BoundaryValue Problems
Ladis D. Kovach Naval Postgraduate School
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BoundaryValue Problems
Ladis D. Kovach Naval Postgraduate School
£ 'V Addison•Wesley Publishing Company Reading, Massachusetts • Menlo Park, California
London • Amsterdam • Don Mills, Ontario • Sydney
Copyright © 1984 by AddisonWesley Publishing Company, Inc. All rights reserved. No pan of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form, or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America. Published simultaneously in Canada. iSBN: 0201117282
ABCDEFGIllJDO8987654
Contents
I
REVIEW OF ORDINARY DIFFERENTIAL EQUATIONS
1.1 Linear homogeneous equations with constant coefficients 1.2 Nonhomogeneous equations with constant coefficients 1.3 CauchyEuler equations 1.4 Infinite series 1.5 Series solutions 1.6 Uniform convergence
£'
BOUNDARYVALUE PROBLEMS IN ORDINARY DIFFERENTIAL EQUATIONS
2.1 Some preliminaries 2.2 SturmLiouville problems 2.3 Orthogonality of eigen functions 2.4 Representation by a series of orthonormal functions 2.5 Convergence and completeness 2.6 Seifadjoint equations 2.7 Other Sturm—Liouville systems 2.8 Numerical methods
3
1
1
7 13
20 27 41
49
49 55
62 67 73
80 86 91
PARTIAL DIFFERENTIAL EQUATIONS
102
3.1 Introduction 3.2 Separation of variables
102 112 vII
Contents
4
3.3 Thewaveequation 3.4 The diffusion equation
121
3.5 Canonical forms
140
FOURIER SERIES
4.1 Introduction 4.2 Fourier coefficients 4.3 Cosine, sine, and exponential series 4.4 Applications
4.5 convergence
5
U
'7
I
133
152
152 153 165 174
182
FOURIER INTEGRALS AND TRANSFORMS
194
5.1 The Fourier integral 5.2 Fourier transforms 5.3 Applications
204 217
BOUNDARY•VALUE PROBLEMS IN RECTANGULAR COORDINATES
194
226
6.1 Laplace's equation 6.2 The wave equation 6.3 The diffusion equation
226
6.4 Fourier and Laplace transform methods 6.5 Verification of solutions
263 275
PROBLEMS IN OTHER COORDINATE SYSTEMS
7.1 Polarcoordinates 7.2 Cylindrical coordinates; Bessel functions 7.3 Spherical coordinates; Legendre polynomials 7.4 Applications
239
253
287 287 299 318 338
Contents
8 NUMERICAL METHODS 8.1 Introduction 8.2 A Monte Carlo method 8.3 Finitedifference approximations 8.4 Application to magnetic induction
ix
355
355 356
359 368
GENERAL REFERENCES
381
APPENDIX
383
Table
I
Exponential and hyperbolic functions
Table II Laplace transforms Table III Fourier transforms
383 385 388
ANSWERS AND HINTS TO SELECTED EXERCISES
389
INDEX
413
Preface
The
author's objective in writing Boundary Value Problems is to present
methods of solving secondorder linear partial differential equations that arise
in applications. For the most part, the methods Consist of separation of variables and (Laplace and Fourier) transform methods. Since these methods lead to ordinary differential equations, it is assumed that the student has the necessary background in this subject. Chapter 1 provides a ready reference to topics in ordinary differential
equations and may be consulted as needed. ft is not intended that this reference chapter be included in a course in boundaryvalue problems, although the section on uniform convergence may be particularly helpful.
In Chapter 2 the difference between initialvalue problems and boundaryvalue problems in ordinary differential equations is pointed out. This leads naturally into the prolific Sturm—Liouville theory, including the representation of a function by a series of orthonormal functions. Convergence and completeness are also presented here. Separation of variables is introduced in Chapter 3 in connection with
Laplace's equation and the heat equation. D'Alembert's solution of the vibrating infinite string is included and extended to a finite string with boundary
conditions. The chapter concludes with the canonical forms of elliptic, parabolic, and hyperbolic equations. Fourier series is the main topic in Chapter 4. In addition to cosine, sine,
and exponential series, there is a section on applications and one on convergence. A heuristic argument extends Fourier series to Fourier integrals in Chapter 5. This extension then leads naturally to the Fourier transform and its applications. All of the foregoing is brought together in Chapter 6, which is devoted to the solution of boundaryvalue problems expressed in rectangular coordi
nates. Included is the treatment of nonhomogeneous equations and nonhomogeneous boundary conditions. Fourier and Laplace transform methods of solution follow and there is also a Section on the important, but often neglected, topic of the verification of solutions.
Preface
Chapter 7 contains the necessary variations to boundaryvalue problems phrased in polar, cylindrical, and spherical coordinates. This leads into discussions of Bessel functions and Legendre polynomials and their properties. A final chapter is devoted to numerical methods for solving boundaryvalue problems in both rectangular and polar coordinates. There is a conscious effort to separate theory, applications, and numerical methods. This is done not only to preserve the mainstream of the development without distracting ramifications but also to provide the instructor with a maximum amount of flexibility. Since some sections are independent of the main theme, they may be included or omitted depending on the available time and the makeup of the class. Additional flexibility can be found in the exercises. There are more than
1400 exercises at the ends of sections and these are divided into three categories. The first group helps to clarify the textual material and fills in details that have
of necessity been omitted. The next, and most numerous, group consists of variations of the examples in the text and sufficient additional exercises to provide the practice most students need for a complete understanding of the material. A third group Consists of more challenging exercises and those that extend
the theory. Some suggestions for outside reading are also included in this group. Exercises that are of a computational nature are indicated by an asterisk (*)
It is a firm conviction of the author that the inclusion of historical sidelights is helpful to the reader and provides a welcome change of pace as well. Unfortunately, historical "facts" are sometimes controversial and provide fuel for hot debates on various topics, such as who was the originator of a particular method and the like. Unless otherwise indicated, we have used Florian Cajori's, A History of Mathematics, 3d ed. (New York: Chelsea, 1980) as a reference. This classic, first published in 1893, has endured to serve as an excellent source book. Much of the material in this text has been used in classrooms during the past fifteen years. Some sections have appeared in the author's Advanced Engineering Mathematics (Reading, Mass.: AddisonWesley, 1982). Preliminary versions of the present text were read by Ronald Guenther, Oregon State University; Roman Voronka, New Jersey Institute of Technology; and Euel Kennedy, California Polytechnic State University, and their incisive suggestions have been incorporated. The contributions of these reviewers is hereby gratefully acknowledged. Thanks are also due to Judy Caswell who did all the typing and to Wayne Yuhasz for his encouragement and editorial guidance. The staff at AddisonWesley has been cooperative and helpful throughout the project. Finally, the many thousands of students who have offered valuable suggestions have provided the most important resource an author can have. Monterey, Calffornia July 1983
L.D.K.
Review of Ordinary Differential Equations
•'
LINEAR HOMOGENEOUS EQUATIONS WITH CONSTANT COEFFICIENTS We present here a brief review of some of the types of ordinary differential equations a student should have met prior to studying boundaryvalue problems. Succeeding chapters will lean heavily on the material in this first chapter. Since practically all our references to ordinary differential equations will be to secondorder linear equations, we will confine our discussion to these. Examples will be used freely, and theory will be kept to a minimum. A common type of problem, which fortunately is also one of the simplest to solve, is the following initialvalue problem:
y"+ay'+by=O, Here
(111) 
y'(O) = d.
y(O) = c,
a, b, c, and d are real numbers, and the primes denote differentiation
with respect to some independent variable, say, x. The homogeneous differential equation in (1.11) has a general solution that is a linear combination of two linearly independent functions, each of which satisfies the given equation. Since there are two initial conditions, a unique solution can always be found. We illustrate with some examples. EXAMPLE 1.1—1
Solve the initialvalue problem
y"—y'6y=O, Solution
The substitution y =
exp
y(O)=3, (rx)
results
r2 — r — 6 = 0
I
y'(O)=4. in the characteristic equation
CHAP. I
Review of Ordinary Differential Equations
and the general solution
y=
c1 exp
(—2x) + ('2 exp (3x).
Substituting the initial values into the general solution and its derivative produces the system of linear equations
+c2=3,
c1
—2c1
We find c1
= I,
+ 3c2
(11—2)
4.
= 2, so the particular solution sought is
y=exp(—2x)+2exp(3x).
U
We observe that the two functions y1(x) =
exp (— 2x) and y2(X) =
exp (3x) are linearly independent on every interval because their Wronskian*
yj(x) y2(x) yj(x)
(—2x) exp (— 2x) exp
—
—2
exp (3x) 3 exp (3x)
=
ex x
—2
3
= 5 exp x
is everywhere different from zero. It is precisely for this reason that the system (1.1—2) has a unique solution, which, in turn, leads to the unique solution of the initialvalue problem. EXAMPLE 1.1—2
y" Solution
Solve the initialvalue problem
+ 2y
+ y = 0,
y(0) = 3,
y'(O) = —5.
The characteristic equation
r2+2r+l
=(r+ 1)2=0
has two equal roots, and it can be shown that y1(x) = exp (—x) and y2(x) = x exp (—x) are two linearly independent solutions of the given differential equation. Hence the general solution is y = c1 exp (— x) + c2x exp (— x),
so that the initial conditions yield the system = =
—Ci + and
3
the particular solution (Fig. 1.1I) y = 3 exp
(— x)
— 2x exp (— x).
U
sThe Wronskian is a special determinant, named in honor of Hoené Wronski (1778—1853), a Polish mathematician and philosopher. The word was coined in 1881 by Sir Thomas Muir (18441934), an English mathematician and educator, who also originated the word "radian."
SEC. 1.1
LInear Homogeneous Equations with Constant Coefficients y
Yi =3exp(—x)
x
—I
Y2
—2x exp (—x)
FIgure 1.11
Graph of 3exp(—x) — 2x.xp(—x).
In this last example, knowing that y' = exp (— x) is a solution, we can (— x) is a second solution, substitute it into the given differential equation, and solve the resulting differential equation for u(x). This elegant method of finding a second linearly independent solution of a differential equation when one solution is known is called the method of reduction of order. The name comes from the fact that the resulting differential equation for u(x) can be treated as afirstorder equation. The reduction of order method is not limited to differential equations with constant coefficients but can be applied to any linear equation, that is, to an equation of the form assume that y2(x) = u(x) exp
y" + a(x)y' EXAMPLE 1.1—3
+ b(x)y = 0.
(1.1—3)
Solve the initialvalue problem
— 4y' + 13y = 0,
y(O) = y'(O) =
3.
Solution In this example the roots of the characteristic equation r2 — 4r + 13 = 0
CHAP. I
Review of Ordinary Differential Equations
are
the complex numbers 2 ±
y=
31.
Hence the general solution is
exp (24(c1 cos
3x + c2
sin 3x)
so that the initial conditions result in the system Cl — 3,
2c1 + 3c2 = 3
and the particular solution
y=
exp (2x)(3 cos 3x — sin 3x).
U
In the last three examples we have examined the three possible cases that can arise in the study of secondorder linear homogeneous equations with constant coefficients. In each case the characteristic equation is a quadratic equation, the roots of which must fall into one of the three cases illustrated in Fig. 1.12.
f(r) = r2 + at + b
(bi
(a)
ftr)
r2 + at + b
(c)
Fl9ure 1.12
Graphs of characteristic equations. (a) Real and unequal roots. (b) Real and equal roots. (C) Complex roots.
Linear Homogeneous Equations with Constant Coefficients
SEC. 1.1
5
In the next section we will consider nonhomogeneous equations of a special kind.
Key Words and Phrases initialvalue problem characteristic equation general solution particular solution
linearly independent solutions Wronskian reduction of order linear differential equation
1.1 Exercises* •
1.
Verify that in order fory = exp (rx) to satisfy y" — — 6y = 0 it is necessary that r satisfy the characteristic equation r2 — r — 6 = 0. (Example 1.1—I)
2.
Obtain the system (1.1—2), and then solve it for c1 and c2.
3.
Verify that the Wronskian of yi(x) = exp (—2x) and y2(x) = exp (3x), written W[y1(x), y2(x)], has the value 5 exp x. Verify that the substitution of y = exp (rx) into y" + 2y' + y = 0 leads to the characteristic equation (r + 1)2 = 0. (Example 1.1—2)
4.
5.
Verify that Yi (x) = exp
(— x)
and y2(x) = x exp (— x) both
satisfy y" + 2y' +
y = 0. 6.
Compute the Wronskian,
7.
Obtain the particular solution in Example 1.12. Obtain the roots of the characteristic equation of y" — 4y' + l3y = 0. Verify that y,(x) = exp (2x) cos 3x and y2(x) = exp (2x) sin 3x both satisfy
8. 9.
—
4y' + 13y =
y2(x)], of the functions in Exercise 5.
0.
Compute the Wronskian of the functions y1(x) and y2(x) of Exercise 9. Obtain the particular solution in Example 1.1—3. 12. Find the general solution to each of the following equations.
10.
•'
11.
(a) (b)
y" — 3y' + 2y
= 0
y—6y'+ 9y=0
— 6y' + 25y = 0 Find the general solution of (c)
13.
—
3y' = 0.
sExercises at the end of each section are divided into three parts. Those in the first group are related directly to the text in that they help to clarify the textual material or supply computational steps that have been omitted. In the second group are exercises that provide the necessary practice so that the student may become more familiar with the methods and techniques presented. The last group includes exercises of a more theoretical or challenging nature.
RevIew of Ordinary Differential Equations
6 14.
Solve each of the following equations completely. (a) + 2y' + 2y = 0 (b) (c)
(d)
15.
y" + y' + 2y = 0 y'(O) = 8y" + 4y' + y = 0, y(O) = 0, x'fr/4) = 3 x" + 4x = 0, xfr/4) = 1,
I
(Hint: The prime denotes differentiation with respect to some independen variable, say, 1.) Solve each of the following initialvalue problems. (a) (b)
(c) 16.
CHAP. I
y(0)=0,
y'(0)=2
y(O)=2, y'(O)=9 y"—4y'+4y=O, y(O)=3, y'(O)= —6
Find the general solutions in each of the following. (a) y — 4y = 0,
the dot representing
(b)
u" + 6u' + 9u = 0,
(c)
y + 5y'
with u = u(v) with y = y(r) (d) withy = y(x) — 2y' — 35y = 0, 17. Solve each of the following initialvalue problems. = 0,
(a) x" + x' — 3x = 0, (b) U" + 5u' + 6u = 0, (c)
8+2iO+w20=O,
x(O) = 0,
u(0) = I,
8(l)=l,
x'(O) =
1
u'(O) = 2
O(l)=l/i
4y" + 20y' + 25y = 0. y(O) = 1, y'(O) = 2 18. Show, by computing their Wronskian, that the functions exp (ax) cos (ax) and exp (ax) sin (ax) are linearly independent for all x. 19. (a) Given that y' = exp (—x) is a solution of y" + 2y' + y 0, assume that y2(x) = u(x) exp (— x) is a solution and thus obtain u "(x) = 0. (d)
(b) 20.
Find u(x) and y2(x) in part (a). Observe that yz(x) is actually the general solu
tion of the given differential equation. Consider the linear, homogeneous differential equation
y" + a(x)y' + b(x)y = 0, and assume that a solution y1(x) (a)
has
been found.
Let Y2(x) = u(x)y1 (x) be a second solution, and obtain the following equa
tion for u(x): y1 (x)u
(b)
"(x) + L2yi'(x) + a(x)y1(x)]u '(x) = 0.
Apply the method in part (a) to the equation x2y"
+ xy'
4y =
to find a second solution Y2(X), given that y1(x) = x2. (Note: The given differential equation must be divided by x2 in order to use the result of 21.
part (a).) Prove that a common factor may be removed from any row and/or column of a determinant. (Compare the paragraph following Example 1.1I.)
Nonhomogeneous Equations with Constant Coefficients
SEC. 1.2
22.
7
Prove that the value of a determinant is unchanged if any row (or column) is
multiplied by a constant and the result is added to corresponding elements in any other row (or column). 23. Prove that interchanging any two rows (or columns) of a determinant changes its sign. 24. 25.
Prove that the value of a determinant having zeros below (Or above) the main diagonal is the product of the diagonal terms. Use the properties in Exercises 21—24 to evaluate the determinant
36 2
4
—4
12
9
—6. —24
NONHOMOGENEOUS EQUATIONS WITH CONSTANT COEFFICIENTS To consider nonhomogeneous equations in general would lead us too far afield. Hence we will deal with secondorder linear differential equations with Constant coefficients, that is, equations of the form
y" + ay' + by
fix),
(1.2I)
where a and b are constants. It can be shown that the general solution of Eq. (1.21) is the sum y(x) =
+
where Yc(X), called the complementary solution, is the general solution of the
reduced equation
y" + ay' + by = 0
(1.22)
and
called a particular integral (or particular solution) is any solution of Eq. (1.2—I). We saw how to find Yc(X) in Section 1.1, so the present section is
concerned mainly with finding What appears to be a simple problem is really not that simple unless we put some restrictions on fix) in Eq. (1.2—1). Accordingly, consider functions belonging to the set IP,,(x) exp
sin ($x), P,,(x) exp
cos
where P,,(x) is a polynomial in x of degree n, that is, =
c0
+ cx
+ c2x2 + .
.
+
(1.2—3)
8
Review of Ordinary Differential Equations
CHAP. 1
Although it may seem restrictive to limitf(x) to functions of the types shown in (1.2—3), a large percentage of elementary problems fall into this category. This is indeed fortunate, since the class of functions (1.23) has a most useful prop
erty, namely, that the class is closed under differentiation. This means that if a function of the type shown in (1.2—3) is differentiated, the result will be a function (or possibly a sum of functions) of the same type. We illustrate with an example.
EXAMPLE 1.21
Find the first and second derivatives of the function
fix) = (x2 — 2x +3)exp(2x)sin(3x). Solution Recall from calculus that to differentiate a triple product, it is necessary to differentiate each factor, multiply the result by the other two factors, and add the three products. Hence
f'(x)
= (2x
—
2) exp (2x) sin (3x)
+ (x2 — 2x + 3) 2 exp (2x) sin (3x)
+ (x2 — 2x + 3) exp (2x) 3 cos (3x) = (2x2 — 2x + 4) exp (2x) sin (3x) + (3x2 — 6x + 9) exp (2x) cos (3x), and similarly,
f°(x) = (— 5x2 + 1 8x — 21) exp (2x) sin (3x) + (1 2x2 — I 2x + 24) exp (2x) cos (3x). Because of the unusual property of the functions (1.2—3) illustrated in Example 1.2—I, we can find a particular integral of Eq. (1.2—1) by a method
called the method of undetermined coefficients. This method consists of assuming a particular form of the solution, substituting into the differential equation, and then reconciling the coefficients of like terms. EXAMPLE 1.2—2
Find a particular integral of the differential equation
y" + y'
—
= (4x + 5)expx.
Solution Since the function on the right is a polynomial of degree one multiplied by exp x, we assume a particular integral y,,(x) of the form
= (Ax + B) exp x. Then
y,(x) = (Ax + B) exp x + A exp x = (Ax + B) exp x + 2A exp x, and substituting into the given differential equation, we find
(—4Ax + 3A — 4B)expx = (4x + 5)expx.
9
Nonhomogeneous Equations with Constant CoeffIcients
SEC. 1.2
When we equate coefficients of like terms, we have A = — I
and B =
—2, so
the required particular integral is
—(x+2)expx.
U
We point out that the complementary solution in Example 1.22 is
= c1 exp (—3x) + c2 exp (2x) When and that this solution has no terms in common with the assumed terms in common, this eventuality must be taken into account the two do have as we will show later.
EXAMPLE 1.23 Find a particular integral of the differential equation
y"+y' —6y=(50x+40)sinx. Solution Since differentiating sin x results in cos x, we choose a particular in
tegral of the form
= (Ax + B) sin x + (Cx + D) cos x, which includes both sin x and cos x terms. When we substitute this and its two derivatives into the given differential equation, the result is — C)x + A — 7B — 2C — D] + cos x[(A — 7C)x + 2A + B + C
sin x(( — 7A
—
7D] = (50x + 40) sin x.
When we equate the coefficients of like terms, we obtain a system of four linear equations in four unknowns, which can be solved by elimination or by matrix methods (for example, Gaussian elimination). We find A = —7, B = —6,
C= —l,D= —3,and
—(7x+6)sinx—(x+3)cosx.
U
In the next example we show the procedure that must be followed when
a term in
duplicates a term in
EXAMPLE 1.2—4 Find a particular integral of the differential equation —
2y' + y = l2xexpx.
Solution We first note that the complementary solution is = (c1 ÷ c2x) exp x.
the righthand member of the differential equation is the product of a polynomial of degree one and an exponential function, we would ordinarily assume a particular integral of the form (Ax ÷ B) exp x. This cannot possibly be a solution of the given equation, however, since it is the solution of y" — 2y' + y = 0. When this situation occurs, we multiply the function (Ax + B) Since
CHAP. I
RevIew of Ordinary Differential Equations
10
exp x by x5, where s is the smallest positive integer that will prevent duplication
In the present case, s = 2; hence we assume
of terms in Yc(X) and
= x2(Ax + B) exp x.
Differentiating this last expression twice and substituting into the given differential equation yields (6Ax + 2B) exp x = 12x exp x,
so that A = 2, B = 0, and y,,(x) = 2x3 exp x. The general solution is then
y(x)=(c1 +c2x+2x3)expx.
•
the function fix) in (1.21) becomes unwieldy, that is, when it consists of a sum (or difference) of a large number of terms, a simplification can be made. We use the Principle of Superposition, which states that if + ay' + by = f1(x)andy = &(x)isasolution y= is a solution of + of y" + ay' + by = f2(x), then y = When
y" + ay'
+ by = f1(x) + f2(x). Hence we can solve a more difficult problem by adding the appropriate solutions of simpler ones. The exercises provide opportunities to use this technique. We note that in Example 1.24 we found B = 0. This shows that we could have assumed a particular integral of the form y,,(x) = Ax3 exp (x) and obtained the correct result more directly. Unfortunately, shortcuts of this kind cannot always be ascertained a priori; hence it is advisable to include all the terms of a polynomial in a particular integral.
Key Words and Phuases complementary solution
reduced equation particular integral
method of undetermined coefficients Principle of Superposition
1.2 Exercises
•
1.
is the general solution of y" + ay' + by = 0 and y,,(x) is any + ay' + by = fix), then the general solution of the latter is Here a and b are constants, and f(x) is an arbitrary function of x.
Show that if yc(x)
solution of y" +
A secondorder differential equation must contain two arbitrary constants in its general solution.) 2. Verify that y = —(x + 2) exp x is a particular integral of y" + y' — 6y = (4x + 5) exp x.
NonhomogeneouS Equations with Constant CoeffIcients
SEC. 1.2 3.
4.
5.
(x + 3) cos x is a particular integral of 40)sinx. Fill in the details required to obtain the particular integral in Example 1.2—4. Use the Principle of Superposition to solve the equation
Verify that y = y" + y' — 6y =
— (7x + 6) sin x —
(50x +
2y' + y = x2 — 2x + 3sinx.
—
•'
6.
11
assuming that there are
In each of the following, indicate the proper form of no duplications of terms in yAx). Refer to Eq. (1.21). (a) fix) = exp (x) cos x + exp (24 cos 2x (Ii) fix) = x3 exp x
(c) fix)=3+2cosx 7.
Solve each of the following to obtain the general solution. — 3y = 2 exp x — 3 exp (2x) (a) y — (b) (c)
(d) (e)
(f)
8.
(8)
y"+4y'+4y=4x2—8x
(h)
y' + 2y' +
y = sin x +
cos 2x
Find a particular integral of
y" + 3y' + 2y = 9.
10.
Find a particular integral of
f
2
exp (3x).
+ 4y = 3 sin 2x.
Solve the initialvalue problem
y(O)=3, 11.
Find the general solution of each of the following equations. (a) y" + y = cos x + 3 sin 2x (b) y' — 5y' ÷ 6y = cosh x (c)
12.
•..
13.
y'(O)=S.
y" +
Solve
2y' + y = cos2 x =
(I + cos 2x)
each of the following initialvalue problems.
(a)
y + 2y'
(b)
y" —
+ 5y = 10 cos x, y(O) = 7y' + JOy = lOOx, y(O) = 0,
(c)
y"—2y'+y=x2—l,
5,
y(O)=2,
y '(0)
=
6
y (0) = 5
y'(O)=l
shown in of parameters, which
The method of undetermined coefficients is limited to the functions
(1.23). we
There is a more general method known as variation
now illustrate using the
equation
y = tanx. (a)
Obtain the complementary solution
= c1cosx+
c2sinx.
12
Review of Ordinary Differential Equations (b)
CHAP. I
Assume a particular solution of the form
= u(x) cos x + v(x) sin x.
that the constants or parameters c1 and C2 have been replaced by functions u(x) and v(x). Our objective will be to obtain two equations in u '(x) and v'(x) that can then be solved simultaneously.) Differentiate to obtain (Note
= — u(x) sin x + v(x)
cos
x
with
u'(x)cosx + v'(x)sinx = 0. that this last condition simplifies y;(x), and provides a second equation in u'(x) and v'(x). (c) Differentiate y(x) in part (b) and substitute into the given differential equation to obtain Observe
—u'(x) sin x + v'(x)cosx = tan (d)
x.
Solve the system
—u'(x)sinx + v'(x)cosx = tanx u '(x) cos x + v '(x) sin x = 0 for u'(x)
14.
and v'(x) by Cramer's rule or by elimination. u'(x) and v'(x) to find u(x) and v(x). and thus obtain the general solution. Note that success in using the
(e)
integrate
(f)
Find method of variation of parameters and v(x) from u '(x) and v '(x).
Use
the method of Exercise 13 to obtain the general solutions of each of the
following equations. (a) y" — y' = x — tan x (b) y" — 2)" + y = exp(x)/(l
(c) y"+y=secxtanx (d) y"+y=secx (e)
(f) 15.
is contingent on being able to obtain u(x)
—
x)2
y"+4y=cot2x
Solve the initialvalue problem
+y=en/(1 —x)2, 16.
Verify that y1(x) = x and yz(x)
y(0)=2,
y'(O)=6.
= l/x are solutions of + x2y' — xy = 0.
Then use this information and the method of variation of parameters to find the
general solution of
x3y+x2y' —xy=x/(1 17.
(a)
Solve
+x).
the equation
y = xsinx by the method of undetermined coefficients. (b) Solve the equation in part (a) by using the method of variation of parameters. —
CauchyEuler Equations
SEC. 1.3 18.
Consider
y" + ay' + by = fix), where a and b are constants with b that this equation always has a 19.
20.
0 and fix) is a polynomial of degree n. Show
solution that is a polynomial of degree n.
