoked such responses.

THE POTENTIAL OF NEUROSCIENCE IS GREAT BUT THE STEPS THAT ARE NEEDED IN DEVELOPING RESEARCH CULTURE IN NEUROARCHITECTURE WILL BE CHALLENGING. Standards of research quality,

protocols for development and review, a structure to save and access data, funding to undertake research, an organizational structure for research to occur and be shared between academia, firms, and clients as well as a consistent and dependable mechanism of distributing and sharing knowledge are all essential. All of this will require a generation of newly educated practitioners to achieve progress. ANFA continues to support interdisciplinary educational programs between architectural students at the New School of San Diego and neuroscience students at the University of California, San Diego (UCSD). ANFA is starting to see the first generation of research interns of approximately six to eight recent graduates from programs around the United States, who have a combined background in architecture and neuroscience. Their influence will be significant and will accelerate the understanding of neuroarchitecture as a field of design practice and research.

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At Stanford University, neuroscientist and Director of their Bio-X Program and Professor of Biological Sciences and Neurobiology Carla Shatz, is exploring relationships among experiences, learning, and effects on the brain. Her hypothesis is that experiences (the domain of architects) alter brain circuitry. Her research shows that our experiences change our brain circuits during early critical periods of learning and development. Her neuroscience research has advanced the understanding of how the eye and the brain become properly connected during early life. She was the first to observe how, during fetal development, the eye tests its connections to the brain’s visual processing regions by sending and resending waves of electrical activity through nerve cells across the retina. Also at Stanford University, Krishna Shenoy, Associate Professor of Electrical Engineering and Bioengineering and Head of the Neural Prosthetics Systems Laboratory conducts neuroscience and neuroengineering research to better understand how the brain controls movement, and to design medical systems to assist those with movement disabilities. His neuroengineering research investigates the design of highperformance neural prosthetic systems, which are also known as brain-computer interfaces and brain-machine interfaces. These systems translate neural activity from the brain into control signals for prosthetic devices, which assist disabled patients by restoring lost functions. The work is in the final clinical stages and will be made available to patients sometime within the next two years.

From these and many other research explorations, the future of neuroarchitecture shines brilliantly. Neuroscience promises to be an influence on design and human performance that hasn’t been seen in decades.

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Application to Architectural Research and Practice Reviewing the perspectives of our interviewees and the current work of scientists, it becomes increasingly evident that discussions about physical science and natural science should be separated rather than combined in relationship to their impact on architecture. THE USE OF EVIDENCE AND RESEARCH IN THE PHYSICAL SCIENCES IS HERE AND NOW. HOWEVER, THE USE OF EVIDENCE AND RESEARCH IN THE NATURAL SCIENCES (NEUROSCIENCE) WILL REQUIRE LONGER-TERM INVESTMENT AND SIGNIFICANT CHANGES IN EDUCATION, RESEARCH COLLABORATIONS, AND PRACTICE MODELS TO ACHIEVE ITS FULL POTENTIAL.

The goal of most architects will be to utilize evidence from research to enhance their design work, not ot become a researcher. However, architects will need to understand research methodologies, opportunities, limitations, constraints, and protocols, in order to determine which data to use and how to apply it in their design context. The people we interviewed made some insightful comparisons between science and design. 

Both physical and natural science retain a traditional reliance on the use of an empirical approach characterized by (1) the use of controlled laboratory experiments, (2) emphasis on quantification (metrics), and (3) investigation at the most basic scientific level (atomic, cellular, molecular).



These defining traditions of the sciences make strict application of scientific research standards problematic and unrealistic when directly applied to architectural research.



ARCHITECTURE IS BOTH ART AND SCIENCE. IT SHOULD NOT BE EVALUATED BY ONLY ONE OF THE TWO BUT MUST BE INTEGRATED IN THOUGHT AND VALUE.

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Architecture must consider the “whole organism” (building) rather than just the individual, singular, most basic of elements (light, acoustics, scale, proportion, etc.) of which it is composed; context is important in architecture thus impeding control of variables.

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sistent and dependable “feedback loop” of understanding, measuring, and analyzing actual building and human performance. 

UTILIZATION OF MULTIPLE RESEARCH METHODOLOGIES TO REAFFIRM, DISPEL, OR ADD NEW INFORMATION TO INDIVIDUAL RESEARCH APPROACHES

Additionally, interpreting metrics obtained from the individual parts into a meaningful whole becomes a complex process in and of itself. More appropriately, architectural research requires an iterative process of examining “whole to part to whole”; made complex as a result of the confounding variables.

WILL CREATE A HYBRID MODEL WHICH IS NEITHER

The vast majority of the architectural designers who we interviewed used a combination of methodologies, such as sophisticated surveys and field measurements, to obtain occupant feedback, before undertaking controlled laboratory experiments utilizing instrumentation and high levels of quantification. In all circumstances, architectural researchers utilized a significant effort of data mining.

INTUITION AND INFORMED EXPERIENCE.



Unlike scientific researchers who begin with a literature search as a part of data mining, architectural researchers rarely depend on a literature search since standards of publication are undependable as to credibility. The data mining used by our interviewees often referenced established code or performance guidelines established by public agencies or in-field performance measurements of specific building types as a foundation for data mining. Many depend upon the expertise of interdisciplinary collaborators from scientific fields for generation of evidence.



In a few instances, firms are attempting to store and retrieve information from their own previous projects as a source of future personal knowledge. In most instances, the knowledge stored is of previous design criteria, rather than actual performance. Clearly, the profession lacks a con-

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STRICTLY IN KEEPING WITH THE SOCIAL SCIENCES, OR NATURAL OR PHYSICAL SCIENCE TRADITIONS.

ARCHITECTURAL RESEARCH TO INFORM DESIGN WILL BENEFIT FROM THE USE OF MULTIPLE RESEARCH METHODOLOGIES—BOTH QUALITATIVE AND QUANTITATIVE IN APPROACH, INCLUSIVE OF INFORMED

REFERENCES 1. Rita Carter, Mapping the Mind. Berkeley and Los Angeles: University of California Press, 1999. 2. Norman Doidge, M.D., The Brain that Changes Itself. New York: Penguin Books, 2007. 3. Esther Sternberg, M.D., Healing Spaces: The Science of Place and Well-Being. Cambridge: The Belknap Press of Harvard University Press, 2009. 4. From Wikipedia, the free encyclopedia: “Physical Science, Natural Science, Neuroscience, The Hard Science, Epidemiology,”http://en.wikipedia.org/wiki/physical_ science. 5. Massimo Pigliucci, Strong Inference and The Distinction Between Soft and Hard Science, Jan. 27, 2009: http:// www.scientificblogging.com/naturally_speaking. 6. From Wikipedia, AbsoluteAstronomy.com: Hard Science, 2009. http://www.absoluteastronomy.com/topics/hard_ science_fiction. Design Research Study 2006. 7. California State University Long Beach—PPA 696: Research Methods: Research Article Critique Form, PPA 697 Outline for a Research Prospectus and Steps in Empirical Research. http://www.csulb.edu/msainttg/ ppa696/696menu.htm 8. Vivian Loftness, Volker Hartkopf, Beran Gurtekin, Ying Hua, Ming Qu, Megan Snyder, Yun Gu, Xiaodi Yang, Building Investment Decision Support (BIDS). www.aia. org/aiaucmp/grupslek_public/documents/pdf/aiap080050. pdf www.aia.org/aiaucmp/grupslek_public/documents/ pdf/aiap080050.pdf

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9. C. Huizenga, S. Abbaszadeh, L. Zagreus, E. Arens, Air Quality and Thermal Comfort in Office Buildings: Results of a Large Indoor Environmental Quality Survey, Design Research Study 2006. 10. Eli Gottlieb, Erik Madsen, Zak Kostura, Rosamond Fletcher, Jonah Stern, Beth Stryker, Center for Architecture Exhibition titled “Make it Work.” Engineering Possibilities, January 2009. Public Exhibition, New York AIA Center for Design, 2009.

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11. Carla Shatz, and Krisha V. Shenoy, Conference on Leading Matters by Stanford University, 2009. Conference, Stanford University, San Francisco Moscone Convention Center, April 2009. 12. John P. Eberhard, “Architecture and the Brain 2007,” Brain Landscape, Oxford University Press, 2009 13. Eduardo Macagno on behalf of the University of California, San Diego (Division of Biological Science, the Swartz Center for Computational Neuroscience and the Calit 2 Virtual Reality Group): Navigation/Way Finding Project, Design Study March 2009.

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5 Putting It All Together Background and Context TO SUGGEST THAT THE DESIGN OF THE CALIFORNIA ACADEMY OF SCIENCES (CAS) IN SAN FRANCISCO EVOLVED FROM AN INITIAL CONCERN ABOUT EVIDENCE-BASED DESIGN WOULD BE ERRONEOUS AND MISLEADING. NEVERTHELESS, THE CAS IS A PERFECT EXAMPLE OF GREAT OUTCOMES THAT CAN RESULT WHEN DESIGN CREATIVITY COMES TOGETHER WITH RESEARCH TO ENHANCE BUILDING PERFORMANCE.

The CAS design process utilized surveys and observations like those often used in social scientific research, as well as computer modeling, simulation, and full-scale mockups. It drew on design architect Renzo Piano’s experience, as well as project-based research, and it took maximum advantage of interdisciplinary expertise from subconsultants and subcontractors. These methodologies all characterize an informed design process.

Figure 5.1 Renzo Piano Concept Sketch

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The CAS client and design team didn’t state they wanted to follow an evidenced-based process, but they chose to fully understand the implications of many complex design choices that needed to be made. To this end, they utilized many of the methodologies described in previous chapters of this book, especially survey, simulation, and modeling. Utility, sustainability, constructability and delight resulted. (See Insert C2) The design by Renzo Piano Building Workshop (RPBW), in collaboration with Chong Partners Architecture (now Stantec), ARUP, and Webcor Construction, began with an inspired design vision created by Renzo Piano. This vision grew from the site and a spatial interpretation of the Academy’s multi-faceted mission. Form and function. The design parti formalizes cultural, historic, and environmental context through the lens of Piano’s personal design genius and experience. (See Insert C1)

Piano Design Philosophy Piano is equally concerned with “the making” of a building and the strength of its initial design concept. The five-phase design process typically used in the United States progresses from schematic design through design development, construction documentation, bidding, and construction administration. Most creative activity occurs in schematic design, with subsequent phases being predominantly about technical implementation. Design is generally allocated only 35 percent of the total effort. In contrast, Piano’s process is iterative. He starts with a vision and then almost immediately turns his attention to structure, environmental aspects of building performance, construction technology, and materiality. Each aspect of design contributes to the design concept and the enhancement of his initial vision. DESIGN IS EVIDENT IN ALL PHASES OF WORK, AS ARE ATTENTION TO DETAIL AND USE OF EVIDENTIAL PROCESSES. It is this

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process of working from “whole to part to whole,” moving from creative intuition to evidence and then back to the vision, which results in extraordinary design innovation. Seeking and applying evidence enhances creativity, as concept evolves to reality. Piano’s beginning with a vision of what might be, based on personal intuition and experience, is quite similar to the way a scientist creates a hypothesis. The past suggests what might come next, but the idea springs from creative thought. Just as Piano then uses experimentation to develop the elements of the design, a scientist pursues his/her research plan using a variety of empirical methods. Designer and scientist both look to some form of valid and reliable evidence, whether quantitative or qualitative, for assurance that the work will result in successful outcomes. Rusty Gage, neuroscientist from the Salk Institute, first drew the author’s attention to the similarities of how architects and scientists use evidence. Gage finds the similarities to be apparent. But architects continue to fear that using scientific methods will diminish their creativity. Thus, they dismiss the use of an evidencebased design process. THE CAS STANDS AS AN EXEMPLAR THAT GREAT DESIGN RESULTS FROM CREATIVE VISION AND CREATIVE USE OF EVIDENCE. Much of the evidence this case study will cover comes from computer simulation, modeling, and full-scale mockups (a form of modeling and rapid prototyping as a principle methodology of generating evidence). In addition, at the project outset, the Academy staff utilized social scientific methodologies to develop evidence to inform functional and operational programming. These included user surveys, benchmarking, and field investigations of the existing facility and other scientific museums.

