梁的振动特征函数分析2
问题7:左端固定、右端自由梁的振动分析
考虑梁的振动方程:
utt+Kuxxxx=0,0<x<l,K>0
u_{tt} + K u_{xxxx} = 0, \quad 0 < x < l, \quad K > 0
utt+Kuxxxx=0,0<x<l,K>0
边界条件:
- 左端固定(位移和斜率为零):u(0,t)=0 u(0,t) = 0 u(0,t)=0, ux(0,t)=0 u_x(0,t) = 0 ux(0,t)=0
- 右端自由(无弯矩和剪力):uxx(l,t)=0 u_{xx}(l,t) = 0 uxx(l,t)=0, uxxx(l,t)=0 u_{xxx}(l,t) = 0 uxxx(l,t)=0
(a) 频率方程和特征函数
分离变量:u(x,t)=X(x)T(t) u(x,t) = X(x)T(t) u(x,t)=X(x)T(t)。空间方程为:
X(4)−μ4X=0,μ4=λK
X^{(4)} - \mu^4 X = 0, \quad \mu^4 = \frac{\lambda}{K}
X(4)−μ4X=0,μ4=Kλ
通解:
X(x)=Acos(μx)+Bsin(μx)+Ccosh(μx)+Dsinh(μx)
X(x) = A \cos(\mu x) + B \sin(\mu x) + C \cosh(\mu x) + D \sinh(\mu x)
X(x)=Acos(μx)+Bsin(μx)+Ccosh(μx)+Dsinh(μx)
边界条件应用:
- X(0)=0 X(0) = 0 X(0)=0:
A+C=0 ⟹ C=−A A + C = 0 \implies C = -A A+C=0⟹C=−A - X′(0)=0 X'(0) = 0 X′(0)=0:
μ(B+D)=0 ⟹ D=−B \mu(B + D) = 0 \implies D = -B μ(B+D)=0⟹D=−B - X′′(l)=0 X''(l) = 0 X′′(l)=0:
−μ2Acos(μl)−μ2Bsin(μl)+μ2Acosh(μl)+μ2Bsinh(μl)=0 -\mu^2 A \cos(\mu l) - \mu^2 B \sin(\mu l) + \mu^2 A \cosh(\mu l) + \mu^2 B \sinh(\mu l) = 0 −μ2Acos(μl)−μ2Bsin(μl)+μ2Acosh(μl)+μ2Bsinh(μl)=0 - X′′′(l)=0 X'''(l) = 0 X′′′(l)=0:
μ3Asin(μl)−μ3Bcos(μl)+μ3Asinh(μl)+μ3Bcosh(μl)=0 \mu^3 A \sin(\mu l) - \mu^3 B \cos(\mu l) + \mu^3 A \sinh(\mu l) + \mu^3 B \cosh(\mu l) = 0 μ3Asin(μl)−μ3Bcos(μl)+μ3Asinh(μl)+μ3Bcosh(μl)=0
设 β=μl \beta = \mu l β=μl,得齐次系统:
{A(coshβ−cosβ)+B(sinhβ−sinβ)=0A(sinβ+sinhβ)+B(coshβ−cosβ)=0
\begin{cases}
A (\cosh \beta - \cos \beta) + B (\sinh \beta - \sin \beta) = 0 \\
A (\sin \beta + \sinh \beta) + B (\cosh \beta - \cos \beta) = 0
\end{cases}
{A(coshβ−cosβ)+B(sinhβ−sinβ)=0A(sinβ+sinhβ)+B(coshβ−cosβ)=0
非零解要求行列式为零:
(coshβ−cosβ)2−(sinhβ−sinβ)(sinβ+sinhβ)=0
(\cosh \beta - \cos \beta)^2 - (\sinh \beta - \sin \beta)(\sin \beta + \sinh \beta) = 0
(coshβ−cosβ)2−(sinhβ−sinβ)(sinβ+sinhβ)=0
化简得频率方程:
coshβcosβ=1,β=μl
\cosh \beta \cos \beta = 1, \quad \beta = \mu l
coshβcosβ=1,β=μl
特征值和特征函数:
- 方程 coshβcosβ=1 \cosh \beta \cos \beta = 1 coshβcosβ=1 的正根 βn \beta_n βn(β1≈4.730 \beta_1 \approx 4.730 β1≈4.730, β2≈7.853 \beta_2 \approx 7.853 β2≈7.853, β3≈10.996 \beta_3 \approx 10.996 β3≈10.996, …)
- 特征值:λn=Kμn4=K(βn/l)4 \lambda_n = K \mu_n^4 = K (\beta_n / l)^4 λn=Kμn4=K(βn/l)4