In Exercise 18, show that the solution is a polynomial of degree n + i in the case where b = 0. If utx), v(x), and w(x) are differentiable functions of x, use the formula for differentiating a product, dx
v±, dx
=
to find d(uvw)/dx. 21.
Show that reconciling the coefficients of like terms in the method of undetermined coefficients depends on the forming of a linearly independent set by the functions involved. (Hint: Recall that if f(x), I = I, 2, . . . , n, are n linearly independent functions over the reals, then = 0
holds only if each c, = 0.)
1.3
CAUCHYEULER EQUATIONS
In the two preceding sections we discussed secondorder linear ordinary
differential equations with constant coefficients. While equations of this type will occur frequently throughout the remaining chapters, we will also have occasion to solve other linear differential equations, that is, equations of the form ao(x)y" + a1 (x)y' + a2(x)y = f(x).
(1.3I)
One type of linear differential equation with variable coefficients that can be reduced to a form already considered is the Cauchy—Euler equation, which has the normal form x2y" + axy' + by = fix),
x > 0,
(1.32)
where a and b are constants. This equation is also called a Cauchy* equation, an Eulert equation, and an equidimensional equation. The last term comes
from the fact that the physical dimension of x in the lefthand member of Eq. (1.32) is immaterial, since replacing x by cx, where c is a nonzero constant, *Augustin.Louis Cauchy (1789—1857), a French mathematician. tLeonhard Euler (1707—1783), a Swiss mathematician.
CHAP. 1
RevIew of Ordinary Differential Equations
14
the dimension of the lefthand member unchanged. We will meet a form of this equation later in our study of boundaryvalue problems having circular symmetry. We assume throughout this section that x 0. For the most part we assume that x > 0, although we also deal with the case x < 0 later. We begin with an example to illustrate the method of solution. leaves
EXAMPLE 1.3I Find the complementary solution of the equation = x2 exp (—x),
x2y" ÷ 2xy' —
x>
0.
Solution This is a CauchyEuler equation, and we make the following substitutions in the reduced equation
= mxm*,
= Xm, so
= m(m —
the homogeneous equation becomes Im('n —
1)
+ 2m
—
2Jxm
= 0.
0, we must have
Because of the restriction x
+ m — 2 = 0,
m2
which has roots m1 = —2 and m2 = 1. Thus
•
+ c2x.
=
= xm, did not come from thin
We remark that the substitution,
air. It was dictated by the form of the lefthand member of the differential equation, which in turn ensured that each term of the equation would contain the common factor x'". It should be pointed out also that if we were interested in obtaining the
general solution of the equation in Example 1.31, we could use the complementary solution above and the method of variation of parameters. (See Exercise 13 in Sectiøn 1.2.)
EXAMPLE 1.32
Obtain the complementary solution of
x2y"+3xy'+y=x3,
x>0.
Solution This time the substitution Yc = Xm leads to
+ 2m +
m2
which has a double root m = —
1.
1
= 0,
Hence we have one solution of the
homogeneous equation, namely, y1(x) = One might "guess" that a second linearly independent solution could be ob
tained by multiplying y1(x) by x. This procedure, however, is limited to the case of equations with constant coefficients and is thus not applicable here. It is
15
CauchyEuler Equations
SEC. 1.3
that y = is not a solution. In this case we can use the method of reduction of order to find a second solution. We set y2(X) = u(x)/x and compute two derivatives. Thus
easy to check
1
y2(x)
u'x
—U
=
=
x(xu — 2u') + 2ux, x4
and substitution into the homogeneous equation results in
xu" + U' =
v and separating the
which can be solved* by setting u' V
0,
du
Then
c2
=
=
andt u = c2 log x. Hence C2
y2(x)
log x,
and the complementary solution is Cl
=—+
C2
—
log x.
We shall see later that the function log x occurs in the case of repeated roots.
U
EXAMPLE 1.33 Find the complementary solution of
x2y"+xy'+y=cosx, Solution
x>0.
in this example we have, after substituting
= xm,
m2 + 1 = 0
so that the solutions are x and x. Hence the complementary solution is
= C,x' +
(1.33)
A more useful form can be obtained, however, by replacing C, and C2 by (c, — ic2)/2 and (c1 + ic2)/2, respectively, and noting that x1
exp (i log x) =
cos
(log x) +
I
sin (log x).
*An alternative method is to note that + u' = 0, leading toxu tWe will consistently use log x for the natural logarithm of x.
= c2.
CHAP. 1
RevIew of Ordinary Differential Equations
16
With these changes the complementary solution (1.3—3) can be written (log x) + c2 Yc(X) = c1 cos
We
•
sin (log x).
shall summarize the various cases that occur when solving the
homogeneous Cauchy—Euler equation
+ axy' + by = 0.
x2y"
(1.34)
Substitution of Yc(X) = x'" and its derivatives into Eq. (1.34) leads to the
equation m(m — 1) + am +
1'
= 0
or
m2 +
(a —
1)m + b
= 0.
(1.35)
This is called the auxiliary equation of the homogeneous CauchyEuter equation (1.3—4).
Case I. (a — j)2 — 4b > say, m1 and m2. Then
0.
The roots of Eq. (1.35) are real and unequal,
Yc(X)
(1.36)
= C,X" + C2Xm2,
and since the Wronskian Xml
Xm2
= (m2 ,fl,Xma_I
*
—
0,
m2xm21
showing that Xml and Xml are linearly independent.*
Case II. (a — j)2 — 41' = 0. The roots of Eq. (1.35) are real and equal, say, m1 = m2 = m. Then y,(x) = xm
one solution of Eq. (1.3—4). A second solution can be found by the method of reduction of order. Let is
y2(x) = XmU(X) be
a second solution, differentiate twice, and substitute into Eq. (1.34). Then utm(m —
* Note
1)
÷ am +
blx"
+ u'(2m +
that the assumption x > 0 is essential here.
+
= 0.
IT
Cauchy.Euler Equations
SEC. 1.3
But the coefficient of u vanishes because xm 2m + a = 1 from Eq. (1.35). Thus
a solution of Eq. (1.34) and
is
xli" + U' = 0, which is satisfied by u = log x and y2(x) = xm log x.
In this case the complementary solution is Yc(X) = xm(c, +
c2
log x).
(1.37)
Case ill. (a —
— 4b < 0. The roots of Eq. (1.3—5) are complex conjugates, say, m1 = a + /31 and = a — /31. Then two linearly independent
solutions of the homogeneous equation are y1(x) =
= x" exp (i/3 log x)
=
and y2(x)
= x°' = x"x" =
Using Euler's
exp (—1/3 log x).
to transform the exponential gives us
y(x)
=
xicos (/3 log x) + i
sin ([3 log x)]
and y2(x) = xa[cos (/3 log x) —
1
sin (j3 log x)J.
Hence the complementary solution becomes =
r[c1
cos
((3 log x) + c2 sin (/3 log x)1.
(1.38)
If the general solution to Eq. (1.3—2) is required, it is necessary to add a
particular solution to the appropriate complementary solution. A particular solution can be found by the method of variation of parameters, although difficulties may be encountered, as was mentioned in Exercise 13 of Section 1.2. Note that the method of undetermined coefficients is not applicable here, since the Cauchy—Euler differential coefficients.
equation does not have constant
There is an alternative method for solving Eq. (1.34). Since x > 0, we can make the substitution u
= logx.
This leads to x = exp u and, using the chain rule, to dy dx *exp (iO) = cos 0 + i sin 0.

dydu dudx

1 dy
xdu
Review of Ordinary Differential Equations
CHAP. 1
We also have d2y
—
dx2
—
dfldy
d fdy\ — dx\xdu dx\dx)
ld x
=
ldy
—
x2 du
(d2y — dy\
1
\dul
duJ method has the advantage that Eq. (1.34) is transformed into x2
This
(dy\du
du \du) dx
+ (a
+
—
by = f(exp u).
Thus the differential equation has constant coefficients, and the methods of
1.1 are available for finding the complementary solution of the CauchyEuler equation. In fact, if flexp u) has the proper form, then the method of undetermined coefficients may lead to the general solution of the nonhomogeneous equation quite easily. We have considered exclusively the case where x > 0. If solutions are desired for values of x satisfying x < 0, then x may be replaced by — x in the differential equation and in the solution.
Section
Key Words and Phrases separating the variables auxiliary equation
CauchyEuler equation
variation of parameters reduction of order
1.3
Exercises
In the following exercises, assume that the independent variable is positive unless other
wise stated. 1.
the substitution u = log x to solve each of the following equations. x2y" + 2xy' — 2y = 0 (Compare Example 1.3I) x2y" + 3xy' + y = 0 (Compare Example 1.32) x2y" + xy' + y = 0 (Compare Example 1.33) Obtain the general solution of the equation Use
(a) (b) (c) 2.
x2y"
÷ 3xy' + y
= x3.
(Hint: Use the substitution of Exercise I and the result of Example 1.3—2.)
3.
Use Euler's formula exp (1ff) = cos
••
4.
+ I sin
0
0
to fill in the details in Case III. Solve the initialvalue problem
y(l) =
— 2y = 0, 5.
19
CauchyEuler EquatIons
SEC. 1.3
y'(l) =
6,
3.
Find the general solution of + 5xy' — 5y = 0.
6.
Find the general solution of 12y"
7.
+ 5ty' + 5y = 0.
Find the general solution of r2u" + 3ru' + u = 0.
8.
Obtain the general solution for
+ xy'
x2y" 9.
Find the general solution of x2y"
10.
9y = x2 — 2x.
.
+ xy'
+ 4y = log x.
Solve the initialvalue problem
y(l)=O, 11.
Solve each of the following initialvalue problems. (a) (b)
•••
12.
+
xy'
0,
y(l) = I, y(l)=O,
y1(x)=x
(c)
xy" + 3y' = 0, y,(x) = 2 x2y" + xy' — 4y = 0, y,(x) =
(d)
x2y"—xy'+y=O,
(b)
14.
y'(l) = 2 y'(l)=l
Use the method of reduction of order to find a second solution for each of the following differential equations, given one solution as shown. (a)
13.
y'(l)=O.
x2
y,(x)=xlogx2
Show that the products xy' and x2y" remain unchanged if x is replaced by cx, where c is a nonzero constant. Show that the substitution x exp u transforms the equation
+ axy' + by = 0, where
a and b are constants, into du
15.
+ (a —
1)
du
+ by = 0.
Solve each of the following initialvalue problems. (a) 4x2y" — 4xy' + 3y = 0, y(l) = 0, y'(l)
(b) x2y45xy'+4y=0,
y(1)=l,
=
y'(l)=3
Review of Ordinary Differential Equations 16.
CHAP. I
Obtain the general solution of the equation
+ axy' = 0,
x2.v"
where a is a constant.
1.4
IN FINITE SERIES
Since we will need to solve secondorder linear equations with variable coeffi
cients that are not of Cauchy—Euler type (Eq. 1.32), we must explore other methods of solution. One powerful method is the power series method. In using this method we assume that the solution to a given differential equation can be expressed as a power series. Inasmuch as we will need certain facts about infinite series and' their convergence, we digress in this section to review some aspects of these. Each of the following is an example of a series of constants: (1.41) (1.42) (1.43)
(1.44)
(1.45)
+...+'2n—l ' +....
I I ——+—— I
3
5
(1.46)
The series in (1.4—1) is divergent because the partial sums
S1=l,S2=I÷2,S3=l÷2+3,S4=l÷2+3÷4, form
a sequence S3. .
.
=
.
3, 6, 10 .
.
.
has no limit point. * On the other hand, the series in (1.4—2) is divergent because its sequence of partial sums has two limit points, + I and 0. The series in (1.4—3) is a trivial example of a convergent series, since its sequence of partial sums has a unique limit point, namely zero.
which
A point is called a limit point of a sequence if an infinite number of terms in the sequence are within a distance of of the point, where is an arbitrarily small positive number. A limit point need not be unique and need not be an element of the sequence. For example, I is the unique limit point of the sequence
Ji
3
7
IS
12' 4' 8' 16'
21
InfinIte Series
SEC. 1.4
By a more sophisticated test (the integral test) it can be shown that the series of (1.4—4) is convergent for p > 1 and divergent for p 1. When
p=
1,
the series is called a harmonic series. The series of (1.4—5) is a
geometric series with first term a and common ratio r. It can be shown (by the I and < 1 and diverges if ratio test) that (1.4—5) converges if a * 0. The sum of (1.45) can be written in closed form as
IrI 0) the radius of convergence of the power series and determine its value by using the
ratio testt as shown in the next example. EXAMPLE 1.41 (x—1)—
Find the radius of convergence of the series
(x— !L+ 2
(x— 3
—
(x— J)4 4
Gotifried Wilhelm Leibniz (1646—1716), the coinventor (with Sir Isaac Newton) of the calculus, who proved the theorem in 1705. tAiso called D'Alembert's ratio test after JeanleRond D'Alembert (1717—1783), a French mathematician who made important contributions in analytical mechanics.
CHAP. 1
RevIew of Ordinary Differential Equations
22
Solution
It will be convenient to write the series using summation notation, —
1Y
n
According to the ratio test, a series converges whenever Un,'
urn
0 or x < 0. Consider the most general secondorder, linear, homogeneous ordinary differential equation,
y" + P(x)y' + Q(x)y = 0.
(1.55)
Those values of x, call them x0, at which both P(x) and Q(x) are analytic are
called ordinary points of Eq. (1.5—5). If either P(x0) or Q(x0) is not analytic, then x0 is a singular point of Eq. (1.5—5). If, however, x0 is a singular point of Eq. (1.5—5) but both (x — x0)P(x) and (x — x0)2Q(x) are analytic at x = x0, then x0 is a regular singular point of Eq. (1.5—5). All other singular points are called irregular singular points.
CHAP. 1
Review of Ordinary Differential Equations
32
EXAMPLE
Classify the singular points of the equation
1.5—3
(1 —x2)y—2xy' +n(n+ 1)y=O, where n = 0, 1, 2 The only singular points are x0 = ± 1. If x0 = (x +
—
l—x2
x—1
(x +
and
1)2n(n + 1)
— 1, —
n(n + 1)(x +
x—l
1—x2
both of these rational functions are analytic at x = regular singular point. Similarly, for x0 = I we have
Since
(x — l)(—2x)
l—x2 so that x0 =
1
—
x+1
and
(x — l)2n(n
+ 1)
1—x2
then
— 1,
1)
the latter is a
n(n+1)(l :_x),
l+x
I
is also a regular singular point.
The point of all this is contained in an 1865 theorem due to Fuchs.* Fuchs' theorem states that it is always possible to obtain at least one power series solution to a linear differential equation provided that the assumed series
solution is about an ordinary point or, at worst, a regular singular point. The work of Fuchs was extended by Frobenius,t who in 1874 suggested that instead of assuming a series solution of the form a,,f, one should use the form L a,,x". The use of this form to solve linear, ordinary differential equations is known today as the method of Frobenius. We illustrate with an example using the CauchyEuler equation referred to above.
EXAMPLE 1.54 Solve the equation +
5xy' + y =
0
by the method of Frobenius.
Solution We have y = =
(n + r)a,,x"'',
=
(ii + r)(n + r —
tLazarus Fuchs (1833—1902), a German mathematician. tGeorg Frobenius (1849—1917), a German mathematician.
33
Series SolutIons
SEC. 1.5
and
on substituting into the given equation we have [2(n
Since the n = 0,
+ r)(n + r — 1) + 5(n + r) +
coefficient of
must be zero for n = 0, 1, 2, .
= 0. . .
, we have for
(2r2 + 3r + 1)a0 = 0.
Choosing a0 to be arbitrary, that is, nonzero, produces 2r2
+ 3r + 1 =
0,
which is called the indicial equation. Its roots are — I and — 1/2. In general,
+ 4nr + 3n) = 0, which can be satisfied only by taking left with the two possibilities, y1(x) =
and
= 0, n = 1, 2 y2(x)
Hence we are
= b0x"2.
Note that the two constants are arbitrary, since each root of the indicial equa
tion leads to an infinite series. In this example, however, each series consists of a single term.
•
When solving secondorder linear differential equations by the method
of Frobenius, the indicial equation is a quadratic equation, and three possibilities exist. We list these together with their consequences here. I. If the roots of the indicial equation are equal, then only one solution can
be obtained. 2.
If the roots of the indicial equation differ by a number that is not an
integer, then two linearly independent solutions may be obtained. 3. If the roots of the indicial equation differ by an integer, then the larger integer of the two will yield a solution, whereas the smaller may or may not yield a solution. It should be mentioned that the theory behind the method of Frobenius is by no means simple. A good discussion of the various cases that may arise (although the
case where the indicial equation has complex roots is omitted) can be found in Albert L. Rabenstein, Elementary Eflfferential Equations with LinearAlgebra, 3d ed. (New York: Academic Press, 1982), pp. 391 ff.
We conclude this section by solving two important differential equations that will appear later in the text in connection with certain types of boundaryvalue problems.
34
Review of Ordinary Differential Equations
EXAMPLE 1.55
CHAP. 1
Obtain a solution of the differential equation
±
= 0,
—
n
(1.56)
0, 1, 2
+ This equation is known as Bessel's differential equation. It was originally obtained by Friedrich Wilhelm Bessel (1784—1846), a German mathematician, in the course
of his studies of planetary motion. Since then, this equation has appeared in problems of heat conduction, electromagnetic theory, and acoustics that are expressed in cylindrical coordinates.
Soluhon
Since the coefficients are not constant, we seek a series solution.
Multiplying Eq. (1.56) by x2, we obtain
x2y" + xy' + (x2 — n2)y = 0.
(1.57)
We note that x = 0 is a regular singular point; hence we use the method of Frobenius. Assume that =
=
I,
a,,,(m + In = 0
=
a,,,(m + r)(m + r
—
and substitute into Eq. (1.57). Then
a,,(m + r)(m + r — l)xm' +
a,,,(m + r)x""
rn=O
+
a,,,Xmt' =
— fl2 rn=0
,n=0
If we replace m by m — 2 in the third series, the last equation can be written
[a,,,(m + r)(m + r — I) + am(m + r) + a,,,
2 — flQrnJX
+ a0r(r — l)xr + a0rx' — Simplifying, we get
(a,,((m + r)2 — n2) + m=2
as
+ a1(r +
+ —
+ I)x" flZt,Xr*l = 0.
+ a0(r2 — n2)x' + a1(r2 + 2r
+I—
= 0.
The coefficient of X' must be zero; hence if we assume * 0, then we obtain r = ± n. We choose the positive sign, since n was defined as a nonnegative integer in Eq. (1.5—6). Since the coefficient
of
must also be zero,
35
Series Solutions
SEC. 1.5
we may
choose a, =
0.
Then the recursion formula is obtained by setting the
equal to zero. Thus
coefficient of
—
a,,,
am 2
In = 2,
m(m ± 2n)
3
The first few coefficients can be computed from this formula. They are as follows: a0
m=2:
a2= 22(n+lj
m = 4.
a4
m — 6.
a6
—
a0
—a2
— 23(n
+ 2) = 24.2(n + l)(n + 2)' —a4
—
223(n
—
a0
—
+ 3) —
26.3!(n + l)(n + 2)(n + 3)
In general we have (—l)ma0
—
a2,,,
—
22mm!(n
m— —
+ 1)(n + 2). . . (n + m)'
1
2
and a solution to Eq. (1.56) can be written as
y,,(x) = a0 m0
22mm!(n + 1 )(n + 2).
=
.
. (n + m)
•
m!(rn+n)!
The Bessel function of the first kind of order n is defined by giving a0 the value l/2"n!. We have
(1)m J,,(x)
=
m!(m + n)!
x
2m+n
n
= 0, 1, 2,. .
.
,
(1.5—8)
a solution of Bessel's differential equation. We will consider this function in greater detail in Chapter 7. EXAMPLE 1.56 Obtain a solution of the equation (1 —
x2)y" — 2xy' + n(n + 1)y = 0,
(1.5—9)
where n is a constant. This equation is known as Legendre's differential equation.*
After Adrien Marie Legendre (1752—1833), a French mathematician who is known mainly for his work in number theory, elliptic functions, and calculus of variations.
CHAP. 1
Review of Ordinary Differential Equations
Since x = ± I are regular singular points (see Example 1.5—3), we may assume a power series about x = 0, which is an ordinary point. Accordingly, put amm(m — l)x2. y" = ammx"', y' = y = Solution
Substituting these values into Eq. (1.5—9) produces a,,,m(m — l)xm2
a,,,+2(m
4.
ammxm + n(n + I)
2
—
Replacing m by m +
l)xm
—
in the first sum, we get
2
I)x"
2)(m +
—
a,,,(m
—
1)
—
1)
+
amxm = 0.
2a2
+ 6a3x
2a1x +
—
l)xm
2amm + amn(n +
1)]f'
n(n + l)a0 + n(n +
1)a1x
= 0.
Setting the coefficient of each power of x equal to zero in the above, we have 2a2 + n(n +
1)a0
= 0,
a2
=
1)a0
a3 =
6a3 — 2a1 + n(n + l)a1 = 0,
[2
—
a0 arbitrary; n(n + 1)Ja,
a1 arbitrary.
In general, we can say am+2(m
+ 2)(m + 1) — [m(m — I) + 2m
—
n(n + l)Ja,,, = 0;
_m(m+l)—n(n+l) am, —
am+2 = (m(
(m + 2)(m +
1)
1)
2)(
1)
am,
m=
0, 1, 2
(1.510)
Equation (1.5—10) is the recurrence relation from which the coefficients
can be found.
SerIes SolutIons
SEC. 1.5
Computing the first few coefficients gives us
a2
—
a4— a
÷ I)
—n(n
—
a0,
i•2
= (2
(4
—
—
n)(n + 3)
—
a2—
n(n — 2)(n + l)(n + 3) 4!
,i)(n + 5) a4= —n(n — 2)(n
—
4)(n + 1)(n + 3)(n + 6!
6•5
a — (1 — n)(n + 2) 3.2 —
a5— —
a7— —
(3
(5
—
—
n)(n + 4) n)(n + 6) 7•6
— (n
—(n — 1)(n + 2)
a,=
3!
—
a3—
(n — 1)(n — 3)(n + 2)(n + 4) 5!
7!
=
n(n
—
2)(n
+ n(n — 2)(n+ 1)(n + 3)
4)(n + l)(n + 3)(n +
—
6! —
+ a, —
a1.
a solution to Legendre's equation can be written as
ao[i — n(n+ I) —
a1,
a,
—
Hence
a0,
a1,
1)(n — 3)(n — 5)(n + 2)(n + 4)(n + 6)
—
5)
(n
—
(n — l)(n + 2)
1)(n
—
3)(n
—
5)
x6 + —
+ (n — 1)(n — 3)(n + 2)(n + 4)
5)(n + 2)(n + 4)(n + 6) 7!
(1.5li) Both series converge for — < x < 1. If n = 0, 2, 4, . . . and a, is chosen to be zero, then the solutions, using Eq. (1.5—11), become 1
y0(x) = a0,
y2(x) = a0( 1 — 3x2), y4(x) = ao(1
—
lOx2 +
etc.
CHAP. I
Review of Ordinary Differential Equations
38
If we also impose the condition that
= I, then we can evaluate the a0 to
obtain P0(x) =
1,
P2(x) =
(3x2
P4(x) =
(35x4
—
1), —
(1.5—12)
+ 3)
30x2
These polynomials are called the Legendre polynomials of even degree. If n = 1, 3, 5, . . . and a0 is chosen to be zero, then the solutions, using Eq. (1.5—11), become y1(x) = a,x, y3(x) = a, (x —
y5(x) = a, (x — 1x3 +
21
etc.
If we again impose the condition that y,,(l) = 1, then we can evaluate the a, to obtain
P,(x) = x,
P3(x) =
— 3x), (1.5—13)
P5(x) =
—
70x3
+ 15x)
These polynomials are called the Legendre polynomials of odd degree.
I
The Legendre polynomials will be of use in Section 7.3, since they arise in boundaryvalue problems expressed in spherical coordinates.
Key Words and Phrases recursion formula
closed form analytic analytic function ordinary point singular point regular and irregular singular point method of Frobenius
indicial equation Bessel's differential equation Bessel function of the first kind
of order n, Legendre's differential equation Legendre polynomials of even degree Legendre polynomials of odd degree
39
SerIes Solutions
SEC. 1.5
1.5 Exercises
•
1.
Show that one solution of the differential equation y" — xy
(a)
0 in Example
1.5—1 can be written as
l4•7• ..(3n
y1(x) = Go
—
Write the second solution in a similar form.
(b)
Find the radius of convergence of the series in part (a). Observe that x0 = 0 is an ordinary point and hence that both solutions are analytic. Verify that yt(X) = x and y2(x) = ex are linearly independent solutions of the — xy' + y = 0. differential equation (x — (a) Show that the solution obtained in Example 1.52 is equivalent to
(c) (d) 2.
3.
y(x) = c1x + c2ex. For what values of x is the above solution valid?
(b)
4.
for the equation
Show that assuming a solution of the form y =
+ Sxy' + y =
0
to the trivial solution y = 0. and 1/x are linearly independent solutions of the equation in Verify that Exercise 4 on every interval not containing the origin. leads
5. 6.
Classify the singular points of each of the following differential equations. n = 0, I, 2, + (x2 — n2)y = 0, + (a) (b) x3y"
—
xy' + y
= 0
(c)
x3(x — 1)5" + x4(x — l)3y' + y = 0 Use power series to solve each of the following equations. (d)
7.
(a)
y"+y=O
(b)
y" — y
= 0
(c)
y'—y=x2
(d)
y'
—
(If
possible, write the solution in closed form.)
(Note that the power series method is not limited to ho,nogeneous equations.)
(e)
8.
(1+x2)y"+2xy'—2y=0
Solve each of the following differential equations by the method of Frobenius. (a) (b) (c)
9.
xy = 0
xy"+y'ixy=O
4xy"+2y'+y=O
x5"'+2xy'—2y=0
Solve the equation xy" + 2y' = 0 by
two methods. (Hint: x is an integrating factor.)
CHAP. I
Review of Ordinary Differential Equations
40 10.
Solve
the equation —
xy'
—
y=0
by assuming a solution that is a power series in (x — 1). In this case the coefficient
II.
x must also be written in terms of x — 1. This can be done by assuming that x = ,4(x — 1) + B and determining the constants A and B. Obtain a solution of
y' + 4xy = 0.
.xy" + 12.
Obtain a solution of xv" — Zv = 0.
•..
13.
The differential equation —
x_v
0
is known as Airy's equation,* and its solutions are called Airy functions (Fig. 1.51), which have applications in the theory of diffraction. (a) Obtain the solution in terms of a power series in x. (b)
Obtain the solution in terms of a power series in (x — I). (Compare Exercise 10.)
14.
