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588 Chapter 11 Boundary Value Problems and Fourier Expansions Proof Multiplying (11.2.2) by φn and integrating yields Z b a f(x)φn(x) dx = Z b a φn(x) ∞ X m=1 cmφm(x) ! dx. (11.2.4) It can be shown that the boundedness of the partial sums {fN}∞ N=1 and the integrability of f allow us to interchange the operations of in...
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Section 11.2 Fourier Expansions I 589 Fourier Series We’ll now study Fourier expansions in terms of the eigenfunctions 1, cos πx L , sin πx L , cos 2πx L , sin 2πx L , . . ., cos nπx L , sin nπx L , . . .. of Problem 5. If f is integrable on [−L, L], its Fourier expansion in terms of these functions is called the Fouri...
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590 Chapter 11 Boundary Value Problems and Fourier Expansions Theorem 11.2.4 If f is piecewise smooth on [−L, L], then the Fourier series F (x) = a0 + ∞ X n=1  an cos nπx L + bn sin nπx L  (11.2.8) of f on [−L, L] converges for all x in [−L, L]; moreover, F (x) =            f(x) if −L < x < L and f is cont...
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Section 11.2 Fourier Expansions I 591 1 2 1 2 −1 −2 x y Figure 11.2.1 Solution Note that wen’t bothered to define f(−2), f(0), and f(2). No matter how they may be defined, f is piecewise smooth on [−2, 2], and the coefficients in the Fourier series F (x) = a0 + ∞ X n=1  an cos nπx 2 + bn sin nπx 2  are not affected by t...
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592 Chapter 11 Boundary Value Problems and Fourier Expansions If n ≥1, then an = 1 2 Z 2 −2 f(x) cos nπx 2 dx = 1 2 Z 0 −2 (−x) cos nπx 2 dx + Z 2 0 1 2 cos nπx 2 dx  = 2 n2π2 (cos nπ −1), and bn = 1 2 Z 2 −2 f(x) sin nπx 2 dx = 1 2 Z 0 −2 (−x) sin nπx 2 dx + Z 2 0 1 2 sin nπx 2 dx  = 1 2nπ(1 + 3 cos nπ). Therefore...
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Section 11.2 Fourier Expansions I 593 Even and Odd Functions Computing the Fourier coefficients of a function f can be tedious; however, the computation can often be simplified by exploiting symmetries in f or some of its terms. To focus on this, we recall some concepts that you studied in calculus. Let u and v be defined...
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594 Chapter 11 Boundary Value Problems and Fourier Expansions We simplify the evaluation of these integrals by using Theorem 11.2.5 with u(x) = x2 and v(x) = x; thus, from (11.2.9), a0 = 1 2 Z 2 0 x2 dx = x3 6 2 0 = 4 3. From (11.2.10), an = Z 2 0 x2 cos nπx 2 dx = 2 nπ " x2 sin nπx 2 2 0 −2 Z 2 0 x sin nπx 2 dx # = 8 ...
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Section 11.2 Fourier Expansions I 595 1 −1 2 −2 1 2 3 4 5 6 x y Figure 11.2.3 Approximation of f(x) = x2 −x by partial sums of its Fourier series on [−2, 2] (b) If f is odd, the Fourier series of f on [−L, L] is F (x) = ∞ X n=1 bn sin nπx L , where bn = 2 L Z L 0 f(x) sin nπx L dx. Example 11.2.4 Find the Fourier serie...
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596 Chapter 11 Boundary Value Problems and Fourier Expansions 1 2 3 −1 −2 −3 1 2 3 −1 −2 −3 x y Figure 11.2.4 Approximation of f(x) = x by partial sums of its Fourier series on [−π, π] Theorem 11.2.4 implies that F (x) =    0, x = −π, x, −π < x < π, 0, x = π. Figure 11.2.4 shows how the partial sum Fm(x) = −2 m X n=...
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Section 11.2 Fourier Expansions I 597 and, if n ≥1, an = 2 π Z π 0 x cos nx dx = 2 nπ  x sin nx π 0 − Z π 0 sin nx dx  = 2 n2π cos nx π 0 = 2 n2π (cos nπ −1) = 2 n2π [(−1)n −1]. Therefore F (x) = π 2 + 2 π X n=0 (−1)n −1 n2 cos nx. (11.2.12) However, since (−1)n −1 =  0 if n = 2m, −2 if n = 2m + 1, the terms in (11....
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598 Chapter 11 Boundary Value Problems and Fourier Expansions Example 11.2.7 (Gibbs Phenomenon) The Fourier series of f(x) =      0, −1 < x < −1 2, 1, −1 2 < x < 1 2, 0, 1 2 < x < 1 on [−1, 1] is F (x) = 1 2 + 2 π ∞ X n=1 (−1)n−1 2n −1 cos(2n −1)πx. (Verify.) According to Theorem 11.2.4, F (x) =          ...
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Section 11.2 Fourier Expansions I 599 1 −1 y = 1.00 y = 1.09 y = − .09 x y Figure 11.2.7 The Gibbs Phenomenon: Example 11.2.7, N = 30 USING TECHNOLOGY The computation of Fourier coefficients will be tedious in many of the exercises in this chapter and the next. To learn the technique, we recommend that you do some exerc...
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600 Chapter 11 Boundary Value Problems and Fourier Expansions 6. C L = π; f(x) = x cos x 7. L = π; f(x) = |x| cosx 8. C L = π; f(x) = x sin x 9. L = π; f(x) = |x| sinx 10. L = 1; f(x) =        0, −1 < x < 1 2, cos πx, −1 2 < x < 1 2, 0, 1 2 < x < 1 11. L = 1; f(x) =        0, −1 < x < 1 2, x cos πx, −1 2 ...