Finally, because of the manner in which these design explorations were undertaken, CAS is fortunate to have a wide range of sensors that provide a plethora

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PUTTING IT ALL TOGETHER

of data that is continually being captured by a computer facility management system. This “feedback loop,” described further in the case study, provides another form of evidence, to be used to improve building performance on an ongoing basis and to inform future projects by the CAS team and others in the design and construction professions.

Client Leadership and Insight The California Academy of Science originated in 1853 and relocated to Golden Gate Park in 1914. The CAS has prospered from being a unique combination of natural science museum, aquarium, and planetarium under one roof. Its mission is even broader. A research and educational institution, the CAS’s stated mission from its inception has been “to explore, explain, and protect the natural world.” The building design functionally and aesthetically supports this mission; the process of design was exploratory and scientific. From 1914 to 1989, CAS expanded into 12 separate buildings, located on the same site as the new building—the Music Concourse of Golden Gate Park. Damage from the 1989 Loma Prieta earthquake forcedclosure of portions of the museum, driving a decision by the board of directors to build a new Academy. In 1999–2000, the board hired Renzo Piano and began the design process. The board expected intense public scrutiny of the design and knew that every decision would have to be backed up.

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ing to pay for nontraditional investigations, including full-scale mockups well beyond the what would be within the traditional scope of design and construction services. These evidence-seeking processes are integral to Piano’s commitment to innovation and resulted in benefits for the CAS and the surrounding community. For their part, the leadership of the California Academy of Sciences was insightful, bold, and creative in support of scientific and design innovation using evidence. Some architects claim that each building that is designed and constructed is a prototype for the next. Unlike an auto manufacturer, as one example of a product developer, which undertakes a lengthy period of research, development, and prototyping prior to letting the first car roll off an assembly line, an architect generally first sees a complete physical manifestation of his/her design creation when construction has been completed. By then, a considerable investment has been made without knowing if the outcome will be of value. Given their fiduciary role, the CAS board’s agreement to permit Piano’s use of full-scale mockups was clearly a wise investment. (See Insert C3–C5)

Project Facts The project is approximately 410,000 square feet. It includes: 

Exhibit halls



An auditorium

By contractual agreement, Piano and THE CAS LEADER-



Retail shops

SHIP TEAM COMMITTED TO A PROCESS OF EXPLORATION



Food service

AND INNOVATION IN ALL AREAS OF DESIGN, ESPECIALLY



Three iconic exhibits for a planetarium, a self-contained rain forest, and an aquarium

entific institution, a process of inquiry was the logical approach.



Approximately two acres of landscaped roof used for educational purposes

The CAS reinterpreted what the “standard of care” for their architect would be, when requiring an exploratory process. They also backed up their intentions by agree-



Two weather stations located on the roof



Photovoltaic panels generating 5 percent of the building total electrical use

IN THE REALM OF SUSTAINABILITY. For the CAS, a sci-

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subterranean floors of support facilities



approximately 200,000 square feet of research laboratories, offices, and collection storage

The design and construction took approximately eight years and cost approximately $480 million. Given this complexity and investment, it’s apparent why the client needed to have confidence that the right design decisions were being made at every step of the process. Many types of evidence were sought and applied, all benefiting the project’s success.

The Primary Research Methodologies Utilized Case Study: Use of Social Scientific Evidence Immediately prior to hiring Piano, then-Executive Director Patrick Kiocelek, PhD, led an 18- to 24month effort of defining what the CAS should be. As a part of that process the Academy conducted over 150 focus group meetings with various stakeholders and experts to help define the future of the Academy for the twenty-first century. These efforts utilized

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traditional social scientific surveys, questionnaires, infield observations, and benchmarking of other comparable scientific facilities. Diverse, interdisciplinary stakeholders participated in this effort to ensure that the institution’s mission would be addressed from multiple perspectives. This highly systematic and thorough process assured that the correct questions were asked of a representative sampling of people and that, thereby, a compelling design hypothesis would form. Armed with this knowledge, specialized museum consultants were hired to substantiate the reasonableness and feasibility of the strategic operating model, or hypothesis. These consultants provided the equivalent of a peer review, a step within scientific research protocols. From the survey research and peer review process, a substantial body of evidence was gathered and became the basis for the functional, experiential, operational, cultural, educational, scientific, and philosophical strategy for the new building. This evidence framed the design program in quantitative and qualitative terms. With this information in hand, combined with cost parameters, clear process mapping, and definition of expectations, the design team had a solid basis to understand what they needed to do.

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C ASE S TUDY Use of Engineering Computer Modeling and Computational Fluid Dynamics Evidence produced through simulation modeling and full-scale mockups had three intended purposes:  To support, refine, and build confidence in the design; specifically the sustainability

strategies and structural approach. Permit the team to enhance the design vision by establishing a better understanding of building performance and expected outcomes.  To support technical code compliance, construction detailing, sequencing, and

budget refinement.  To have an ability to monitor actual system performance and to adjust the systems

to enhance operations. ARUP was the integrated engineering firm responsible for the design of structural, mechanical, electrical, and plumbing; facade consulting; acoustics consulting; sustainability consulting; lighting design; and life-cycle analysis. Their London office worked closely with Renzo Piano Building Workshops on the initial concepts and collaborated with ARUP’s San Francisco office in the simulation modeling and mockup development. The use of performance-based code compliance, permitted under the prescriptive code’s “alternative materials and method of design” clause, was uniquely allowed by the San Francisco Building Department and was used on more than a dozen such performance-based approaches to seismic design, fire safety design, and energy conservation. Although effective for analyzing complex structures, performance-based compliance can be labor intensive and require specialized expertise, as well as more fee and time for design and agency reviews. Prior to beginning the research, it’s necessary for the design team and reviewing agency to agree on the assumptions, design methodology, and evaluation criteria. Reviewing agencies will often employ the expertise of a third-party peer review consultant.

CASE STUDY / Use of Engineering Computer Modeling and Computational Fluid Dynamics

C A S E S T U D Y: U S E O F E N G I N E E R I N G C O M P U T E R M O D E L I N G A N D C O M P U T A T I O N A L F L U I D D Y N A M I C S

For the CAS, ARUP provided innovative research efforts, focused on Computational Fluid Dynamics (CFD) modeling of the natural ventilation system; occupant flow analysis with simulation modeling; and development of a lighting system for the live penguin exhibit, which mimics the lighting conditions of their home environments in South America.

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One example of the research is the calculation of (natural) ventilation effectiveness of the exhibition hall. This study confirmed the feasibility of naturally ventilating the exhibit hall and thus obtained LEED points derived from Credit EQ-2. The exhibition hall is a large, crossed-shaped space, approximately 424 feet long by 248 feet wide and 61 feet tall at its maximum height. The hall has two large domes, the planetarium and the rainforest. Both are mechanically ventilated and self-contained. An external piazza is situated at the center of the exhibition hall. All three spaces are represented as obstructions in the model. The ability to naturally ventilate this large space eliminated a significant consumption of energy, which would have been necessary to mechanically ventilate the space. THE IMPACT OF THIS STUDY IS SIGNIFICANT TO THE ONGOING FISCAL IMPACT OF THE OPERATION AS WELL AS TO THE DESIGN CONCEPT.

A CFD analysis was carried out as a means of calculating the mean age of air and the air change effectiveness at all points within the modeled zone, as described in ASHRAE Standard 62-2001. No-wind conditions represent the worst-case scenario, when ventilation relies principally on buoyancy and/or stack effect. The CFD model provides a numerical analysis of the worst-case conditions for both cold winter mornings and hot summer afternoon conditions. The natural ventilation in the exhibition hall depends on open windows at high and low levels on each entrance facing the hall, to provide fresh air into the space, as well as on high-level skylights above the domes of the rainforest and planetarium, for exhaust of warm air. On a design day summer afternoon, all windows on each facade are fully open, as are operable skylights on the roof, corresponding to a free open area equivalent to 13.5 percent of the overall facade. The radiant floor is then set in a cooling mode. On a design day winter morning, only the windows at high level are partly open (10 inches) and some of the skylights above the rainforest are open, corresponding to a free open area equivalent to 2.2 percent of the overall facade. The radiant floor is then set in a heating mode. (See Insert C6–C9)

USE OF LITERATURE SEARCH TO CONFIRM VALIDITY OF METHODOLOGY A literature search confirmed that CFD is often used in the design of mechanically ventilated and naturally ventilated spaces. It was also determined that the degree of ventilation effectiveness is defined by a function of age of air, nominal time constant,

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and the arithmetic average of the ages of air measured at breathing level within the space. From this literature search, confirmation of the methodology (CFD) and the metrics were ascertained from the beginning. Nine specific steps were taken to perform a virtual tracer gas decay test using CFD. The nine-step procedure was applied for summer and winter conditions and calculations made of age of air, nominal time constant, and air-change effectiveness. The methodology included: 1. A literature search confirming the use of CFD and the choice of metrics 2. Specific procedures and controls 3. Stated assumptions and definition of worst-case conditions 4. Testing over a prolonged period resulting in case studies for summer and winter

SUMMARY OF RESULTS The results are presented in degrees Farenheit and compare summer and winter conditions, in terms of average, maximum, and minimum temperatures, as well as average and maximum air speeds. The ventilation effectiveness is assessed for both summer and winter against concentration and air flow at exhaust air streams, age of air at breathing levels, nominal time constants, and air-change effectiveness. The CFD analysis indicated that for the exhibition hall, the proposed ventilation strategy would maintain temperatures within the design comfort range for peak summer and winter conditions, provide ventilation higher than 0.9 and meet LEED Credit EQ-2. Additionally, the CFD analysis provided a means to prove a performance-based code compliance for the space to be naturally ventilated.

CASE STUDY / Use of Engineering Computer Modeling and Computational Fluid Dynamics

C A S E S T U D Y: U S E O F E N G I N E E R I N G C O M P U T E R M O D E L I N G A N D C O M P U T A T I O N A L F L U I D D Y N A M I C S

To satisfy Title 24 criteria, the same analysis technique was applied to a typical office space where ventilation consists of a mixed system with natural ventilation in the areas closest to windows and mechanical cooling and heating for the areas more than 24 feet from the perimeter. The results of the study proved the effectiveness of a naturally ventilating strategy for the exhibition areas, developed ongoing operating expectations of the space, provided performance-based code compliance, and informed designers as to size, location, and number of openings related to air intake on the facade and exhaust from the skylight design.

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CASE STUDY / Development of a Fire Suppression System within the Collections Area

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C ASE S TUDY Development of a Fire Suppression System within the Collections Area For operational reasons, the collection storage area needed to be in close proximity to working scientists, as opposed to a remote location. The collections include approximately 6 million scientific specimens, the majority of which are in “wet containers” filled with alcohol and ethanol. The total amount of flammable liquid (estimated at 350,000 liters in thousands of these glass containers) formed a serious concern for a public assembly building. Complicating the issue, the specimens are stored in a highdensity mobile storage (compactor) system. In addition to a need to create multiple 4-hour separations, the challenge was to research and test the feasibility of an automatic fire suppression system that would satisfy code requirements for secondary containment of spills, provide fire suppression water, and not damage the specimens. The investigation methodology included a survey of alternative, nonconforming building solutions. This search led to examination of a high misting system more commonly used in aircraft carriers and oil tankers for fire suppression. The use of this concept was tested, peer-reviewed by an expert, and validated with full-scale mockups built in Texas. Three fire tests were performed which confirmed the performance of the misting system and, because of their low flow rates, eliminated the need for a special drainage and containment system. A similar process was used to address the dry specimen collection. In this case, an alternate solution requiring a custom-designed sprinkler system was developed and tested in Canada. WITHOUT THE PERFORMANCE APPROACH, THE USE OF FULL-SCALE MOCKUPS, TESTING, PEER REVIEW, AND USE OF PUBLISHED TESTING REFERENCES, THE DESIGN AND FUNCTIONALITY WOULD HAVE BEEN COMPROMISED, THE AMOUNT OF STORAGE WOULD HAVE BEEN LESSENED, AND RESEARCH ACTIVITY WOULD HAVE BEEN IMPAIRED.