Compare the solutions of Exercise 13 with those of y" — y =
15.
Solve the initialvalue problem
0.
Comment.
y(0)=y'(O)=l. 16.
Solve the differential equation
+ 2y' + y = 0. 17.
18.
Find the interval of convergence of the two series in the solution of Exercise 16. Solve the initialvalue problem
y"+y'+xy=O, 19.
y(O)=y'(O)=l.
Obtain the general solution of
2x2y—xy' 20.
Obtain the general solution of'
x2r + x2y' — 2y = 0. 21.
Illustrate Theorem 1.5—I by differentiating the series in Exercise 11 of Section 1.4
and finding the radii of convergence of the differentiated series. (Note that this does no: constitute a proof of the theorem.) 22.
Illustrate Theorem 1.5—2 by differentiating the functions and series in Eqs. (1.5—1) through (1.5—4).
23.
Find the general solution of
y"
+
xy'
+
y = 0.
'After Sir George B. Airy (1801—1892), an English mathematician and astronomer.
41
Series Solutions
SEC. 1.5
Figure 1.51
Airy tunctions.
16 UNIFORM CONVERGENCE We give a brief discussion of some of the theoretical aspects in the present section, not for the sake of the theory per se but to prepare for a wide variety of applications. It will be shown, for example, that we will have to broaden our concept of convergence.
Polntwlse Convergence Recall
a
what is meant by saying that a sequence of functions, defined for
x
b,
ff1(x),f2(x),f3(x), converges
. . .
. .
.J,
to f(x). When we write
f(x) =
for all x in [a, b],
we mean that the difference between f(x) and can be made arbitrarily small provided that n is taken large enough. In more precise mathematical language we would say that given any positive number and any point x0 in the interval [a, b], we can satisfy I
whenever n
f(x0)
I
(1.6—1)
x0), an integer. In other words, given 0, we can find an integer N such that the inequality (1.61) holds whenever n N. The important thing to notice here is that N will usually depend on and x0, so we write
x0).
RevIew of Ordinary Differential Equations
42
EXAMPLE 1.61
with 0
0.
Show that the series sin n2x
S= n=I
n2
absolutely convergent (hence convergent for all x) by the comparison test. Show that the differentiated series is
(b)
cos n2x
is
10.
divergent for all x.
(C)
Explain.
(a)
Show that the series sin nx
uniformly for all x. Show that the differentiated series converges
(b)
diverges for some values of x. 11.
(a)
Show that the infinite series defines the function fix):
—l<x 0 on [a, bJ and (see Section 2.2)
a,y(a) + a2y'(a) = 0, b,y(b) + b2y'(b) = 0, we have b
—
Y2Yd = 0,
(2.36)
as can easily be shown (Exercise 5). We have proved the following theorem. THEOREM 2.31
In a regular SturmLiouville problem,
a1y(a) + a2y'(a) = 0,
b,y(b) + b2y'(b) =
(2 37)
0,
eigenfunctions belonging to djfferent eigenvalues are orthogonal on (a, bJ with weight function w(x).
It follows from Theorem 2.3—1 that the eigenfunctions of a regular SturmLiouville problem can be used to form an othonormal set of functions. These functions, in turn, are useful in approximating other functions, as we will show in Section 2.4. In Section 2.7 we will see that under certain other conditions, Eq. (2.36) can be satisfied so that obtaining orthogonal eigenfunctions will not be Limited to regular Sturm—Liouville problems. Key Words and Phrases orthogonal set of functions
weight function orthonormal set of functions
Kronecker delta norm of a function Lagrange's identity
Boundary•Value Problems in Ordinary Differential Equations
66
CHAP. 2
2.3 Exercises
•
1.
Show that I
Jo
2.
(a)
sin nx sin mx dx =
2
= n. if Show that
Ix t
J°
cosnxcosmxdx=
2
if ni = n. (b)
Show that
n=0,1,2
Jo
3. 4.
Verify that the norm of the functionf(x) = I on 10, Obtain an orthonormal set from the orthogonal set
is
lsinnx,n = 1,2,... 5.
••
6.
of Example 2.2—I. Verify Eq. (2.36). State the orthogonality relation for the eigenfunctions of the problem
y"+kv=O, v(I) = 0.
y(O) + y'(O) = 0, (Compare Example 2.23.)
Verify the orthogonality of the eigenfunctions of Exercise 6, using X1 = 4.493 and 8.
= 7.725. Obtain the orthonormal set of eigenfunctions for the problem .v" + >5v = 0,
9.
y(7r) = 0.
(Hint: See Exercise 6 in Section 2.2.) Obtain the orthonormal set of eigenfunctions for each of the following problems. Note that in some cases, zero may be an eigenvalue. 0, (a) y" + X.v = 0, y(O) —0 (b)
v" + (1 + X)v = 0,
(C)
(Hint: See Exercise 9 in Section 2.2.) v" + Xv = 0, i' '(0) = 0, v'(c) =
(d) 10.
y'(O) = 0,
(a)
y(0)
0,
v(7r)
0
0
+ Xv = 0, y'(O) = 0, y(c) 0 Verify that the eigenfunctions of the problem
y" + 2v' + (I — X)v = 0,
v(0) = 0,
v(l) = 0,
are .v,,(x) = sin n = I. 2, 3 (b) Transform the problem of part (a) so that it has the form (2.3—7). (Hint: See (C)
Section 2.2.) Verify that the eigenfunci ions of the problem in part (a) are orthogonal on 10, II using the proper weight function.
'Calculator problem.
•"
II. (a)
Verify chat the eigenfunctions of the problem
÷(l—X)y=O,
y'(O)=O,
arey0 = I andy,,(x) = (n cos nx + sin nx) exp(—x), n (b) 12.
67
RepresentatIon by a Series of Orthonormal Functions
SEC. 2.4
(a)
y"+Xy=O, =
(b)
= 1,2
Obtain an orthonormal set of eigenfunctions for the problem in part (a). Verify that the eigenfunctions of the problem
+ w),
y'(—7r)=y'(7r)O n=
1,2
0,
Show that the eigenfunctions in part (a) are orthogonal on [— w, jr]. (Hint: Use the trigonometric identity
sin A cos B = isin (A + B) + isin (A — B).) Obtain the orthonormal set of eigenfunctions for the problem in part (a). Show that Lagrange's identity leads to (C)
13.
fb
30 y,Ly2dx=
30
y2Ly1dx
for functions Yi and Yi satisfying Eqs. (2.2—6) and (2.2—7). This shows that L is a
14.
symmetric operator on the space of all realvalued twice continuously differentiable functions on [a, bJ that satisfy the boundary conditions (2.2—7). If
n = 1, 2, is
.
.
.
I
an orthogonal set on [a, bJ with weight function w(x), verify chat
'n=l,2,... I
is
2
an orthonormal set on [a, bJ with weight function w(x).
4 REPRESENTATION BY A SERIES OF ORTHONORMAL FUNCTIONS The set of vectors
S = 1e1, e2,
.
.
.
,
e,,}
of W' where = (e13,
.
.
.
, ei,,),
with eu = oil,
(2.4—1)
BoundaryValue Problems In Ordinary Dilferential Equations
CHAP. 2
forms a natural basis for R". From the above definition we see that the vectors
in S are mutually orthogonal, that is, the inner product* of any pair, denoted by (ei, e1), is given by (2.4—2)
(e1, ej) =
of
An important consequence of the foregoing is that an arbi/rary vector v can be uniquely expressed as
v=
(2.4—3)
scalars. Moreover, the c can be easily computed from Eq. n), for example, we form the inner product of (1 k both members of Eq. (2.43) with ek. Then
where the c are
(2.43). To find C&
(v, ek) =
ek) =
e*) =
Ck,
so that Eq. (2.4—3) can be written as
v=
(v,
(2.4—4)
We are tacitly assuming a knowledge of the properties of the socalled Euclidean inner product* in in the above. (See Exercise 2.) Now define the inner product of two functionsf and g with respect to the weight function w as
(Jg) =
(2.45)
In order that this definition be useful it is necessary thatt w(x) > 0 on (a, b), and it will simplify matters if f and g are both piecewise continuous on (a, b). A functionf is piecewise continuous on (a,ifb)this interval can be partitioned into a finite number of subintervals such that: 1. f is continuous on each open subinterval and 2. f has finite left and righthand limits at each point of subdivision.
We give some examples to clarify the above definition.
Also called the dot product and the scalar product. The notation <e1, e1> is also used by some
authors.
tif w(x) =
0 at isolated points
of (a, 1'), then this will not cause any problems.
SEC. 2.4
RepresentatIon by a Series of Orthonormal Functions
EXAMPLE 2.41
The functionf defined as (
21,
I,
forO < I < I,
forlt 0
on (a, b) except at a finite number of points where it may be zero. Then we can
write
fix) =
c.cb1(x)
(2.49)
for appropriate constants c1. It is generally acknowledged that analogies are useful in helping us to bridge the gap between a wellknown concept and an unfamiliar one. in this This assumption is widely used in finding inverse Laplace transforms where we assume that two functions are equal if they differ by a null function n(x) that has the property: n(t) di = 0 for every x > 0.
SEC. 2.4
Representation by a Series of Orthonormal Functions
particular case, however, we must pause and ask the question, "What is the
meaning of the equality in Eq. (2.4—9)?" Obviously, we must first give some meaning to the constant coefficients c1; second, we must determine the type of convergence (if any) of the infinite series so that we will have some idea of how the series represents fix). Until we clear up these points, we will change Eq. (2.49) to* fix) —
(2.410)
where the symbol — is to be read, "is represented by." In this section we define the c, and leave the matter of convergence to Section 2.5. We define the coefficients c, in (2.4—10) as follows:
c = (f,
=
(2.411)
dx.
Hence (2.410) becomes
fix) —
(f,
(2.4—12)
which is analogous to (2.44). In most of the applications in later chapters of this text the weight function w(x) will be equal to one. Accordingly, we will be using simpler equations than the ones shown as Eqs. (2.4—5), (2.4—7), and (2.4—li).
Key Words and Phrases natural basis
inner product of functions Euclidean inner product piecewise continuous function
jump discontinuity norm of a function infinitedimensional basis
2.4 Exercises
•
I. 2.
Use Eq. (2.4—4) to represent the vector v = ek (I n). k Prove each of the following properties of the inner product in R'. If be1,
u
=
v
c,e,,
and
=
*Henceforth we will omit the upper limil on infinite series.
w=
BoundaryValue Problems In Ordinary Dilferential Equations
72
3.
then (a)
(u, v) = (v, u);
(b)
(U,
(c)
(u, cv) = (Cu, v) = c(u, v) for an arbitrary constant c;
+ w) = (u,
CHAP. 2
+ (u, w);
(d) (u, u) 0 with the equality holding if and only if ii = 0. Compute each of the following limits for the piecewise continuous function g(l) in Fig. 2.4—2. lim g(t) (a)
tim g(t)
(b)
(d)
(C)
,.O_
1—0
lim gQ)
(f)
lim g(t)
(e)
i—2
(g)
lim g(t)
(h)
urn g(i) /—I—
tim g(t) s—2
urn g(t)
1—3
4.
1ff, g, and h are piecewise continuous functions on (a, b), c is an arbitrary constant, and w(x) > 0 on (a, b), prove each of the following properties of the inner product defined in Eq. (2.45). (a) (b) (c)
5.
(f,g)
(g,f)
(f,g.th)=(f,g)+(J,h)
(I, cg) = (cf, g) = c(f, g) Prove that =
c1
using the definition of the norm of a function given in Eq. (2.47).
••
6.
Graph each of the given functions. (a)
(b)
forOt 0 and is continuous.
If any one of these conditions does not hold or if the interval a x b is unbounded, then the SturmLiouville differential equation (2.7—1) is called
singular. Thus Eqs. (2.75) and (2.76) are singular on bounded intervals. It may also happen that although the SturmLiouville equation is non
singular, the boundary conditions may not have the form shown in Eq. (2.7—2). Consider the following example.
Find the eigenvalues and corresponding eigenfunctions of the following problem. EXAMPLE 2.7—1
y"tXy=0, y'(—c) = y'(c).
y(—c) = y(c),
Solution The boundary conditions here are called periodic boundary conditions. They will arise later when we consider boundaryvalue problems over circular regions in Section 7.1. We leave it as an exercise to show that X < 0 leads to the trivial solution (Exercise 3). For X > 0 we have
y(x) =
c,
y'(x) =
cos
—c1
+ c2 sin sin + c2
cos
The condition y( — c) = y(c) results in 2c2 Sin C'.[X
which can be satisfied either by c2 = condition y' ( — c) = y' (c) results in 2c1
0
= 0,
or by
= mr/c,
n=
1,
2
The
= 0,
sin
which can be satisfied either by c10=or by 'JX = nir/c. Hence the eigenvalues are =
(mr)2
= 1,2,
.
.
.
with corresponding eigenfunctions =
cos (!'!x) +
sin
(2.77)
BoundaryValue Problems in Ordinary Differential Equations
where the
and
are
CHAP. 2
not both zero but are otherwise arbitrary constants.
We leave it as an exercise to show that X = ing eigen function
0
is an elgenvalue with correspond
y0(x) =
is an arbitrary constant (Exercise 4).
where
U
The orthogonality property of the eigenfunctions of Example 2.71 will
be useful in Chapter 4 in our study of Fourier series. We observe that Eq. (2.7—7) shows that to each eigenvalue X,, there correspond two linearly independent eigenfunctions (Exercise 5). We can easily prove a theorem similar to Theorem 2.3—1 for the case of
periodic boundary conditions. THEOREM 2.71
For a regular SturmLiouville problem with periodic boundary conditions and such that r(a) r(b), eigenfunctionsbelonging to eigen values are orthogonal on Ia, bj with weight function w(x). Proof
The periodic boundary conditions are in general
y(o) = y(b),
y' (a) = y' (b).
From Eq. (2.35) we have —
=
X2)
(2.78)
—
and the righthand member becomes r(b)fy,(b)y2'(b) — y2(b)y(b)J — r(a)fy,(a)y(a) — y2(a)y(a)] = — — r(a)fy,(a)y(a) — y2(a)y(a))
0 It is important to note that if r(x) is constant on [a, b], then r(a) = r(b) so that periodic boundary conditions also lead to orthogonal eigenfunctions.
From Eq. (2.78) we can see that the condition r(a) = r(b) = 0 is enough to show that eigenfunctions belonging to different eigenvalues are orthogonal. Accordingly, the functions Yn(X) that are continuous on [—
1, 1]
and satisfy Eq. (2.76) form an orthogonal set on that interval with weight function w(x) = 1. We shall study these functions — called Legendre polynomials— in Section 7.3.
We also see from Eq. (2.78) that either of the two conditions
r(a) =
0,
y,(b)y(b) — y2(b)y(b) =0,
r(b) =
0,
y1(a)y(a)
(2.79)
or —
y2(a)y(a) =0,
(2.7—10)
is
89
Other Sturm.LIouvIlIe Systems
SEC. 2.7
sufficient to ensure the orthogonality of the eigenfunctions. In general the of a singular
following theorem covers the case of eigenfunctions Stunn—Liouvilie system. THEOREM 2.72 The eigenfunctions
of a singular SturmLiouvile system on (a, bJ are orthogonal on (a, hi with weight function w(x) if they are square integrable there and jf
=0
r(x)(y1(x)y(x) —
for every distinct pair of eigenfunctions y,(x) and y2(x). We
will see in later chapters that a versatile method of solving
boundaryvalue problems leads to both regular and singular SturmLiouville problems. The existence of orthogonal sets of eigenfunctions for these problems will be essential to obtaining solutions to our boundaryvalue problems. Key Words and Phrases separated
boundary conditions
singular Sturm—Liouville differential
equation
periodic boundary conditions Legendre polynomials singular SturmLiouville system
2.7 ExercIses
•
1.
In what ways does Eq. (2.7—5) fail to meet the requirements for a regular SturmLiouville differential equation?
2.
In what way does Eq. (2.76) fail to meet the requirements for a regular
SturmLiouville differential equation? 3. Show that X < 0 leads to the trivial solution of the problem in Example 2.71. 4. Show that X = 0 is an eigenvalue of the problem in Example 2.71, and find the corresponding eigenfunction. 5. Exhibit the two linearly independent sets of elgenfunctions of the problem in Example 2.7—1.
••
6.
The Mathieu equatlon*
y(O) = y(ir),
j(O) = y + a(Oy =
0,
'Emile L. Mathieu (1835—1890), a French applied mathematician.
tOeorse W. Hilt (18381914), an American astronomer, who studied the motion of the moon.
BoundaryValue Problems in Ordinary Differential Equations
90
CHAP. 2
and Y2(t) are periodic solutions of where a(t) is periodic. Show that if equation with period ir and belonging to distinct eigenvalues, then y,(t) Mathieu's
with weight function one.
and y2(t) are orthogonal on 10, 7.
Solve the following problem.
y"+X2y=O, y(O) ÷ 8.
y'(O) + y'(ir) =
= 0,
0.
Obtain the solution to each of the following singular Sturm—Liouville problems.* (a)
y"+Xy=O, y(O) = 0.
(b) y"+Xy=0, y'(0) = 0,
(c) y"+Xy=O,
Iy(x)I < M
Iy(x)I <M
Iy(x)I < M
9. 10.
Show that zero is not an eigenvalue in any of the problems in Exercise 8.
Solutions of Teliebycheff's djfferentia/ equationt
(I — x2).v" — xv' + n1y = 0,
n = 0, 1,2
(2.7—Il)
are Tchebvcheff polyno,nials defined by
T,,(x)
cos (n arccos x),
—I x
1.
(2.712)
(c)
± I are regular singular points of Eq. (2.7.! 1). Show that x Solve Eq. (2.7—Il) by a series method (see Section 1.5), and note that the restriction on n is necessary so that the solution will converge for x = ± I. Write out the first six Tchebycheff polynomials.
(d)
Show that the T,,(x) are orthogonal on (—1, 1) with weight function
(e)
(Hint: Make the substitution a = arccos x in Eq. 2.7—12). (I — x2) Explain how Eq. (2.7—Il) leads to a singular Sturm—Liouville problem. Show that the square of the norm is given by
(a)
(b)
(f)
2
(g) (h)
(I)
=
and
I! T,,
2=
for n > 0.
Obtain from the T,,(x) an orthonormal scries on (— 1, 1). Graph the first four polynomials. Find out how Tchebycheff polynomials are used to represent a function with
minimum error. Read Curtis F. Gerald's Applied Numerical Analysis (Reading, Mass.: AddisonWesley, 1978), Sections 10.5—10.7.
*The notation Iy(x) < M, where Mis some positive constant, means that y(x) is bounded on the given interval. tPafnuti L. Tchebycheff(1821—1894), a Russian mathematician. Various transliteracions of his name, such as Chebishev, are in use.
NumerIcal Methods
SEC. 2.8
2.8
NUMERICAL METHODS
When solving initialvalue problems in ordinary differential equations, we are
given the values of the dependent variable and the slope at some initial point (in the case of secondorder equations). To carry out a numerical solution for such a problem, we need to find successive values of the unknown function in some way. There are a number of methods for doing this, including the follow
ing: Euler's method, Heun's method, AdamsBashforth method, AdamsMoulton method, and RungeKutta methods.* We have seen that solving boundaryvalue problems in ordinary differ
ential equations presents some additional difficulties. For one thing, a boundaryvalue problem may have a unique solution, many solutions, or no real solution. For another, starting with the value of the unknown function at one boundary, we must somehow assign the initial value of the slope correctly if we expect to match the value of the function or the slope at another boundary. In other words, we must supply some missing initial condition in order to attain a specified value at the terminal point. If the correct initial condition is assigned, the terminal or target condition will be satisfied, and we are through. If the target condition is not satisfied, however, then we must adjust the initial condition in some systematic manner until the target condition is met within some specified tolerance. If the problem involves a linear differential equation and linear boundary conditions, then only one adjustment of the missing initial condition may be necessary. If the problem is nonlinear, however, then some iterative scheme must be used. In the latter case, questions of convergence and stability must be considered.
We can best illustrate the foregoing by giving an example using a boundaryvalue problem that has a unique solution that can be found analytically.
EXAMPLE 2.81
Solve the boundaryvalue problem
y"—y=2x,
y(O)=O,
y(l)=l.
Solution We can readily check (Exercise I) that the complementary solution is = c1 cosh
x+
c2 sinh X
and a particular integral is Yp(X) = —2X.
*Brjef descriptions of these can be found in Section 1.6 of Ladis D. Kovach, Advanced Engineering Mathematics (Rcading, Mass.: AddisonWesley, 1982).
Boundary•Value Problems in Ordinary Differential Equations
CHAP. 2
Hence the general solution of the given differential equation is .yg(X)
= c1 cosh x + c2 sinh
The condition y(O) = 0 implies that c1 =
y(x) = Finally, the condition y(l) =
1
c2
—
Zr.
so that
0
sinh x — 2x.
leads to
c2 sinh I —
2
=
1,
that is, = 3/sinh 1,
and
sinh x — 2x.
y(x) =
•
(2.81)
A graph of Eq. (2.8—1) is shown in Fig. 2.81 as a solid curve. It shows that the curve obtained by using points that satisfy Eq. (2.8—1) is correct rather
than one of the dashed curves in Fig. 2.81. The boundaryvalue problem of Example 2.8—1 can be easily converted into an initialvalue problem. From Eq. (2.8—1) we have
y'(x)
= sinh
cosh x — 2 1
y
1.0
0.8 0.
solution 0.4
0.2
0.2
0.4
0.o
0.8
1.0
FIgure 2.81 Analytical solution (Example 2.81).
Numerical Methods
SEC. 2.8
so
93
that 2
—
=
= 0.553.
1
Thus the problem of Example 2.8—1 is equivalent to the initialvalue problem
(Exercise 2)
y"—y=2x, y(O) = 0,
0<x 0;
1 > 0;
0 <x < L.
u(x, 0) = f(x),
The problem is shown diagrammatically in Fig. 3.42. Since the partial differential equation and the boundary conditions are homogeneous, we use
the method of separation of variables (see Section 3.2). The substitution u(x, a') = transforms the P.D.E. into .7,
kTX
ft
—i—— —
— _X2
where the separation constant has been chosen to be negative. There are two
reasons for this choice. First, the problem in X(x) is a Sturm—Liouville problem that has only the trivial solution if the separation constant is positive or zero; second, the problem in 1(t) must have a solution that approaches zero as a' — from physical considerations. The SturmLiouville problem
X" +
X(0) =
X2X = 0,
has eigenvalues n2, n =
1,
2, .
. .
0,
X(L) =
0,
, with corresponding eigenfunctions
n = 1,2
= sin
(3.4—3)
The differential equation kn2ir2 L2
Sin other than thermal applications, k is called the ddfrsivllv coef/kien! or ihe Iransporl coefficient.
137
The Diffusion Equation
SEC. 3.4
y Insulation 00
Ion
0)
I.
f(x)
u(x, 0)
FIgure 3.42 Heat flow (Example 3.41). has
solutions
(kn2ir2,)
exp
=
(344)
2
In Eqs. (3.43) and (3.4—4) we have set the arbitrary constants equal to unity, and are known only to within an arbitrary since the functions constant. Although products of the form
Sifl yXeXP
1) =
I
kn2 it2
V
satisfy the diffusion equation, we cannot hope (in general) to satisfy the given initial condition (LC.) with such a product. Hence we consider
u(x, t) =
kn2ir2
sin
exp (_
a linear combination of products, and try to find the u(x, 0) =
t),
(3.45)
We have
x = f(x),
sin
(3.46)
and it can be seen that by placing suitable restrictions onf(x) we can obtain the from =
f(s) sin
s ds.
(3.4—7)
This is possible because the set of functions nil.
L
x,
it =
1,
2,
is orthogonal on the interval (0, L) with weight function w(x) = tion 2.3 and Exercise 17.)
1.
(See Sec
CHAP. 3
Partial Differential Equations
Hence
the final solution of the problem can be written as sin
u(x, t) =
'vs ds.
(3.4—8)
We point out that representing f(x) by an infinite series of sine functions may require that some restrictions be placed onf(x). It will also be necessary to cx'amine conditions under which the series in Eq. (3.4—8) converges and can be U differentiated. These questions will be considered in Chapter 4. Note that from Eq. (3.48) we have lim u(x,
1)
= 0
provided that the are bounded.* We call u(x, 1) = 0 the steadystate solution of the problem in Example 3.41. This is the solution after the effect of the initial temperature distribution has been dissipated. Since the steadystate solution is independent of time, it can be obtained easily by setting u, equal to zero in the diffusion equation, that is, by solving u"(x) = 0,
u(L) = 0.
u(0) = 0,
The solution shown in Eq. (3.4—8), on the other hand, is called the transient
solution. Key Words and Phrases directional derivative thermal diffusivity heat equation steadystate solution transient solution
diffusion
diffusion equation thermal diffusion heat conduction thermal conductivity
3.4 Exercises S
J•
Referring to Eq. (3.4—2), show that if there is a source of heat continuously distributed throughout V given by f(x, y, z, I), then the diffusion equation becomes kV2u +
2.
cp
=
at
Show that the equation obtained in Exercise I becomes Poisson's equation if u is independent of i and Laplace's equation if, additionally, there are no heat sources present. Section 2.5.
139
The Diffusion Equation
SEC. 3.4
3.
In the diffusion equation (3.42), u is given in °C and tin seconds. Determine the units of k, and K, if c is given in caloriesec/(g °C).
4.
In obtaining Eq. (3.4—2) it was assumed that K was constant. If K is a function of position, show that the diffusion equation becomes
VKVu = 5.
Show that the SturmLiouvilie problem
X"(x) — X2X(x)= 0,
X(0) =
0,
X(L)=
0,
has only the trivial solution when X is real (including zero). 6.
Explain why the solution of the problem of Example 3.41 must have the property
urn u(x, 1) = 0. 7. 8.
Obtain the eigenfunctions Verify that the functions
in Eq. (3.4—3).
:) = sin —Lx exp
I L2
satisfy the partial differential equation and the boundary conditions of Example
•'
3.4I. 9.
Find the specific solution for the problem of Example 3.4—1 for each of the follow
ing cases. (a)
f(x) =
(b)
f(x) =
3sin1x
2
10.
(a)
sin
+
3
sin—1x
Solve the problem of Example 3.4—1 for the case u(x,
(b)
11.
13.
= 00,
0
<x
0 it is said to be of hyperbolic type; and where B2 — 4AC = 0
it is said to be of parabolic type. We consider first the effect of a coordinate transformation given by
Canonical Forms
SEC. 3.5
= E(x,
E
(3.5—2)
y).