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Section 11.2 Fourier Expansions I 601 21. Find the Fourier series of f(x) = (x −π) cos x on [−π, π]. 22. Find the Fourier series of f(x) = (x −π) sin x on [−π, π]. 23. Find the Fourier series of f(x) = sin kx (k ̸= integer) on [−π, π]. 24. Find the Fourier series of f(x) = cos kx (k ̸= integer) on [−π, π]. 25. (a) Supp...
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602 Chapter 11 Boundary Value Problems and Fourier Expansions and An = 2 L Z L 0 f(x) cos 2nπx L dx, Bn = 2 L Z L 0 f(x) sin 2nπx L dx, n = 1, 2, 3, . . .. L − L x y Figure 11.2.8 y = f(x), where f(x + L) = f(x), −L < x < 0 − L L x y Figure 11.2.9 y = f(x), where f(x + L) = −f(x), −L < x < 0 28. Show that if f is integ...
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Section 11.3 Fourier Expansions II 603 (a) Show that Z b a (f(x) −Fm(x))φn(x) dx = 0, n = 1, 2, . . ., m. (b) Show that Z b a (f(x) −Fm(x))2 dx ≤ Z b a (f(x) −Pm(x))2 dx, with equality if and only if an = cn, n = 1, 2, . . ., m. (c) Show that Z b a (f(x) −Fm(x))2 dx = Z b a f2(x) dx − m X n=1 c2 n Z b a φ2 n dx. (d) Co...
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604 Chapter 11 Boundary Value Problems and Fourier Expansions In this section we discuss Fourier expansions in terms of the eigenfunctions of Problems 1-4 for Sec- tion 11.1. Fourier Cosine Series From Exercise 11.1.20, the eigenfunctions 1, cos πx L , cos 2πx L , . . ., cos nπx L , . . . of the boundary value problem ...
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Section 11.3 Fourier Expansions II 605 L − L y = f(x) y = f(−x) x y Figure 11.3.1 Example 11.3.1 Find the Fourier cosine series of f(x) = x on [0, L]. Solution The coefficients are a0 = 1 L Z L 0 x dx = 1 L x2 2 L 0 = L 2 and, if n ≥1 an = 2 L Z L 0 x cos nπx L dx = 2 nπ " x sin nπx L L 0 − Z L 0 sin nπx L dx # = −2 nπ ...
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606 Chapter 11 Boundary Value Problems and Fourier Expansions From Exercise 11.1.19, the eigenfunctions sin πx L , sin 2πx L , . . ., sin nπx L , . . . of the boundary value problem y′′ + λy = 0, y(0) = 0, y(L) = 0 (Problem 1) are orthogonal on [0, L]. If f is integrable on [0, L] then the Fourier expansion of f in ter...
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Section 11.3 Fourier Expansions II 607 L − L y = f(x) y = − f(−x) x y Figure 11.3.2 Solution The coefficients are bn = 2 L Z L 0 x sin nπx L dx = −2 nπ " x cos nπx L L 0 − Z L 0 cos nπx L dx # = (−1)n+1 2L nπ + 2L n2π2 sin nπx L L 0 = (−1)n+1 2L nπ . Therefore S(x) = −2L π ∞ X n=1 (−1)n n sin nπx L . Theorem 11.3.2 impl...
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608 Chapter 11 Boundary Value Problems and Fourier Expansions (Problem 4) are orthogonal on [0, L]. If f is integrable on [0, L] then the Fourier expansion of f in terms of these functions is ∞ X n=1 cn cos (2n −1)πx 2L , where cn = Z L 0 f(x) cos (2n −1)πx 2L dx Z L 0 cos2 (2n −1)πx L dx = 2 L Z L 0 f(x) cos (2n −1)πx...
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Section 11.3 Fourier Expansions II 609 Theorem 11.3.3 If f is piecewise smooth on [0, L], then the mixed Fourier cosine series CM(x) = ∞ X n=1 cn cos (2n −1)πx 2L of f on [0, L], with cn = 2 L Z L 0 f(x) cos (2n −1)πx 2L dx, converges for all x in [0, L]; moreover, CM(x) =              f(0+) if x = 0 f(x) ...
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610 Chapter 11 Boundary Value Problems and Fourier Expansions where dn = Z L 0 f(x) sin (2n −1)πx 2L dx Z L 0 sin2 (2n −1)πx 2L dx = 2 L Z L 0 f(x) sin (2n −1)πx 2L dx. We’ll call this expansion the mixed Fourier sine series of f on [0, L]. It can be shown (Exercise 58) that the mixed Fourier sine series of f on [0, L]...
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Section 11.3 Fourier Expansions II 611 converges for all x in [0, L]; moreover, SM (x) =              0 if x = 0 f(x) if 0 < x < L and f is continuous at x f(x−) + f(x+) 2 if 0 < x < L and f is discontinuous at x f(L−) if x = L. Example 11.3.4 Find the mixed Fourier sine series of f(x) = x on [0, L]. Solut...
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612 Chapter 11 Boundary Value Problems and Fourier Expansions with bn = −2L n2π2 Z L 0 f′′(x) sin nπx L dx. (11.3.5) (c) If f′(0) = f(L) = 0, then f(x) = ∞ X n=1 cn cos (2n −1)πx 2L , 0 ≤x ≤L, with cn = − 8L (2n −1)2π2 Z L 0 f′′(x) cos (2n −1)πx 2L dx. (11.3.6) (d) If f(0) = f′(L) = 0, then f(x) = ∞ X n=1 dn sin (2n −1...