- 角频率:ωn=λn=K(βn/l)2 \omega_n = \sqrt{\lambda_n} = \sqrt{K} (\beta_n / l)^2 ωn=λn=K(βn/l)2
- 特征函数:
Xn(x)=cos(μnx)−cosh(μnx)+bn[sin(μnx)−sinh(μnx)] X_n(x) = \cos(\mu_n x) - \cosh(\mu_n x) + b_n \left[ \sin(\mu_n x) - \sinh(\mu_n x) \right] Xn(x)=cos(μnx)−cosh(μnx)+bn[sin(μnx)−sinh(μnx)]
其中 μn=βn/l \mu_n = \beta_n / l μn=βn/l,bn=−coshβn−cosβnsinhβn−sinβn b_n = -\dfrac{\cosh \beta_n - \cos \beta_n}{\sinh \beta_n - \sin \beta_n} bn=−sinhβn−sinβncoshβn−cosβn
注意:无零特征值(λ=0 \lambda = 0 λ=0 仅给出平凡解)。
(b) 图形化求解频率方程
定义函数:
f(β)=coshβcosβ−1
f(\beta) = \cosh \beta \cos \beta - 1
f(β)=coshβcosβ−1
绘制 f(β) f(\beta) f(β) 的图像,其与 β \beta β 轴的交点 (βn,0) (\beta_n, 0) (βn,0) 给出频率 ωn=K(βn/l)2 \omega_n = \sqrt{K} (\beta_n / l)^2 ωn=K(βn/l)2。
- 根的位置:
β1≈4.730 \beta_1 \approx 4.730 β1≈4.730(在 π≈3.14 \pi \approx 3.14 π≈3.14 和 3π/2≈4.71 3\pi/2 \approx 4.71 3π/2≈4.71 之间),
β2≈7.853 \beta_2 \approx 7.853 β2≈7.853(在 2π≈6.28 2\pi \approx 6.28 2π≈6.28 和 5π/2≈7.85 5\pi/2 \approx 7.85 5π/2≈7.85 之间),
β3≈10.996 \beta_3 \approx 10.996 β3≈10.996(在 3π≈9.42 3\pi \approx 9.42 3π≈9.42 和 7π/2≈10.99 7\pi/2 \approx 10.99 7π/2≈10.99 之间)。
Python 绘图代码:
import numpy as np
import matplotlib.pyplot as pltbeta = np.linspace(0, 15, 1000)
f = np.cosh(beta) * np.cos(beta) - 1plt.figure(figsize=(10, 6))
plt.plot(beta, f, label=r'$f(\beta) = \cosh\beta \cos\beta - 1$')
plt.axhline(0, color='r', linestyle='--')
plt.scatter([4.730, 7.853, 10.996], [0, 0, 0], color='k') # 标记前三个根
plt.xlabel(r'$\beta$')
plt.ylabel(r'$f(\beta)$')
plt.title('图形化求解频率方程: $\cosh\beta \cos\beta = 1$')
plt.legend()
plt.grid(True)
plt.show()
© 特征函数正交性证明
考虑特征值问题 X(4)=γX X^{(4)} = \gamma X X(4)=γX(γ=λ/K \gamma = \lambda / K γ=λ/K),边界条件:
X(0)=X′(0)=0,X′′(l)=X′′′(l)=0
X(0) = X'(0) = 0, \quad X''(l) = X'''(l) = 0
X(0)=X′(0)=0,X′′(l)=X′′′(l)=0
设 γm≠γn \gamma_m \neq \gamma_n γm=γn 对应特征函数 Xm,Xn X_m, X_n Xm,Xn:
∫0lXm(4)Xndx=γm∫0lXmXndx
\int_0^l X_m^{(4)} X_n dx = \gamma_m \int_0^l X_m X_n dx
∫0lXm(4)Xndx=γm∫0lXmXndx
分部积分:
∫0lXm(4)Xndx=[Xm′′′Xn−Xm′′Xn′+Xm′Xn′′−XmXn′′′]0l+∫0lXmXn(4)dx
\int_0^l X_m^{(4)} X_n dx = \left[ X_m''' X_n - X_m'' X_n' + X_m' X_n'' - X_m X_n''' \right]_0^l + \int_0^l X_m X_n^{(4)} dx