=
We have (Exercise 1) + U,77,, = uEEY +
= uy
± = =
+ +
+
+ + + Uq,177y +
+
+
+
+ +
With these substitutions, Eq. (3.5—1) becomes A(x,
+ E(x, y)u1,, + C(x, y)u,,,, + 15(x, y)ut + E(x, y)u = G(x, y),
(3.53)
where (Exercise 2)
A(x, y) =
+ BEXEY +
y) = C(x, y) =
+
A
E(x,
y) = A
Ce.,
(3.5—4)
(3.55)
+
+
+ BEE,, + Ct.,, +
+ Es,.,
(3.57)
+
+ E%..
(3.5—8)
+
+
If B * 0, then Eq. (3.5—1) can be changed into Eq. (3.5—3) with E = 0 by a coordinate transformation involving rotation of axes. Let
x = E cos 0 sin 0 ÷
y=
sin 0, cos o.
3 59)
Then Eq. (3.5—5) becomes (Exercise 3) —
A sin 20 + B cos 20 + C sin 20 = 0
or
cot 20 =
AC
.
(3.5—10)
EXAMPLE 3.51 Use rotation of axes to eliminate the mixed partial derivative in uXX
+ UXY +
+ U, = 0.
Solution We readily see (Exercise 4) that the given equation is everywhere elliptic. Then, using Eq. (3.5—10), we have cot 20 = 0, that is, 0 = ir/4. Applying this value to Eqs. (3.5—9) produces
Partial Differential Equations
142
lxi I—
I
I
I
r
i
i
I
CHAP. 3
in matrix form. Since the 2 x 2 matrix is an orthogonal matrix, that is, one whose inverse is equal to its transpose, we have
ri
1
1
(3.5—11) I
I
We can use Eq. (3.5—11) to compute A,
C, and
as
given in Eqs. (3.54)
through (3.57) to obtain (Exercise 5) =—
+
UE.
•
(3.512)
In Example 3.51 the principal part of the given partial differential equation, that is, ux.,.
can
+ uxy + IA,,,
be compared to a quadralic form with matrix
/1
M=(
\1/2
Eliminating the
1/2 1
is equivalent to diagonalizing M (see below). Since M
a symmetric matrix, it can be diagonalized by means of an orthogonal matrix. The resulting diagonal matrix displays the eigenvalues of M on its diagonal. We leave it as an exercise to show that the eigenvalues of M are 3/2 is
and 1/2 (Exercise 17). Any nonzero vector x in the plane that satisfies the equation Mx = Xx is called an eigenvector of M, and the corresponding scalar X is called the elgenvalue belong
ing to x. A square matrix P having the property that its inverse is equal to its transpose pT (rows and columns interchanged) is called an orthogonal matrix. A symmetric (rows equal to corresponding columns) matrix M can be diagonalized, meaning that an orthogonal matrix P can be found such that PTMP is a diagonal matrix (one having zeros everywhere except possibly along the main diagonal).
We remark that the coordinate transformation (3.5—2) is assumed to be
such
143
Forms
SEC. 3.5
that f and are twice continuously differentiable and that the determinant
J= 'lx
'ly
called the Jacobian* of the transformation, is different from zero in the region of interest. Under these conditions it can be shown that the sign of the discriminant is invariant, since (Exercise 16) —
4AC = J2(B2 — 4AC).
(3.513)
If an equation is of hyperbolic type, then it can be transformed into a particularly simple form by using a coordinate transformation that will make A = C = 0. We note from Eqs. (3.54) and (3.56) that both equations will then have the form +
Assuming
+
= 0.
* 0, this last can be written as A
(&)2 + B
Along any curve where
(i)
+ C = 0.
(3.514)
y) is constant, we have
d4 =
+ 4,.dy = 0,
that is, — —
dy dx
Thus Eq. (3.514) becomes
A(dy\2 —
c—o —
with solutions
dy dx
B±\/B2_47C
351 (.5)
called characteristic equations of Eq. (3.5—1). Solutions of these equations are
called characteristic curves (or characteristics) of Eq. (3.5—1). Along the characteristics the partial differential equation takes on its simplest form. It is these socalled canonical forms (or normal forms) that we will investigate in more detail.
After Carl 0.
J.
Jacobi (1804—1851), a German mathematician. The notation
a(E, ii)/ö(x, y) is also used for the above Jacobian.
CHAP. 3
PartIal Differential Equations
144
Parabolic Equations In this case, B2 — 4AC = 0, and Eqs. (3.5—15) reduce to
(3516)
—
—
dx

Now, A and C cannot both be zero (Why?), so assume that A
0.
Then the
solution of Eq. (3.516), namely, i/i(x,
y) = constant
y), and = constant defines a single family of characteristics. The value of is arbitrary provided that it is twice continuously differentiable and the aforementioned Jacobian is nonzero. provides the value of E =
EXAMPLE 3.52 Transform the differential equation ÷ y2u,,,, = 4x2
+
to canonical form, and then solve the resulting equation.
Solution The given equation is parabolic everywhere, and Eq. (3.5—16) becomes dy

y
dx — x This last differential equation has solutions given by y/x = constant; hence we
make the coordinate transformation E '1
Thus A =
= 0 and C =
=Y.
(Exercise 6), so the given partial differential
equation becomes = —p—
Integrating with respect to
or
=
4
we get U,,
=
+
and
= u(E,
+
÷
Hence in terms of the original variables we have the general solution
145
Canonical Forms
SEC. 3.5
u(x, y) =
•
+
+
Note that Eq. (3.5—14) can be rewritten as A +
414C
B ±
2C
dy
L35 17 )
= 0 and C * 0, then the characteristic equations (3.517) can be used. Thus for parabolic equations the canonical form is given by either instead of Eqs. (3.5—15). If A
=
H(u€,
u,
H represents a linear function of terms in the indicated variables.
Hyperbolic Equations
In the case of hyperbolic equations the characteristic equations
dy_ dx have
2C
two real and distinct solutions whenever A
* 0. Denote these solutions
by
y) and
y) = c2. Then the coordinate transformation
= = results
in A =
v)
C = 0 and the canonical form
=
u,
E.
ij).
A similar result can be obtained if A = 0, but C * 0.
(3.5—20)
_ CHAP. 3
Partial Differential Equations
146
Transform the differential equation
EXAMPLE 3.53 —
— (cos2 x)u,,, — (cos x)u,.
(2 sin
=0
to canonical form, and solve the resulting equation.
Here B2 — 4AC = 4, so that the equation is hyperbolic everywhere. The solutions of the characteristic equations Solution
dv dx
—sIflX±
I
are
y) — cos x + x — y = and
y) = cos x — x Hence
y=
—
we make the coordinate transformation E
= cosx + x — = cosx — x
v,
Then A = C = 13 = E = 0 and E = —4, so that the canonical form + becomes = 0. From this we have Ut = h(E) and u = that is, u(x, y) = f(cos x — x
—
y) ÷ g(cos x + x —
wheref and g are twicedifferentiable but otherwise arbitrary functions of the indicated variables. U The next example illustrates the case of a hyperbolic equation in which
B = 0.
EXAMPLE 3.54
Transform the equation 0
—
to canonical form, and solve the resulting equation.
Here we have B2 . 4AC = > 0, showing that the equation is hyperbolic everywhere except on the x and yaxes. We consider a region that does not include any part of either axis, for example, a region in the first Solution
quadrant. The characteristic equations dv have
v
solutions (Exercise 8) y = c,x and y = c/x; hence we make the coordi
147
Canonical Forms
SEC. 3.5
y
I t= I
??= I
x
0
Figure 3.51 Characteristic curves (Example 3.54).
nate transformation y
S
= xy.
ThenA = C = £ =
= —4y2 = —4E77,andb = 2y/x = 2E.Thusthe given partial differential equation becomes (Exercise 9) 1
Ut,, — s—
= 0,
(3.521)
which is equivalent to the canonical form shown in Eq. (3.520). We can solve Eq. (3.5—21) by observing that it is a firstorder linear differentiaL equation in Ut. Then we obtain the solution (Exercise 10) u(E, n) =
+ g(77),
that is,
u(x,y) =
g(xy).
The characteristic curves are shown in Fig. 3.51.
U
CHAP. 3
Partial Difterential Equations
148
Elliptic Equations in the case of elliptic equations the characteristic equations (3.5—17) have com
plex conjugate solutions. Hence in order to obtain real characteristics it is necessary to make two coordinate transformations. We illustrate with an example.
EXAMPLE 3.55 In the region where the equation xUxx + uyy = is
elliptic, transform the equation to canonical form.
Solution Since B2 — 4AC = — 4x, the equation is elliptic in the halfplane x > 0. In this region the characteristic equations are dy = — dx
with solutions
y =
+
y=
and
+
C2.
We first make the coordinate transformation
o = y + 2x"2i, r = y — 2xk'2i but since these are complexvalued, we make a second coordinate transformation defined by a =
+
r=
—
As a result of these two transformations we have (Exercise 11)
and Then A
C=
1,
= 0, and E = +
is
I
= ;;
—
so
that the canonical form
Uq +
obtained (Exercise 12).
We observe that, in general, the canonical form for an elliptic equation can be written as + Uq,j =
U,,
U,
(3.5—22)
The simplest example of an elliptic equation is Laplace's equation. in summary, parabolic equations have a single family of characteristic curves given by E = constant; hyperbolic equations have characteristic curves
149
Canonical Forms
SEC. 3.5
given by
= constant, which form a curvilinear coordinate
= constant and
system; elliptic equations have no real characteristic curves. Key Words and Phrases principal part
quadratic form
discriminant elliptic type hyperbolic type parabolic type orthogonal matrix
eigenvalue
Jacobian characteristic equalions characteristic curves canonical form
3.5 Exercises S
1.
Use the coordinate transformation defined in Eqs. (3.5—2) to compute each of the following partial derivatives. and (a) (b)
u,,, and
(Hint: Note that Ou
Ox
—
Ou OE
+
Ox
—
in which any function of x andy, such as u.. or ui,, may be inserted. There is a
similar formula from part (a) that can be used to obtain derivatives with 2. 3.
respect to y.) Verify that the coefficients A, etc. are given by Eqs. (3.5—4) through (3.5—8). (a) Solve Eqs. (3.59) for and in terms of x and y. (b) Use the results in part (a) to compute y) from Eq. (3.5—5). (c) Show that setting mx, y) = 0 in part (b) leads to
cot2O= provided that B
AC B
* 0.
5.
Show that the partial differential equation in Example 3.5—I is elliptic everywhere. Carry out the details to arrive at Eq. (3.5—12).
6.
Use the coordinate transformation
4.
and
to compute A, 7.
C,
Compute A, A, C, i,
and £ in Example 3.52. and E in Example 3.53.
CHAP. 3
Partial Differential Equations
150 8.
Show that the solutions of dx
=
x
arey = c,xandy = c2/x. 9. Obtain Eq. (3.521) in Example 3.54. 10. Solve Eq. (3.5—21). (Hint: Make the substitution v = ut.) 11. In Example 3.5—5, fill in the details necessary to arrive at
E=v 12.
•'
13.
14.
i=2x 1/2
C, 15, and E, and then obtain the canonical In Example 3.55, compute A, form shown. By differentiation, verify that the following are general solutions of the partial differential equations given in the examples of this section.
(a)
u(x, y) =
(b)
u(x, y) = f(cos x — x
(c)
u(x, y) =
2x2
+ g
+
(.!.)
(Example 3.52)
y) ÷ g(cos x + x — y).
—
+ g(xy).
+
(b) (c)
(d)
(Example 3.54)
(f)
+ xu3,, = +
+
(I
—
+ —
—
+ u7 0 (1 — y2)u,,, = 0
+ x2zi,,, = 0
(e)
+ 4u,, =
—
(g)
—
y2u3,,,
= xy
Compute the Jacobian \X. y for each of the following transformations. (a) (b) (c) (d) (e)
•SS
16.
(Example 3.53)
For each of the following equations, determine the regions where the equation is elliptic, hyperbolic, or parabolic. (a)
15.
and
E=y/x, E=y/x, E=y,
Prove that —
4AC = J2(B2
where J is the Jacobian of the transformation. 17. Find the eigenvalues of the matrix
—
4AC),
SEC. 3.5
151
Canonical Forms 1/2
M=L \1/2
I
(Hint: See Section 4.4 of the author's Advanced Engineering Mathematics (Reading, Mass.: AddisonWesley, 1982).) 18.
angle, transform each of the following equations to one that does not have a ui., term. (a) =0 + 4ury + (b) + + = 0 (Note that the equation need not be elliptic to use this technique.) By rotating the x and yaxes through an appropriate
Fourier Series
4.1 INTRODUCTION This chapter and the next are transitional ones in our study of boundaryvalue
problems. Up to this point we have reviewed some of the basic concepts in ordinary differential equations (Chapter 1). We will continue to make frequent use of this material, with Sections 1.3 and 1.5 playing a prominent rote in the remaining chapters. We will also refer to Sturm—Liouville problems and the representation of functions by a series of orthonormal functions (Chapter 2) in future chapters. We will consider more varied boundaryvalue problems than
the ones discussed in Chapter 3. Examples 3.22 and 3.41 dealt with the potential and diffusion equations, respectively. These equations together with the wave equation will be treated in greater detail (in higher dimensions, in various coordinate systems, etc.) in later chapters. As a preliminary to more complicated types of boundaryvalue prob
lems, however, we present a branch of mathematical analysis that had its origins in the eighteenth century. As early as 1713, Taylor suggested that the function sin
x
could be used to explain the steadystate motion of a vibrating string of length
L fixed at both ends. In 1749 and 1754, D'Alembert and Euler published papers in which the expansion of a function in a series of cosines was discussed. A problem from astronomy at that time involved the expansion of the
reciprocal of the distance between two planets in a series of cosines of 152
153
Fourier CoeffIcients
SEC. 4.2
multiples of the angle between the radius vectors. In 1811, * Fourier developed
the idea of expanding a function in a series of sines and cosines to the point at which it became generally useful.
4.2
FOURIER COEFFICIENTS
In Section 2.4 we represented a piecewise continuous functionf(x) by a series of orthonormal functions. Given that the set
I = 1,2, is
.
orthonormal on Ea, bJ with weight function w(x), that is, w(x) dx = ô,1.
Then
f(x)
—
(4.2—1)
where
= (f,
dx
=
(4.2—2)
and the symbol — means "is represented by, in the sense of convergence in the mean" (see Eq. (2.5—10)).
It was shown in Section 2.3 that the sets
lsinnx,
n
= 1,2,..j
and nx,
n = 0,
1, 2,
.
orthogonal on 10, ir] with weight function one. By dividing each function in the above sets by its norm we obtain the orthonormal sets are
n =
1, 2
(4.24)
Fourier's paper was submitted in 1807 but was rejected by Lagrange, one of the examiners,
presumably because he failed to understand how the motion of a vibrating string, for example, could be periodic in a spatial coordinate.
CHAP. 4
Fourier Series
154
We leave it as an exercise to show that the set
±, is
n = 1,
sin nx,
cos nx,
2,
.
.
(4.25)
an orthonormal set on [— w, ir] with weight function one (Exercise 2). By using the orthonormal set (4.2—5) we can obtain the Fourier series
representation of f(x):
f(x)
a0
cos nx +
÷
sin nx.
(4.26)
—
In this representation the Fourier coefficients are given by =
f(x)cosnxdx,
n
= 0,1,2,...
(4.27)
and
1Cr = —)
1(x)
san
nx dr,
n = 1, 2
(4.2—8)
We observe that if a function f(x) is to have a valid Fourier series representation as given by (4.26) on an interval extending beyond [— ir, TJ, then it must be periodic. This is due to the fact that the individual terms of the series are, themselves, periodic. Recall that a function is periodic of period
p
f(x ÷ p) = f(x) for all values of x. Each term in the representation of (4.2—6) is periodic of period 2w. (Note that a constant function f(x) = k satisfies the above definition of periodicity for any value of p.) Thus a function must be periodic of period 2i in order for the Fourier representation (4.2—6) to hold outside of ir, ii. This requirement is not a restriction in case we are interested only in since then it is unimportant to what values representing the function on (0, the series might converge outside this interval. A second property that the function f(x) must have is that it must be piecewise smooth. A function f(x) is said to be piecewise smooth if f(x) and
f'(x) are both piecewise Continuous. See Fig. 4.2—1 for an example of a piecewise smooth function. (See also Exercise 4.) Sufficient (but not necessary) conditions for obtaining a Fourier series representation of a function are given in Theorem 4.21. These conditions are
The smallest value of p for which the relation holds is called the fundamental period
off.
Fourier CoefficIents
SEC. 4.2
155
1(x)
g(x)
0
(b)
f(x) and f'(x) are both piecewise continuous; (b) g(x) is piecewise continuous, but g'(x) is not.
called
the Dirichiet conditions, since they appeared in papers of Dirichiet
published in 1829* and 1837.t THEOREM 4.21
If f(x) is a periodic function of period 2,r and piecewise smooth for x ir, then the Fourier series representation (4.26) of 1(x) con— verges to f(x) at al/points where f(x) is continuous and converges to the average of the left and righthand limits of f(x) where f(x) is discontinuous.
At the present time the convergence problem for a Fourier series is still
unsolved. The Dirichiet conditions are known not to be necessary, and necessary conditions that have been obtained are known not to be sufficient. Suffice it to say that the conditions stated in Theorem 4.21 are satisfied by a
large number of the functions that we encounter in applied mathematics; •"Sur Ia convergence des series trigonométriques qui servent a representer une fonction arbiiraire entre des limites données," J. rel. ang. Math., 4(1829), pp. 157—169. rUber die Darsteliung ganz willkurlicher Funktionen durch Sinus und Cosinusreihen," Report. Phys., 1 (1837), pp. 152174.
156
Fourier Series
CHAP. 4
we will not delve any deeper into the theory at this point. We illustrate in the following examples how Fourier series representations are obtained. hence
EXAMPLE 4.2—1
Find the Fourier series representation of the function for —
0, 1(x) = x,
rc
<x
0.
•
From a practical viewpoint the evaluation of u(x, t) from Eq. (5.25) for various values of x and t may be done numerically. The use of the fast
Fourier transform (FF1') technique is recommended in this case.*
Anthony Ralston and P. Rabinowitz, .4 First ('ourse in Numerical ,4nalvsis (New York: McGrawHill, 1978), p. 263 if.
CHAP. 5
Fourier Integrals and Transforms
208
Fourier Sine Transform
If f(x) is an odd function, then we define the Fourier sine transform pair f(x) sin ax dx,
= fAa) =
(5.26)
f(x) =
2
—
j
f5(a) sin ax da.
We use repeated integration by parts to compute the Fourier sine transform of
d2u/dx2 to obtain
i
. —i sin ax dx = du sin ax dx dx .
a
— o
jodx
cos ax dx
dii = —aijo—cosaxdx dx =
—cxii
cos ax
1°' u Jo
0
sin ax dx.
Hence = au(O) —
(5.27)
In the above computation we have made the assumptions that u and du/dx approach zero as x — oo and that
is
finite.
Fourier Cosine Transform
If 1(x) is an even function, then we define the Fourier cosine transform pair =
1(x) =
=
f(x) cos ax dx, (5.28)
cos ax dcx.
In the same manner as before, we can compute the Fourier cosine transform of
d2u/dx2 to obtain (Exercise 3) = —u'(O)
—
(5.29)
under the previous assumptions. When the meaning is clear, we will Omit the
subscripts "s" and "c" in order to simplify the notation.
209
Fourier Transforms
SEC. 5.2
EXAMPLE 5.22 Solve the following boundaryvalue problem (Fig. 5.22):
P.D.E.: B.C.: LC.:
u, =
0
u(x, 0)
<x
c, in unity for Jt
I
< c, and in onehalf for
= c. Still another, and
sWerner (Carl) Heisenberg (1901—1976), a German physicist. tSee Kurt B. Wolf, integral Transforms in Science and Engineering (New York: Plenum Press, 1979), Chapter 7.
214
FourIer Integrals and Transforms
CHAP. 5
more mathematical, way of expressing the above is in the form
f(t)
da.
=
We mention one important offshoot of the rectangular pulse example. If we let c become infinite, then the energy of the pulse is confined to a zero bandwidth. Under this limiting condition, 7(a) becomes the socalled Dirac delta functions ô(a), which has the unusual properties
= 0
if a * 0
(5.211)
and
ô(a)da =
1.
(5.2—12)
The Dirac delta function plays an important role in ordinary differential equa
tions when the forcing functions are impulses. In connection with Fourier transforms, the delta function broadens the theory by admitting periodic functions that do not possess Fourier transforms.t Although the Dirac delta function defined above is not a function in the mathematical sense, it is a useful entity. This "pseudofunction" belongs to a
class of generalized functions, and its use as a function may be studied by "distribution the most useful properties of 6(a) is its sifting property, that is, its ability to pick (or sift) out the value of a function at a par
ticular point. If f(t) is continuous on t 0, then f(t) 6(1) di = f(0)
(5.2—13)
and f(t) &(t —
=
(5.214)
Key Words and Phrases Fourier transform pair
Fourier transform inverse Fourier transform fast Fourier transform (FF1') Fourier sine transform Fourier cosine transform
perfect insulation spectrum of a function spectral bandwidth Heisenberg uncertainty principle Dirac delta function
*After Paul A. M. Dirac (1902— ), a British theoretical physicist known for his work in quantum mechanics. tSee R. N. Bracewell, The Fourier Transform and Its Applications, 2nd ed. (New York: McGrawHill, 1978). Arthur E. Danese, Advanced Calculus: An Introduction to Applied Mathematics, Vol. 2 (Boston: Allyn and Bacon, 1965), Chapter 24.
215
Fourier Transforms
SEC. 5.2
5.2 Exercises
•
1.
2.
Obtain the Fourier transform pair Eqs. (5.2—2) from Eqs. (5.2—1). (Hint: Replace a by 2,rX in the second of Eqs. (5.2—1).)
Verify that
f(a) exp
U(a, t) = is
the unique solution of the initialvalue problem in Example 5.21.
3.
Obtain the result shown in Eq. (5.2—9).
4.
Solve Example 5.2I if 1(x) is defined as follows (see Fig. 5.2I)
l+x,
forOxO, for x > c. in Example 5.23.
6.
Carry out the details required to obtain
7.
What is the solution of the problem in Example 5.21 if f(x)
8.
Solve Example 5.22 if the boundary condition u(0,
9.
10.
= exp (— lxi)?
I) = 0
is replaced by
1) = 0.
If f(x) = exp (—x), solve each of the following problems: (a)
Example 5.22
(b)
Exercise 8
(a)
Obtain the spectrum of the function 1(1)
(b) 11.
1)
_jcos 1,
for —w/2
— ko,
elsewhere
i
Graph the function and its spectrum.
Find the Fourier transform of each of the following functions defined on (— (a)
b
(sin 7rx, g(x) =
0,
=
or, more compactly, by y) = J(a)e 20.
21.
IaIY
Discuss ways in which a particular solution of Eq. (5.35) might be found. Use the Fourier transform to find a solution of the equation
(a)
3y" + 2y' + xy = 0. (b)
Verify the solution obtained in part (a). (Hint: Show that after substituting into the given differential equation and collecting the terms, the result can be written
exp(—iu)du. Then use Cauchy's theorem — see
Section 10.5 of the author's Advanced
Engineering Mathematics (Reading, Mass.: AddisonWesley, 1982).) 22.
Read the article "Computerized Tomography: The New Medical XRay Technology," by L. A. Shepp and J. B. Kruskal in Amer. Math. Monthly 85, No. 6, JuneJuly 1978, pp. 420439.
Applications
SEC. 5.3
225
REFERENCES Bracewell, Ronald N., The Fourier Transform and its Applications, 2nd ed. New York:
McGrawHill, 1978. An excellent book that is especially suited for applied mathematicians and engineers.
Davies, B. 1978.
Integral Transforms and Their Applications. New York: SpringerVerlag,
An advanced treatment of the Fourier transform that includes transforms in two or more variables.
Erdelyi, A., Magnus, W., Oberhettinger, F., and Tricomi, F. 0., Tables of Integral Transforms (Baleman Manuscript Project). New York: McGrawHill, 1954. An excellent set of tables of Fourier and Laplace transforms. Kraut, Edgar A., Fundamentals of Mathematical Physics. New York: McGrawHill, 1967.
An excellent coverage of integral transforms and partial differential equalions at an intermediate level.
Ian N., Fourier Transforms. New York: McGrawHill, 1951. This is a complete theoretical and applied treatment of the subject at an
Sneddon,
advanced level.
Ian N., The Use of Integral Transforms. New York: McGrawHill, 1972. This advanced theoretical coverage is very complete and includes tables of Fourier transforms.
Sneddon,
Weinberger, H. F., A First Course in Partial Djfferential Equations with Complex Variables and Transform Methods. Waltham, Mass.: Blaisdell, 1965. A somewhat advanced and thorough treatment of the Fourier transform and other topics.
Wolf, Kurt B., Integral Transforms in Science and Engineering. New York: Plenum Press, 1979. An advanced coverage of the Fourier transform but one that contains many excellent computergenerated graphs.
Boundary•Value
6 Problems in Rectangular Coordinates
6.1
LAPLACE'S EQUATION
In Section 3.2 we indicated that one of the most common secondorder partial differential equations is Laplace's equation, +
ui,,
= 0.
+
(6.11)
Up to this point we have dealt with this equation in one and two dimensions. We now present an example of a boundaryvalue problem in three dimensions in order to illustrate double Fourier series. EXAMPLE 6.11
Solve the following boundaryvalue problem:
O<x 0, C2 = E/p; B.C.; u(L, I) = 0, t > 0 (the end x L is kept fixed), t) = F0, I > 0 (a constant force is applied at x = 0); l.C.: u(x, 0) = 0, 0 < x < L (the bar is initially unstrained), o < x < L (the bar is initially at rest). U(X, 0)= 0, We have indicated in the mathematical formulation of the problem how
the physical facts are translated into mathematical terms. Since u(x,
1)
0 shows that the displacement is zero when x = L, that is, the end x = L is kept fixed. As was stated earlier, the force on a crosssection at x is given by represents the displacement of the bar, u(L,
EA and
at the end x =
0
1)
ox
this force is given as F0i1. From this it follows that = F0.
the bar is initially unstrained, it cannot have any displacement at t = 0, that is, u(x, 0) = 0. Finally, the bar is initially at rest, meaning that the velocity Since
244
CHAP. 6
Boundary Value Problems in Rectangular Coordinates
F0
(x,O)
Figure 6.25
zero, at time I = 0. The ability to translate physical phenomena into mathematical symbolism is an invaluable aid in problem solving. ur is
Although there are three homogeneous conditions, separation of variables will produce the result u(x, I) = 0, which is not a solution (Exercise 8). The difficulty is caused by the fact that the resulting SturmLiouville problem in T has a unique trivial solution. This situation could be remedied if we could somehow transfer the nonhomogeneous boundary condition into an initial condition. We can obtain a solution by making the change of variable u(x, I) = U(x, I) — where 0(x) is to be determined. Then the problem becomes the following one:
PIlE.: B.C.:
= U(L, 1)
EUX(O, I.C.:
I)
0 <x
0;
— x),
0
< L.