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Section 11.3 Fourier Expansions II 613 Solution Here a0 = 1 L Z L 0 (3Lx2 −2x3) dx = 1 L  Lx3 −x4 2  L 0 = L3 2 and an = 2 L Z L 0 (3Lx2 −2x3) cos nπx L dx, n ≥1. Evaluating this integral directly is laborious. However, since f′(x) = 6Lx −6x2, we see that f′(0) = f′(L) = 0. Since f′′′(x) = −12, we see from (11.3.4) t...
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614 Chapter 11 Boundary Value Problems and Fourier Expansions Therefore CM(x) = 32L3 π3 ∞ X n=1 1 (2n −1)3  (−1)n5 + 18 (2n −1)π  cos (2n −1)πx 2L . Example 11.3.8 Find the mixed Fourier sine expansion of f(x) = x(2x2 −9Lx + 12L2) on [0, L]. Solution Since f(0) = f′(L) = 0, and f′′(x) = 6(2x −3L), we see from (11.3.7...
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Section 11.3 Fourier Expansions II 615 In Exercises 11-17 find the Fourier sine series. 11. C f(x) = 1; [0, L] 12. C f(x) = 1 −x; [0, 1] 13. f(x) = cos kx (k ̸= integer); [0, π] 14. C f(x) =  1, 0 ≤x ≤L 2 0, L 2 < x < L; [0, L] 15. C f(x) =  x, 0 ≤x ≤L 2 , L −x, L 2 ≤x ≤L; [0, L]. 16. C f(x) = x sinx; [0, π] 17. f(x) ...
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616 Chapter 11 Boundary Value Problems and Fourier Expansions (b) In addition to the assumptions of Theorem 11.3.5(b), suppose f′′(0) = f′′(L) = 0, f′′′ is continuous, and f(4) is piecewise continuous on [0, L]. Show that bn = 2L3 n4π4 Z L 0 f(4)(x) sin nπx L dx, n ≥1. In Exercises 36-41 use Theorem 11.3.5(b) or, where...
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Section 11.3 Fourier Expansions II 617 53. f(x) = (x −L)3 + L3 54. f(x) = x(x2 −3L2) 55. f(x) = x3(3x −4L) 56. f(x) = x(x3 −2Lx2 + 2L3) 57. Show that the mixed Fourier cosine series of f on [0, L] is the restriction to [0, L] of the Fourier cosine series of f3(x) =  f(x), 0 ≤x ≤L, −f(2L −x), L < x ≤2L on [0, 2L]. Use ...
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CHAPTER 12 Fourier Solutions of Partial Differential IN THIS CHAPTER we use the series discussed in Chapter 11 to solve partial differential equations that arise in problems of mathematical physics. SECTION 12.1 deals with the partial differential equation ut = a2uxx, which arises in problems of conduction of heat. SEC...
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Section 12.1 The Heat Equation 619 12.1 THE HEAT EQUATION We begin the study of partial differential equations with the problem of heat flow in a uniform bar of length L, situated on the x axis with one end at the origin and the other at x = L (Figure 12.1.1). We assume that the bar is perfectly insulated except possibl...
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620 Chapter 12 Fourier Solutions of Partial Differential for all (x, t). Since vt = XT ′ and vxx = X′′T, vt = a2vxx if and only if XT ′ = a2X′′T, which we rewrite as T ′ a2T = X′′ X . Since the expression on the left is independent of x while the one on the right is independent of t, this equation can hold for all (x, ...
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Section 12.1 The Heat Equation 621 Definition 12.1.1 The formal solution of the initial-boundary value problem ut = a2uxx, 0 < x < L, t > 0, u(0, t) = 0, u(L, t) = 0, t > 0, u(x, 0) = f(x), 0 ≤x ≤L (12.1.4) is u(x, t) = ∞ X n=1 αne−n2π2a2t/L2 sin nπx L , (12.1.5) where S(x) = ∞ X n=1 αn sin nπx L is the Fourier sine ser...
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622 Chapter 12 Fourier Solutions of Partial Differential Example 12.1.1 Solve (12.1.4) with f(x) = x(x2 −3Lx + 2L2). Solution From Example 11.3.6, the Fourier sine series of f on [0, L] is S(x) = 12L3 π3 ∞ X n=1 1 n3 sin nπx L . Therefore u(x, t) = 12L3 π3 ∞ X n=1 1 n3 e−n2π2a2t/L2 sin nπx L . If both ends of bar are i...
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Section 12.1 The Heat Equation 623 Definition 12.1.4 The formal solution of the initial-boundary value problem ut = a2uxx, 0 < x < L, t > 0, u(0, t) = 0, ux(L, t) = 0, t > 0, u(x, 0) = f(x), 0 ≤x ≤L (12.1.7) is u(x, t) = ∞ X n=1 αne−(2n−1)2π2a2t/4L2 sin (2n −1)πx 2L , where SM(x) = ∞ X n=1 αn sin (2n −1)πx 2L is the mix...
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624 Chapter 12 Fourier Solutions of Partial Differential L x u y = x Figure 12.1.2 Example 12.1.4 Solve (12.1.8) with f(x) = x −L. Solution From Example 11.3.3, the mixed Fourier cosine series of f on [0, L] is CM(x) = −8L π2 ∞ X n=1 1 (2n −1)2 cos (2n −1)πx 2L . Therefore u(x, t) = −8L π2 ∞ X n=1 1 (2n −1)2 e−(2n−1)2π...