In addition to these two specific examples of use of evidence for performance-based design, ARUP effectively informed and enhanced the design with studies permitting unprotected exterior steel beams, a three-story ramping for the rainforest’s spatial expression, and a uniquely designed acoustical ceiling solution. Each of these was in conflict with the prescriptive code but shown to be code compliant as a result of intensive research and creative investigative approaches.

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301 CASE STUDY / Use of Full-Scale Architectural Mockups as Evidence

C A S E S T U D Y: U S E O F F U L L - S C A L E A R C H I T E C T U R A L M O C K U P S A S E V I D E N C E

C ASE S TUDY Use of Full-Scale Architectural Mockups as Evidence

 Figure 5.2 Early Concept Model Built in Wood

 Figure 5.3 FullScale Curtain Wall and Movable Shading Device

  Figure 5.4 FullScale Glass and Photovoltaic Canopy Overhang THE ENGINEERING SOLUTIONS, WITH EXAMPLES NOTED ABOVE, EMPHASIZED THE USE OF LITERATURE SEARCHES, SCIENTIFIC TESTING METHODOLOGIES, COMPUTER SIMULATION AND MODELING, AND PEER REVIEW AS APPROACHES TO EVIDENCE-BASED DESIGN AND PERFORMANCE-BASED CODE COMPLIANCE. SIMILAR BUT DIFFERENT APPROACHES TO SEEKING EVIDENCE WERE USED FOR THE ARCHITECTURAL DESIGN ELEMENTS. THESE WERE DONE, AS WERE THE ENGINEERING STUDIES, WITH THE INTENT OF INFORMING DESIGN, ENSURING PERFORMANCE-BASED CODE COMPLIANCE, AND VALIDATING CONSTRUCTION FEASIBILITY AND DESIGN DETAILING.

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CASE STUDY / Use of Full-Scale Architectural Mockups as Evidence

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The architectural process included the following:  Translating design sketches from RPBW into 2D and 3D computer drawings to

reveal interfaces and aesthetic impact  Development of architecturally scaled models to view scale and proportion in 3D  Full-scale, offsite mockups by manufacturers of the subsystems including: 

Roof structure framing



Roof canopy with photovoltaic cells



Various window wall and mechanized shading devices



Glass (Bolla) dome for the rainforest



Landscape roof system: soil erosion, slope stabilization, irrigation, selection of plant material, and installation processes



Steel tensegrity and glass system covering the piazza

In some instances, there was an additional step of using full-scale mockups made of wood, prior to the use of the selected material. These helped develop refined architectural decisions related to scale, proportion, light transparency, etc. In yet other instances, onsite full-scale mockups made of the specific material followed the offsite mockups created by the foreign manufacturers. These were tested for integration with other structural, architectural, or construction systems. If a specific system, such as the Glass Dome (Bolla), was a third-generation design previously used by Piano, fewer steps and mockups were necessary for design reasons. Prior experience, in these cases, provided adequate evidence for design. However, even in these cases, mockups were used for code compliance, testing agency, and subcontractor understanding. THE USE OF FULL-SCALE MOCKUPS AS A WAY TO CREATE EVIDENCE BRINGS TOGETHER AN INTERDISCIPLINARY PERSPECTIVE TO INNOVATION. It engages the science of construction technolo-

gy with the physical sciences, in performance-based code compliance. The CAS design process drew evidence from many sources, testing the most complex of situations using various approaches and addressing a variety of hypotheses. (See Insert C10–C12) Beyond informing design, the use of full-scale mockups reduced risk by increasing understanding and reducing first cost. The general contractor, Webcor, and its specialty subcontractors reviewed the mockups and provided critiques. This savings is evidenced by the fact that the successful low bidders were those who participated in the creation of the mockups. The bid spread between those who understood the evidence and those who didn’t was an indicator of actual construction cost savings.

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C ASE S TUDY Use of Evidence Gained by Ongoing Monitoring and Refinement of Building Operations Most buildings are designed such that the interior environment is independent, and not reflective, of what is happening on the exterior relative to heating, cooling, air movement, and light. The building “skin” hermetically seals and isolates the interior environment from the impact and changes to exterior conditions. Thermostats and manually operated light switches determine thermal comfort for the occupants and dictate the required mechanical and electrical system functions in response to heating, cooling, and electrical needs. Unlike most buildings, the CAS is designed such that there is a strong relationship between the exterior thermal environment and the resulting interior environment. Similarly, interior occupant and thermal conditions can trigger changes to the building’s facade, which is sometimes open to light and air and sometimes closed. THE RESULT IS A BUILDING WHICH IS DYNAMIC, RATHER THAN STATIC—ITS BUILDING SYSTEMS (ELECTRICAL, HEATING, COOLING), SKIN, AND SKYLIGHTS CONSTANTLY ADJUST IN RESPONSE TO CHANGING EXTERIOR CLIMATIC CONDITIONS.

Starting with information received from the two weather stations on the roof, the computer facility management system receives the information about the exterior and integrates it with information about the interior environment received from sensors. Signals are sent to actuators that cause the building openings, including skylights, windows, and shades, to open or close in response.

CASE STUDY / Use of Evidence Gained by Ongoing Monitoring and Refinement

C A S E S T U D Y: U S E O F E V I D E N C E G A I N E D B Y O N G O I N G M O N I T O R I N G A N D R E F I N E M E N T

This highly automated system results in a well-documented understanding of building performance that is supported by the USGBC LEED process. This process results in three unique and distinctive operational conditions:  Balance: A constant balancing of building systems to coordinate between dynamic

interior and exterior conditions is needed.  Integration and Interface: Green buildings, which depend upon more

automation, require greater design integration of systems and controls, as well as attention to the interactions among subsystems. The current construction model that defines the roles and responsibilities of the general contractor and his/her subcontractors doesn’t adequately address the interface and integration

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in highly automated buildings. The design and installation supply chain needs greater attention to work smoothly.  Data: This system-balancing process requires use of sophisticated technology and

management skill but results in an operation that is “data rich.” HAVING A HIGH VOLUME OF HIGH-QUALITY DATA HAS PERMITTED CAS MANAGEMENT TO MAKE SYSTEMS-RELATED OPERATIONAL AND FISCAL DECISIONS THAT MAXIMIZE THE TOTAL BUILDING PERFORMANCE. Of particular value, the data has been provided in “real time” thus

permitting an immediate reaction from the feedback loop. In addition to being able to isolate performance of individual systems, the data can be seen in comparison to other functions that inform the interfaces, interlock, or action and reaction of dependent systems. It is anticipated that once an adequate amount of baseline data has been developed, the data will be used to forecast and anticipate facility needs rather than merely react. The use of building performance data collected at the CAS is considered to be part of a phased strategy for continual improvement. The CAS facilities management team, led by Ari Harding, has developed a high level of sophistication to monitor, refine, and improve the continuous operation of the facility systems. Getting good feedback on the system operations is an important part of the use of evidence and data in design and operations. Harding identified the following stages of work for their program:  Commissioning 

Phase 1A: Approximately a year following completion of construction, most building systems were being run and tested during installation of exhibits. However, complete system functions could not be tested until the building was fully occupied with staff, equipment, exhibits, and visitors in place.



During the nine months since the September 2008 opening, the commissioning efforts have been focused on adjusting and calibrating the systems to work as designed.



Phase 1B: During this same nine-month period, corrections, additions, and resolution of issues raised during commissioning have taken place. CAS management acknowledge that for a building as complex as this, perfection of all systems and their interfaces is not the appropriate expectation. Although corrections, additions, and resolution of issues made during ongoing operations is challenging, the need to adjust over time is reasonable.

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 Establishing a Baseline 

It is anticipated that formal commissioning will be completed by the end of one year of occupancy (September 2009). From this time forward, major systems should be operating as desired and baseline data will provide reliable, consistent, and dependable data.

 Comparative Analysis 

A comparison between actual system performance against the optimum “Gold Standard” will set clear performance metrics. 

By September 2010, a full year of operations will have provided seasonal insight and context for the benchmarked data. After this, it’s anticipated that a comparative graph of actual performance versus optimum performance will be charted for all systems.



At this point the data is stable and benchmarks are known. CAS management can move from a reactive mode of using data to make corrections when needed, to using the data as a forecasting and modeling resource based upon trend lines.

CASE STUDY / Use of Evidence Gained by Ongoing Monitoring and Refinement

C A S E S T U D Y: U S E O F E V I D E N C E G A I N E D B Y O N G O I N G M O N I T O R I N G A N D R E F I N E M E N T

IN ADDITION TO USING DATA AS A MEASURE OF UNDERSTANDING BUILDING PERFORMANCE, CAS MANAGEMENT WILL BEGIN TO USE SURVEYS, QUESTIONNAIRES, AND FIELD OBSERVATIONS TO DETERMINE (STAFF) OCCUPANT SATISFACTION AS ANOTHER FORM OF

Again, this survey process is in keeping with green building management principles. (See Insert C13–C15)

EVIDENCE.

Figure 5.5 CAS Roof Operable Skylights Activated by Information from Weather Stations

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REFERENCES 1. Isabelle Lavedrine (OVE ARUP & Partners, California Ltd.): Computational Fluid Dynamics (CFD) Modeling of Exhibit Hall and Typical Research, Collection and Administration (RCA) for LEED Credit EQ-2. Design Study, 2007. 2. Armin Wolski, Geza Szakats, Susan Lamont (OVE ARUP & Partners, California Ltd.): Margaret Law Award 2008 San Francisco Submission—Fire Engineering, Design Study, 2007. 3. Kang Kiang, Project Manager on the California Academy of Science for Chong Partners. Personal interview with Kang Kiang, June 2009. 4. Ari Harding (Building Management Systems Specialist for the California Academy of Science). Personal interview with Ari Harding, June 2009.

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5. Susan Wels, California Academy of Sciences: Architecture in Harmony with Nature. Chronicle Books, San Francisco, 2008.

Photo Credits 1. Tim Griffith, photographer; all completed images of CAS. 2. Stephanie Stone, California Academy of Sciences, drawings and diagrams. 3. Kang Kiang, photographs of full-scale mockups. 4. Isabelle Lavedrine, ARUP, photographs of computational fluid dynamic modeling.

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6 The 2005 Latrobe Fellowship

“Today’s design and construction environment is extraordinarily complex. Clients have to make an increasing number of decisions that have lasting impact on both their operations and communities. For architects to contribute value to these clients, we have to seize the opportunity to move beyond intuition and to provide rigorously developed evidence about predictive relationships between design and human response. Our clients will benefit most from the design process if we inform decisions with credible (scientific) research.” —GORDON CHONG, FAIA, PROJECT DIRECTOR, 2005 LATROBE FELLOWSHIP

Introduction This book is about a transformation occurring in the architectural profession. The previous chapters exemplify how developing and applying evidence can enhance creative design, particularly in the realms of building and environmental science. Most architects, by virtue of traditional architectural education and practice, can relate to the extraordinary engineering and formal aspects of this achievement.

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Figure 6.1 A Future Profession That Designs Places That Enhance Human Performance The future profession we envision will be equally effective in creating architecture that enhances human performance. As specifically illustrated in some of the work of the experts highlighted in Chapters 2 through 4, significant advances have been made in linking design and human response. However, as a whole profession, we are at an early point in this journey. Biennially, the American Institute of Architects (AIA) College of Fellows awards a grant, named for architect Benjamin Henry Latrobe, for research leading to significant advances in the architecture profession. The 2005 Latrobe Fellowship was awarded to Chong Partners Architecture (now Stantec Architecture), Kaiser Permanente, and the University of California, Berkeley, to explore the use of evidence from the social and physiological sciences to better understand human response

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to physical enviornments, and thereby make better design decisions that create places for better healing, learning, and work collaboration and productivity. The research focused specifically on health-care environments and the question of whether design can aid healing (reduced “time to heal” and medical errors, in turn, increase hospital financial performance). Credible evidence of design impacts on healing and errors does exist; but so do assertions based on very weak indicators. The Latrobe research sought a model for creating evidence that would be reliably strong, meaningful in terms a client would value, and inspirational. As with many explorations relatively early in a transformation, the 2005 Latrobe followed a different course than what was initially expected. But it resulted in lessons of value for all design practitioners. Some

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are applicable today and others point toward a future with a much greater degree of predictability for design outcomes. These will be discussed in two categories: (1) the Process Model and Methodologies; and (2) the Literature and Experimental Findings.