0,
This problem can be solved by the method of separation of variables. We make the assumption that U(x,
I)
=
and
245
The Wave Equation
SEC. 6.2
substitute into the partial differential equation. Then
XT = c2X"T, and when we divide both members by the nonzero (Why?) quantity c2XT, we get =
(6.24)
—X2.
We know that the separation constant must be negative for two reasons — first, because must be periodic in t (Why?) and, second, because the problem in
X(x) has only the trivial solution if the separation constant is positive or zero (Exercise 10).
We leave it as an exercise (see Exercise 11) to show that the Sturm— Liouville problem
X" + X2X =
X(L) =
0,
0,
X'(O) =
0,
(6.25)
has solutions X,,(x) =
cos (2n
n = 1, 2
—
It is important here to note that the eigenvalues of the problem (6.2—5) are = (2n— and
1
2
n = 1, 2,
.
that zero is not an eigenvalue. The second equation in (6.2—4) can be
written T1, = 0,
+ (2,12j
(6.26)
T,,(0) = 0,
where the boundary condition comes from the homogeneous initial condition on U(x, 1). The solutions to (6.2—6) are (Exercise 12) =
(2n_
I
n = 1, 2
Now we take a linear combination of products
U(x, t) =
a,,
cos (2n —
so that
cos (2n —
(6.2—7)
'I
which satisfies all homogeneous conditions. When we impose the nonhomoge
neous l.C., we get U(x, 0) =
cos (2n —
1)
x=
(L
—
x),
246
Boundary Value Problems In Rectangular Coordinates
CHAP. 6
f(x) F0L
£
x
0
L
FIgure 6.26
which is a Fourier cosine series representation of the function (Fo/E)(L — x), shown in Fig. 6.26. Note, however, that if we proceed as in Section 4.3 to make an even periodic extension of this function, we obtain the function shown in Fig. 6.2—7. This cannot be correct because such an extension would have a constant term a0. We have already established that zero is not an eigenvalue of the problem (6.25) or, stated another way, that a0 = 0. Accordingly, the even periodic extension in this case must be the function 4(x), shown in Fig. 6.28. We can now write the solution as U(x, 1) =
I$Ix + Ct) + F(x — cl)1, f(x)
L
L
FIgure 6.27 The even periodic extension of (F01L) (L — x).
(6.2—8)
247
The Wave Equation
SEC. 6.2
4'( v) F0L
Figure 6.28 The function 4'(x).
following the method used to obtain Eq. (3.3—6). Alternatively, the solution given by (Exercise 13) can be written as in Eq. (6.2—7) with the coefficients a,,
F0
= —
r2L
j
(L
—
x) cos (2n —
8F0L Eir2(2n — 1)2'
—
dx
1)
12 '
(6.29)
To see that Eqs. (6.2—7) and (6.2—8) are equivalent, we use the
trigonometric identity
cos a cos /3 =
[cos
(a +
/3)
+ cos (a —
/3)]
in Eq. (6.2—7). Then we have + ci) + cos
U(x, 1) =
—
ci)],
where —
(2n
—
l)7r
2L
The function 4(x), however, has the Fourier cosine series representation
4(x) =
cos w,,x.
Boundary Value Problems In Rectangular Coordinates
248
CHAP. 6
Thus
+ ci) =
cos
+ ci),
with a similar expression for 1(x — ci), and the equivalence of Eqs. (6.27) and (6.2—8) is established. Accordingly, the solution to the original problem is u(x, I) =
9(x
— L) + U(x,
(6.2—10)
1)
with U(x, 1) expressed in one of the two equivalent forms. We leave the full verification of these results for the exercises (see Exercises 14 and 15).
•
In the problem of Example 6.22 we showed how a nonhomogeneous
boundary condition can be transferred from one independent variable to another by a change in the dependent variable. Other examples of this technique will be given in Section 6.3. Another problem in which the onedimensional wave equation applies is considered next. Let 0 be the angular displacement of a crosssection of a uniform circular shaft from some equilibrium position. If 0 is small, then, according to the theory of elasticity, 0 satisfies the partial differential equation
0,, =
(6.2—11)
with c2 = Gg/p, where 0 is the shear modulus of elasticity, p is the density (mass per unit volume), and g is the acceleration due to gravity. Suppose that a shaft of circular crosssection and length L is clamped at one end while the other end is twisted, then freed. As the shaft oscillates, the free end is clamped at time t = t0. At this instant the angular and the angle 0 is zero. State all conditions that apply, and velocity is solve the boundaryvalue problem. EXAMPLE 6.2—3
Solution We take coordinates so that the shaft lies along the xaxis with the free end at x = L. Then we have the following.
P.D.E.:
0,, =
0;
0
B.C.:
0(0, t) 9(L, 1)
I.C.:
9(x, to) =
= 0, = 0,
0,(x, to) =
0,
1 > 0 (clamped at one end), 1 > to (free end clamped at t = 1
to);
0<x0,
= 0.
Fig. 629.) Solve the vibrating string equation for the case of a string length of L and initial conditions
(See
22.
u(x,0)=x(L—x), 0)
*23.
24.
1 and c = If L (a) u(I/4, 2)
3
= 0.
in Exercise 22, compute (b)
u(I/2, 3/2)
Deduce from Eqs. (6.2—7) and (6.2—9) that 1
—
'7=
1)2
—
8
I
y I:)
0
(L,0)
FIgure 6.29
252
Boundary Value Problems in Rectangular Coordinates 25.
CHAP. 6
The nonhomogeneous wave equation leads to the following problem:
P.D.E.:
F(x, u,, = u(x, 0) = f(x),
l.C.: (a)
(b)
1),
<x
—
u,(x,
i>
0; = 0.
1> 0;
29.
Solve each of the following nonhomogeneous problems: (a)
P.D.E.: l.C.:
= 1,
u,, —
u(x, 0) = sin bx,
u,(x,O)=0, (b)
P.D.E.:
l.C.: 30.
6.3
253
The Diffusion EquatIon
SEC. 6.3
— —
cc <x < 00, cc <x < cc,
t > 0;
—cc<x 0;
Read the paper "Motivating ExistenceUniqueness Theory for ApplicationsOriented Students." by A. D. Snider in Amer. Math. Monthly, December 1976, pp. 805807.
THE DIFFUSION EQUATION
A classic example of a secondorder partial differential equation of parabolic type is the diffusion equation. It has the form
k > 0,
u, =
(6.31)
where V2 is the Laplacian operator 32
32
32
+
+
We show the operator in three dimensions and in rectangular coordinates here.
In this section we consider the diffusion equation together with various boundary conditions. It will be convenient to think of these problems as prob
lems of heat conduction under various conditions. In some cases we will specify the temperatures at the boundaries; in other cases we will specify the flux of heat across the boundaries or the transfer of heat by convection into
surroundings kept at constant temperature. This last case will involve Newton's law of cooling in the form
h>0,
u>u0,
(6.32)
where du/dn is the (outwardpointing) normal derivative at the boundary, h is a positive constant, and uo is the constant temperature of the surroundings, that is, the ambient temperature. At a point of the surface S we define theflux of heat 4 as the quantity of heat per unit area, per unit time, that is being conducted across S at the point. The flux 'I is proportional to the directional derivative of the temperature u in
254
CHAP. 6
Boundary Value Problems In Rectangular Coordinates
normal
it'=
Figure 6.31 Flux. a
direction normal to the surface S, that is, 4)
=
—Kr,
(6.33)
the proportionality constant K (> 0) is the thermal conductivity and au/an is the rate of change of temperature along the outward pointing normal
where
of flux are calories/cm2 /sec. In Examples 6.3—1, 6.3—2, and 6.33 we will illustrate how various boundary conditions can be treated. In these examples we will be considering a slender rod of constant crosssection encased in an insulating jacket so that heat conduction takes place in the xdirection only. We will thus be dealing with the onedimensional heat equation in rectangular coordinates. The equation also applies to an infinite slab of finite width whose faces are insulated and whose edges are kept at constant temperatures or are insulated. (Fig.
6.3—I). The SI
EXAMPLE 6.31
Solve the following problem.
P.D.E.: B.C.:
I.C.:
=
0
u(x, 0)
t> 0;
< x < L,
t) = 0,k u(L,t) =o,J 1(x),
> 0
o.
< x < L.
This is the problem of heat conduction in a bar whose left end is perfectly in
sulated, whose right end is kept at temperature zero, and along which there is an initial temperature distribution defined by 1(x). See
Solution into
Using
separation of variables, let u(x,
) =
the partial differential equation. Then X(x)T(t) = X"(x)T(t),
Systéme
International d'Unites.
Fig.
6.3—2.
X(x)T(t), and substitute
255
The Diffusion Equation
SEC. 6.3 V
Insulation
i(L
u(x,O)f(x) FIgure 6.32 and dividing by X(x)TQ), we get (Exercise 2)
X"(x)_
T(t) —
X(x)
—
The SturmLiouville problem in X(x) is
X" + X2X = 0,
X'(O) =
X(L) =
0,
0,
with solutions (Exercise 3)
,=
X1,(x) =
1,2
Since the firstorder equations T1,(t)
T1,(t) = 0
4L2
have solutions T1,(t) = exp
ir2(2n— [—
we take for u(x, 1) the linear combination
u(x, t) =
exp
1)2
4L2
cos
1)ir
(6.34)
Then, applying the IC., we have a21,
 cos
(2n — 2L
x = f(x).
I
If f(x) meets the required conditions, then it can be expanded in a Fourier cosine series so that a21,..1
=
f(s) cos
(2n
s ds,
n = 1, 2
The complete solution is given by Eq. (6.34) with (6.3—5).
U
(6.3—5)
defined in Eq.
256
Boundary Value Problems in Rectangular Coordinates
CHAP. 6
The next example illustrates how a nonhomogeneous boundary condi
tion can be made homogeneous.
EXAMPLE 6.32 Solve the following problem. See Fig. 6.33.
P.D.E.: B.C.:
I.C.:
t> 0;
0 < x < L,
=
u(O, t) = 0, k u(L, 1) = uo, a constant, j 0 < x < L. u(x, 0) = 0,
o.
Solution
The method of separation of variables fails here because it leads to
u(x, t) =
0,
which is not a solution (Exercise 6). If we make a change of
variable, however, the difficulty can be overcome. Accordingly, let u(x, t) = U(x, 1) +
çb(x),
so that the problem becomes the following one.
P.D.E.: B.C.:
0 < x < L,
+ 4"(x),
=
U(O, t) +
U(L, t) + /4L) = I.C.: Now if we choose
U(x, 0) +
t> 0;
= 0,
f
= 0,
0 < x < L.
so that it satisfies
4'(x) =
0,
= 0,
.b(L) = u0,
(6.36)
then the resulting problem in U(x, 1) is one that can be solved by the method of separation of variables. The details are left for the exercises. (See Exercises 7 and 8.)
•
The
technique used in solving the problem of Example 6.32 is an
illustration of a powerful method in mathematics, that is, reducing a problem to one whose solution is known. Other examples of this technique occur in the integral calculus, where integration by substitution is used, and in ordinary differential equations, where certain secondorder equations are reduced to firstorder ones. See also Exercises 24 and 26. We observe that an alternative way of looking at Example 6.3—2 is the
following. One end of a bar is kept at temperature zero, and the other at y
00
ui=uxx
u(x,0)0 Figure 6.33
257
The Diffusion EquatIon
SEC. 6.3
temperature u0, a constant. The entire bar is initially at temperature zero. It is
apparent from physical considerations that as t — oo, the temperature u(x) for 0 x L will approach uox/L. But this is just another way of saying that u0x/L is the steadystate solution. This is the solution to the problem that can be stated as u"(x) = 0,
u(L) = u0.
u(O) = 0,
Thus the function 4(x) in (6.3—6) is the solution of the steadystate problem. When this solution is added to the transient solution, the result is the complete solution obtained in Exercise 8.
EXAMPLE 6.33 A cylindrical rod of length L is initially at temperature 1(x). Its left end is kept at temperature zero, while heat is transferred from the right end into the surroundings at temperature zero (Fig. 6.34). Find u(x, 1). Solution
Here the problem to be solved can be expressed as follows:
P.D.E.:
0 <x
0;
L,
= 0, = hu(L, I), 0 = f(x),
h
<x
> 0, f < L.
> 0•
Using separation of variables, we have
X_T_
xT_
hence
X(x) =
c1
cos Xx ÷ c2 sin Xx.
The first boundary condition implies that c1 = 0, whereas the second results in
tan XL =
(6.37)
— XJh.
Thus a solution can be written as u(x,
g)
=
c,,
exp (—
sin X,,x,
y
0
o
— —
u(.v. 0) = f(x)
Figure 6.34
0
0
(6.38)
258
Boundary Value Problems In Rectangular Coordinates
CHAP. 6
and if we apply the initial condition, this becomes
u(x, 0) =
sin XnX
f(x),
where the X,, are solutions of Eq. (6.3—7). Since the problem
X" + X2X = 0,
hX(L) + X' (L) =
X(0) = 0,
0,
(6.39)
is a regular Sturm—Liouville problem (Exercise 10), we know that to each eigenvalue there corresponds an eigenfunction sin Moreover, the eigenfunctions form an orthogonal set on [0, LI with weight function one. Finally, this orthogonal set is complete with respect to the class of piecewise smooth functions on [0, U. Thus we can represent such a functionf(x) by a series of the functions sin The coefficients in Eq. (6.3—8) are given by (Exercise 11)
cfl=
fis)
sin X,,s ds
L sin2 X.,s ds =
+ h2) fL jf(s)sinx,,sds. + h
(6.310)
We conclude this section by mentioning that the onedimensional Fermi* age equation for the diffusion of neutrons in a medium such as graphite Is Ô2q
0x2
r)
—
Oq(x, r)
—
or
Here q represents the number of neutrons that "slow down" (that is, fall below some given energy level) per second per unit volume. The Fermi age, r, is a measure of the energy loss. Key Words and Phrases heat conduct ion convection Newton's law of cooling ambient temperature nonhomogeneous boundary condition
steadystate solution transient solution diffusion of neutrons Fermi age
Enrico Fermi (1901—1954), Italian nuclear physicist, who supervised the construction of the firsi nuclear reactor.
259
The Diffusion EquatIon
SEC. 6.3
8.3 ExercIses •
1.
Show that a time scale change given by r = ki will transform the diffusion equatiOn (6.3—1) into
= V2u.
In Example 6.31, show that (a) choosing X = 0 leads to the trivial solution in X(x); (b) choosing + X2 for the separation constant leads to the trivial solution in X(x). 3. Find the eigenvalues and eigenfunctions of the SturmLiouvilie problem
2.
X" + 4.
5.
6. 7.
X2X = 0,
X'(O) =
0,
X(L) =
0.
Explain why there is no a0term in the solution to Example 6.3—1. Verify the solution to Example 6.3—I completely. Apply the method of separation of variables to the problem of Example 6.3—2, and show that the result is u(x, t) = 0. (Hint: Examine the problem in T(O.) Show that the solution of the problem in (6.36) is
= uox/L. Using the result in Exercise 7, solve the problem of Example 6.32. In Example 6.3—3, show that: (a) X = 0 leads to the trivial solution in X(x); (b) the separation constant + X2 leads to the trivial solution in X(x). (Hint: Show thatf(X) = tanh XL + (X /h) is zero for X = 0 but nowhere else by examining f'(X).) 10. Verify that the problem in (6.3—9) is a regular SturmLiouville problem. 11. Obtain the coefficients c,, in Eq. (6.310). (Hint: After integrating, use Eq. (6.3—7) and cos to find sin •• 12. Solve the following problem: 8. 9.
P.D.E.: B.C.:
0 <x
0;
> o.
= 0,) 0) = f(x),
u(O,t)
L,
0 <x
o.
u,=uxx+C,
this equation under the assumptions that the edges x = 0 and x L of the slab are kept at temperature zero, the faces of the slab are insulated, and the initial temperature distribution is f(x). (1lint: Make the following change of variable: u(x, 1) = U(x, 1) + In Exercise 15, put f(x) = 0, and obtain the solution. (Note: This problem is a Solve
16.
simplification of one that occurs in the manufacture of plywood, where heat is supplied by means of highfrequency heating.) 17. Solve the following problem: P.D.E.:
u, =
0
<x < 2,
t > 0;
1) = 0,
B.C.:
u(2,t) =0, I.C.: 18.
0 <x
0,
u(x, 0) = ax,
2.
Solve the following problem:
P.D.E.: B.C.:
u, = 0 u(0, t) = 0,1 )
u41, 1) = 0,, I.C.:
u(x, 0) =
UoX,
<x < I,
I
> 0;
1>0; Uo > 0,
0 < X < I.
x = a, y = 0, and y = b of a semiinfinite, solid, rectangular parallelepiped are kept at temperature zero, and there is an initial temperature distribution on the bottom face given by f(x, y). Find the temperature in the interior at any time 1. (Hint: Compare Example 6.11.)
19.
The faces x = 0,
20.
A rod one unit in length is perfectly insulated along its length so that heat conduction can take place in only the xdirection. The left end is kept at temperature zero, and the right end is insulated. If the temperature is given initially by the function ax2 (a is a positive constant), find the temperature in the rod at any time I. (a) Solve the following problem:
21.
P.D.E.: B.C.: I.C.:
u, =
0
<x < w,
I) = 1) = 0, u(x,0) =S1n2x,
I > 0; 1 > 0;
The Diffusion Equation
SEC. 6.3
(b) 22.
23.
261
Verify the solution to part (a) completely.
A rod ,r units long is encased in an insulating blanket except for the two ends, which are kept at zero. If the initial temperature distribution is given by x sin x, find the temperature at any point in the rod at any time 1. If f(x) in Example 6.3—I is defined as I. Osx 0;
SEC. 6.4
265
Fourier and Laplace Transform Methods
U0
Figure 6.42
Solution It is appropriate to use the Fourier sine transform to transform because 0 < x < oo and u(0, t) is known. Thus (refer to Eq. 5.27) dü(cx, t)
= auo — a2U(a, 1),
and this firstorder, nonhomogeneous, ordinary differential equation has the solution
ü(a, t) =
a
[1 — exp (— a
using the initial condition ü(cx, 0) = 0 (Exercise 2). The inverse Fourier sine
transform of
1) is
u(x, 1) = .n.
JO
[1 — exp (— a2!)) sin
dcx ax —. cx
But from Exercise 14 in Section 5.1, sin ax dcx =
a
jO
2
if x > 0.
Hence
u(x, t) = Uo —
jO %
exp (—a2!) sin ax
and using the result sin ax
a
=
Ix0
cos as ds,
da a
266
Boundary Value Problems in Rectangular Coordinates
CHAP. 6
we have
u(x, f) =
—
The
jexp(_a21)da
uo —
2u0 fx
—
fo.
ds
cxsds
cos
exp (— a 2 I) cos
as da.
a integral appears in tables of definite integrals; hence u(x,
exp (—s2/4t)
U0
1) = Uo —
ds
3°
Now the substitution v2 = s2/4( transforms the last result into (Exercise 3)
u(x,I) =
2u0 fr,/..,
u0 —
exp (— v2) dv
vir .0
(6.42)
= u0 — = 14o[l —
= u0 erfc
(ti)'
using the definition of erfc, the complementary error function:
erfcx = where
1
—
erfx
=
2
fo
es ds,
3
the error function, erf x, is defined by 2 tx erfx=—i
U
An interesting observation can be drawn from the form of the solution in Eq. (6.42). A change in the boundary temperature u0 is instantly transmitted to any other point on the xaxis. This implies that heat is propagated with an infinite velocity, which at first seems paradoxical. Recall that in Sec
tion 3.4, where we derived the diffusion equation, we used an equilibrium concept. Accordingly, u(x, 1) has meaning only if we assume that the system (rod, plate, etc.) is essentially in equilibrium for all t.On the other hand, conduction
of heat is a result of randomly moving molecules transferring their kinetic energy as a result of collisions. Since the time scale of the latter motion is so different from that needed to reach an equilibrium temperature, we can assume that changes in temperature are propagated with infinite speed.
EXAMPLE 6.4—2(a) We solve the problem of Example 6.42 again, this time using the Laplace transform. Recall the definition* of the Laplace —
real part.
the most general case, s may be a complex number with some restriction placed on its
267
FourIer and Laplace Translorm Methods
SEC. 6.4
transform of u(i),
s>O.
U(s) =
Hence, using the fact that u(x, 0) = 0,
e"
e" u(x, t) dl
+s
u(x, 1)
—
= sU(x, s),
so that the partial differential equation d2U(x, s) —
dx2
= sU(x,
becomes
s) =
0
with U(0, s) =
u0 dt =
Now the solution of this secondorder, homogeneous, ordinary differential equation is
U(x, s)
c,(s)
e
We take c1 (s) to be zero so that U(x, s) will remain bounded for x > 0, and applying the condition U(0, s) = uo/s, we have (Exercise 4) U(x, s)
e
(6.43)
Using the table of Laplace transforms in Table II of the Appendix, we find u(x, I) = u0 erfc (x12../i) as
before.
The last example illustrates the effect produced by a nonhomogeneous boundary condition. Such a condition resulted in a nonhomogeneous differential equation in the transformed variable. In Section 6.3 we presented another method for dealing with a nonhomogeneous boundary condition. (See Example 6.32.) The following example shows how easily the Laplace transform can handle some nonhomogeneous boundary conditions.
EXAMPLE 6.43 Solve the following problem using the Laplace transform (Fig. 6.43).
Boundary Value Problems in Rectangular CoordInates
CHAP. 6
a
0 a
Figure 6.43
P.D.E.: B.C.:
0 <x < d,
u, = u(0, 1) =
I
u(d, I) = 1.C.:
t > 0;
> 0; 1W \
u(x,0) = a +
0 <x < d,
b
and the boundary conditions results in the problem d2U(x, s) dx2
— sU(x,s) = —a
—
U(d,s) =
U(0, s) =
This is an ordinary differential equation with complementary solution (see Section 1.2) =
+
A particular integral, —
—
a + —
bd2 d2s ÷
sin
(dx),
can be found by the method of undetermined coefficients (see Section 1.2). The sum of s) and s) is the general solution, and evaluating c1 (s) and
269
FourIer and Laplace Transform Methods
SEC. 6.4
of the conditions U(0, s) = U(d, s) = als, we have
c2(s) with the aid
U(x,
s) =
a
+
bd2 d2s +
.
2sIn(dx).
In obtaining the inverse of this we note that sin (irx/d) can be treated as a constant. Thus u(x,
t) = a
(6.44)
+
The details are left for the exercises. (See Exercise 5.)
•
EXAMPLE 6.44 Solve the following problem using the Laplace transform.
P.D.E.:
=
0
B.C.:
u(0, I) = u(c,t) =0,5
I.C.:
u(x,0) = b
<x
0;
I
>
/lr\ (1rx),
sin
Solution Transforming the equation and the boundary conditions yields
d2U(x,s) dx2
—
= s2U(x,s) — bssin(_x)÷
.
.
bsin
(_x).
U(0, s) = U(c, s) = 0,
which has the solution (Exercise 7), U(x,
s)
c2b(s—l) =
+
.
sin
(ix).
Hence u(x,
I) =
b sin(!x)[cos
—
(1!!)].
•
(6.45)
In the next example we simplify the conditions in Example 6.43 and show that, in spite of this, the problem is seemingly intractable by the method of Laplace transformation.
EXAMPLE 6.45 (Fig. 6.44).
Solve the following problem using the Laplace transform
270
Boundary Value Problems In Rectangular Coordinates
I
CHAP. 6
I
Ill =
1
0
B.C.:
LC.:
u(0, 1) =
0;
/
u(1, t) = 1,f
>
0) =
0 <x
0,
=
B.C.: I.C.:
= h(t), u(x,
Solution We may use the Fourier
0< x
> 0; 0.
cosine transform to
transform x because
given. Then I)
u(x, t)
is transformed into — h(t) and problem becomes
du(a,
x>
= 0,
0)
I
t)
—
cos
ax dx,
a2ü (see Eq. 5.2—9). Thus the transformed
+ a u(cr, 1) = 2
is a firstorder linear differential equation. Multiplying by the in
tegrating faclort exp (a2!) produces
u(a, I) =
— exp (—
a2!)
exp (&s) h(s) ds + C].
ssee Chapters 3 and 10 of the author's Advanced Engineering Mathematics Mass.: AddisonWesley, 1982.) tSee Section 1.3 of the author's Advanced Engineering Mathe,natics (Reading, Mass.: AddisonWesley. 1982).
CHAP. 6
Boundary Value Problems in Rectangular Coordinates
272
and the condition u(a, 0) = 0
shows that C =
u(a, 1) = — exp =
0.
Hence (Exercise ii)
exp (a 2s) h(s) ds
(— a2!)
exp [a2(s — t)Jh(s) ds,
—
(6.4—6)
and
u(x, t) =
=— — —
—
exp [a2(s — t))li(s) ds
cos czx da
—
h(s) ds
(i h(s) exp
1
exp 1a2(s — I—
x2/4(t
—
1)]
cos cxx
dcx
s)]ds
assuming that the order of integration may be interchanged.
(6 4—7)
•
Up to this point, most of the solutions that we have obtained have been formal solutions in the sense that they have been obtained computationally. Since some of these formal solutions are phrased in terms of infinite series or improper integrals, it remains to verify their validity. This topic is discussed in the next section.
Key Words and Phrases integrating factor formal solution
complementary error function (erfc x)
error function (erf x) Laplace transform
6.4 Exercises •
1.
Solve the following twopoint boundaryvalue problem (See Example 6.41 .): d2V(x, a) dx2

— a2v(x, a) = 0,
a)
—
v(0, a) = 0, 2.
dx
=

Solve the following problem:
dü(a, 1) — + cr2u(a, 1) = auo, di
Ü(a, 0) = 0.
273
FourIer and Laplace Transform Methods
SEC. 6.4
(Hint: Use the fact that the given equation is linear and hence multiplying by the integrating factor exp (&t) leads to a form that can be easily integrated. Alternatively, the method of undetermined coefficients may be used to obtain a particular solution.) 3. Obtain Eq. (6.42) from the previous step in the text. 4. Verify that Eq. (6.4—3) in the text is the correct solution of the given problem. 5. Given that
d2U(x,s)
7
— sU(x,s) = —a
U(O, s) = U(d, s) = (a) (b) (c)
s). Obtain the complementary solution Obtain a particular integral by the method of undetermined coefficients. Obtain the complete solution
U(x, s) =
/ir\ \d/
a bd2 . + sin ( —xI. s d2s+72
Find the inverse Laplace transform of the function U(x, s) that was found in part (c). Verify completely the solution in Eq. (6.44). Solve the following twopoint boundaryvalue problem:
(d)
6. 7.
s2U(x,s) = b(l — s)
s) = 0.