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Section 12.1 The Heat Equation 625 so u satisfies (12.1.9) if v satisfies vt = a2vxx + a2q′′(x) + h(x), 0 < x < L, t > 0, v(0, t) = u0 −q(0), v(L, t) = uL −q(L), t > 0, v(x, 0) = f(x) −q(x), 0 ≤x ≤L. This reduces to vt = a2vxx, 0 < x < L, t > 0, v(0, t) = 0, v(L, t) = 0, t > 0, v(x, 0) = f(x) −q(x), 0 ≤x ≤L (12.1.11) if ...
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626 Chapter 12 Fourier Solutions of Partial Differential or u(0, t) = u0, ux(L, t) = uL, t > 0; however, this isn’t true in general for the boundary conditions ux(0, t) = u0, ux(L, t) = uL, t > 0. (See Exercise 47.) USING TECHNOLOGY Numerical experiments can enhance your understanding of the solutionsof initial-boundar...
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Section 12.1 The Heat Equation 627 12.1 Exercises 1. Explain Definition 12.1.3. 2. Explain Definition 12.1.4. 3. Explain Definition 12.1.5. 4. C Perform numerical experiments with the formal solution obtained in Example 12.1.1. 5. C Perform numerical experiments with the formal solution obtained in Example 12.1.2. 6. C Pe...
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628 Chapter 12 Fourier Solutions of Partial Differential 17. C ut = 9uxx, 0 < x < 4, t > 0, ux(0, t) = 0, ux(4, t) = 0, t > 0, u(x, 0) = x2, 0 ≤x ≤4 18. ut = 4uxx, 0 < x < 2, t > 0, ux(0, t) = 0, ux(2, t) = 0, t > 0, u(x, 0) = x(x −4), 0 ≤x ≤2 19. C ut = 9uxx, 0 < x < 1, t > 0, ux(0, t) = 0, ux(1, t) = 0, t > 0, u(x, 0...
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Section 12.1 The Heat Equation 629 32. ut = uxx, 0 < x < 1, t > 0, u(0, t) = 0, ux(1, t) = 0, t > 0, u(x, 0) = x(x3 −2x2 + 2), 0 ≤x ≤1 33. ut = 3uxx, 0 < x < π, t > 0, ux(0, t) = 0, u(π, t) = 0, t > 0, u(x, 0) = x2(π −x), 0 ≤x ≤π 34. ut = 16uxx, 0 < x < 2π, t > 0, ux(0, t) = 0, u(2π, t) = 0, t > 0, u(x, 0) = 4, 0 ≤x ≤2...
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630 Chapter 12 Fourier Solutions of Partial Differential 45. C ut = a2uxx, 0 < x < L, t > 0, ux(0, t) = 0, u(L, t) = 0, t > 0, u(x, 0) =  1, 0 ≤x ≤L 2 , 0, L 2 < x < L 46. C ut = a2uxx, 0 < x < L, t > 0, u(0, t) = 0, ux(L, t) = 0, t > 0, u(x, 0) =  1, 0 ≤x ≤L 2 , 0, L 2 < x < L 47. Let h be continuous on [0, L] and l...
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Section 12.2 The Wave Equation 631 (a) Show that u is defined for (x, t) such that t > 0. (b) For fixed t > 0, use Theorem 12.1.2 with z = x to show that ux(x, t) = π L ∞ X n=1 nαne−n2π2a2t/L2 cos nπx L , −∞< x < ∞. (c) Starting from the result of (a), use Theorem 12.1.2 with z = x to show that, for a fixed t > 0, uxx(x, ...
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632 Chapter 12 Fourier Solutions of Partial Differential Equations L x u Figure 12.2.1 A stretched string 1. The mass density (mass per unit length) ρ of the string is constant throughout the string. 2. The tension T induced by tightly stretching the string along the x-axis is so great that all other forces, such as gr...
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Section 12.2 The Wave Equation 633 T1 θ2 T2 x u θ1 Figure 12.2.2 A segment of the displaced string where ∆s is the length of the segment and x is the abscissa of the center of mass; hence, x < x < x + ∆x. From calculus, we know that ∆s = Z x+∆x x p 1 + u2x(σ, t) dσ; however, because of (12.2.2), we make the approximati...
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634 Chapter 12 Fourier Solutions of Partial Differential Equations Letting ∆x →0 yields uxx(x, t) = ρ T utt(x, t), which we rewrite as utt = a2uxx, with a2 = T/ρ. The Formal Solution As in Section 12.1, we use separation of variables to obtain a suitable definition for the formal solution of (12.2.1). We begin by lookin...
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Section 12.2 The Wave Equation 635 Then ∂vn ∂t (x, t) =  −nπa L αn sin nπat L + βn cos nπat L  sin nπx L , so vn(x, 0) = αn sin nπx L and ∂vn ∂t (x, 0) = βn sin nπx L . Therefore vn satisfies (12.2.1) with f(x) = αn sin nπx/L and g(x) = βn cos nπx/L. More generally, if α1, α2, ..., αm and β1, β2,..., βm are constants ...
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636 Chapter 12 Fourier Solutions of Partial Differential Equations yields cos nπat L sin nπx L = 1 2  sin nπ(x + at) L + sin nπ(x −at) L  (12.2.10) and sin nπat L sin nπx L = −1 2  cos nπ(x + at) L −cos nπ(x −at) L  = nπ 2L Z x+at x−at sin nπτ L dτ. (12.2.11) From (12.2.10), ∞ X n=1 αn cos nπat L sin nπx L = 1 2 ∞ ...
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Section 12.2 The Wave Equation 637 Proof Throughout this proof, k denotes an integer. Since f is differentiable on the open interval (0, L), both p and q are differentiable on every open interval ((k −1)L, kL). Thus, we need only to determine whether p and q are differentiable at x = kL for every k. (a) From Figure 12....