Process Model and Methodologies THE 2005 LATROBE HYPOTHESIS: CREDIBLE, APPLICABLE “EVIDENCE” OF RELATIONSHIPS BETWEEN DESIGN AND CLIENT ORGANIZATIONAL PERFORMANCE WILL RESULT FROM (1) A COLLABORATIVE APPROACH THAT UNITES THE PERSPECTIVES, SKILLS, AND RESOURCES OF THE ARCHITECTURAL FIRM, UNIVERSITY RESEARCH COMMUNITY, AND CLIENT; AND (2) USE OF BOTH SCIENTIFIC RESEARCH METHODS AND INDUCTIVE REASONING ARE CRITICAL TO THE PROCESS.

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The Latrobe research team posed and examined this hypothesis using a research model with three characteristics: 1. Collaboration among a practicing architectural firm, a university research community, and a leading health-care provider to seek the best ways to utilize the skills and knowledge of all three in a trans-disciplinary framework. 2. Use of behavioral sciences, biomedical and neuroscience methodologies, as well as inductive reasoning 3. Application of metrics to measure human responses to various design conditions and to evaluate organization performance impacts The research was intended to assess the usefulness of this three-part model for future design evidence production, as well as to compile and create knowledge for design application in the short term.

Figure 6.2 Components of the Three-Part Model as a Research Plan

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Why Three Perspectives? The strength of much of the work discussed in Chapters 2 through 5 of this book derives from teams with diverse skills and experience. Understanding the client’s needs, the design process, and research quality standards are all needed to develop evidence for design that is both scientifically defensible and applicable. Therefore, experts in this book advocate that architects would benefit from engaging people from various disciplines in the evidence-building process.

al.). The principles of Mode 2 are useful guidelines for any design practitioner with an interest in evidence for design. Unlike the more traditional Mode 1 research, typical of work developed solely in academia, Mode 2 engages the skills and perspectives of people, such as architects and their clients, who understand how the research will be practically applied and how success will be evaluated. Consider these five Mode 2 characteristics. They provide a platform for designers to meaningfully develop and interpret design research.

The Latrobe team tried to demonstrate the validity of this theory. From experience in design practice, research, and education, the 2005 Latrobe research team agreed at the outset that architects, academic researchers, and clients approach knowledge production and management differently. Architects have valuable experience, technical knowledge, and creative skills, but often rely more on intuition than evidence backed by rigorous research. University researchers understand scientific protocols but work in isolation from the people who best understand the questions of most value to answer. Therefore, many from this community pursue topics of scholarly interest that have limited applicability. And then there are the in-house facilities and real estate professionals. They might believe that design has the power to support their core business goals but they lack access to the “evidence” they need to make credible business cases, backed by relevant financial and other performance metrics. Ultimately, not being able to sell the investment in an innovative design, they end up delivering cost-conscious environments that are suboptimal in terms of their influence on human outcome.

5. It must accommodate multiple definitions of quality because there are many players and a lack of strict disciplinary criteria with which scientific peers can evaluate. (For example, the designer and client may judge if the research has been sufficient to influence the desired results.)

The Latrobe team wanted to examine an approach to creating evidence for design that was more powerful than what each constituent might be able to do alone. An inspiration came from the research framework known as Mode 2 Knowledge Production (Gibbons et

Many designers believe that scientific research and design process are incompatible. Science is not trusted because it appears to have no room for artistic inspiration. Evidence created by scientific research is feared to be overly prescriptive, limiting the designer’s

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1. It is generated in the context of application. It arises from the very work of problem resolution, e.g., a design innovation intended to promote a human performance outcome. 2. It is trans-disciplinary. A range of methods, e.g., design charrette and behavioral survey, is used with tools and perspectives coming together often in novel forms to solve a specific problem. 3. It is produced across knowledge organizations, e.g., design firm, health-care provider and research institute, and in a variety of settings. 4. It is reflexive, in that there is conversation between the researchers—scientists and designers—and the subjects—client organizations. The problemresolution environment influences the topic, the research design, and the end uses.

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Figure 6.3 An Integrated Client-Architect-Researcher Evidence Production Model range of expression. One could argue that this is an erroneous view and that creativity plays a major role in shaping scientific research design. However, when Mode 2 knowledge development is used in the context of evidence-based design, the debate becomes moot because the designer is a participant and the design process integral to shaping the intent and outcome. For the Latrobe, designers worked side by side with neuroscientists, social scientists, and the client to enhance the usefulness of the research outcomes.

design inquiry process within project schedules and budgets.

Why Behavioral, Biomedical, and Neuroscience Methods?

The use of physiological responses to environmental stimuli is more recent and more complex. Neuroarchitecture, for example, is early in its development. Nevertheless, the understanding of how the body responds to specific aspects of place promises new levels of capability in affecting human performance in the realms of health and cognitive performance. We will no longer have to rely on self-assessment of what causes productivity but actually witness brain functionality in different spaces, as measured by very specific causal elements.

Behavioral sciences have been at the heart of environmental design research for many years. They continue to be powerful in revealing and communicating linkages between design attributes and human response. Although social science methods require rigor to be valid, they can be fairly readily adapted to the looser

The 2005 Latrobe sought to introduce an element of physiological measurement, in order to push forward this new way of assessing design effectiveness. It did so by seeking both medical data (in a data mining exercise at KP) and stress measures (in an experiment conducted at several university labs).

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The Research Plan The research plan comprised four major tracks. Following a literature search, two types of experiments were conducted, based on what team members believed would be the most productive methodology. Although this dual track diverged from the intended “transdisciplinary” approach, it had potential to investigate one issue from two perspectives and then discover if the two methods reinforced each other. The following illustrates the four components of this research effort: 1. Problem Definition and Research Plan  Team building/Establishing goals  Engaging stakeholders and experts  Preliminary literature search 

Lighting and health



Color and health



Evidence-based practice

 Refining pilot study topic(s)  Research plan development

2. The Natural Experiment (The Kaiser Permanente (KP) Integrated Data Model—IDM), Principal Investigator: Robert Mangel, PhD. (See credits at end of this chapter for the many contributors from KP.) Many organizations collect extensive data to monitor their own performance effectiveness. The concept of the IDM was to link physiological and opinion data, routinely collected within KP’s medical records and patient surveys, with design attributes of the rooms occupied by the corresponding patients. Data mining would then support queries such as “Do patients in rooms with northern daylight exposure heal or feel differently from those with southern light?” The large volume of data would create very strong, continually refreshing evidence without being intrusive to staff or patients. Large samples are one way to diminish the impacts of naturally occurring variations that are difficult to control in complex environments, e.g., hospitals. In addition, large-scale studies have other appealing aspects for corporate decision-making, in that executives with decision

Figure 6.4 The Integrated Data Model Components

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authority are often accustomed to benchmarking and other large survey-type research. In addition to analyzing existing physical conditions, the IDM system could be used to measure the effects of direct design interventions, e.g., room modifications, hypothesized based on other research discovered through literature search or even based on intuition and experience. Envisioned was an integrated database with attributes of 30 hospitals (totaling over 60 million square feet) and perhaps 100,000 patient stays cumulative over time. At the time of completion of the Latrobe, the IDM was designed and being implemented. Early pilots supported the notion of its power but there were no design findings to be reported with high confidence.

Key Findings about the Model and Methodologies 

Integrating active medical records data with design attributes captured in an equally “active” CAFM system is a very powerful method for future health-care EBD research. (Parallel opportunities to mine organizational performance data exist in other types of institutions.)



Physiological data, such as heart rate variability and EEG brain waves, can be very compelling evidence for design, as it has been proven to indicate health risk, health status, and cognitive function.



One concern about laboratory experimentation as a method used in EBD is that it does not directly assess real life design applications. Nevertheless, the use of scientific method, including controlled research design and statistical analysis of results to substantiate the reliability and validity, increases strength of evidence. Combining lab findings with design intuition and field interventions can create solid evidence.



Each research approach used to build evidence that informs design has its limitations. Evidence is perhaps best if looked at from multiple perspectives (opinion surveys, observation of behavioral performance, laboratory experiments, or in-field measuring of environmental conditions), and subject to various measures (organizational, economic, psychological, social, and physiological).

3. The Laboratory Experiment, Principal Investigator: Eve Edelstein, PhD. (See credits at end of this chapter for the full research team.) This approach was based on using rigorously controlled experimental (lab) conditions and multiple measures to enhance the strength of evidence. Physiological and cognitive responses to specific light qualities were analyzed and interpreted in the context of an extensive literature base. Although by definition, lab research is Mode 1, this experiment was conceived jointly with the trans-disciplinary team to address some critically important design issues; and it was complemented by field measurements and design charrettes, thereby relating it more closely to Mode 2 applications. 4. The Model, Principal Investigator: W. Mike Martin, PhD., FAIA (See credits at the end of this chapter for the full research team.) The research approach itself was observed and analyzed as it unfolded to assess its value for future design research.

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Literature and Experimental Findings Literature searches about evidence-based practice and lighting (the focal topic of the Latrobe pilots) discovered useful information that practitioners can use today. The laboratory experiments also resulted in lessons learned to inform design decision-making.

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Literature about Evidence-Based Practice The team researched precedents for evidence-based practice in Design, Medicine, Management, and Education. (This effort was led by Robert Brandt, Steven Doctors, and Eve Edelstein.) A few common guiding principles emerged that might be useful to design practitioners who are establishing their own approaches or trying to critically assess those of others. 

There are a variety of types of useful and credible evidence.



How “strong” the evidence is, i.e., how powerful it is in terms of predicting an outcome or describing a relationship between two factors (such as “view” and “healing”), will depend on the methodology used to create the evidence.



The basic rules of scientific research do apply. Evidence should be “valid,” i.e., it should address the topic it is intended to address (and not be a reflection of another superfluous condition), and it should be “repeatable,” i.e., we can feel fairly sure the results will recur. These seem obvious, but how often do we jump to a solution based on a single observation rather than a body of knowledge? As designers, we want answers. But are they the right answers? Was it the “daylight” or the “view” that caused a particular patient response? If we don’t know, how can we decide about the size, placement, and orientation of windows beyond merely what feels right?



Taken together, greater control of potentially superfluous factors, consistency of results across subject groups, and a fairly tight range of responses among research subjects increase the value of research data as a predictor.



Careful experimental design, including randomization and control, increases the strength of research results, as do large datasets and systemized methodologies.

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There is value in having commonly accepted standards for attributing value to knowledge intended to be applied as evidence. (We embrace “evidencebased design,” but does that mean the same thing to all of us? Not currently.)



Evidence-based practice does not necessarily remove the soul from practice. The practitioner’s judgment and values, informed by experience, are central.



Context must always be considered.



A key consideration in evidence-based practice is communication. We must demand to know enough about the source, the context in which it was developed, and methods used to create evidence, to make a responsible decision about how seriously to trust that evidence and to decide when it’s relevant to apply it.

Lighting Design Literature The following is extracted from the literature review conducted by Eve Edelstein, PhD, and contained in the 2005 Latrobe Research Report. Many behavioral and physiological responses are now associated in the literature with exposure to electrical lighting, daylight, and solar orientation. The field has progressed through multiple generations of study, which include the investigation of endocrine changes related to electrical light exposures, such as the role of melatonin in sleep and wake cycles. Human studies have disclosed that cardiac rhythms, stress, endocrines, hormones, growth and aging, developmental, cognitive, and emotional responses demonstrate circadian rhythms in normal individuals. The evidence base reveals diseases and disorders associated with disruption of circadian or circannual light conditions. For example, hypertension may be related to the disruption of normal diurnal conditions and cancer risk may be associated with light-induced disruption of me-

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latonin production (which is implicated in the control of cancer growth). Seasonal Affective Disorder is now an accepted consequence of seasonal lighting and climactic changes, and electrical light therapies are being actively investigated.



Pain



Perception and self-report of pain and pain management



Medication rates relative to lighting dosage and length of stay

The categories below represent a partial list of human responses to light.

Circadian cycles can be modulated by a variety of external cues, but light is the primary variable that aligns (or entrains) humans to diurnal, nocturnal, and seasonal rhythms. In 2001, a new class of cells was discovered in the retina of the eye, thought to be “circadian” receptors that sense slow changes in light levels, rather than receptors for vision. This discovery renewed research to explore the spectrum, intensity, and duration of light that influence biological responses.