(Compare Example 6.44.) 8. 9. 10.
Obtain the inverse Laplace transform of the function U(x,
Example 6.44. Solve the twopoint boundaryvalue problem in Example 6.45 for U(x, s). In the problem of Example 6.4—5, make the substitution u(x, 1) = U(x,
•.
1)
s) of
+ 4(x).
Then solve the problem by the method of separation of variables. II. Obtain Eq. (6.4—6) from the given firstorder linear differential equation. 12. Verify that the result in Eq. (6.47) follows from Eq. (6.4—6). Solve Example 6.4I given that 1(y) = 13 14. (a) Solve the following problem using a Fourier transform (Fig. 6.46):
P.D.E.: B.C.:
l.C.: (b)
=
uAO, 1) = Uo, u(x, 0) = 0,
interpret this problem physically.
x>
0,
1
I > 0;
x>
0.
> 0;
274
CHAP. 6
Boundary Value Problems In Rectangular Coordinates
Figure 6.46 15.
Solve Exercise 14 using the Laplace transform.
16.
(a)
Obtain the bounded harmonic function v(x, y) over the semiinfinite strip o < x < c, y > 0, that satisfies the following conditions: (I)
17.
v,(x, 0) = 0
.v) = f(y).
Obtain the bounded harmonic function v(x, y) over the semiinfinite strip o 0, that satisfies the following conditions: 0) = 0
(ii)
y) = 0
(iii) v(x, b)
f(x).
(b)
Interpret this problem physically.
(a) (b)
Graphf(x) = exp(—x2). Graph f(x) = erf x. (Hint: Values of erf x can be found in tables.) Graphf(x) = erfcx.
Graph u(x, t) = uo erfc (x/2..Jj) for various fixed values of 1; take u0 = convenience. Solve the following problem: B.C.:
I.C.:
21.
v,Ac,
(a)
x > 0,
P.D.E.:
20.
(iii)
Interpret this problem physically.
(c) (d)
19.
(ii)
(b)
(i)
18.
v(O, y) = 0
1
I
for
> 0;
= h(t), t > 0; u(x, 0) = 0, x > 0. u(0, I)
(Hint: Pattern your solution after Example 6.46.) In the result of Exercise 19, replace h(t) by u0, a constant, and then compare your answer with that for Example 6.42. Show that 0
a>0.
*22.
(a)
Use the result in (6.42) to compute each of the following:
u(l, (b)
23.
u(l,
u(l, 9).
u(I, 4),
I),
Show that the derivatives of the error function erf x are given by the following.
erfx =
(b) d2 —erfx dx2 24.
1/4),
Graph the results obtained in part (a).
(a)
•.e
275
Verification of Solutions
SEC. 6.5
(—x2) 4
—
—xexp(—x2)
Solve the following problem by using the Laplace transform:
P.D.E.:
U,, =
+ sin
I) = 0,
B.C.:
u(0,
1.C.:
u(x, 0)
0,
wi,
0
u(c, t) = 0, u,(x,
0)
0,
<x
0; 0< x
0;
c.
25.
Explain the difficulties encountered when attempting to solve the problem of Example 6.46 by using the Laplace transform.
26. 27.
Verify the solution to Example 6.4—6 completely. Using the value u(l, 1) in Exercise 22, find the lime required for the temperature to
28.
reach onehalf this value at x = 1. Read the article "Random Walks and Their Applications," by George H. Weiss, Amer. Scienlisi 71, No. 1, pp. 65—70. Comment on how the article ties in with the
29.
solution of Example 6.42. Show that the solution to the problem in Example 6.42 can be written as u(x, I) = where 0 1, thus showing the maximum and minimum values of the result.
30.
6.5
Verify the solution to Exercise 14(a) completely.
VERIFICATION OF SOLUTIONS
In all but a few cases the solutions of our boundaryvalue problems in the
previous sections were obtained by using separation of variables (the Fourier method) or by using an integral transform method. The steps leading to a solution were often numerous and somewhat involved. As a result we were usually content with the solution if it satisfied the given boundary and initial conditions and if it seemed reasonable from physical considerations. Occasionally, there was an exercise in which a calculation and graph had to be made, and these helped to give a feeling of confidence in the solution. In this section we discuss how a specific solution can be completely verified. To do this, we must show that the solution satisfies the given partial differential equation identically. This is not a trivial matter in case the solution
Boundary Value Problems in Rectangular Coordinates
276
CHAP. 6
in the form of an infinite series or an improper integral. The differentiation of a series term by term and the interchange of differentiation and integration require that certain conditions be satisfied. It would be advisable at this point to review Sections 1.6, 2.5, and 4.5. We give an example of the verification of a solution using one of the first solutions we obtained. is
Given the problem of Example 3.41, namely,
EXAMPLE 6.51
P.D.E.:
u, =
B.C.: l.C.:
u(O,
0
<x < L,
t > 0;
1 > 0; I) = u(L, 1) 0, 0 <x < L, u(x, 0) = f(x),
verify the solution u(x, 1) =
b,, Sifl
air L
/
X
kn2ir2\
L21)'
(6.51)
where
2fL f(s) sin flT ds. 30 .
L Solution
It is a simple matter to verify the boundary conditions. We need
only observe that the b,, are bounded (see Theorem 2.5—1) and so is the function exp (— kn2ir2t/L2). The initial condition is satisfied, since we assume that f(x) is piecewise smooth and has a valid Fourier sine series representation. Now consider the partial derivative
u, =
kir2
.
sin
— ,i
—
air
x exp
/
_ht
I
We have
Mk
exp(_
and for all such that 0 < lo < where Mis the maximum value of By the ratio test the last series of positive constants is convergent; hence the
series defining u, is uniformly convergent by the Weierstrass Mtest. In a and are defined by uniformly convergent similar manner (Exercise 3), series for all given values of the variables. Accordingly, term by term differentiation of (6.5—I) is valid by Theorem 1.62, and we have = — L2
so that
=
is
verified.
b,,n sin
S
air L
X
/
kn2 it2
V
277
Veilfication of Solutions
SEC. 6.5
In the next example we consider a solution that is expressed in the form of an improper integral.
EXAMPLE 6.52 Given the problem of Example 5.21, namely,
P.D.E.: I.C.: verify
the
=
<x
—
U(x, 0) =
f(x),
—
1>
0;
<x
0;
L,
the solution
u(x, I) =
14.
I
sin
f(s)
exp (— kn2ir2t/L2)
sin
ds.
Under what conditions is the problem wellposed?
The case of an infinite string acted upon by an external force and subject to initial conditions leads to the following problem.
P.D.E.:
U,, =
I.C.:
u(x,
0)
—00 <x
0;
— cc <x
0;
is
Boundary Value Problems In Rectangular Coordinates
286 (b)
Verify the solution.
(C)
Compute u(l, I).
(d)
Determine whether or not the problem is wellposed.
CHAP. 6
REFERENCES Carrier, G. F., and C. E. Pearson, Partial Differential Equations: Theory and Practice. New York: Academic Press, 1976.
Churchill, R. V., and J. W. Brown, Fourier Series and Boundary Value Problems, 3d ed. New York: McGrawHill, 1978.
Copson, E. 1., Partial Djfferential Equations. Cambridge: Cambridge University Press, 1975.
Dennemeyer, Rene, Introduction to Partial Differential Equations and Boundary Value
Problems. New York: McGraw.Hill, 1968.
Friedman, Avner, Partial Differential Equations of Parabolic Type. Englewood Cliffs, N. J.: PrenticeHall, 1964. Sagan, Hans, Boundary and Eigen value Problems in Mathematical Physics. New York: John Wiley, 1961. Tychonov, A. N., and A. A. Samarski, Partial Differential Equations of Mathematical Physics, Vol. I. San Francisco: HoldenDay, 1964. Weinberger, H. F., A First Course in Partial Differential Equations with Complex Variables and Transform Methods. Waltham, Mass.: Blaisdell, 1965. Williams, W. E., Partial Differential Equations. Oxford: Clarendon Press, 1980. Zachmanoglou, E. C., and D. W. Thoe, Introduction to Partial Djfferential Equations with Applications. Baltimore: Williams and Wilkins, 1976.
Boundary•Value Problems in Other Coordinate Systems
7.1 POLAR COORDINATES a region has circular symmetry, there is usually an advantage in using polar coordinates. The relationship between rectangular and polar coordinates is shown in Fig. 7.1I and the equations accompanying the figure. From these relations we can compute the partial derivatives: Whenever
lip lix
=
lip
—p sin 4),
8y
=
=p
COS 4).
x = p cos y = p sin x2 arctan
Figure 7.11 Polar Coordinates. 287
=
Boundary Value Problems in Other Coordinate Systems
288
CHAP. 7
If u(x, y) is a twicedifferentiable function of x and y, then by the chain rule,
auayau cos 4,
au_auax
+ — sin 8)'
4,.
(7.1—1)
Hence 82u
a
— —

a
/ au \
au
COS 4) +
fau\
a
/au
a
u—) cos 4, +
/ ôu
a + — ( — I sin 4, +
(COS
(sin 4,)
ap
sin 4,,
since the other two terms are zero.
In order to evaluate a term like 8/op (ôu/ôx) we observe that Eq. (7.11) applies not only to u(x, y) but to any differentiable function of x andy. We can, in fact, write Eq. (7.1—1) symbolically as —
ap
4, +
sin 4,.
Ox
—
Thus
—
cos 4, ÷
=
sin
u
cos 4, ÷
4,
sin2 4,,
assuming that which is the case for the functions with which we will = be dealing. In a similar manner we find I
02u
=
sin 4, cos 4, + u1,,,
sin2 4, —
—
p
cos2 4,
p
and since
Iäu — = — u. cos 4, p pap
+ — u,, sin p
ô2u
t92u
1
—
1
4,,
we have i
1
t9u
a2u
(7.12)
289
Polar Coordinates
SEC. 7.1
In Eq. (7.12) we have the Laplacian in two dimensions in both polar and rectangular coordinates. If u is independent of 4), then we have the simpler result ôu 8X
For
8p
8y
8
P 8P
P '9P
/ ôu\ \
(7.13)
ÔP/
Observe that Eqs. (7.1—2) and (7.1—3) must be dimensionally correct. = = T/L2. example,* if [uJ = T and (xJ = fyi = L, then
Hence each term in the polar coordinate versions of the Laplacian must also have the same dimension. Recalling that angles are expressed in dimensionless radians will now help us to remember Eq. (7.12). EXAMPLE 7.11 Find the steadystate, bounded temperatures in a circular metallic disk of radius c if the temperatures on the edge are given byfl4)). See Fig. 7.12. Solution We first observe that f(4)) is assumed to be a piecewise smooth function. We also note that u(p, — ir) = u(p, and u,(p, — 7r) = u,(p, ir), these restrictions being necessary so that the temperatures will be uniquely determined. Then we have the following problem:
P.D.E.: B.C.:
18
(pus) +
u(c, 4)) = f(4)),
1
= 0,
0 < p < c,
—
< 4)
7r;
— ir < 4) ir.
It appears that we do not have enough boundary conditions to solve the prob
lem, but the fact that the temperatures must be bounded will provide additional information. We use the method of separation of variables and assume
Figure 7.12 Temperatures in a disk. *The square bracket is read "has the dimension of." Standard usage gives T(temperature), I (time). L (length), rn (mass), etc.
Boundary Value Problems in Other Coordinate Systems
290
CHAP. 7
we can write
u(p, 4)) = R(p) 4'(4)). Then
/
4'd
dR\
pdp\If'dp,
Rd24' p2
dçb
or dividing by R4'/p2, we have
pd / dR\
1d24'
2
n=0,l,2
Choosing the separation constant as we have will insure that 4' [and u(p,
4))]
will be periodic of period 2w in 4). This choice is dictated by the physical nature
of the problem. Thus the equations =
+ have solutions (Exercise 1)
a,, cos n4) + b,, sin n4). The second ordinary differential equation can be written as
+p
d
— n2R,, = 0.
(7.14)
We first take the case ii = 0 and solve the resulting equation by reduction of order* to obtain (Exercise 2) Ro(p) =
log p
+ C2.
In order that this solution remain bounded in the neighborhood of p = 0 we
must take c1 = 0. Hence the solution corresponding to n = 0 is a constant that we may take to be unity. Equations (7.1—4) are CauchyEuler equations (see Section 1.3) whose solutions are (Exercise 3) R,,(p) = A,,p" + B,,p",
and we must have B,, = 0 so that R,,(p) [and u(p, 4))] will remain bounded at p = e > 0, that is, in the neighborhood of p = 0. Without loss of generality we can also take A,, = 1. Then
u,(p, 4)) =
cos n4) +
sin n4))p"
*Let v, = dR,,/da, divide the result by a, and obtain a firstorder differential equation that can be integrated, since it is the derivative of a product.
291
Polar Coordinates
SEC. 7.1
bounded functions that satisfy the given partial differential equation. To satisfy the boundary condition, we take are
u(p,
=
(a,, cos n4 + b,, sin ngb)p"
+
(7.1—5)
and leave it as an exercise (Exercise 4) to show that the solution to the problem
is given by Eq. (7.15) with the constants a,, and Li,, defined as follows:
a,, =
n = 0, 1, 2,
f(s) cos ns ds,
.
(7.16) b,, =
n = 1,
f(s) sin ns ds,
2
is being represented by a Fourier series, this function must satisfy the conditions necessary for such representation (see Section Since the function 4.5).
U
We observe that p = 0 is a regular singular point of the CauchyEuler equations (7.1—4). Hence a natural question that might be asked is, "What is the value of the solution in Example 7.1—1 when p = 0 and is this result reasonable?" From Eq. (7.15) we have
urn u(p, since the coefficients
=
and b,, are bounded. But we also have from Eq. (7.16)
ft jf()
1
1
= 2
which is the mean value of the function f on the boundary p = c. In other words, the value of the harmonic function at the center of the circle is the average or mean of its values on the circumference. We can confirm this result in another way and, at the same time, obtain a form more suitable for verification of the solution. If we substitute the coefficients and b,, as given by Eqs. (7.1—6) into Eq. (7.1—5), we have (Exercise 5)
u(p,
1
f(s)
= .
Now let (p/c) = r, 4
r"
—
1
+
cos
—
s)] ds.
s = 0, and consider
cos nO =
ii = 2 [i
+
1
—
re'
1
1
+ 1
—
—
(7.17)
292
CHAP.?
Boundary Value Problems In Other Coordinate Systems
1, which is the case here. With some algebraic manipulation (Exercise 6) the last expression can be written as
provided that r exp (± /0)1
1,2,3, 0,
a = 0, 1,2, Coefficients:
A1 =
—
dx,
2÷
j Source of X3:
Coefficients:
= 1, 2, 3,
= 0
A1 = A
xf(x) dx xf(x)J0(X,c) dx,
=
j = 2, 3,4,
EXAMPLE 7.21 Evaluate dx.
Solution We use integration by parts with u = dx = x3J,(x)
—
x2
2
and dv = x2J1(x) dx,
after observing that
dx =
sJ0(s)
ds = xJ,(x),
using Eq. (7.210). Now, applying Eq. (7.29), we have
x2J,(x) dx =
x2J2(x).
xJ0(x) dx. Thus
309
Cylindrical Coordinates; Bessel Functions
SEC. 7.2
Hence x3J0(x) dx = x3J1(x) — 2x2J2(x) — 2)2(1),
=
a result that can be reduced. From Exercise 4(e) we have +
Jfl(X) =
1(x),
while from Exercise 17(a) we obtain J,(x) —
= —J,,,. 1(x).
Subtracting this last equation from the previous one produces 2,i
+ J,,,1(x).
J,,(x) =
Equation (7.223) with n =
and x =
2
1
J2(l) =
(7.2—23)
can now be used to write —
so that x3J0(x) dx =
U
= 0.210.
—
EXAMPLE 7.2—2 Obtain the FourierBessel series representation of J(x) = I in terms of Jo(X1x) on the interval 0 < x < 1, where the X are such = O,j = 1,2 that Solution
From Eq. (7.219) we have for n = 0, c = J2(x)
and
xJo(X1x) dx,
by making the substitution s = 2
= using
X1x,
Ix,
j
= 1,
= 1, 2,
.
.
this becomes ds
2
Eq. (7.210). Hence we have
f(x)
= 1—2
(7.224)
We leave it for an exercise to show that (7.224) is valid for x = 0 (see Exercise 27). Observe, however, that f(1) = 0 and that for x near zero the
CHAP. 7
Boundary Value Problems In Other Coordinate Systems
310
converges very slowly. In Fig. 7.22 we show the result of adding the first ten terms of the representation in (7.2—24). series
Bessel Functions of the Second Kind We conclude this section with a brief reference to the Bessel function of the second kind of order n. It is a second linearly independent solution of Bessel's differential equation, which can be obtained by the method of variation of parameters. * The computation will be omitted, and we give details only of Y0(x) and graphs of this function as well as Y1(x) and Y2(x) in Fig. 7.23. The Bessel function of the second kind of order zero is given by t
Yo(x) =
+
+
(ç
+
—
+— (7.2—25)
is called Euler's constant. It is an irrational number defined
where the term by
— log
n)
0.577215.
I
1(x)
Figure 7.22 A representation by a FourierBessel series.
See Edgar A. Kraut, Fundamentals of Mathematical Physics (New York: McGrawHill, 1967), pp. 264 if.
tSome authors call this the Neumann function of order zero, while others call it Weber's Bessel function of the second kind of order zero.
CylindrIcal Coordinates; Bessel Functions
SEC. 7.2
311
Y (x)
0.5
Y1(x)
0,4
('\...y2(x)

,,'
.i\ 4
/
/
—0.3 
1i
'0.4—0.5
:
—0.6
0.7
5
\.../—
/
S
Bessel functions Y0(x),
—0.8
Y1(x), and
Y2(x) on (0, 14l
—0.9
—1.0 — 1.1
S
:
Figure 7.23
Of importance in our future work is the fact that all Bessel functions of the second kind contain the term log (x/2). Consequently, Y,,(O) is undefined,
as Fig. 7.2—3 indicates. In view of the fact that the applications involving Bessel functions in this text are such that x > 0, we will not be using Bessel functions of the second kind. It should be noted, however, that the latter are required in certain instances — for example, in solving problems involving electromagnetic waves in coaxial cables.
In connection with Bessel functions we should also mention the Hankel This integral transform pair is defined as follows:
( X) =
1(p)
=
x;'
=
r f(p)J,,(Xp)
p dp, (7.226)
F,,(X)J,,(Xp) X dX.
This transform arises naturally in connection with the Laplacian in cylindrical coordinates. The Hankel transform may lead to significant simplification in problems involving Bessel's equation. *After Hermann Hankel (l839—1873), a German mathematician.
Boundary Value Problems In Other Coordinate Systems
312
CHAP. 7
Key Words and Phrases function of the first and second kind of order n cylindrical harmonics orthogonality relation
Fourier—Bessel series
Bessel
square of the norm norm Hankel transform
7.2 Exercises •
1.
Obtain Eq. (7.2—1) from Eq. (7.1—2).
2.
By making the substitutions y = R and x = Xp, show that Eq. (7.24) can be reduced to Eq. (1.56). Use the ratio test to show that the series (7.2—8) representing Bessel's function of the first kind of order n converges for all x. Use Eq. (7.2—8) to prove each of the following:
3. 4.
(a)
0
(b)
= 0
(c)
= —J1(x) = —J3(x)
(d)
=
(e)
[xV,,(x)J = x"J,,_,(x),
(f)
•.
n =
—
that x =
n =
1,
1,
2,
2,
is a regular singular point of Bessel's differential equation
5.
Verify
6.
(7.2—Il). (Hint: See Section 1.5.) Obtain Eq. (7.2—23).
7.
Obtain the general solution of each of the following differential equations by
0
inspection:
d /
dy\
(a)
(b) 4xy"+4y'+y=O y?
(c)
8.
If
= 0,
= 0
(C)
es.)
then obtain each of the following:
(a)
(b)
(Hint: Let u =
= J1(s)ds =
= 0
9.
10.
313
CylindrIcal Coordinates; Bessel Functions
SEC. 7.2
Obtain each of the following: (a)
Jo(s)Ji(s) ds =
(b)
s2J0(s)Ji(s) ds =
—
Expand each of the following functions in a Fourier—Bessel series of functions J0(X3x) on the interval 0 < x < c, where Jo(X1c) = 0. (Note: The coefficients are given by Eq. (7.2—19), but the integral need not be evaluated in all cases.) (a)
f(x) =
I
(b)
1(x) =
x2
(Note: Use the following reduction formula: + (a — l)x" '.Jo(x)
s"Jo(s) ds =
— (a — 1)2
(c)
1(x) =
ds,
a = 2, 3
)
for0<x 0.
Obtain the relation
l'(nsI)=nl, (c)
i' > 0.
'exp (—1) di,
r(p + 1) (b)
(7.227)
n=0,l,2
Show that
I'(l/2) =
CHAP. 7
Boundary Value Problems In Other Coordinate Systems
318
r(v)
V
Figure 7.26 The gamma function.
31.
Obtain
the following approximation for small values of x (x — 0): J1(x)
32.
±
Obtain the following approximation for large values of x (x — 00):
2
1 J1(x)=—=cosix
\
33.
(a)
(b)
4 —)
Prove that between consecutive positive zeros of zero of
there
is at least one
Prove that between consecutive positive zeros of J,,(x) there is at least one
of Prove that the zeros of J,(x)
zero (c)
and J,,+1(x) separate
each other.
73 SPHERICAL COORDINATES; LEG ENDRE POLYNOMIALS
Spherical coordinates (r, 8) may be defined as shown in Fig. 7.31. We have r 0,0< < 27rand0 0 ir.Aword of caution is inorderhere. Some authors use p instead of r, some interchange and 0, and some follow both
practices. it is essential, therefore, to note a particular author's definition. in cylindrical coordinates (p. z) the Laplacian is ô2u
18
V2u = — + — 8p2
+
The relation between rectangular and spherical
(7.31)
coordinates is given by
SEC. 7.3
Spherical Coordinates; Legendre Polynomials
x = r sin 0 cos
r sin 0 sin &
y
z = r cos 0,
and we could obtain the Laplacian in spherical coordinates from these. It is a bit simpler and more instructive, however, to begin with Eq. (7.3—1) and evaluate the four terms of that sum in spherical coordinates. If we hold fixed, then u is a function of p and z, and by virtue of
z = r cos 0,
p= r
sin 8,
u is a function of r and 0. Thus we have by the chain rule Ou
—
8p
Ou Or
+ OuOO
OrOp
808p
POU+ z 3u ri3r r2 00
—
(7.32)
In obtaining Eq. (7.3—2) we have used the relations z2 +
p2
=
r2
and
p/z = tan 0 to find Or/Op and OO/Op. Note that z is held constant when differentiating r and 0 partially with respect to p. Then 02u
8
0p2 — Op
(pOu÷ z \r Or
Ou'\
r2 aol'
and we use Eq. (7.3—2), since it serves as a formula for differentiating any func
tion of r and 0. Symbolically,
8( )8( )p+ Op
—
Or
r
8( ) z 88 r2
y
Figure 7.31 Spherical coordinatee.
Boundary Value Problems in Other Coordinate Systems
320
CHAP.?
Hence
+
+
p
—
+
p2 82u
—
+
— r2 8r2
(_ ! \ r2r
÷ UrP
82uz\
Z(82UP + r2
+
z
82u
+
(2p
+
1 ôu 2p 82u + r ôr r3 ôr80
p2 8u
+
r3 ör
z2 82u r4 802
2pz 8u
—
r4
In a similar manner we can calculate i32u/8z2. We have
ôr 8z
8z
80 ôz — 8r
— 8z \ r a,! I au
—
2
\_
I 8u — r 8r
—
p r2
z (82u z
1\z
(
i9u
—
\
8z \ r2
8u (
—
80
8 fpdu
82u_8 fzau\ ôz
r
\z
p[492U z
82u (
r3 8r
z2 82u
+
p
802
—
z1 8u
p 82u
2pz 82u
—
r' 8r80
r2 8r2
+
p2 82u 2pz ôu + r4 80 r4 802
Hence
+
—
8u(r2
—
—
1 ôu
—
r 0r
— p2\
z2 +
—
ô2u
/ I
+
82u(z2 + p2 82u(Z2 + p2\ + 8r2 \ r2 k J
82u
+ 8r2 + r2802
Finally, adding the equivalent of the terms
18u
an d
I
e32u
we have —
82u
2 ôu
1
82u
1
82u
cot 0 ôu
(7.33)
321
Spherical Coordinates; Legendre Polynomials
SEC. 7.3
which is the Laplacian in spherical coordinates. It corresponds to Eq. (7.3—1)
in cylindrical coordinates and to V2u =
82u
ô2u
+ —i + —iax ay az
in rectangular coordinates. We point out as in Section 7.2 that Eq. (7.3—3) must be dimensionally = T/L2 in a heat conduction problem, each of the adcorrect. Thus since dends must have the same dimension.
Solution of Laplace's Equation In Spherical Coordinates Laplace's equation (also called the potential equation) in spherical coordinates can be written as 2 ôu
Vu= 2
82u
I
+
+ r
I
cot 0 ôu =0.
ô2u
+
An equivalent form of this equation is (Exercise 1)
/
8
ôu \
i
a
r2sinOôO
(.
8u \
82u
1
(7.34) We
seek a solution by the method of separation of variables. Assume that u(r,
0) =
and substitute into Eq. (7.34). Then 1
d
I
dR\
d/
I
de\
.
d24
1
=0.
Next, divide each term by R4'O/r2 sin2 0 to obtain
sin2 0 d I R Since
dr
dR
"I
dr ) +
sin 0 d /
.
the lefthand member is independent of 1
d2+
d
= m2,
0
\
I
dO)
d2cF
—
we have
m = 0, 1,2,.
.
(7.35)
. ,
the first separation constant m is chosen to be a nonnegative integer in order that the function 4) (and also u) be periodic of period in 4). This is often necessary from physical considerations, as we shall see later. Separating variables again produces where
1
d (2dR\_
R dr
dr / —
1
i
Le sin è
d (. dO
dO'\
m2
do / — sin2 oJ —
CHAP. 7
Boundary Value Problems in Other Coordinate Systems
322
where we have called the second separation constant X. At
this point, nothing
further is known about this quantity. Thus we have reduced Laplace's equation to the following three secondorder, linear, homogeneous ordinary differential equations:
(sin
o
(7.36)
= 0,
+
+
(x
d
—
=
XR = 0.
dr' dr'
(7.38)
Note that the first and third equations each contain one of the two separation
constants, while the second contains both constants. Products of solutions of these three equations are called spherical harmonics. Equations (7.3—6) have constant coefficients, so their solution presents no difficulty. They are
m = 0,
= Am cos
1, 2,.. .,
(7.39)
Am and B,,, are arbitrary constants that can be determined from given boundary conditions. Next we look at Eq. (7.3—8), which can be written in the equivalent form where
r2
dr
÷ 2r
—
dr
XR
0.