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638 Chapter 12 Fourier Solutions of Partial Differential Equations Theorem 12.2.4 The formal solution of (12.2.1) is an actual solution if g is differentiable on [0, L] and g(0) = g(L) = 0, (12.2.15) while f is twice differentiable on [0, L] and f(0) = f(L) = 0 (12.2.16) and f′′ +(0) = f′′ −(L) = 0. (12.2.17) Proof We ...
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Section 12.2 The Wave Equation 639 Solution We leave it to you to verify that f and g satisfy the assumptions of Theorem 12.2.4. From Exercise 11.3.39, Sf(x) = 96L4 π5 ∞ X n=1 1 (2n −1)5 sin (2n −1)πx L . From Exercise 11.3.36, Sg(x) = 8L2 π3 ∞ X n=1 1 (2n −1)3 sin (2n −1)πx L . From (12.2.8), u(x, t) = 96L4 π5 ∞ X n=1...
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640 Chapter 12 Fourier Solutions of Partial Differential Equations L .5 L .5 L x y Figure 12.2.7 Graph of (12.2.21) which converges to f for all x in [0, L], by Theorem 11.3.2. Therefore u(x, t) = 4L π2 ∞ X n=1 (−1)n+1 (2n −1)2 cos (2n −1)πat L sin (2n −1)πx L . (12.2.22) This series converges absolutely for all (x, t)...
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Section 12.2 The Wave Equation 641 x = 0 x = L x = 2L x = − L x = − 2L x = − 3L x = 3L x y − .5L .5L Figure 12.2.8 The odd periodic extension of (12.2.21) x = 0 x = L x = 2L x = − L x = − 2L x = − 3L x = 3L x y .5L − .5L Figure 12.2.9 Graphs of y = Sf(x −at) (dashed) and y = Sf(x −at) (solid), with f as in (12.2.21) In...
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642 Chapter 12 Fourier Solutions of Partial Differential Equations L at .5L .5L x =.5L − at x =.5L + at x y Figure 12.2.10 The part of the graph from Figure 12.2.9 on [0, L] L .5L y = .5L − at x =.5L + at x = .5L − at x y Figure 12.2.11 The graph of (12.2.23) on [0, L] for a fixed t in (0, L/2a) USING TECHNOLOGY Althoug...
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Section 12.2 The Wave Equation 643 12.2 Exercises In Exercises 1-15 solve the initial-boundary value problem. In some of these exercises, Theorem 11.3.5(b) or Exercise 11.3.35 will simplify the computation of the coefficients in the Fourier sine series. 1. utt = 9uxx, 0 < x < 1, t > 0, u(0, t) = 0, u(1, t) = 0, t > 0, u...
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644 Chapter 12 Fourier Solutions of Partial Differential Equations 14. utt = 9uxx, 0 < x < 1, t > 0, u(0, t) = 0, u(1, t) = 0, t > 0, u(x, 0) = x(3x4 −10x2 + 7), ut(x, 0) = 0, 0 ≤x ≤1 15. C utt = 9uxx, 0 < x < 1, t > 0, u(0, t) = 0, u(1, t) = 0, t > 0, u(x, 0) = 0 ut(x, 0) = x(3x4 −10x2 + 7), 0 ≤x ≤1 16. We saw that th...
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Section 12.2 The Wave Equation 645 are the mixed Fourier cosine series of f and g on [0, L]; that is, αn = 2 L Z L 0 f(x) cos (2n −1)πx 2L dx and βn = 2 L Z L 0 g(x) cos (2n −1)πx 2L dx. In Exercises 18-31, use Exercise 17 to solve the initial-boundaryvalue problem. In some of these exercises Theorem 11.3.5(c) or Exerc...
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646 Chapter 12 Fourier Solutions of Partial Differential Equations 30. utt = uxx, 0 < x < 1, t > 0, ux(0, t) = 0, u(1, t) = 0, t > 0, u(x, 0) = x4 −4x3 + 6x2 −3, ut(x, 0) = 0, 0 ≤x ≤1 31. utt = uxx, 0 < x < 1, t > 0, ux(0, t) = 0, u(1, t) = 0, t > 0, u(x, 0) = 0, ut(x, 0) = x4 −4x3 + 6x2 −3, 0 ≤x ≤1 32. Adapt the proof...
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Section 12.2 The Wave Equation 647 38. C utt = 9uxx, 0 < x < 1, t > 0, u(0, t) = 0, ux(1, t) = 0, t > 0, u(x, 0) = 0, ut(x, 0) = x2(3 −2x), 0 ≤x ≤1 39. utt = 9uxx, 0 < x < 1, t > 0, u(0, t) = 0, ux(1, t) = 0, t > 0, u(x, 0) = (x −1)3 + 1, ut(x, 0) = 0, 0 ≤x ≤1 40. utt = 3uxx, 0 < x < π, t > 0, u(0, t) = 0, ux(π, t) = 0...
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648 Chapter 12 Fourier Solutions of Partial Differential Equations are the Fourier cosine series of f and g on [0, L]; that is, α0 = 1 L Z L 0 f(x) dx, β0 = 1 L Z L 0 g(x) dx, αn = 2 L Z L 0 f(x) cos nπx L dx, and βn = 2 L Z L 0 g(x) cos nπx L dx, n = 1, 2, 3, . . .. In Exercises 50-59 use Exercise 49 to solve the init...