Stress, modulation of cortisol/stress hormones



Heart disease and hypertension



Melatonin responses



Sleep/activity/feeding cycles



Cancer



Basal metabolic rate, protein synthesis, and thyroid responses



Growth



Aging responses



Hormone function



Obstetric



Neonatal responses



Ophthalmic development and health



Hyperbilirubinemia and kernicterus



Long-term visual function in NICU graduates



Gastro-intestinal conditions



Diabetes



Neural immune responses



Inflammation and autoimmune disorders



Brain development and function



Ataxia, neuropathy



Concentration



Alertness



Attention deficit disorder



Working memory



Psychologic and psychiatric conditions



Decreased memory, dementia



Depression, emotional labiality



Seasonal Affective Disorders

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Numerous studies have led to the development of “dose response curves” to electrical light that reveal peak sensitivity in the blue wavelength (between 420 and 470 nm) for modulations of melatonin suppression that regulates sleepiness. Bright white light has also been demonstrated to be effective in modulating mood, sleep, and activity cycles (Ancoli-Israel et al., 2003). The range of spectra that influence the multiple circadian systems is yet to be fully explored. Although research has focused on short wavelengths in the blue range, a broader range of spectra is also associated with biological responses (Revell et al., 2006). Testing of red light has been uncommon, and many researchers have assumed that there is little to no effect of red light on the neuroendocrine or circadian systems. However, Hanifin and colleagues (2005) found that normal healthy humans exposed to 630 nm and 700 nm elicited small reductions of plasma melatonin levels. These findings are consistent with other studies that reveal the influence of a long wavelength light on cardiac responses (Schafter and Kratky, 2006).

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The Laboratory Experiment The laboratory experiment used rigorously designed and controlled conditions to demonstrate specific changes related to alterations of the environment. Measurement methods most likely to yield statistically valid results were selected based on the literature review. Statistical significance was achieved by minimizing the complexity of the test environment and by testing the influence of one environmental change at a time. The laboratory experiment explored how architecture might influence human exposure to light within built settings, and how varied light levels and spectra might influence health outcomes. Medical research acknowledges that chronic stress is a major contributor to heart attack, cancer, and diabetes. Further, we are able to alter lighting and to measure heart rate variability and EEG (key indicators of stress); thus determining linkages between lighting and health outcomes. The Latrobe experiment showed that heart rate activation increased and variability decreased during brief exposure to bright white light (with a peak in the blue spectrum) during exposure. These results are consistent with melatonin studies using longer exposures at night. Yet more interesting were the results that showed that heart rate responses were highly significantly different in red light conditions from those in white light; with the red light associated with situationally appropriate cardiac activation and relaxation during cognitive tasks. Following the experiment, a team of designers and client representatives considered the findings and interpreted how they might apply to design. This step is inductive, and the team did not intend to imply that the design ideas have been rigorously tested and validated. However, the interpretive process illuminates how the

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design process can come together with scientific evidence to strengthen the creative process. Several design charettes were held to discuss the potential impact of introducing biologically relevant light levels on architecture and design. How did the design team interpret the experimental findings and related survey of the literature? EVIDENCE: CIRCADIAN SYSTEMS NEED DARKNESS AS WELL AS LIGHT The need for light is well known but circadian systems also require periods of darkness. In many current hospitals, light intrusion into patient rooms from outside the building, as well as from corridors and other proximate interior spaces, is often at levels sufficient to disrupt the patient’s circadian rhythms. Design Interpretation 

Patient rooms must have the ability to be darkened, including an ability to control light intrusion from both outside and inside the building.



Accessible controls should provide patients with the ability to adjust light for their individual needs. A single-touch, programmable control for medical staff to immediately establish optimal lighting for assessment and procedures should be provided at bedside and/or at clinical stations



Achieving optimal light level starts outside the building, with external shading and shielding devices. A kinetic skin that adapts to seasonal and diurnal light changes (but has manual overrides) may help balance needs for circadian light and darkness, view and glare control.



Shades should be installed to effectively seal out light around the window perimeter.



Low-intensity lighting on the corridor side of the patient room walls may reinforce pathways for safety while not limiting light pollution into patient rooms.

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Figure 6.5 Section at Patient Room and Corridor

Figure 6.7 Kinetic Skin: Rotating Exterior Louvers

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Figure 6.6 Kinetic Skin: Sliding Exterior Shutters

Figure 6.8 Sectional Perspective of Nursing Stations at Corridor

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EVIDENCE: NATURAL LIGHT CYCLES PROMOTE HEALTH; CIRCADIAN SYSTEMS NEED VARIED LIGHT CONDITIONS

serve different circadian needs, especially for transitioning shift workers. 

For areas where daylight is not feasible or practical (such as imaging rooms), [there should be] controlled electrical lighting that can be varied according to user, function, frequency, intensity, and distribution to provide useful circadian stimulation.



For night shift and swing shift workers, daytime patterns of light frequency variation should be recreated and provided to the extent feasible while still supporting patient needs for darkness and staff needs for visual acuity, safety, and security. The use of white and blue frequency light augmented by task and safety lighting may support staff circadian sleep/wake patterns. Red light in corridors could be explored as a means to support night time monitoring while minimizing circadian sleep/wake patterns in patients. White lighting at clinical stations would provide for taskrelated visual acuity. Individual controls at staff stations are essential.



Localized “light showers” (brief exposure to light that stimulates the melatonin systems) at distributed desks may provide for needed circadian activation.

Atria and light wells might, but do not necessarily, provide sufficient circadian light to interior areas. Orientation, floor level, and atrium proportions should be modeled for circadian light frequency, as well as intensity. (The two do not always correspond.)



Low level ambient light should be complemented by task lighting at work centers for visual acuity. Bright light should be screened so as not to penetrate into patient rooms.



Light shelves may be used to introduce daylight to corridors where “borrowed light” to the distributed nursing areas is often blocked by doors, window coverings, and bed drapes.



Staff should have access to spaces for both darkness and light. There should be a break room with daylight, as well as a separate on-call room to

Lighting needs vary by individual medical condition, visual acuity, preference, and culture. An individual’s history of light exposure (over several hours, days, weeks) influences his or her need for circadian light. Swing and especially night shift workers may suffer from stress responses due to misalignment of their sleep/wake cycles and natural daylight and darkness.

Natural daylight can be considered the “gold standard” and it comprises different frequencies, intensities, and dynamic patterns of light exposure that are related to measurable differences in biological responses. Constant exposure to a single frequency and level of light is not ideal for normal circadian patterns. Daylight and electrical lighting that emulates natural diurnal, nocturnal, and seasonal cycles is most likely to support circadian needs and health. Design Interpretation 

Brightness and frequency of light should vary throughout the day. The objective is to provide the appropriate cycle frequency of light, including light in the range of spectra and intensities— blue and bright white spectra, known to influence melatonin-related sleep/wake cycles, and red spectrum, which influences heart rate variability.



Building core and shell design should allow for controlled daylight penetration to the central nursing stations or team work areas (often not currently provided in interior areas of large-footprint buildings).



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Design Interpretation

Robert S. Mangel, PhD, Kaiser Permanente (KP)



W. Mike Martin, PhD, FAIA, University of California, Berkeley*







Lighting controls are as important as lighting. Patient and family are likely to make preferred adjustments, but they may not know what light is healthiest. The ideal system would combine computerized control to provide desirable circadian light (that the patient or staff may not choose) and overrides to adapt to preferences. Patient controls must be accessible and easy to use, and should allow control of electric light as well as window coverings. Cultural preferences may have a great influence on color choices. Patient control of color through LED lighting may provide a sense of control and ability to easily adapt the environment as the needs and preferences of occupants change. Special lighting needs should be considered when setting such levels. For example, elder patients are more likely to need greater light levels, but may be more disturbed by glare and reflection.

Credits The 2005 Latrobe Fellowship was sponsored by the American Institute of Architects College of Fellows.

Core Team Gordon H. Chong, FAIA, Chong Partners Architecture* Robert M. Brandt, AIA, Chong Partners Architecture* Galen Cranz, PhD, University of California, Berkeley

Contributors Chong Partners Architecture (now Stantec Architecture) THE LABORATORY EXPERIMENT RESEARCH TEAM

Eve A. Edelstein, Ph.D Principal Investigator Division of Biological Sciences, University of California, San Diego Academy of Neuroscience for Architecture Robert J. Ellis, John J. Sollers III, Ph.D., Julian F. Thayer, Ph.D. Department of Psychology, Ohio State University, Columbus Ruey-Song Huang, Ph.D., Tzyy-Ping Jung, Ph.D., Scott Makeig, Ph.D. The Swartz Center for Computational Neuroscience, University of California, San Diego Robert Brandt, AIA Team Leader for Chong Partners Architecture We acknowledge the generous contributions of time, expertise, equipment, and laboratory resources by our advisors and contributors. CHONG PARTNERS ARCHITECTURE

Barbara P. Denton, Assoc. AIA, Kaiser Permanente (KP)*

Katherine Anderson

Steven I. Doctors, PhD Candidate, University of California, Berkeley

Cathy Barrett

Eve A. Edelstein, MArch, PhD, Consultant to Chong Partners Architecture*

Teresa Au Larry Bongort Edward Dean Jeff Farley

* Grant recipient Chong Partners Architecture is now Stantec Architecture , University of California Berkeley, and Kaiser Permanente

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Bret Harper Roland Lau

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John Sealander

KAISER PERMANENTE

Giovanni Succi

Thanks to the following individuals who gave of their time and expertise to make this project a success.

Chris Tymoff UNIVERSITY OF CALIFORNIA, BERKELEY

Gabriel Arboleda, Arch Ph.D. student

John Kouletsis, Director, Strategy, Planning, and Design

Professor Cris Benton, Architecture Department

Dr. Joe Selby, Director, Northern California Division of Research

Professor Harrison Fraker, Dean College of Environmental Design

Christine Malcolm, Sr. Vice President, Hospital Strategy and National Facilities

UNIVERSITY OF CALIFORNIA, SAN DIEGO

Dr. Eduardo Macagno Dr. Sonia Ancoli-Israel THE NEW SCHOOL OF ARCHITECTURE & DESIGN

Terry Klein Stephen LeSourd

Dr. Dave Newhouse, Associate Physician in Chief, Fremont Medical Center Katie Holmes, Leader, Service Enhancement Abelardo Ruiz, Sr. Project Manager, NFS Care Environment Linda Raker, Sr. Project Manager, NFS Care Environment Ronald Knox, Vice President, National Diversity

RENSSELAER POLYTECHNIC INSTITUTE

Mariana Figuero, Ph.D. NATIONAL INSTITUTES OF MENTAL HEALTH

Esther M. Sternberg, M.D. SMITH GROUP

Duc Manh Tran (Chong/Smith Group) DAYSIMETER

Dr. Mark Rae Dr. Mariana Figueiro Dr. Andrew Bierman LIGHTBOOK, INC. SILVERMAN AND LIGHT

Chuck Silverman

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Gayle Tang, Director, National Linguistic and Cultural Programs, National Diversity Marty Kaplan, PhD Mike Mannina, National Manager, NFS CAFM Services Michael Schroeder, Project Manager, NFS Care Environment Wenbin Mo, PhD, Senior Data Consultant, National Market Research Joan Wu, Data Consultant, National Market Research Janet Ban, Senior Data Consultant, National Market Research Long Ngo, PhD, Senior Data Consultant, National Market Research Perry Class; Josh Lail; Loleatha Robertson; Joe Yun; Lan Nguyen; Harry Cho

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7 Applying What We’ve Learned

This is a book about design, although not design as it’s typically practiced. Rather, we’ve focused on evidence and how evidence can be created and applied to make the work of architects and other design professionals relevant to the twenty-first century. The design professions must change to remain viable as the world around us changes. Technology and economics have sharpened client expectations for return on investment and changed the way our clients work. Although public admiration for signature design is very much alive, designers are more than ever being held accountable for high-performing buildings. It’s rapidly becoming the norm to expect buildings and their interiors to be sustainable and cost-effective and to lead to positive behavioral outcomes—places that help people heal, learn, produce, and thrive. THIS APPROACH TO DESIGN ISN’T JUST FOR LARGE, SPECIALIZED PRACTICES; NOR DOES IT ASK THE DESIGNER TO GIVE UP PASSION FOR THE ART OF ARCHITECTURE. IT’S ABOUT ADDING VALUE, NOT LIMITING CREATIVITY. TO THE TRADITIONAL APPROACH TO DESIGN, EVIDENCE-BASED DESIGN ADDS CONSIDERATION OF MANY TYPES OF KNOWLEDGE THAT HELP US ANTICIPATE HOW THE DESIGN WILL AFFECT HUMAN AND ENVIRONMENTAL PERFORMANCE.