∫0lXm(4)Xndx=[Xm′′′Xn−Xm′′Xn′+Xm′Xn′′−XmXn′′′]0l+∫0lXmXn(4)dx
边界条件下端点项为零:
γm∫0lXmXndx=γn∫0lXmXndx
\gamma_m \int_0^l X_m X_n dx = \gamma_n \int_0^l X_m X_n dx
γm∫0lXmXndx=γn∫0lXmXndx
(γm−γn)∫0lXmXndx=0
(\gamma_m - \gamma_n) \int_0^l X_m X_n dx = 0
(γm−γn)∫0lXmXndx=0
因 γm≠γn \gamma_m \neq \gamma_n γm=γn,有:
∫0lXm(x)Xn(x)dx=0
\int_0^l X_m(x) X_n(x) dx = 0
∫0lXm(x)Xn(x)dx=0
(d) 特征值简单性证明(奖励)
对特征值 γn \gamma_n γn:
- 通解有四个参数,但四个边界条件:
- X(0)=0 X(0)=0 X(0)=0 和 X′(0)=0 X'(0)=0 X′(0)=0 减少两个自由度
- X′′(l)=0 X''(l)=0 X′′(l)=0 和 X′′′(l)=0 X'''(l)=0 X′′′(l)=0 通过频率方程关联
- 解空间一维,故特征值简单(几何重数为1)
(e) 特征函数草图(奖励)
前几个特征函数(设 l=1,K=1 l=1, K=1 l=1,K=1):
- β1≈4.730 \beta_1 \approx 4.730 β1≈4.730, b1≈−1.00078 b_1 \approx -1.00078 b1≈−1.00078
- β2≈7.853 \beta_2 \approx 7.853 β2≈7.853, b2≈−1.00000 b_2 \approx -1.00000 b2≈−1.00000
- β3≈10.996 \beta_3 \approx 10.996 β3≈10.996, b3≈−1.00000 b_3 \approx -1.00000 b3≈−1.00000
特征函数:
Xn(x)=cos(μnx)−cosh(μnx)+bn[sin(μnx)−sinh(μnx)]
X_n(x) = \cos(\mu_n x) - \cosh(\mu_n x) + b_n \left[ \sin(\mu_n x) - \sinh(\mu_n x) \right]
Xn(x)=cos(μnx)−cosh(μnx)+bn[sin(μnx)−sinh(μnx)]
Python 绘图代码:
import numpy as np
import matplotlib.pyplot as pltl = 1
beta_roots = [4.730, 7.853, 10.996] # 前三个根
b_values = [-1.00078, -1.00000, -1.00000] # 近似 b_nx = np.linspace(0, l, 100)
plt.figure(figsize=(10, 6))for i, (beta, b) in enumerate(zip(beta_roots, b_values)):mu = beta / lX = (np.cos(mu * x) - np.cosh(mu * x) + b * (np.sin(mu * x) - np.sinh(mu * x)))plt.plot(x, X, label=f'$n={i+1}$, $\\beta_{i+1} \\approx {beta}$')plt.title('左端固定、右端自由梁的特征函数')
plt.xlabel('$x$')
plt.ylabel('$X_n(x)$')
plt.legend()
plt.grid(True)
plt.show()
特征函数行为:
- X1(x) X_1(x) X1(x):无节点,左端固定,右端自由
- X2(x) X_2(x) X2(x):一个节点(靠近左端)
- X3(x) X_3(x) X3(x):两个节点
- 所有函数满足:
- 左端:X(0)=0 X(0)=0 X(0)=0, X′(0)=0 X'(0)=0 X′(0)=0
- 右端:X′′(l)=0 X''(l)=0 X′′(l)=0, X′′′(l)=0 X'''(l)=0 X′′′(l)=0
问题8:左端简支、右端自由梁的振动分析
考虑梁的振动方程:
utt+Kuxxxx=0,0<x<l,K>0
u_{tt} + K u_{xxxx} = 0, \quad 0 < x < l, \quad K > 0
utt+Kuxxxx=0,0<x<l,K>0
边界条件:
- 左端简支(位移和弯矩为零):u(0,t)=0 u(0,t) = 0 u(0,t)=0, uxx(0,t)=0 u_{xx}(0,t) = 0 uxx(0,t)=0
- 右端自由(无弯矩和剪力):uxx(l,t)=0 u_{xx}(l,t) = 0 uxx(l,t)=0, uxxx(l,t)=0 u_{xxx}(l,t) = 0 uxxx(l,t)=0