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Section 12.2 The Wave Equation 649 62. Suppose λ and µ are constants and either pn(x) = cos nλx or pn(x) = sin nλx, while either qn(t) = cos nµt or qn(t) = sin nµt for n = 1, 2, 3, .... Let u(x, t) = ∞ X n=1 knpn(x)qn(t), (A) where {kn}∞ n=1 are constants. (a) Show that if P∞ n=1 |kn| converges then u(x, t) converges f...
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650 Chapter 12 Fourier Solutions of Partial Differential Equations (c) Solve utt = a2uxx, −∞< t < ∞, t > 0, u(x, 0) = f(x), ut(x, 0) = g(x), −∞< x < ∞. In Exercises 64-68 use the result of Exercise 63 to find a solution of utt = a2uxx, −∞< x < ∞ that satisfies the given initial conditions. 64. u(x, 0) = x, ut(x, 0) = 4ax...
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Section 12.3 Laplace’s Equation in Rectangular Coordinates 651 y x a b Figure 12.3.1 A rectangular region and its boundary where α, β, γ, and δ can each be either 0 or 1; thus, there are 16 possibilities. Let BVP(α, β, γ, δ)(f0, f1, g0, g1) denote the problem of finding a solution of (12.3.2) that satisfies these conditi...
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652 Chapter 12 Fourier Solutions of Partial Differential Equations BVP(α, β, γ, δ)(0, 0, g0, 0), and BVP(α, β, γ, δ)(0, 0, 0, g1) is a solution of BVP(α, β, γ, δ)(f0, f1, g0, g1). Therefore we concentrate on problems where only one of the functions f0, f1, g0, g2 isn’t identically zero. There are 64 (count them!) probl...
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Section 12.3 Laplace’s Equation in Rectangular Coordinates 653 y x a b uxx + uyy = 0 u(x,0) = f(x) u(x,b) = 0 u(0,y) = 0 u(a,y) = 0 Figure 12.3.4 The boundary value problem (12.3.4) however, because of the nonhomogeneous Dirichlet condition at y = 0, it’s better to require that Yn(0) = 1, which can be achieved by divid...
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654 Chapter 12 Fourier Solutions of Partial Differential Equations is the Fourier sine series of f on [0, a]; that is, αn = 2 a Z a 0 f(x) sin nπx a dx, n = 1, 2, 3, . . .. If y < b then sinh nπ(b −y)/a sinh nπb/a ≈e−nπy/a (12.3.9) for large n, so the series in (12.3.8) converges if 0 < y < b; moreover, since also cosh...
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Section 12.3 Laplace’s Equation in Rectangular Coordinates 655 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 0 0.2 0.4 0.6 0.8 1 0 0.5 1 1.5 2 2.5 3 Figure 12.3.5 1 2 1 2 3 x y Figure 12.3.6 Example 12.3.3 Define the formal solution of uxx + uyy = 0, 0 < x < a, 0 < y < b, u(x, 0) = 0, uy(x, b) = f(x), 0 ≤x ≤a, ux(0, y) = 0, ux(...
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656 Chapter 12 Fourier Solutions of Partial Differential Equations X′(a) = Y (0) = 0; hence, we let k = −λ in (12.3.3). Thus, X and Y must satisfy X′′ + λX = 0, X′(0) = 0, X′(a) = 0 (12.3.12) and Y ′′ −λY = 0, Y (0) = 0. (12.3.13) From Theorem 11.1.3, the eigenvalues of (12.3.12) are λ = 0, with associated eigenfunctio...
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Section 12.3 Laplace’s Equation in Rectangular Coordinates 657 Example 12.3.4 Solve (12.3.11) with f(x) = x. Solution From Example 11.3.1, C(x) = a 2 −4a π2 ∞ X n=1 1 (2n −1)2 cos (2n −1)πx a . Therefore u(x, y) = ay 2 −4a2 π3 ∞ X n=1 sinh(2n −1)πy/a (2n −1)3 cosh(2n −1)πb/a cos (2n −1)πx a . (12.3.15) For graphing pur...
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658 Chapter 12 Fourier Solutions of Partial Differential Equations y x a b uxx + uyy = 0 u(x,0) = 0 uy(x,b) = 0 u(0,y) = g(y) ux(a,y) = 0 Figure 12.3.10 The boundary value problem (12.3.16) and Y ′′ + λY = 0, Y (0) = 0, Y ′(b) = 0. (12.3.18) From Theorem 11.1.4, the eigenvalues of (12.3.18) are λn = (2n −1)2π2/4b2, wit...
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Section 12.3 Laplace’s Equation in Rectangular Coordinates 659 Therefore vn satisfies (12.3.16) with g(y) = sin(2n −1)πy/2b. More generally, if α1, ..., αm are arbitrary constants then um(x, y) = m X n=1 αn cosh(2n −1)π(x −a)/2b cosh(2n −1)πa/2b sin (2n −1)πy 2b satisfies (12.3.16) with g(y) = m X n=1 αn sin (2n −1)πy 2b...
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660 Chapter 12 Fourier Solutions of Partial Differential Equations y x a b uxx + uyy = 0 uy(x,0) = 0 u(x,b) = 0 ux(0,y) = 0 ux(a,y) = g(y) Figure 12.3.11 The boundary value problem (12.3.20) From Theorem 11.1.4, the eigenvalues of (12.3.22) are λn = (2n −1)2π2/4b2, with associated eigen- functions Yn = cos (2n −1)πy 2b...
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Section 12.3 Laplace’s Equation in Rectangular Coordinates 661 satisfies (12.3.20) with g(y) = ∞ X n=1 αn cos (2n −1)πy 2b . Therefore, if g is an arbitrary piecewise smooth function on [0, b], we define the formal solution of (12.3.20) to be u(x, y) = 2b π ∞ X n=1 αn cosh(2n −1)πx/2b (2n −1) sinh(2n −1)πa/2b cos (2n −1)...