The model developed and exemplified by the work of the experts featured in the book is grounded in a belief that

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to remain relevant in a rapidly changing world, full of cultural, economic, and environmental challenges, architects must expand their domain of expertise, the issues they will explore, and the methodologies they will employ. If they do, innovation will thrive. If the design professions fail to embrace change, the gulf will grow between what they can provide and what building owners and occupants need to succeed within their own value systems. THE APPROACH WE ADVOCATE IS “EVIDENCE-BASED” BUT IT DOESN’T SIMPLY MIMIC EMPIRICAL SCIENCE. This new design model would blend the creative use of intuition and experience that has served the design professions well, with an empiricism that is specifically appropriate to the architectural profession. Design that is broadly informed by reliable evidence will lead to better buildings; buildings that are technologically creative and good for people.



We were excited by the potential of neuroscience to inform architecture with an understanding of biological response to environments.



We were impressed by sophistication of the new digital tools and processes that have impacted not only how we work, but what types of work are now being undertaken by leading architects and other design professions.



We were disappointed to see how many architects are fearful and dismissive of the influence of scientific evidence on design, but once we better understood this perception, we felt encouraged that foundations already exist in the design process to bridge the gap.

How might the design professions evolve without risking the very qualities that have made design so compelling to so many people for so long? The authors set out on a journey to discover current best practices and next steps toward empirically informed design that would inspire designers. As criteria for our search, we determined that the methods and processes must be useful and feasible for practitioners working in small, medium, and large firms; design students and faculty; clients and professional organizations.

In the end, our research convinced us that utilizing evidence is an inevitable part of future practice, critical to design innovation and client service. We discovered that there are lessons to be learned from the sciences about how evidence-based design might be practiced. Equally important, we believe that this model of evidence-based practice for design won’t ask the designer to become a scientist; abandon subjective thought; or relinquish his or her role as creator, form giver, and integrator. Using scientific methods to inform design does not imply a prescriptive design process, with limited choices for the designers. Information from scientific disciplines, such as neuroscience, may enrich the designer’s considerations but not at the expense of creative expression.

As we searched, we were often inspired, occasionally disappointed, and ultimately excited for what the evidence-based approach could bring to design practice.

What Does This Mean for Design Practice?



We were inspired by the explorations of new building materials and building systems in search of greater design expression and new ways of generating and saving energy.



We were also inspired by sophisticated efforts to use lessons from the social sciences to redefine organizational behaviors and performance.

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There are a number of positive steps toward evidencebased design practice being taken by individuals, professional organizations, and universities. Nevertheless, design professionals have not yet come together with a consistent point of view about how to advance a model that would be feasible for typical designers and would work well within a design culture.

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To move in this direction, the authors considered the work of experts who already embrace the notion and precedents from medicine and other professions that have begun to establish systematic approaches. We also asked ourselves how these lessons might best integrate with the existing strong foundation of design education and practice. Two overarching principles emerged along with two key questions.

Expanded Horizons Using evidence is intrinsic to the design process. Every time we do a cost estimate, we are modeling. Structural calculations rely on performance data. When we test how two materials react to each other and perform as a system, evidence is created. Examples go on and on, but it’s not enough. Evidence-based practice doesn’t eliminate the traditional process of design inquiry. It simply raises the bar. It adds the dimension of transparent performance outcomes. It makes designers more active participants in defining needs and advising how design can help to achieve client goals. It encourages innovation in the building sciences by replacing what was done last time, or what is code minimum, with what would yield the best results for the client, the public, and the planet. This involves more testing, seeking information, and envisioning with the help of new technologies. IT SEEKS INPUTS FROM THE LARGER WORLD AROUND US; NOT MERELY ONE’S OWN PRACTICE OR EVEN THE DESIGN WORLD WE KNOW THROUGH PEERS AND TRADE PUBLICATIONS. If a social scientist, an energy specialist, or neuroscientist has the information needed to predict how a place will affect its inhabitants, why not bring that disciplinary expertise into the design conception?

There isn’t any one best source or best method of inquiry. The physical, natural, and social sciences provide a knowledge base that can enrich design decisions and make them more relevant beyond the design community. Methods to produce new knowledge also come

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from varied disciplines. No one is best and bringing several perspectives together will yield the most compelling evidence and best designs.

Strength of Evidence Evidence is information that serves a special role. By definition, it is intended to help form an opinion or make a judgment. It indicates something about something else. In design practice, evidence has value if it is reliable and valid as an indicator of how a design attribute (or set of attributes) will affect something that is important to the designer or client. The attribute could be a color, a workstation standard, a window placement—any number of things that the designer manipulates to create space. Similarly, the outcome could be cost, energy efficiency, structural integrity, user satisfaction, and any one of many other things that might result from the design. Given the purpose of evidence, the notion of reliability is critically important. That means that time and time again, we can predict with reasonable confidence the outcomes of a design choice. Validity of the evidence is also important. We need to know what the evidence is reflecting—the cause of the effect—and that’s often not easy in complex environments. A commonly cited example is research that suggests a relationship between healing and windows. Is it the daylight or the view or specific types of light or views (or other) that create the positive response in the patient? Valid evidence would correctly identify the right cause and effect. Evidence-based medicine has struggled with several models to codify “strength of evidence.” As design professionals evolve a model for evidence-based practice that is right for architecture, there’s no requirement to mimic medicine. However, there are several basic constructs about strength of evidence that seem very appropriate because they’re founded in many years of good research practices. We need to remain cognizant of the fact that although all

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information can in some way help us make choices, valid and reliable evidence is what we’re seeking. The gold standard for creating strong evidence is experimentation in which the subjects are randomly selected, and an intervention is performed with all variables rigorously controlled. However, this is not always broad enough to inform a designer’s question; not feasible in the average practice. As an alternative, observation and cohort studies can yield very strong evidence if systematically done. Rigor will, however, ultimately affect strength of evidence. While systematic observation is considered fairly strong, unsystematic observation is at the bottom of the scale. A preponderance of evidence increases its strength. A large volume of data tends to weed out anomalies and increases the odds that the findings are reliable. Multiple indicators also can be very compelling. In medicine, data from different sources all pointing to the same conclusion is often considered in aggregate to be a stronger predictor of outcome than a single highly controlled experiment. IN CREATING EVIDENCE FOR DESIGN, WE NEED TO SEEK THE STRONGEST EVIDENCE WE CAN, WHICH ADDRESSES THE QUESTION AT HAND IN A WAY THE DECISION-MAKERS WILL APPRECIATE, AND THAT IS FEASIBLE WITHIN OUR RESOURCES.

The Right Methodology and the Right Metrics Let’s say you’re starting a project and you want to try an evidence-based approach. The first question might be: What kind of evidence will I need and what’s the right methodology to get it? We believe, as in the evidence-based medicine model, there is no one right methodology. The best available information can come from various types of research, each of which may increase one’s understanding of the implications of design choices. Nevertheless, we need a place to begin.

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It all starts with defining the critical question that the evidence needs to inform. What are your client’s goals? What do you think the opportunity is for this project to add value? While this might sound vague, the answers are generally clear in actual application. Just don’t start the dialogue with questions about the design solution. If you do, the response will likely be a proposed design solution rather than a context for rigorous exploration and investigation. Ask instead about organizational or other performance objectives and the research topics will emerge. For example, a health-care client might be concerned about how the design might improve nurse recruiting, lessen time for a patient to heal, or speed the emergency room induction process. With further probing, you would define the existing context and possibly even refine the goals with quantitative targets for improvement. Typically, the next step would be to review the existing literature. In the case of your health-care client, you would find existing evidence about each of the topics your client cares about. That’s because a lot exists on these topics. It’s just that the quality of it varies greatly and also it’s not easy to tell. It’s then up to your client and you to determine if you need more to feel confident about applying the evidence. If so, in this example, each of the goals clearly focuses on a research endeavor you could pursue with survey (nurse satisfaction), simulation modeling (emergency room throughput), data mining (medical records compared to room attributes), and observational techniques (nurse walking patterns and time with patients). We advise that literature review would go beyond design research sources. In the example above, nurse satisfaction might be best covered in human resources/ organizational dynamics research. Patient outcome could be informed by biomedical research. Although the linkages to design are generally not established in these disciplines, the core issues are. That narrows

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your job to linking the core issues to design, perhaps through an intervention and postoccupancy evaluation. The significant learning from a broad, cross-discipline study is that it keeps paramount what you are solving for, e.g., reducing nurse stress and fatigue by changing the layout, not shortening the corridors. Literature review will provide most of the clues you need to decide about the need to do original research and what methods and metrics to use, if you do. Existing peer-reviewed research will provide a background of prior studies and generally explain what findings have been validated over time and which ones need further study. The review will explain what methods the researcher chose to use in the research design and why, as well as the statistics used to analyze the data. We’re not suggesting that an untrained researcher should try to “do this at home.” Often the best approach is to engage an expert research partner. However, learning about the methodologies and metrics others have used can help a designer frame the research need enough to know if an expert research team is needed or if a simpler solution would suffice. Many forward-looking design firms have someone with research skills on their staff or have alliances with other firms, who can be objective external partners. IT’S GENERALLY GOOD ADVICE, IF YOU’RE NOT A TRAINED RESEARCHER, TO ENGAGE A DIVERSE AND INTERDISCIPLINARY TEAM OF EXPERTS TO VERIFY THAT THE CORRECT CRITICAL QUESTION IS BEING ASKED AND MOST APPROPRIATE, FERTILE METHODOLOGIES CONSIDERED.

YOU ALWAYS WANT TO PUSH FOR THE STRONGEST POSSIBLE EVIDENCE THAT’S FEASIBLE AND THAT’S NOT OVERKILL TO ANSWER THE QUESTION AT HAND. Choice of the right metrics runs parallel to methods. It starts with the question and an understanding of how the client needs to garner approval from their stakeholders. Self-rating on a basic 1-to-10 scale might suffice if your client wants to know how satis-

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fied the staff is (although in the spirit of always using more than one measure, you might also review turnover records). In contrast, in the emergency room example, patient or staff ratings would be very weak indicators compared to a simulation that predicts that a design intervention would increase “X” patients per hour and equates that to revenue increase or labor savings. SUMMARIZING, WE BELIEVE THAT THERE ARE SIX ATTRIBUTES OF QUALITY RESEARCH FOR DESIGN: 

A clearly defined and provocative research question, related to client goals, and informed by prior research and experience (Hypothesis)



Use of both disciplinary and interdisciplinary knowledge as a foundation (Epistemology)



Use of accepted standards for measuring performance outcomes (Metrics)



Striving for the most reliable and valid performance predictors, preferably from more than one study and using more than one methodology (Strength of evidence)



Peer review to certify the quality of methodology and reasonableness of outcomes (External validation)



Clear and understandable communication of research approaches, including assumptions, limitations, constraints, and methodology, so others can make good critical judgments about applicability to their context (Transparency)

Where Do We Go from Here? NEUROSCIENTIST FRED (RUSTY) GAGE OF THE SALK INSTITUTE MADE THE STATEMENT: “WITHOUT EVIDENCE THERE IS NO SCIENCE.” IT’S VERY DIFFERENT IN THE ARCHITECTURAL DESIGN PROCESS. IT’S DIFFICULT TO IMAGINE SAYING, “WITHOUT EVIDENCE WE ARE NOT ARCHITECTS.” BUT ARE WE THE BEST ARCHITECTS WE CAN BE?