This is a Cauchy—Euler equation. It can be solved by making the substitution R= in which case the differential equation becomes r2k(k
— l)r"2 +
=0
—
or (k2
+ k — X)rk = 0.
Hence R = pk is a solution of Eq. (7.3—8) provided that k2 + k — X = 0. To
find a second, linearly independent solution may not be so simple. If we choose n(n + 1), and if we further (wisely) choose k = — (n + 1), k = n, then X then also X = n(n + I). Thus with X n(n + 1), Eq. (7.38) has the two linearly independent solutions and (Exercise 2), so the general solution can be written as R,,(r) =
+
(7.3—10)
In order to solve Eq. (7.3—7) we make the following substitutions: x = cos 0,
0(0) = y(x),
d
=
dxd
.
= —sin
d
323
SpherIcal Coordinates; Legendre Polynomials
SEC. 7.3
Then
dxde d I. 0—— 1. de\ —sin O—isin d— Isin 0—1= dOdx dx\ dot dO \ .
= sin
dl.
0
dy dy
=
With these substitutions, Eq. (7.3—7) becomes
[n(n+ l)_lmX2]y=o or, in equivalent form, (1 —
+ 1)
+
—
= 0.
— 1
(7.311)
Equation (7.3—11) is Legendre's associated differential equation. Its general solution, found by a series method, is Yn.m(X)
=
+ dnmQnm(X),
P'(x) and
are called associated Legendre functions of the first and second kind, respectively. The use of subscripts and superscripts indicates that these functions depend on m and n as well as on the argument x. The arwhere
bitrary constants Cnm and dnm depend on m and n as well. If m = 0, then Eq. (7.3—li) becomes (1 —
+ n(n + l)y =
—
0,
(7.3—12)
which is known as Legendre's differential equation. A particular solution is the Legendre polynomial of degree n, n = 0, 1, 2, . . . (see Example 1.5—6). Note that n must be a nonnegative integer in order to obtain a solution of Eq. (7.312) that is bounded on —1 x 1. A second linearly independent solution is Since has a singularity at x = ± 1 (as we will show later), it can be used only when
y=
x * 1 (0 * 0) and when x * — (0 * ir). 1
The case where u is independent of 4, implies m = 0 (see Eq. (7.39)). In this case Laplace's equation in spherical coordinates (7.3—4) reduces to
18 /ir2—i+ äu\ 8 1. öu\ 0, —— 8r 8ri r2 sin0 —isinO—i= 80, 80 \ 1 .
'.,
with solutions that are products of =
+
324
Boundary Value Problems in Other Coordinate Systems
and
E,,P11(cos 8) +
e,,(O)
0),
n=
0,
CHAP. 7
1, 2.
Admittedly, we have made a number of seemingly restrictive simplifying assumptions in order to get to this point in solving Laplace's equation in spherical coordinates. This was done not merely to simplify the mathematical aspects. We shall see in Section 7.4 that many of the applications will yield to our simplified approach, It should be kept in mind, however, that the nature of the separation constants m and X depends on the boundary conditions in any given case.
Legendre Polynomials In Example
1.5—6
we solved Legendre's differential equation (7.3—12) by the
method of Frobenius and obtained the particular solutions P,,(x), called Legendre polynomials. For reference we list the first few Legendre polynomials here:
P,(x) = x,
Po(x) = I, P3(x) =
— 3x),
P2(x) =
— 1),
P4(x) =
— 30x2 + 3).
Graphs of P2(x), P3(x), and P10(x) are shown in Fig. 7.32. Some properties of the Legendre polynomials that are useful in solving certain boundaryvalue problems are listed below. (See also Exercise 3.) (a)
P2,,+1(0)
= 0
(b)
P,,(1) =
I
(c)
PH(
(d)
P,,1(x) — = (n + l)P,,(x), xP,,(x) — P,,..1(x) = nP,,(x), n= P,+j(x) — P,_1(x) = (2n + l)P,,(x),
(e)
(f)
1)
(— 1
n= 1,
2,
1,
2,
.
.
3 •3
.
.
n=
1,
2,
.
Note that property (f) is the sum of properties (d) and (e). We can prove property (d) from the definition of the Legendre polynomials,
Pfl(x) =
k!(n—2k)!(nk)!
_________________________________
32S
Spherical Coordinates; Legendre Polynomials
SEC. 7.3
where
N = n/2 if a is even and N = (a — 1)/2 if a is odd. '
I
(
—
2k + 2)!
k!(n — 2k + 1)!(n
* =0
P,+1(x)
1)k(2fl
X
n—2k+I
1)
—
1
n2k
=
k
=0
1)k(2n — 2k)!(n — 2k) k!(n — 2k)!(n — k)!
=
— 2k + 2)(2n — 2k +
—
We have
=
* =0
1)k(2n
I
IX2n__2!
XII_21C
k!(n—2k)!(nk+iXn—k)! —
2k)!(n — 2k) n2k x
k!(n—2k)!(n—k)!
= (2n—2k+1
X k=O
=
Property (e) may be shown in a similar manner (Exercise 3).
Orthogonality of Legendre Polynomials
Now we show under what conditions the Legendre polynomials are orthogonal. This property of orthogonality is essential in solving boundaryvalue problems as we will see in the following section. We begin with the fact that the Legendre polynomials P,,(x) satisfy Legendre's differential equation, dx
((I —
+
n(n +
= 0,
a = 0, 1, 2
Multiplying this equation by Pm(X) and integrating from — —
+ n(n + 1) ç
1
to 1 results in
Pm(X)Pn(X)dX
0. (7.3—15)
Boundary Value Problems in Other Coordinate Systems
326
CHAP. 7
I) 0.9
0.8
Legendre Polynomials P2(x), P3(x), P10(x)
0.7
on 0, 1
.. .S .a
0.6 0.5
S
0.4
S S
0.3
a .
.
0.2
S a S
0.1
Figure 7.32 Legendre polynomials.
The first integral may be integrated by parts, putting U
du = dx, v = (I —
= Pm(x),
dv =
dx,
[(1 —
x2
=
(x)J dx
—
x2)

—
(1
dx.
—
The first term on the right vanishes at both limits by virtue of the term (1 — x2). Thus Eq. (7.3—15) reduces to (1 —
—
dx ÷
n(n +
1)
Pm(X)Pn(X) dx
0.
327
SpherIcal Coordinates; Legendre PolynomIals
SEC. 7.3
In this last equation, m and n have no special significance except that they are both nonnegative integers. Hence we may interchange m and n to obtain —
(1
+ m(m +
—
ç
1)
Pn(X)Pm(X)dX
0.
Subtracting this equation from the previous one yields (n — m)(n +
m
+
Pm(x)P,,(x)dx =
1)
Now supposethatn * m.Thenn — m * Oandn + m + (Why?) Hence we are left with the result
m*
Pm(X)Pn(X)dX = 0,
.11
1
0.
= Ois impossible.
(7.316)
n.
This shows that the set Pi(x), P2(x),
.
.
.
I
an orthogonal set on (— I, I] with weight function one. See also Exercise 24. In applications the Legendre polynomials are often expressed in terms of 0. Let x = cos 0, dx = — sin 0 dO, and change the limits accordingly. Then Eq. (7.316) becomes is
Pm(COS 8)P,,(cos
O)(
— sin OdO)
= 0,
m * n
or
sin 0 Pm(COS O)P,,(cos
0) dO
m * ii.
= 0,
Thus the set
IP0(cos 0), P1(cos 0), P(cos 0), is
.
.
.
an orthogonal set on the interval 0 0 z with weight function sin 0. If in Eq. (7.316) we replace n by 2n and m by 2m, then P2m(x)P2n(X) dx =
2
P2m(X)P2n(X) dx = 0,
n*
m.
other words, the Legendre polynomials of even degree are orthogonal on with weight function one. Similarly, the Legendre x I with polynomials of odd degree are orthogonal on the interval 0 x weight function one (Exercise 4). In
the interval 0
1
Legendre Series* The orthogonality property of the Legendre polynomials makes it possible to
represent certain functionsf by a Legendre series, that is, a series of Legendre polynomials. This representation is possible because Legendre's differential *Some authors call this a FourierLegendre series.
Boundary Value Problems in Other Coordinate Systems
328
CHAP. 7
equation (7.3—12), together with an appropriate boundary condition, constitutes a singular Sturm—Liouville problem of the type discussed in Section 2.7
(see Exercise 23). Moreover, it can be shown* that the normalized Legendre polynomials that we will obtain in this section form a complete orthonormal set with respect to piecewise smooth functions on (— 1, 1). For such a function we can write
f(x) = In
A0P0(x) + A1P1(x) + A2P2(x) + A3P3(x) +
order to find A2, for example, we multiply the above by P2(x) and integrate Ito 1. Then
from —
f(x)P2(x) dx
Po(x)P2(x) dx
A0
+ A1
P1 (x)P2(x) dx
+
P2(x)P2(x) dx
2
+ A3
Pj(x)P2(x) dx ÷
Because of the orthogonality property of the P,,(x), each integral on the right with the exception of the third one is zero. Thus f(x)P2(x) dx = A2
dx,
j"
from which we get
f(x)P2(x) dx
A2=
dx
Each coefficient A,, can be found in the same way so that, in general,
A,, =
f(x)P,,(x) dx
n = 0, 1,
2
(7.3—17)
[P,(x)]2 dx
Next we evaluate the denominator in Eq. (7.3—17). This quantity is referred to as the square of the norm and is denoted by IP,jP2. In order to evaluate this term we first need a result known as Rodrigues' formulat
See Ruel V. Churchill and J. W. Brown, Fourier Series and Boundary Value Problems, 3rd ed., (New York: McGrawHill, 1978), pp. 234 if.
tAfter Olinde Rodrigues (17941851), a French economist and mathematician.
329
Spherical Coordinates; Legendre Polynomials
SEC. 7.3
which can be
We begin with the binomial expansion of (x2 —
written as (x2
1)k
(
—
k!(n— k)!
=
Differentiating this n times yields (Exercise 16) (—1)"n!(2n
d"(x2 — IY =
2k)! xn_2k,
—
k!(n — k)!(n — 2k)! where the last whereas n — I
(7.3IS)
term is a constant. But n — 2N = 0 implies that N = n/2, — 2N = 0 implies that N = (n — 1)/2. Then, since N is a non
negative integer, it is defined in Eq. (7.3—18) as n/2 if n is even and (n — 1)/2 if
n is odd. Recall the definition of =
where
in summation form, (7.314)
k!(n
N is defined as in Eq. (7.318). A comparison of Eqs. (7.314) and
(7.3—18) shows that I
—
'
df
= 2'n!
(7.3—19)
which is Rodrigues' formula. We can use Eq. (7.319) to evaluate
follows. We have
as
dx =
—
1
and integrating by parts with u =
(x2
dv =
du =
dx
v=
—
(x2
1
—
produces
dx
=
T
—
d.,_I
(x2—
(x2 —
dx].
)" dx
I
)" dx,
CHAP.?
Boundary Value Problems in Other Coordinate Systems
330 The
first term on the right vanishes at both limits by virtue of the term
(x2 —
I). Hence after (n —
1)
integrations by parts we have
[P.1(x)]2 dx =
(x2 —
IY dx.
One more integration produces —
dx =
I)"
We now observe that p(n) (x)
(2ti)!
—
,,
—
from Eq. (7.314). Using the reduction formula found in most integral tables,
ix" (ax"
+ npb
+
dx],
and integrating n times, we have I
3'
(x2— l)"dx— ' —
' (2n +
1)!
Thus, putting everything together (Exercise 5), we have 1 3' [P" (x)J2
I)" (2n)! (—
dx —
(2n +
— 2"n! 2"n!
1)!
or = 2n
II
n = 0, 1, 2
1'
(7.320)
Hence the set Po(x) '/2
P,(x)
P2(x)
'
an orthonorinal set on the interval — We can also update Eq. (7.317) to read is
1
A=
2n +
x
1 with weight function one.
I
f(x)P,,(x) dx,
n
0, 1, 2
(7.321)
Legendre series have something in common with Fourier series. If a function is defined only on the interval (0, 1), it can be represented by a series
331
Spherical Coordinates; Legendre P&ynomials
SEC. 7.3
of Legendre polynomials of even degree. This is accomplished by making an even extension of the function as we did to obtain Fourier cosine series in Section 4.3. We illustrate the procedure for this and for an odd extension in the following example.
EXAMPLE 7.31
Define
O<x 0,
0 < p < c, 0 < p < C,
z > 0.
Solution
As shown in Fig. 7.4—6, the mathematical statements may be interpreted in the following way. (a)
Find the steadystate (independent of t) temperatures at any point within a solid, semiinfinite right circular cylinder of radius c.
CHAP. 7
Boundary Value Problems in Other Coordinate Systems
348
00 UlnbiQnt
Convective heat transfer
————
0=0 Figure 7.46
(b)
There is convective heat transfer from the lateral surface into a sur
rounding medium at temperature zero. Another way of saying this is that the lateral surface is cooling in accordance with Newton's law of cooling. (c) The temperature of the base is a given function of p. that is, f(p). (d) We seek a bounded solution, which means that
urn u(p,
z) = 0
and u(p, z) is bounded in the neighborhood of the zaxis, that is, as
p.0. Other interpretations are equally valid, since we are solving the potential equa
tion (Laplace's equation). We use separation of variables, assuming that the desired solution can be written as a product, that is, u(p,
z) = R(p)Z(z).
Then we have R
+ R' pR
—
Z
— _x2
where we have chosen the separation constant as —
X2
so that Z (and u) will not
be periodic in z. Thus we are led to the following two ordinary differential equations:
pR" + R' + X2pR = Z" —
X2Z
0,
= 0
R '(C) ÷ hR(c) =
0,
349
Applications
SEC. 7•4
The first equation is Bessel's differential equation of order zero; its general
solution is
R(Xp) = AJo(Xp) + BY0(Xp).
We take B =
0
because Y0(Xp) is undefined for p = 0. Applying condition (b)
yields
(7.49)
+ hJ0(Xc) = 0, which defines the positive X's, call them X,, tion has the general solutions Z(X1z) =
C1
+
exp
D1
j = 1,
The second equa
2
exp (—
in which we take C, = 0 to keep the solution bounded for z > 0.
Hence the solution may be written as exp (— X1z)Jo(X,p).
u(p, z) = We apply condition (c) to obtain
u(p, 0) =
A.
= ftp),
which shows that f(p) must be expressed as a Fourier—Bessel series. In view of Eq. (7.4—9) the coefficients A1 are obtained from Eq. (7.221), that is, 2X2
=
j = 1,2
(X''
Thus the updated solution can be written as u(p, z)
2
=
XJ exp (—
+
C2
(X)
f, 3°
xf(x) .Jo(X1x) dx, (7.410)
where the X1 are positive roots of + hJ0(X,c) = 0,
h>
0.
U
We have presented a few examples to show how circular symmetry in a
problem can lead to Bessel functions and spherical symmetry to Legendre polynomials. We have used separation of variables to solve the boundaryvalue problems, since this technique allows us to transfer homogeneous condi
tions to the separate ordinary differential equations. We have also used our knowledge of the physical situation wherever possible to assign particular values to the separation constants.
Boundary Value Problems in Other Coordinate Systems
350
CHAP. 7
In conclusion we point out that the method of separation of variables is
not limited to problems phrased in rectangular, polar, cylindrical, and
spherical coordinates. Other coordinate systems in which the method can be used include the following:* elliptic cylindrical coordinates, conical coordinates, parabolic coordinates, elliptic coordinates (both prolate and oblate), ellipsoidal coordinates, and paraboloidal coordinates. Key Words and Phrases average value
steadystate solution updating convective heat transfer
Newton's law of cooling bounded solution potential equation
7.4 Exercises In Example 7.4—I, show that
S
1
d20
cotO dEl +
is
equivalent to I
2.
n(n + I)
d
I.
dO\
1)0=0.
Show that we must take D,, = F,, 0 in Example 7.4—1 even though the region in which we seek a solution does not include the points r = 0, (b, 0) and (b, jr). Why
must these points be excluded? (Hint: Look at the partial differential equation being solved.) 3.
Translate each of the given boundary conditions of Example 7.42 into the
4.
mathematical statements shown. Carry out the details in separating the variables in Example 7.42.
S.
Solve
Z'(O)=O. (Compare Example 7.42.) 6. Fill in the necessary details to obtain the A in Example 7.42. 7. Use separation of variables to obtain the ordinary differential equations in Example 7.4—3.
8.
Use separation of variables to obtain the two ordinary differential equations in Example 7.44. See Section 5.4 of the author's Advanced Engineering Mathematics (Reading, Mass.:
AddisonWesley, 1982).
9.
351
Applications
SEC. 7.4
In Example 7.4—4, explain why we must have urn UD(p, t) = 0.
10.
Obtain a solution to the following problem:
d
/ du\
du(c)
dp
•• 11.
=0.
Obtain the solution to the problem in Example 7.4—1, given that the surface
temperature is a constant 1000. Does your result agree with physical fact and with Theorem 6.11? 12. Obtain the solution to the problem in Example 7.4—1 if the surface temperature is given byflcos 0) = cos 0. (Hint: Recall from Section 7.3 that P, (cos 8) = cos 0.) *13. (a) In Eq. (7.4—2), put b = c = 1, and write Out the first three terms of the sum. (10 Use the result in part (a) to compute u(0, 0). (C) Is the result in part (b) what you would expect? Explain. 14. Solve the problem of Example 7.4—2, given that the base and curved lateral surface
are both kept at zero and the top is kept at 100°. What would the result be if the separation constant in Example 7.4—3 were of the opposite sign? Do these results agree with physical fact? Explain. 16. In Example 7.43, change 1(p) to 1, and obtain the solution corresponding to Eq. (7.4—3). Is such an initial displacement physically possible? Explain. 17. Solve the problem of Example 7.44, given that the outer edge of the disk is kept at temperature zero instead of being insulated and all other conditions remain the 15.
same.
Find the bounded, steadystate temperatures inside a solid hemisphere of radius b if its plane surface is kept at temperature zero and the remaining surface has a temperature distribution given by f(cos 0). 19. Modify Exercise 18 so that f(cos 8) = 100, and obtain the solution. 20. A solid hemisphere of radius b has its plane surface kept at a constant 1000, and its curved surface is insulated. Find the steadystate temperature at an arbitrary point in the interior. 21. Use the condition f(cos 0) = 100 in Example 7.46, and obtain the solution. 22. Modify condition (c) in Example 7.4—7 to u(p, 0) = 100, and obtain the solution. 23. (a) Change the homogeneous boundary condition in Example 7.47 to u(c, z) = 0, and obtain the solution. (b) Give a physical interpretation of the problem in part (a). 24. Concentric spheres of radius a and b (a < b) are held at constant potentials V, and V2, respectively. Determine the potential at any point between the spheres. 25. A dielectric sphere* of radius b is placed in a uniform electric field of intensity £ in the zdirection. Determine the potential inside the sphere and outside the sphere. (Hint: Both the potential inside (v) and the potential outside (V) must satisfy the 18.
•This is not a solid sphere.
CHAP. 7
Bounday Value Problems In Other Coordinate Systems
352
potential equation. Continuity conditions are given by
0 < 0 < w,
v(b, 6) = V(b, 0),
and Kv,.(b, 0) = V,4:b, 0),
K > 0.
< 0 < T,
0
Moreover, tim V(r, 0) = 26.
= — Er cos 0.
— Ez
Find the potential of a grounded, conducting sphere of radius b
placed
in a
uniform electric field of intensity E in the zdirection. (Hint: Again '72v = 0 with v(b, 0) = 0 and
urn v(r,0) = 27.
—Ez = —Ercos8.)
Show that the positive roots of
h > 0,
+ hJ0(Xc) = 0, are
the same as those of KJ0(Xc) +
2$.
Using the fact that r =
(x2
+ y2 +
29.
0.
show that
fl\
8
K>
= 0,
1
Show that the functions
u(p, are
4),
z) =
potential functions for n =
1,
exp (— Xz) J,,(Xp) cos n4)
(Hint: Use the recurrence relations in
2
Exercises 4(e) and 26 of Section 7.2.)
30. A homogeneous membrane of radius b is fastened along its circumference. It is given an initial displacement C(b2 — p2), causing it to vibrate from rest. Show that the displacements z(p, 1) are given by
z(p, t) = 8Cb2
••• 31.
where the X1 are roots of J0(X) = 0. (a) Solve the following problem.
B.C.:
v(a, 1) = 0,
1
limv(p,t)=0, l.C.:
O 0; u(0, 1) = u(2, I) = 0, 0 <x < 2. u(x, 0) = 100,
B.C.: 1.C.:
The computations can be arranged in a table from which we can read discrete values of u(x, 1).
•
i=x=0
x=0.2
x=0.4
x=0.6
x=0.8
o
o
20
40
60
80
0.132 0.264
0 0 0 0
20
40 40 40 37.5 37.5 34.38 34.38 31.26 31.26
60
80 70
0.3% 0.528 0.660 0.792 0.924 1.056 1.188
0
20 20 20 18.75 18.75 17.19
0 0
17.19 15.63
0
0
60
70 62.5
55 55
62.5 56.25 56.25 50.79 50.79
50 50
45.32 45.32 41.03
x=l.0 100
80 80 70 70 62.5 62.5
56.25 56.25 50.79
x=l.2 80
80 70 70
62.5 62.5 56.25 56.25 50.79 50.79
In contrast to the last finitedifference method we present next an imin the
plicit method. If we write the partial differential equation u, = form Ujj+1 — U,j
j+1
—k
U•.1
—
, U1j+1
j+1
+ U1+i
83 9

can no longer solve for one of the temperatures in terms of known quantities. Equation (8.3—9) is obtained by representing in terms of finite differences at the ith node for the (j + l)st time step by using a centraldifference formula, whereas is represented at the (j + 1)st time step by we
using a backwarddifference formula. In order to use Eq. (8.3—9) it is necessary
Numerical Methods
364
CHAP. 8
The advantage of the method, however, lies in the fact that it is stable for all values of & and thus removes one of the restrictions in the explicit method. A modification of the above implicit method uses the average value of the finitediffcrcnce expressions for u,,,, in Eqs. (8.3—4) and (8.3—9). This modification is known as the CrankNicolson method. It has the advantages of being stable for all values of r in Eq. (8.37) and having a truncation error + (or discretization error) of the order of One serious disadvantage of a finitedifference method is that interpolation of some kind must be used to obtain solutions at points that are not this difficulty could be overcome by using a grid points. It would appear finer grid, but there is a limit to how fine a grid can be. At some stage in the computation the truncation and roundoff errors can deteriorate the accuracy of the calculations. Moreover, the finer the grid, the greater the number of computations that have to be performed and the larger the amount of storage required. Limitations on the fineness of the grid also cause serious difficulties in the vicinity of a boundary that is irregular. In an attempt to correct these shortcomings of finitedifference methods a variational form of the method, called the finiteelement method, has been developed. The finiteelement method utilizes the relationship between Euler's equation in the calculus of variations and a partial differential equation. For example, Euler's equation for the functionalt
to solve a set of simultaneous algebraic equations for the
+ u3)dxdy
F[uJ =
(8.310)
is ui,, + u,,,, = 0, the potential equation. In other words, the function that minimizes the functional in Eq. (8.3—10) is harmonic. The significance of this is that the integrand in Eq. (8.3—10) can be written as I
grad u
12
and interpreted as kinetic energy. Thus it seems natural that the finiteelement method has its origin in the field of solid mechanics and structural analysis. The Dirichlet problem over a region R having a boundary C can be solved by finding a function u that minimizes the integral in Eq. (8.310) and assumes the given values on C. This latter problem, while more complicated than a direct approach, has a number of aspects that lead to a more accurate solution. Instead of using square or rectangular grids, it is possible to use other configurations— for example, triangles of various sizes as shown in Fig. 8.3—3.
In this way the node lines may be a better approximation to the boundary. Furthermore, the sides of the triangles may be polynomials (called spline func
*Given a set F of functions defined on an interval (a, bJ, we define a functional F(u] to be mapping from .F into the set of real or complex numbers that assigns a unique number to each function u ofF. (See Exercise 16.) a
FIniteDifference Approximations
SEC. 8.3
365
Figure 8.33 A triangular grid.
lions) so that even closer fits to ab irregular boundary may be achieved and differentiability at the nodes may be preserved as well. Details of the finiteelement method and the variational principle on which it is based can be found in books listed at the end of this chapter. Key Words and Phrases difference equation relaxation method centraldifference formula truncation error forwarddifference formula explicit and implicit difference equations
stable method backwarddifference formula CrankNicolson method Ilniteelement method functional spline function
8.3 Exercises
•
1.
The formula d2u
1
+ 2h) — 2u(x + h) + u(x)I
=
is known as a forwarddqfference formula, whereas the formula d2u 2
I
= 1,j[u(x
+ h) — 2u(x) + u(x — h)]
is known as a centraldifference formula. Explain the meaning of these terms. 2.
Verify Eq. (8.3—6).
3.
Explain the units of k in Example 8.3I.
4.
••
CHAP. 8
NumerIcal Methods
366
S
in Example 8.3I. Consider the Dirichiet problem over a rectangular plate measuring 10 cm by 20 cm Explain why there is symmetry about the line x =
I
with one of the shorter sides held at temperature 1000 and the other three sides held at zero. Choose coordinate axes as shown in Fig. 8.2—3 in the exercises of Sec
6. 7.
8.
tion 8.2. Divide the region into eight subregions by lines 5 cm apart parallel to the axes so that three interior points will be produced. (a) Use Eq. (8.3—2) to write a system of three algebraic equations. (b) Solve the system of equations in part (a). Compare the results in part (a) with those of Exercises 5 and 6 in Section 8.2. (C) In Exercise 5, change the grid spacing from 5 cni to 2.5 cm. How many interior points (and equations) are there now? Change the grid spacing of Exercise 5 to 3 cm, and solve the resulting system of equations. (Hint: Use symmetry.)
Show that the onedimensional wave equation and initial conditions u,, g(x) can be approximated by the finitedifference u(x, 0) = f(x), u,(x, 0) equations 2U(x, 1) — U(x, t — k) + X2[U(x + ft. 1) — 2U(x, 1) + U(x — h, i)J, U(x, I + Ic) IJ(x, k) = kg(x) + f(x), U(x, 0) = f(x),
k/h. (Note: It can be shown that the convergence of U to u that X < I.) where X =
9. 10.