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662 Chapter 12 Fourier Solutions of Partial Differential Equations y x a uxx + uyy = 0 u(x,0) = f(x) u(0,y) = 0 u(a,y) = 0 Figure 12.3.12 A boundary value problem on a semi-infinite strip Example 12.3.9 Define the bounded formal solution of (12.3.24). Solution Proceeding as in the solution of Example 12.3.1, we find that ...
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Section 12.3 Laplace’s Equation in Rectangular Coordinates 663 See Exercises 29-34 for other boundary value problems on a semi-infinite strip. 12.3 Exercises In Exercises 1-16 apply the definition developed in Example 1 to solve the boundary value problem. (Use Theorem 11.3.5 where it applies.) Where indicated by C , gra...
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664 Chapter 12 Fourier Solutions of Partial Differential Equations 13. C uxx + uyy = 0, 0 < x < 1, 0 < y < π, uy(x, 0) = 0, u(x, π) = 0, 0 ≤x ≤1, ux(0, y) = 0, ux(1, y) = sin y, 0 ≤y ≤π 14. uxx + uyy = 0, 0 < x < 2, 0 < y < 3, uy(x, 0) = 0, u(x, 3) = 0, 0 ≤x ≤2, ux(0, y) = 0, ux(2, y) = y(3 −y), 0 ≤y ≤3 15. uxx + uyy =...
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Section 12.3 Laplace’s Equation in Rectangular Coordinates 665 25. C uy(x, 0) = 0, u(x, b) = 0, 0 < x < a, ux(0, y) = 0, u(a, y) = g(y), 0 < y < b a = 2, b = 2, g(y) = 4 −y2 26. u(x, 0) = 0, u(x, b) = 0, 0 < x < a, ux(0, y) = 0, ux(a, y) = g(y), 0 < y < b a = 1, b = 4, g(y) =  y, 0 ≤y ≤2, 4 −y, 2 ≤y ≤4 27. u(x, 0) = 0...
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666 Chapter 12 Fourier Solutions of Partial Differential Equations has no solution unless Z a 0 f0(x) dx = Z a 0 f1(x) dx = Z b 0 g0(y) dy = Z b 0 g1(y) dy = 0. In this case it has infinitely many formal solutions. Find them. 37. In this exercise take it as given that the infinite series P∞ n=1 npe−qn converges for all p...
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Section 12.4 Laplace’s Equation in Polar Coordinates 667 (g) Conclude that u satisfies Laplace’s equation for all (x, y) such that 0 < y < b. By repeatedly applying the arguments in (c)–(f), it can be shown that u can be differentiated term by term any number of times with respect to x and/or y if 0 < y < b. 12.4 LAPLAC...
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668 Chapter 12 Fourier Solutions of Partial Differential Equations We first look for products v(r, θ) = R(r)Θ(θ) that satisfy (12.4.1). For this function, vrr + 1 r vr + 1 r2 vθθ = R′′Θ + 1 r R′Θ + 1 r2 RΘ′′ = 0 for all (r, θ) with r ̸= 0 if r2R′′ + rR′ R = −Θ′′ Θ = λ, where λ is a separation constant. (Verify.) This eq...
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Section 12.4 Laplace’s Equation in Polar Coordinates 669 so the general solution of (12.4.6) is Rn = c1rn + c2r−n, (12.4.7) by Theorem 7.4.3. Consistent with our previous assumption on R0, we now require Rn to be bounded as r →0+. This implies that c2 = 0, and we choose c1 = ρ−n. Then Rn(r) = rn/ρn, so vn(r, θ) = Rn(r)...
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670 Chapter 12 Fourier Solutions of Partial Differential Equations Solution From Example 11.2.6, θ(π2 −θ2) = 12 ∞ X n=1 (−1)n n3 sin nθ, −π ≤θ ≤π, so u(r, θ) = 12 ∞ X n=1 rn ρn (−1)n n3 sin nθ, 0 ≤r ≤ρ, −π ≤θ ≤π. Example 12.4.2 Define the formal solution of urr + 1 r ur + 1 r2 uθθ = 0, ρ0 < r < ρ, −π ≤θ < π, u(ρ0, θ) = ...
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Section 12.4 Laplace’s Equation in Polar Coordinates 671 satisfy these requirements. Therefore v0(ρ, θ) = lnr/ρ0 ln ρ/ρ0 and vn(r, θ) = ρ−n 0 rn −ρn 0 r−n ρ−n 0 ρn −ρn 0 ρ−n (αn cos nθ + βn sin nθ), n = 1, 2, 3, . . ., where αn and βn are arbitrary constants. If α0, α1,..., αm and β1, β2, ..., βm are arbitrary constant...
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672 Chapter 12 Fourier Solutions of Partial Differential Equations ur r + r−1 ur + r−2 uθ θ = 0 u(ρ,θ) = f(θ) u(r,γ) = 0 γ x y Figure 12.4.3 The boundary value problem (12.4.10) The indicial polynomial of this equation is s(s −1) + s −n2π2 γ2 =  s −nπ γ   s + nπ γ  , so Rn = c1rnπ/γ + c2r−nπ/γ, by Theorem 7.4.3. To...
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Section 12.4 Laplace’s Equation in Polar Coordinates 673 This motivates us to define the bounded formal solution of (12.4.10) to be um(r, θ) = ∞ X n=1 αn rnπ/γ ρnπ/γ sin nπθ γ , where S(θ) = ∞ X n=1 αn sin nπθ γ is the Fourier sine expansion of f on [0, γ]; that is, αn = 2 γ Z γ 0 f(θ) sin nπθ γ dθ. 12.4 Exercises 1. De...