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Architects and other design professionals would do well to better understand the implications of their work on the people who are affected by it. This does need to go beyond conjecture, if the design profession wants to do responsible work with positive outcomes and have credibility with clients. That doesn’t mean the average architectural practice needs to transform into a research company; nor should the design process revert to a research science model. It’s merely about an opportunity to evolve into something richer and more sustainable. The assumption by many is that evidence must be treated like codes and program criteria; a necessary evil, useful but constraining. Our research and experience suggests something very different—that evidence is information that can inspire better solutions and enhance the value of the designer to their client through better outcomes. If we’re right, evidence-based practice will help the average architect solve more complex problems, and do so creatively, and maintain good client relationships.

is essential to create a database of peer-reviewed research initiatives that can be archived and retrieved by the public.

The Most Fruitful, Near and Long-Term Areas for the Application of EvidenceBased Design Based upon our research we have identified three specific areas where greatest innovation will occur. Some are here and now; others will be in the near term; and some will require more time to become feasible for most practices, but the seeds are already here for those who wish to lead the profession. All can be incorporated into practices of all sizes through differing operating mechanisms sensitive to the skills and resources of the practitioners. 

How? 

Develop a better appreciation for research methods, in order to make good judgments about the strength of evidence they might choose to apply to their projects. This should start with design education.



Actively seek information from beyond the design world and consider what it might mean for solving design problems. Multi-disciplinary collaborations, with the architect as orchestrator, would be one great starting point.



Fearlessly measure the outcomes of each design intervention to inform the next project.



Expand beyond individual project research and advocate for shared databases on design impacts. We advocate expansion of the work instigated by the University of Minnesota and their database titled “Informed Design.” Other academic, institutional, and professional organization support

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Building Performance: In response to a desire to create new types of formal architecture—more complex structures—and to advance environmental sustainability building—reduce carbon footprint—designers, chemists, and physicists are coming together to recombine and repurpose materials, and develop new ultra-performing materials and systems. Evidencebased methods are being used to assess how these initiatives might enhance building performance. 



Research about new materials and building systems is being done primarily by smaller, designoriented firms with principals who are engaged in teaching. The research, design, and teaching are integrated activities that intellectually stimulate and inform each other. Design exploration is the primary incentive and research is the “means rather than the end.” This exciting opportunity is being enhanced since major building product manufacturers are putting their scientific, business, and marking knowledge and resources behind collaborations with designers.

Human Performance: Use of environmental psychology methodologies—surveys and observational

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studies—are becoming more commonplace as part of design programming, in all sizes of firms. The most forward-looking work seeks to use design as a lever to improve organizational performance. In that sense, some practitioners distinguish their research from programming and postoccupancy evaluations, both of which are often understood to be all about defining space, rather than influencing effective human behaviors. 



Regardless of what it’s called, using evidence to assure performance outcomes, rather than spaces without regard to their impacts, will become the norm for designers who are respected by their clients as adding value. Some of this evidence will come from shared databases and some from original research by the practitioners; but most will not be limited to one project or one firm. Research collaborations with social scientists and designers will improve the quality of both quantitative and qualitative evidence and prove that physical environments can measurably support and even transform human performance.

Neuroscience: The new field of neuro-architecture, which brings together architecture and neuroscience, will provide timely physiological feedback as well as potentially a more reliably predictive understanding of human response to design. There is a recent group of graduates from joint neuroscience and architectural programs who will be able to apply the science to design decisions and thereby create truly human-centric environments. With added research, more evidence, and a stronger database of dependable knowledge, we will soon see neuroscience used as evidence for a new level of informed design. This will be the new frontier.

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A Final Word Starting right now, design practitioners and educators should be aware of the varied evidence-based initiatives being explored today and consider ways to use the knowledge, tools, and methods to improve the impacts their work has on those who experience it. THE NEXT GENERATION OF PRACTITIONERS WILL NEED TO RAISE THE BAR FURTHER. They should be armed with many new approaches that will permit a more relevant practice model, one that is needed to respond to the complexity of global challenges. Architectural education will have a major role in influencing and directing this change, in a collaborative context with practice, and clients. The goal of our book has been not merely to identify the importance of empiricism in architecture. We’ve also intended to shed light on the range of evidence that can be useful; how new evidence can be developed; and what methodologies and standards are needed to yield information one can trust. OUR HOPE IS THAT THESE IDEAS WILL RESONATE WITH MANY PRACTITIONERS AND EDUCATORS, WHO BY EXPLORING AND APLYING THEM WILL FIND THAT THEIR WORK IS RICHER AND HAS HIGHER IMPACT; THEIR PROFESSIONAL CREDIBILITY IS ENHANCED; THEIR COMMERCIAL SUCCESS BOLSTERED. WE DON’T BELIEVE EVIDENCE-BASED PRACTICE SHOULD BE FOR A RARIFIED FEW. WHEN SYSTEMS TO CREATE, COMMUNICATE, AND APPLY STRONG, DIVERSE EVIDENCE ARE IN PLACE AND EMBEDDED WITHIN THE CREATIVE DESIGN PROCESS, ARCHITECTURE WILL BE RECOGNIZED AS A VALUABLE, KNOWLEDGE-BASED PROFESSION—A VISION SHARED BY MOST DESIGNERS.

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Index A Academy of Neuroscience for Architecture (ANFA), 235, 273, 275–276, 278, 288 ACC Project, 54 Actuated tensegrity, 284 Acuators and sensors, 285 AEC Division, 128 Aegis Hyposurfaces, 285 AIA College of Fellows Latrobe Fellowship 2005, 10, 256 AIA Committee on the Environment, 39 Air Quality, 258, 265, 267 Albright, Tom, 235 Almquist, Julia R., 161 Alternative Energy Generation, 129 Alzheimers disease, 175 Anatomy of the brain, 233 ANSYS, 95 Apple Store Los Angeles, 66 Manhattan (5th Avenue), 62 Architectural Record, 128 Architecture Engineering Construction (AEC), 12, 131 Arens, Edward, 261 ARUP , 110, 294, 297, 300, 306 ASHRAE Standard, 261, 267, 298 AutoCAD, 71 Autodesk, 128 B BatWing, 102, 107 Behavioral science, 259 BIDS database, 257–260 BIO X, Stanford University, 289 Biological Response to Environment, 322 Biophilia, 254

329

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INDEX

Bishopsgate Tower, 119 Boeing, 103 Bolla, Glass dome, 302 Brager, Gail, 268 Bromberg, Joyce, 157 Brooks, David, 2 Brownell, Blaine, 282 Building Energy Performance Data Standards, 34 Building Information Model (BMI), 13, 71, 163, 255 Building materials and building systems, 322 Building monitoring systems, 75, 1 Building orientation, 129 Building performance, 1, 12, 131, 326, 232, 236, 254–260, 281 Building Thermal Units (BTUs), 159 Burnstein, Phillip G., 12, 128 Buro Happold Consulting Engineers, 94 C CAL iT2, 289 California Academy of Science (CAS), 9, 256, 293 Cam, Calvin, 166 Camera Obscura-Mitchell Park, 83 Carnegie Mellon University, 253 Carrier, Karen, 66 Carter, Rita, 233 Cellophane House, 249 Center for Disease Control and Prevention (CDC), 142 Center for Health Design, 5, 145 Center for Integrated Facility Engineering (CIFE), 157, 161 Center for the Built Environment (CBE), 33, 40, 261, 268–269, 281 Centre Pompidou, 107 Cerebellum, 234 Cerebral cortex, 234 Chang, Renee, 132 Chicago Project, 134 Chong Partners Architecture (now Stantec Architecture), 10, 235, 256, 294 Chong, Gordon, 256, 268 Circadean system and design, 263–268 CityCar, 24 Clinical evidence, 17 Collaboration, 257 Columbia University, 77

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Commissioning, 304–305 Computational Design Optimization (CDO), 120 Computational Fluid Dynamics (CDF) , 297–299 Computational tools, 171 Computer Facility Management System, 304–305 Construction management rools, 158 Consultation room design, 161–164 Cooke, Gilbert, 235, 289 Corpus callosum, 234 Cost modeling, cost-base database, cost benefit analysis, 255, 257, 259 Cottage industry, 132 Craig, David, 150 Creativity, 4, 152, 159–160, 165–166, 173, 176 Crissy Field Center, 42, 48 D DalyGenik Architects, 52 Data mining, 7, 14–15 Database infrastructure, 172 Day lighting, 34 Deep pleats, 109 DEGW, 150 Denton, Barbara, 139, 268 Department of Defense (DOD), 142 Department of Energy (DOE), 34, 142, 238 Desalinization, 104 Design metrics, 240–241 Designtex, 147 DeSimone Consulting Engineers, 99 Deutsche Immobilien-Fonds AG (DIFA), 122 Digital project, 71, 74 Digital technology, 70 Digital tools, 15 Disruptive Organic Photovoltaic (CPV), 242 Division of Biological Science, University of California San Diego, 289 DOE2, 33, 60 Doidge, Norman, 334 Dragonfly, 94 Drivers-of-change, 112, 116 Dual-ontology, 101 Ductal concrete, 286 Dupont, 238

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E Echotech, 71 Ecological sustainability, 9, 59 eCommerce, 110 Edelstein, Eve, 262–263, 268 Education, 179 Electrical Power Research Institute (EPRI), 256 Electroencephalography (EEG), 234 EMERGENT, 93 Empirical Science, 322 Enclosure Systems, 129 Energy efficient digital technologies, 237 Energy modeling, 233 Energy optimization, 129 Energy Plus, 44 Environmenatl Design Research Association (EDRA), 145 Environmental ethics, 252 Environmental Protection Agency (EPA), 142 Environmentally Preferred Purchasing (EPP), 148 Epidemiology, 278–279, 325 Ergonomics, 254, 258 Ethyleen tetrafuoroethylene (ETFE), 283 Evidence, 321 Evidence-based design (EBD), 2, 321 Evidence-based medicine (EBM), 5, 323 Evidence-based practice (EBP), 4, 322 Evidence-based practice precedents, 262–263 Experience, 322 External validation, 325 F F-22A Raptor, 103 Fabricated physical prototypes, 171 Fabrication technologies, 15 Facebook, 131 Fashion Institute of Technology (FIT), 79–81 Feedback loop, 262, 269, 295, 304 Fiber reinforced polymer, 286, 286 1560 Trapelo Road, 137 Fischer, Martin, 157, 166 Fog Zero, 41 Foot candles, 44

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Foresight, 111 4D Models, 158 Freshwater Plaza, 104 Frontal lobe, 234 Full scale mock ups, 294–295, 297, 300, 302 Functional magnetic resonance imaging (FMRI), 234 Futures workshop(s), 111, 114, 117 G Gage, Fred (Rusty), 235, 272, 288, 294 Garfield Centre, 139, 142 Generative components, 71 Giatti Wool Mill, 101 Glass (Bolla) dome, 302 Global population, 27 Golden Gate Park, 295 Google, 131 GPS—Electronic way finding, 243 Green building performance, 167–169, 303 Greenbuild, 48 Griffith, Tim, 306 GSA, 164 H Hall, Edward, 144 Hamilton, Kirk, 5 Hard science, 232, 236, 275–276 Harding, Ari, 304 Hartkopp, Volker, 260 Hearthstone Alzheimer Care, 174 Heat coefficient, 37 Heating Ventilation Air Conditioning (HVAC), 96 Helsinki University of Technology, 166 Henrickson, Steve, 235 High misting fire suppression, 302 High-definition electroencephalograph multi electrode cap with wireless telemetry, 289 High-performance skin, 36 Hippocampus, 234 Housing design, 181 Human and environmental performance, 321 Human performance, 1, 232, 255, 277, 323, 326,

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334

INDEX

Human-centric design research, 158 Humann, Christian, 64 HUT-600, 167 Hybrid structures, 287, 287 Hydrogen producing algae glass, 297 Hypothalmus, 234 Hypothesis, 252, 255, 273–274, 276, 325 I IKEA, 76 Imaging Technologies, 233–234 Industry Foundation Classes (IFC), 166 Information, 13 Information Age, 171 Informed design, 326 Integrated data model, 260–262 Integrated Design Excellence Analysis (IDEA), 203 Integrated Project Delivery (IPD), 13 Intellectual capital, 14, 171 Interdisciplinary collaborations, 6 Interdisciplinary teams, 160, 178 International Standards Organization (ISO), 249–250, 267 Intuition, 239, 248, 251, 322 Iterative process, 14, 171 J Jacobs, Jane, 144 Eberhard, John, 235 Journal of the American Medical Association (JAMA), 279 Joyce Bromberg, Steelcase, 235 K Kaiser Permanente, 10, 40, 140, 235, 256 Kelly, Caroline, MID, 161 Kennedy, Sheila, 236, 281 Kiang, Kang, 306 Kiocelek, Patrick, 296 Kipnis, Jeff, 94, 101 Kishna Shenoy, Stanford University, 290 Knowledge, 13 Knowledge-based profession, 327 Kouletsis, John, 139