Use the relaxation method to find the potential at the interior nodal points, given that the potential on the boundary is as shown in Fig. 8.34. V2u = xy on the square region bounded by x = 0, x = 1, y 0, and 0 on the boundary. (a) A guitar string is 80 cm long. At a point 20 cm from one end it is raised 0.6 cm from its equilibrium position, then released from rest. Find the displacements of points along the string as a function of time. Let 10 cm, = 179 and a2 = 3.136 x lOu. (b) By determining the time required for one complete cycle of motion from part (a), compute the frequency with which the string vibrates. Solve
y = I. Use a spacing of 1/3, and take u 11.
requires
tO
10
Figure 8.34
10
12.
Consider the following problem:
0 <x < 1, U(l.t) =o.j t>O.
P.D.E.:
= U,,,
B.C.:
(a) (b)
1
> 0;
= 0,1
U(O, 1)
U,(x, 0) = 0, U(x, 0) = sin irx,
l.C.:
— 1
sin at cos
at
Appendix
386
Table II (continued) 1(1)
F(s)
8.s—a 9. 10.
ii. 12.
exp (at)
1
texp (at)
(s — a)2
1' exp (at)
(s — a)
t" exp (at),
(s — a)
sinh at
S' — a'
cosh at
S' — a2
s+2a
14
cos' at
+ 402)
S' — 2&
cosh2 at
s(s2 — 4a') 2a2
16.
sin' at sinh' at
17.
202$
sin at sinh at
18
a(s' — 2a2)
•
cos at sinh at
+2a')
iz(s2
20
sin at cosh at
s'+4a4
21 •
cos at cosh at
+ 2as
22
t Sin at
+ a')'
•
23.
n a positive integer
—
a2
I cos at
(s' + a2)' 2as
2
t sinh at
—
2 5.
26 27
28.
t cosh at
(ç2 — a')'
(s— b)2 +a2
s—b (s —b)2+ a'
exp (bt) sin at
exp (bt) cos at exp (at) — exp (bt)
(S
—
—
b)
a—b
387
AppendIx
Table II (continued) f(1)
F(s) 29. 30.
31. 32.
S
a exp (at) — b exp (bi)
(s — a)(s — b)
a—b ab (c
(5  a)(s — b)(s — C)
 a)(s  b)(s . c)
(S
(cosh
— a)
(0, fort < a, (1, for t > a,
exp(—as)
38. (s2 + X2)_ttz 39.
J0(Xi)
—logt — C
log —
40.Iog 41. log
42.Iog 43.
at — 1)
I
36. exp (—as) 37.
b)e"' + (a — c)ebt + (b —
(I — cos at)
+ a2) —a2)
35.
—
(a — b)(a c)(c — b) a(b — c)e'' + b(c — a)eb + c(a — (a — b)(b — c)(a —
I
33.
b exp (at) — a exp (In) ab(a — b)
+
I
a)(s — b)
s(s
a
(1 — exp
s—a
(exp (bt) — exp (at))
b
s+a
sinh at
s—a
arctan
(at))
ía
sin at exp
b>O
fib!)
46. F(s — b)
exp (bt)f(t)
47. s..Jk(s +
erf .Ikt,
48.
eri(ki) k > 0
[1
—
erfc (k/2V,),
49. 50. 2a(../s 51.
k>0
÷2a + —
k>0
I, (at) exp (— at) (X2 +
V > —1
a0
Appendix
Table lii Fourier transforms
f(a)
1(x) exp
=
(lax)
f(a)
dx
f(x)
2sinac
Xj < C,
1,
>
0,
C,
X1 — C a2 2.
a2 + x2
—h, —c
21/i
(1 — COS ac)
h,
0,
4.
0
<x 0 (a) sin The suggested substitution produces Tm(X)Tn(X)
.'
dx =
Now, DeMoivre's formula (cos a cos na is a polynomial of degree n Jo
+ in
a) da.
Tm(COS
I sin a)" = cos na
+
I
sin
na
shows
that
cos a. Finally, we know that
if m * n.
cos ma cos ncr da = 0
Section 2.8, p. 98 3.
(a) y=3sinhx—2x
7.
= 0.910, ys = 0.840, 0.207, Yio
8.
= 0.750, Ye = 0.641, y, = 0.5 14,
Y' = —O.005,y2 =
= —O.045,y,
Ye = — 0.174, y, = — 0.234, Ye = — 0.300, 13.
(a)
The
= 0.368,
0.032
cosh x
general solution is y =
—0.079,y5 = —0.122, = — 0.371, Yio = — 0.445
+ c2 sinh x. Boundary conditions
transform this into the system
51.543lc, ÷ I.1752c2 = 1.5431, 13.7622c, + 3.6269c2 = 3.7622,
which is easily solved by Cramer's rule to obtain c1 = 1, c2 = 0. Hence the
solution is y = cosh x. (c)
In finitedifference form the differential equation becomes —
2y1
+
—
Ft2
or + = (Ft2 + 2)y1. Using Ft = 0.25, produces the system
= —1.5431 Y4 = 0 = —3.7622,
(—2.0625y2 + —
2.0625y3 + V3 —
16.
= 1.5431, andy, = 3.7622
which has solutions Yz = 1.8894, = 2.3538, y. = 2.9653. be the approximate value of y at the midpoint x = 1/2. Then Let 9 4 — 29 + 1 = 3 (9)2 0.25
2
which has approximate solutions 1.855 and —7.188. We choose the first of these,
andwithh = 0.2wetryy, = 3anduse =
+ 2yj — Y1i,
i = 1, 2, 3, 4.
This yields the values of Y2 = 2.540, = 2.467, y, = 2.759, and y, = 3.509. Next we try = 2.8 to obtain the values = 2.070, = 1.60, = 1.279, and
Answers
396
= 1.058. Using linear extrapolation, we find a better approximation to y,, 2.7953. With this value we obtain Y2 = 2.0594, y., = 1.5780, = 1.0071. The above values may be refined further. The = 1.2460, and other solution can be found by starting withy, = —2.5 and improving this value.
namely, y, =
y=sinhx
(d) 18.
= 1.175,y(l)
9=
17.
10.018
2 + h2 — 1
(e)
—h2x, + Yo
—l
Y2
—h2x2
2÷h2
—1
CHAPTER 3 SectIon 3.1, p. 109 The given expression satisfies the partial differential equation identically, and it contains two arbitrary functions; hence it qualifies as the set of all solutions. S. (b) elliptic when x> 0; hyperbolic when x < 0; parabolic when x = 0 (d) hyperbolic outside the unit circle with center at the origin; elliptic inside this unit circle; parabolic on the unit circle 11. (b), (d), and (e) are not linear 15. f(y — 3x) and g(y + 2x) are solutions, where! and g are twicedifferentiable functions of x and y. 3.
hyperbolic
(b)
19.
If the roots of Eq. (3.1—3)
(c)
0 or y =
parabolic if x
17.
are
a±
0, otherwise hyperbolic
then
u(x, y) = fEy + (a + 131)4 + g[y + (a — (31)4. 22.
If we consider first the term xv',, differentiate, and substitute into the biharmonic equation, we have after rearranging terms
4a
+
axLaxl Since
is
o
ay'J
+
Lax'
a'*,l+
a'
ay'J
harmonic, each bracketed term is zero. The term
+
L ax2 is
ay'J simpler.
Section 3.2, p. 119 4.
(a)
(c)
Starting with Eq. (3.211) and applying the nonhomogeneous boundary condition produces u,,(x, 0) = b,, sin nx = 2 sin 3x. Hence n = 3, b, = 2, and u(x, y) = (2/sinh 3b) sin 3x sinh 3(b — y). Using the hint, sin 2x cos x = (sin 3x + sin x)/2. Hence we need two
397
Answers
terms, one with n = 1 and b3 = 1/2, the other with n = 3 and b3 = 1/2. Thus
sin x sinh (b — y)
u(x,
8.
u(x,
9.
(b)
12.
T'
— 2 sinh b
+
sin 3x sinh 3(b — y) 2 sinh 3b
3 sin xsinh(b — y) sinh b
=
(d)
0 —
0.9721
XT = 0, kX" + (a — X)X = 0
13. T'—XT=O,kX"÷bX'—XX=O 0, kX" + bX' — XX = —a
14.
T' — XT
15.
Y" +
= 0, Y(0) = Y(b) = 0, has solutions
—
(n2ir2/b2)X = 0, X(T) = 0, has solutions = [sinh
(x —
= sin
(niry/b).
/cosh
Hence the solution can be taken as a linear combination of functions of the form
u,,(x,y) = 1. 17.
1
.
—i (x — ir) /cosh
fir2
X" + X2X = 0, X(O) = X(ir) = 0, has solutions X,,(x) = sin fix. = sinh ny. Hence solutions are Y" — n2 V = 0, Y(0) = 0, has solutions y) = sin nx sinh ny, that is, linear combinations of u(x, Y)
b,. sin fix sinh fly.
The nonhomogeneous condition produces
43(x) = U(x, li) =
b,, sin nx sinh nb,
showing that
sinh nb =
43(x) sin nx dx.
21. X"—XX=0,Y"tXyY=0,ify*0 Section 3.3, p. 131 5.
43(x) =
— x), but has already been defined in the interval L, so that the above equation now extends 43(x) to the interval 2L — x L, that is, —3L —x —L or L x 3L. —
—L x —L
= c2(u,. + u,, + u.)
7. S.
(a)
y,, has dimensions of acceleration;
= d(dy/dx)/dx has dimensions of cm'.
Answers
398 y = sinxcosal (cos x sin at)/a 10. y 3irx . 2L 9.
15.
17. 18.
22.
cos
v 
— c'°'
L
sin
37rW
L
=
Assuming the function of ito be of the form exp (iwl) is equivalent to choosing the sign of the separation constant so that T(i) will be expressed in terms of sines here. and cosines. The separation constant is The boundaryvalue problem becomes (see Exercise 20) a2y"(x) — g = 0, y(O) =
y(L) = 0, whose solution is 4g(x — L/2)2 = 8a2y + gL2, which is a parabola. Differentiating, we find dy/dx = 0 when x = L/2 and the maximum displacement is —gL2/8a2.
Section 3.4, p. 138 3.
6.
9.
ii. 13.
15. 16.
k has units of cm2/sec; K has units of calorie/°C cm. The bar is insulated except for the ends, which are kept at zero for all time; there are no heat sources; and heat flows from a region of higher temperature to one of lower temperature (a) 3 sin (2irx/L) exp (— 4kw21/L2) (a) The problem u(x) = 0, u(0) = 0, u(L) = 100 has solution u = lOOx/L. (c) u(x) = 100 (d) u(x) = 50(1 + x/L) The substitution u(x, 1) = + 1,t) leads to the differential equation a2kf" — bf' = 0 with solutions + bt) = c, + c2 exp [b(ax + bt)/ka2J. Substituting shows that b = a2k. this result into u, =
c=I/k The diffusion of respiratory gases is rendered more rapid by the large surface area of the lungs.
Section 3.5, p. 149 14.
(b)
(d) 15. 18.
hyperbolic everywhere except on the xaxis, where it is parabolic; parabolic on the unit circle, elliptic in its interior, and hyperbolic elsewhere;
(f) parabolic everywhere (b) —y/x2 (d) — 2y/x (a) cot 20 = — 3/4, 8 = — 0.4636; rotation through an angle 0 results in = 0.
+
399
Answers
CHAPTER 4
Section 4.2, p. 161 4.
g'(l) is undefined
6.
(a)
7.
9.
2/3 (e) 4 Use mathematical induction. 2 /cos x cos 3x w 4w
(c)
(a)
\
sin
x
32
+
(e) 24
2
sin 3 ix
4 fsin
(c)
sin 2x
+
3
(— 1)"
cos 2nirx
n—I
(2,, — l)2ir2
1
+ 43 —
4
4
sm2(2n — 1)wx
cos(2n — l)x + (2n—1)2
2 w
—
n=I
1
sin 4nix
—
n
8'ç'.cos(2n— l)x 2n—l
(I)
11= I
3/2
(g)
10.
(a)
1
13.
(a)
w/2
14.
(b)
I
17.
Twenty terms give a result that is approximately 1.2 percent low.
26.
(a)
(c)
(d)
(e)
r/2
(c)
(f)
I
exp(2ir) —
i(i \2
w
I
1
(e) I
+r
—
nsinnx
n2+1
n—I
Section 4.3, p. 170 =
8.
i
—
(ins) f(s) [exP
+ exp (— ins)
—,
exp (ins) —exp (— ins)]
from which the desired result follows. 9. 10.
= (d)
f(s)
exp (— in rrs/L) ds, n = 0,
± 1, ± 2,.
F(—x) = (—x)exp[(—x)21 = —xexp(—x2) = —F(x)
ds
Answers
400
tan (—x) = (—x)(—tan x) = x tan x = F(x) (—x)2/1 — x = x2/1 — x, which is neither —F(x) nor F(x) 12. (d) F(—x) 13. 11 f is odd and g is even, then f(—x) = —f(x) and g(—x) = g(x); hence —f(x)g(x), showing that the product is odd. — x)g( — x) = 11.
(e)
14.
(a)
15.
(b)
16.
(a)
F(—x) =
sin (nTx/2)
a
!{(_l)fl+I
(h)
17.
(b)
18.
(b)
f
'I
—r
cos (n irx)
I
cos(mrx/2) (2nTx)
cos
4n2—1
n=1
n sin (2nx)
8
(a)
21
1) + 4
—
2
—
(— 1)"
+
w
19.
—x
4n2=
1
'7= I
23.
+
1)2
1
sin(2n—i)x
24 '7= I 1
2
27.
(2n —
Ietx =
(b)
26.
cos(2n — l)Tx
4
1
(a)
—
4
2n—l
r
cos(2n — 1)irx
n=1
(2n—
1)2
C,, = 0 if n is even (including n = 0) and c,, = 21(inir) if n is odd; thus the series
can be written as 2
exp [i(2n —
I
2n—1
IT '7= —
Note that this can be written in terms of sines and cosines, in which case the cosine
28.
terms vanish and the sine terms double so that the final result is the same as when we use Eq. (4.36). x I. Then Make an even periodic extension of the function g(x) = 1, — 1 I and all other c,, = 0.
31. f(—x) = —x —x2 = —x(1
+ x) = f(x + 1) = f(x)
401
Answers 37.
If 1(x) is even, then f( —x) = f(x). Differentiating this produces —
X —
df( — x)
—
df( — x)
d(—x)
—
dx
dx = — df( — x) dx d(—x)
df(x) dx
sincef'(x) is even. Hence df(x) =—df(x), that is,f(x) = —f(—x) + C. But — x) = f(x) so that 21(x) = C, proving the assertion. 39.
21.sin x —
.
sin
—
2x +
i.
sin
1.
3x + — sin 5
3
1.
\
Sx — — sin 6x•i
/
3
Section 4.4, p. 181 7.
V(x, y) = csch ir sin wx sinh
9.
Let x = 1/2, and compute V(x, y) for various values of y. Approximate results are shown in the following table:
— y)
0.1 0.2 0.7 y 0.3 0.4 0.5 0.6 0.8 0.9 V(l/2,y) 0.72 0.52 0.38 0.28 0.20 0.14 0.09 0.06 0.03
Repeat for x = 0.1, 0.2, 0.3, and 0.4. Note that by symmetry the results are the same for x = 0.9, 0.8, 0.7, and 0.6, respectively. Locate the values of V(x, y) on a suitable square, and connect points of equal Vby a smooth curve. It is also helpful to compute V(x, 0) for the above values of x. See figure below.
0
0
0
0
0
0
0
0.4
0.8
0.8
0.4
0
Answers
402 10.
(a)
P.D.E.:
12.
0
U,, =
B.C.: I.C.:
< x
0; 1 > 0;
1,
0) = 0, 0 <x < I Thrai
0.02
(b)
u(x, $) =
(a)
YAT, I) = 0 implies that there is no vertical force on the string at x =
(c)
is, the end is free (see Section 3.3). I must be "small" in comparison to the length of the string.
that
Section 4.5, p. 190 Write sin (N + )i as sin Ni cos t + cos Ni sin t, and then use L'Hôpital's rule. 8. The series converges uniformly by the Weierstrass Mtest. 10. f"(x) does not exist because the infinite series is divergent. 4.
13.
sin_(2n—l)x
(a)

(c)
(2n—l)2
2
14.
(a)
The representation of Fix) = x, 0 < x < 2ir, F(x +
F(x) is
SIflflX
hence
f(x) (c)
—
x)
—
Sinceflx) satisfies the hypotheses of Theorem 4.5—4, we can integrate from zero to a to obtain —
0
f(x)dx =
=
2ir.
a
Then, replacing a by x, we have 
1
—
cosnx —i
0
x
2ir.
the even periodic extension of the function on Outside the interval (0, the left is given by the series on the right. The series is the ad2 term in the representation of g(x). (d)
15.
— —
403
Answers 16.
Since (see Exercise 3)
sin(2n+ 1): 2sint and
=
1
2
+ cos2t+ cos4t+
+ cos2nt
cos 2k! dl = 0, the result follows.
Jo
CHAPTER 5 Section 5.1, p. 201 2.
11.
The integral is finite. Only the function in part (a) is absolutely integrable, the integral being 2.
2 f'. asiflaX
19. (c)
(e) 20.
(a) (c)
23.
a
sin
—a
2
(b)
sin
—
2
2a sin a +
—
f
2
ax dcx
cos a
— a2 cos a — 2
— sin ax dcx
cos ax dcx
(b) (d)
21.
2 (o.
siflcr
2
(1
+ 2cosa)cosaxda
a [exp (lair) +
L
1+ia
1

1
+ a2
exp (— lax) dcx
exp (— lax) dcx
When x = L, we have h
h
—L irJO (d)
a
h 2
ii\2/
using Exercise 14. When x = 0, we have I
dcx
—) 2ir
i +—3
ada
I 2
1. 2
noting that the first integrand is an even function, whereas the second is odd.
Section 5.2, p. 215 4.
7(a) = 2 u(x,
)= 4
(1 —
cos
ax dx =
sin2 (a/2) exp(— a'!) cos ax
dcx
404
Answers
S
f(cx) =
exp
0
(lax) dx =
a
[I
—
a
0
2 t= exp(—a21)cos ax
7.
u(x, t) =
9.
(a)
u(x, 1)
10.
(a)
f(a) = [2 cos (ajr/2)]/(l — a!)
11.
(b)
dcx
+
exp(—a2kl)cosax
2
=
21w —cx sin
4a cos
+
0
cx
dcx
(a/2)J exp (ia/2) —
(d)
exp (iac)J;
[1 — exp (iac)j exp( — a2kI) cos cxx dcx
2bi
u(x, 1) =
bi
a2
+ 2(a2 — 2) sin cx a3
(e)
12.
(a) (c)
13.
(a)
21/i
(1 — cos ac)
a h
a
[I
cos
(a/h)]
(a — sin a)
a I
—
+ Sin aw 1
(c) 14.
(C)
— sin (a/2)J 1r2—a2 Using the inverse Fourier transform, 2w cos
(a/2)Ii
1
2w (OD
15.
(a)
J=
24.
r=
f(x)exp(iax)dx
= f(—a)
3
fix — b) exp (lax) dx
r 
f(x — b) exp (ia(x — b)] exp (jab) d(x — /4 = f(cx) exp (lab)
2i sin 6wa a2 — I
Section 5.3, p. 221 6.
Consult the table of Fourier transforms in the Appendix.
7.
u(x, s') =
2u0
fo. sin
ax El — exp (—ka2i)] da
405
Answers 8.
(b)
9.
U(X,
COS axexp (—ka2t)
2a
u(x, 1) =
sin ax (I
2u0
(— k&t)
a
)
cos ax
2/3
10.
u(x I) =
12.
(a)
y(x) = cY0(x)
14.
(b)
u(O, 1) = u(c, 1) =
16.
(a)
y(x) = —
(c)
y(x) =
(a)
y(x) =
21.
aL) exp
cos
—
da
El — exp (—
dcx
dcx
2
1
— arctan c; u(c/2, 1) = — arctan
c
1•
ciri.
—Sin
a
o
(—
Cfo.
! + ax\dcr j
(a
a2/2) cos
—
exp (Ia3 — &) exp
T
ax) dcx
(—lax)
dcx
CHAPTER 6 Section 6.1, p. 236 2.
Use the identity sinh (A — B) = sinh A cosh B — cosh A sinh B.
4.
B,,,,, =
6.
V(x, v) =
7.
V(x,
15.
4ab(— mn sinh
=

o
w
—
a
sinha(b—y)
a2 + I
sinh (ab) sinh a(b
sin
2
1) 1—&
sin (cix)
—
dcx
sinh
cos (2nx) sinh 2n(,r — y)
2 4 u(x,y)=—+(7—y)+—
sinh (2nir)
—
I
1
17. I
—
4n2
2
1
n—I
18.
u(x,
2a y) = —
20.
(C)
u(x,
.Io. I)
+ 2n
dcx
+ 1
I
\
—
2n)
sinh [cx(J — x)J cos (ay) dcx (a2 + a2) sinh a (—
=
niry sin
+ sinh nirx sin niry)
nsinhn,r N
I
406
Answers 24.
If &(x,
28.
(b)
32.
y) = — Ø,.(x, y)
u(a. 0) = 0; u(0. 0) = 10 (h) f(x, v) = xy = u(x, y) as given in the solution to Exercise 20(c).
Section 6.2, p. 249 3.
u(x, v, 1) = k sin
I 4. 7.
B,,,,,
sin (lrx/a)
cos (cirVa2
+ b2t/ab)
+ b2/2ab sec' 64a2b2
2r6(2n—1)3(2m
n =
1,2
m = 1,2,
—
E has dimensions g cm/cm2 sec2; p has dimensions g/cm3
20.
T0 has dimensions g cm/sec2 cm; w has dimensions g/cm2; g has dimensions cm/see2; G has dimensions g cm/sec2 cm2 b2,,..1 = 4kL/cir2(2n — 1)2, n = 1, 2,
21.
u(x, I) =
23.
u(I/4, 2) = 3/16, u(1/2, 3/2) = — 1/2
24.
Compute U(0, 0).
27.
(b)
28.
u(x, I) =
19.
wx/LJ cos ((2n — (2n — 1)2 1)
(—
(b)
Tct/LJ
dx — dx dx/2. Hence the resulting = 'J increase in potential energy is Tour dx/2, where T0 =
The difference ds — dx
b,, sin nx cos
b,, = 29.
1)
where
cf(s) sin
ns ds, n =
1, 2,
.
u(x, 1) = (1/bcXcosh bx sinh bct) + 2xt2 +
Section 6.3, p. 259 4.
12.
Because the steadystate solution is zero. u(x, t) =
b2,,..1 exp (— ir2(2n
b2,,..1 =
—
1)21/4L2J
sin [(2n
—
sin [(2n — 1)ws/2LJ ds, n = 1, 2, .
where
________
________—
407
Answers 15.
Cx(L
u(x, I) =
x) +
—
b 17.
u(x,
i,,, sin (nirx/L) exp (— n272t/L2), where
2
fcs(s — L)
2 fL
"LJoL
1) = ta,, cos
((2n
+
2
f(s)] sin
exp [—(2n
—
where
—
n=l 8a
a,,=—1 u(x,
1) = sb,, sin
[(2n — 1)irx/2j exp [—(2n — 1)272k1/4], where 16a = ff3(2n —
a,,
21.
(a)
22.
u(x, 1) = — sin xexp (—ki) —
u(x, 1) =
[1
j'fl=1.2i..
2n—1)2
L
20.
_21
[T(2n —
—
1) — 2)
cos 2x exp (— 4kt)J Note that Sifl2
—
x=
sin 2nxexp (—4n2k1) n(4n2—1)2
16
2
Section 6.4, p. 272
10.
u(x, I)
=I
sin (2n — 1),rx exp [—(2n —
4 —
—
ii=1
14.
(a)
U(X, 1) =
2Uo
(= [exp
=UoX+— —
16.
(a)
v(x,
17.
(a)
v(x,
22.
U(1. 1/4)
30.
Use the relation
=
2
2u0 T
jo0
2
=
(— a21)
o
0
cos ax dcx
1)
—
exp (— cx2() a2
Nx
—
a
0
sinh (ax) COS cx cosh (cxc) cos
0
1)2ir21J
2n — 1
cos (as) ds
(ax) cosh (cxy)d cosh (crb)
r00
f(s) cos (as) ds
O.6Iuo; u(l, 4) = O.89uo
=
—
J'sincxsds.
(1
—
cos
2x).
408
Answers
Section 6.5, p. 283 cosh sinh
— y)
—
(—
y)] + exp
I
— w,,(b —
— exp (—
—
exp (— w.y)[1 + exp I — I — exp (—2w,,b)
—
1
—
16.
exp Iw.,(b — exp
—
—
y)J)
2exp(—w..y) — exp(—2b)
xl) di = l/x, x> 0; the convergence is uniform for a x
0).
exp (— at), we can take M(t) = exp (— at). Note that
= 1/a. 17. 20.
Take M(t) = exp (—I). y attains its maximum value exp (— (c) When a = I is an odd function.
CHAPTER
1
The function
7
Section 7.1, p. 295
1.
2. 7.
The case n = 0 leads to a constant that is also periodic of period 2w. Divide by p, and then make the substitution v = dR/dp. One interpretation is the following: find the steadystate temperatures in the walls of an infinitely long pipe having inner radius b and outer radius c if the outside of the pipe is kept at temperature zero, while the inside surface has a temperature (b)
given by The pipe is infinitely long, that is, —
10.
< z < cc, so that there are no boundaries in the z.direction. Moreover, the boundary values on the inside and outside surfaces are independent of z. Note that the differential equations are Cauchy—Eu Icr equations (see Section 1.3).
14.
u(p,
8.
=
ii P
whereao =
4
—3
T/2
fts)dsanda,, =
cos
4 fxi2
n = 1,2,3,...
409
Answers 18.
(a)
u(p) = 1100 log (p/b)J/log (a/b)
(!4
(p)fl 19.
u(p, çb) =
22.
(a)
+ —
+
P Po
z(p) = (Zo log p)/log Po, 1
Section 7.2, p. 312
7.
(a) y = c1J0(x) + c2Y0(x); (c) y = cjJo(ex) + c,Yo(ex)
8.
(a)
Make the substitution u = X1s;
(C)
evaluate
9.
(a)
Use
10 •
(b
ds as in part (a), and then let b —
integration by parts with u = J0(s), dv = X3J1(Xjc)
.4(X,x)
(8—X3)
0
11 •
( b)
2
12.
(b)
The transformed equation is ,2
(a)
ds.
2
c
14
J1(s)
x