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674 Chapter 12 Fourier Solutions of Partial Differential Equations 5. Define the formal solution of urr + 1 r ur + 1 r2 uθθ = 0, ρ0 < r < ρ, 0 < θ < γ, ur(ρ0, θ) = g(θ), ur(ρ, θ) = 0, 0 ≤θ ≤γ, u(r, 0) = 0, uθ(r, γ) = 0, ρ0 < r < ρ, where 0 < γ < 2π and 0 < ρ0 < ρ. 6. Define the bounded formal solution of urr + 1 r ur + 1...
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CHAPTER 13 Boundary Value Problems for Second Order Ordinary Differential Equations IN THIS CHAPTER we discuss boundary value problems and eigenvalue problems for linear second order ordinary differential equations. Section 13.1 discusses point two-point boundary value problems for linear second order ordinary differ- ...
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Section 13.1 Two-Point Boundary Value Problems 677 13.1 TWO-POINT BOUNDARY VALUE PROBLEMS In Section 5.3 we considered initial value problems for the linear second order equation P0(x)y′′ + P1(x)y′ + P2(x)y = F (x). (13.1.1) Suppose P0, P1, P2, and F are continuous and P0 has no zeros on an open interval (a, b). From T...
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678 Chapter 13 Boundary Value Problems for Second Order Ordinary Differential Equations This boundary value problem is homogeneous if F = 0 and k1 = k2 = 0; otherwise it’s nonhomoge- neous. We leave it to you (Exercise 1) to verify that B1 and B2 are linear operators; that is, if c1 and c2 are constants then Bi(c1y1 + ...
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Section 13.1 Two-Point Boundary Value Problems 679 Proof Recall that B1(z) = αz(a) + βz′(a) and α2 + β2 ̸= 0. Therefore, if B1(z1) = B1(z2) = 0 then (α, β) is a nontrivial solution of the system αz1(a) + βz′ 1(a) = 0 αz2(a) + βz′(a) = 0. This implies that z1(a)z′ 2(a) −z′ 1(a)z2(a) = 0, so {z1, z2} is linearly dependen...
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680 Chapter 13 Boundary Value Problems for Second Order Ordinary Differential Equations Since the determinant of a product of matrices is the product of the determinants of the matrices, (13.1.8) and (13.1.12) imply (13.1.9). (b) =⇒ (c): Since {y1, y2} is a fundamental set of solutions of Ly = 0, the general solution o...
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Section 13.1 Two-Point Boundary Value Problems 681 Therefore the solution of (13.1.13) can be written as y = x3 + c1x + c2x2. Then y′ = 3x2 + c1 + 2c2x, and imposing the boundary conditions yields the system c1 + c2 = 3 c1 + 4c2 = −9, so c1 = 7 and c2 = −4. Therefore y = x3 + 7x −4x2 is the unique solution of (13.1.13)...
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682 Chapter 13 Boundary Value Problems for Second Order Ordinary Differential Equations Theorem 13.1.3 Suppose the homogeneous boundary value problem Ly = 0, B1(y) = 0, B2(y) = 0 (13.1.15) has only the trivial solution. Let y1 and y2 be linearly independent solutions of Ly = 0 such that B1(y1) = 0 and B2(y2) = 0, and l...
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Section 13.1 Two-Point Boundary Value Problems 683 This is the Green’s function for the boundary value problem (13.1.16). The Green’s function is related to the boundary value problem (13.1.16) in much the same way that the inverse of a square matrix A is related to the linear algebraic system y = Ax; just as we substi...
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684 Chapter 13 Boundary Value Problems for Second Order Ordinary Differential Equations The Green’s function is G(x, t) =        (cos t −sin t)(cos x + sin x) 2 , 0 ≤t ≤x, (cos x −sin x)(cos t + sin t) 2 , x ≤t ≤π. We’ll now consider the situation not covered by Theorem 13.1.3. Theorem 13.1.4 Suppose the homogen...
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Section 13.1 Two-Point Boundary Value Problems 685 Example 13.1.7 Applying Theorem 13.1.4 to the boundary value problem y′′ + y = F (x), y(0) = 0, y(π) = 0 (13.1.25) explains the Examples 13.1.2 and 13.1.3. The complementary equation y′′ + y = 0 has the linear inde- pendent solutions y1 = sin x and y2 = cos x, and y1 s...
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686 Chapter 13 Boundary Value Problems for Second Order Ordinary Differential Equations 9. (a) State a condition on a and b such that the boundary value problem y′′ + y = F (x), y(a) = 0, y(b) = 0 (A) has a unique solution for every continuous F , and find the solution by the method used to prove Theorem 13.1.3 (b) In t...
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Section 13.1 Two-Point Boundary Value Problems 687 22. Find the Green’s function for the boundary value problem y′′ = F (x), y(0) −2y′(0) = 0, y(1) + 2y′(1) = 0. (A) Then use the Green’s function to solve (A) with (a) F (x) = 1, (b) F (x) = x, and (c) F (x) = x2. 23. Find the Green’s function for the boundary value pro...
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688 Chapter 13 Boundary Value Problems for Second Order Ordinary Differential Equations 13.2 STURM-LIOUVILLE PROBLEMS In this section we consider eigenvalue problems of the form P0(x)y′′ + P1(x)y′ + P2(x)y + λR(x)y = 0, B1(y) = 0, B2(y) = 0, (13.2.1) where B1(y) = αy(a) + βy′(a) and B2(y) = ρy(b) + δy′(b). As in Sectio...
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