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INDEX

335

Kryder’s Law, 14 Kwinter, Stanford, 100 L Laing, Andrew, 150 Lamont, Susan, 306 Latrobe Fellowship, AIA College of Fellows , 235, 248 2005 Latrobe Fellowship, 256 Lavedrine, Isabelle, 306 Lawrence Berkeley National Lab (LBNL), 33, 40, 64 LDI Corporation, 147 Leadership in Energy and Environmental Design (LEED), 32, 38, 135, 249, 255, 263, 298 LED lighting, 241 Lee, Laura, 132 Legible, 17 Lenticular trusses, 90 Life cycle tools, 257 Lighting design literature, 263–265 Limbic system, 234 Literature search, 273, 298–299 Litracon, 286 Lockheed Martin, 103 Loftness, Vivian, 253 Loisos + Ubbelohde, 41 Loisos, George, 32 Louvre Pyramid, 66 Lovins, Amory, 246 Luebkeman, Chris, 110 M MaCagno, Edwardo, 235, 289 Magnetic resonance imaging (MRI), 234 Magnetoencephalography (MEG), 234 MAHARMA, 147 Make it Work Exhibition, AIA New York, 283 Mapping, 172 Masseschuetts Institute of TechnologyMIT, 17 MATx, 237, 241, 246–247, 282 Mayo Clinic, 161–164 Mean Radiant Temperature (MRT), 60 Mechanical cathedral, 106

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336

INDEX

Mechanical cooling, 44 Mechanical Electrical Plumbing (MEP), 98 Media Labs Smart Cities Research Group, 17 Membrane Systems, 283 Metrics, 232, 325 Mies van der Rohe, 101 Miller, Herman, 238 Mitchell, William (Bill) J., 17 Mobility-on-demand, 23, 28 Mode 2 Knowledge Production, 258–259 Modeling, 13 Models, prototypes, full scale mock ups, 294 Moore’s Law, 14 Multidisciplinary shared simulation models, 163 Multiple-criteria Decision Model (MCDM), 49 N National Academy of Science (NSF), 238, 273 National Architectural Accrediting Board (NAAB), 22 National Endowment for the Arts (NEA), 238 National Facility Services (NFS), 147 National Facility Service Division, Kaiser Permanente, 139 National Gallery in Berlin, 101 National Institute of Mental Health (NIH), 253, 256, 276 National Institute of Occupational Safety Health (NIOSH), 142 Natural science, 232, 236, 288 Natural ventilation, 44 Near Infra-red Spectroscopy (NIRS), 234 Nervi, Pier Luigi, 101 Neuro-architecture, 235 Neuro-genesis, 272 Neuro-plasticity, 233–234 Neuro-science, 8, 232–233, 259, 327 New England Journal of Medicine, 279 New Material & Design System Development, 236, 281 New York City Department of Parks, 243 Department of Transportation, 243 Economic Development Corporation, 243 Newman, Oscar, 256 Nine-step process, 141 Nonrationalized approach, 173 North Face, 238

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INDEX

337

O Observation, 177 Occipital Lobe, 234 Occupant Satisfaction Survey, 265–267 Open Source education, 252 Operational prototypes, 24 Opto-electronics skunkworks, 239 Organizational Behaviors and Performance, 322 Orr, David, 57 OSRAM, 238 P Pacific Energy Center, 32 Parametric drawing, 11 Parietal lobe, 234 Peer Review, 296–297 Pelli Clarke Pelli Architects, 128 Pelli, Cesar, 130 Performa, 111 Performance based-code compliance, 297, 300–301 Perspective, 11 Photovoltaic cells and panels, 301 Physical and natural sciences, 8 Physical model, 11 Physical science, 232, 236, 275, 281 Physics, 8 Physiological research, 232 Physiological response, 259, 261 Playpen, 22 Positron emission topography (PET), 234 Postoccupancy evaulations, 6 Postrationalized approach, 173 Powell, Kevin, 164 Pragmatism, 184–185 Prerationalized approach, 173 Process-based, 78 Product Model Fourth Dimension (PM4D), 166 Productivity, 267 Proto-form, 82 Prototype, 12 prototyping, 14 Psychology, 7

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338

INDEX

Q Qualitative measurement, 232 R Radiant Software, 64 Rapid prototyping, 15, 294 Re-fabricating architecture, 248 Reflective practice, 12 Reliability, 172 Reliable evidence, 323 Renzo Piano Building Workshop (RPBW), 293 Research,182 context, 143 integrity, 184 methods, 143, 146–149, 151–153, 158–159 six sigma, 165 six step process, 162 plan, 260 program, 166 Revit, 71, 73, 130 Rhino, 71, 74 Robo Scooter, 24 Royal Institute of British Architects (RIBA), 34 S Sackett, William, 5 Saint-Gobain, 238 Saitowitz, Stanely, 64 Salk Institute, 272, 325 Schon, Donald A., 2 Scientific evidence, 19, 322 Scientific method, 4 Sea Port Tower, 87 Semantic Differential Scale, 266 Shading, 44 Sharples, Christopher, 70 Sharples, William, 70 Shatz, Carla, 289 SHoP Architects, 70 Siemans, 238 Simulated performance, 171

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INDEX

339

Simulation, 7, 14 simulation technology, 12 Simulation, modeling and data mining, 270 Smart Wrap, 248, 285 Social sciences, 7 and design, 142 areas of investigation, 145–146 Social Scientific Questionnaire, 266 Society of Neuroscience, 273 Sociology, 7 Soft Energy Path, 246 Soft House, 241, 246–247 Solar nano-material, 241 Solar textiles, 241 Standard of care, 295 Stanford Graduate Housing, 60 Stanford University, 157 Sternberg, Esther, 235, 276, 288 Stone, Stephanie, 306 Strength of evidence, 325 Structual expressionism, 101 Student Housing Art Center College of Design, 52 Sustainability, 9, 59 Sustainable Fabric Alliance Program, 146, 147 Sustainable products, 145 Szakkats, Geza S, 306 T TED conference, 116 Templates 2000, 139 Temporal lobe, 234 Thalmus, 234 Thermal comfort, 254, 258, 265, 266, 281 3D Printing, 15 3DS Max, 130 Timberlake, James, 248, 281 Title 24, 40 Total Health Environment Initiative, 139, 143 Transmaterial One and Transmaterial Two, 282 Transparency, 3, 10, 325 Typical design practitioners, 6

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340

INDEX

U U value, 37 Ubbelohde, Susan, 32, 64 Underhill, Paco, 170 U.S. Department of Defense (DOD), 142 U.S. Department of Energy (DOE), 34, 142, 238 U.S. General Services Administration (GSA), 34 U.S. Green Building Council, (USGBC), 303 University of California Berkeley, 10, 235, 261 University of California San Diego, Division of Biological Science, 289 Urban densification, 27 V Valid evidence, 323 Validity, 172 Virtual models, 15, 171 Virtual Reality (VR) Technologies, 289 Virtual Reality-Experimential Virtual Environment (VR-EVE), 167 Visualization, 233 Vitruvius, 231 W Watkinson School, 42, 48 Weather stations, CAS, 303 Webcor Builders, 294 West Thames Street Pedestrian Bridge, 90 Wheel robots, 28 Wild structures, 98 Wiscombe, Tom, 93 Wolski, Armin, 306 Work flow, 71 Y Yale University, 12 Z Zeisel, John, 174–175, 235 Zero car, 25

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C1 Environmental strategies

C2 California Academy of Science birds-eye view of roof

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C3 California Academy of Science entry elevation

C4 California Academy of Science Landscape roof forms

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C5 California Academy of Science operable skylights providing nighttime cooling

C6 Predicted Velocity vectors at 3’-6” AFL in the Exhibit Hall under summer design day conditions

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C7 Temperature-colored air flow pattern in the Exhibit Hall under summer design day conditions

C8 Predicted Velocity vectors in a North-South section in the Exhibit Hall under summer design day conditions

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C9 Predicted velocity vectors around and inside the Exhibit Hall of the California Academy of Sciences representing wind patterns along the roof and inside the Hall in a north-south section

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C10 Full Scale Structural Steel Mock-Up

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C11 Full Scale Roof System Mock-Up

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C12 Landscape Mock-Up

C13 Cal Acad. Science interior shading devices over the central piazza

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 C14 California Academy of Science glass bolla enclosing the rainforest environment

 C15 California Academy of Science transparent glazed covering of central interior piazza

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BRANDT

Architecture/Design

CHONG MARTIN

The Power of Evidence to Create Design Excellence his practical, accessible book—for design professionals and students alike—is about design excellence and how to achieve it. The authors propose an evidence-based design approach that builds on design ingenuity with the use of research in ways that enhance opportunities to innovate. They show the power of research data to both reveal new design opportunities and convince stakeholders of the value of extraordinary work. A guide for all designers who want to earn their place as their clients’ trusted advisor and who aspire to create places of beauty and purpose, the book demonstrates: • An approach to applying evidence to design that neither turns designers into scientists nor requires large-firm resources • The wide range of types of evidence that can be applicable to design and where to look for it • Direct, practical application of the evidence-based design approaches in use today • Provides tools to distinguish strong evidence that can improve design decisions from misleading assertions resulting from weak research • Benefits of evidence-based design, including improved human and building performance Two featured case studies illustrate the theory and practice of evidence-based design. The work of the authors’ 2005–2007 AIA College of Fellows Benjamin Latrobe Research Fellowship provided an empirical foundation for this book, and addresses the use of rigorous research methods to understand relationships between design choices and health outcomes. The California Academy of Sciences, designed by Renzo Piano Building Workshop, Chong Partners Architecture, and Arup, provides transparent evidence that enhances building technology performance in the context of a powerful design expression. In-depth interviews and case studies are clustered around three research categories: modeling, simulation, and data mining; social and behavioral science and the physical and natural sciences; and including cutting-edge use of neuroscience to understand human response to physical environments. The twenty-two featured thought leaders include: William Mitchell, MIT Media Lab; Fred Gage, Salk Institute; Phil Bernstein, Autodesk; Sheila Kennedy, Kennedy & Violich; James Timberlake, KieranTimberlake; William and Chris Sharples, SHoP Architects; Vivian Loftness, Carnegie Mellon University; John Zeisel, Hearthstone; Paco Underhill, Envirosell; Susan Ubbelohde and George Loisos, Loisos+Ubbelohde Architecture-Energy; Chris Luebkeman, Arup; Martin Fischer, Stanford University CIFE; and Kevin Powell, GSA.

R OBERT B RANDT , AIA, LEED AP, a real estate planner for Intuit, has more than thirty years of design/ behavior and strategic planning experience with Stantec, Chong Partners, and as a managing partner at HLW International. His clients have included News Corporation, General Motors, University of California, San Francisco, and Amgen. Brandt was a team leader for the 2005–2007 AIA Latrobe Research Fellowship. G ORDON H. C HONG , FAIA, served as the national president of The American Institute of Architects in 2002 and president of The Academy of Neuroscience for Architecture from 2007 to 2009. As a founder of Chong Partners Architecture, he led the team that received the 2005–2007 AIA Latrobe Research Fellowship. W. M I K E M A R T I N , P H D, FAIA, Professor Emeritus, University of California, Berkeley, has served as the undergraduate dean of the College of Environmental Design and chair of the Architecture Department. A co-recipient of the 2005–2007 AIA Latrobe Research Fellowship for Research, Martin served as president-elect of the San Francisco chapter of the AIA and as the editor of Architecture California (AIACC).

design informed

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DRIVING I N N OVAT I O N WITH

EVIDENCEBASED DESIGN

ROBERT BRANDT GORDON H. CHONG W. M I K E M A R T I N

design

informed DRIVING I N N OVAT I O N WITH

EVIDENCEBASED DESIGN