(a) 频率方程和特征函数
分离变量:u(x,t)=X(x)T(t) u(x,t) = X(x)T(t) u(x,t)=X(x)T(t)。空间方程为:
X(4)−μ4X=0,μ4=λK
X^{(4)} - \mu^4 X = 0, \quad \mu^4 = \frac{\lambda}{K}
X(4)−μ4X=0,μ4=Kλ
通解:
X(x)=Acos(μx)+Bsin(μx)+Ccosh(μx)+Dsinh(μx)
X(x) = A \cos(\mu x) + B \sin(\mu x) + C \cosh(\mu x) + D \sinh(\mu x)
X(x)=Acos(μx)+Bsin(μx)+Ccosh(μx)+Dsinh(μx)
边界条件应用:
- X(0)=0 X(0) = 0 X(0)=0:
A+C=0 ⟹ C=−A A + C = 0 \implies C = -A A+C=0⟹C=−A - X′′(0)=0 X''(0) = 0 X′′(0)=0:
−μ2A+μ2C=0 -\mu^2 A + \mu^2 C = 0 −μ2A+μ2C=0(自动满足,因 C=−A C = -A C=−A) - X′′(l)=0 X''(l) = 0 X′′(l)=0:
−Aμ2cos(μl)−Bμ2sin(μl)+Aμ2cosh(μl)+Bμ2sinh(μl)=0 -A\mu^2 \cos(\mu l) - B\mu^2 \sin(\mu l) + A\mu^2 \cosh(\mu l) + B\mu^2 \sinh(\mu l) = 0 −Aμ2cos(μl)−Bμ2sin(μl)+Aμ2cosh(μl)+Bμ2sinh(μl)=0 - X′′′(l)=0 X'''(l) = 0 X′′′(l)=0:
Aμ3sin(μl)−Bμ3cos(μl)+Aμ3sinh(μl)+Bμ3cosh(μl)=0 A\mu^3 \sin(\mu l) - B\mu^3 \cos(\mu l) + A\mu^3 \sinh(\mu l) + B\mu^3 \cosh(\mu l) = 0 Aμ3sin(μl)−Bμ3cos(μl)+Aμ3sinh(μl)+Bμ3cosh(μl)=0
设 β=μl \beta = \mu l β=μl,得齐次系统:
{A(coshβ−cosβ)+B(sinhβ−sinβ)=0A(sinβ+sinhβ)+B(coshβ−cosβ)=0
\begin{cases}
A (\cosh \beta - \cos \beta) + B (\sinh \beta - \sin \beta) = 0 \\
A (\sin \beta + \sinh \beta) + B (\cosh \beta - \cos \beta) = 0
\end{cases}
{A(coshβ−cosβ)+B(sinhβ−sinβ)=0A(sinβ+sinhβ)+B(coshβ−cosβ)=0
非零解要求行列式为零:
(coshβ−cosβ)2−(sinhβ−sinβ)(sinβ+sinhβ)=0
(\cosh \beta - \cos \beta)^2 - (\sinh \beta - \sin \beta)(\sin \beta + \sinh \beta) = 0
(coshβ−cosβ)2−(sinhβ−sinβ)(sinβ+sinhβ)=0
化简得频率方程:
coshβcosβ=1,β=μl
\cosh \beta \cos \beta = 1, \quad \beta = \mu l
coshβcosβ=1,β=μl
特征值和特征函数:
-
零特征值(λ=0 \lambda = 0 λ=0):
解 X(4)=0 X^{(4)} = 0 X(4)=0 得 X(x)=ax3+bx2+cx+d X(x) = a x^3 + b x^2 + c x + d X(x)=ax3+bx2+cx+d
边界条件:- X(0)=0 ⟹ d=0 X(0) = 0 \implies d = 0 X(0)=0⟹d=0
- X′′(0)=0 ⟹ 2b=0 ⟹ b=0 X''(0) = 0 \implies 2b = 0 \implies b = 0 X′′(0)=0⟹2b=0⟹b=0
- X′′(l)=0 ⟹ 6al=0 ⟹ a=0 X''(l) = 0 \implies 6a l = 0 \implies a = 0 X′′(l)=0⟹6al=0⟹a=0
- X′′′(l)=0 X'''(l) = 0 X′′′(l)=0(自动满足)
唯一非零解:X(x)=x X(x) = x X(x)=x(线性函数)
-
正特征值:
方程 coshβcosβ=1 \cosh \beta \cos \beta = 1 coshβcosβ=1 的正根 βn \beta_n βn(β1≈4.730 \beta_1 \approx 4.730 β1≈4.730, β2≈7.853 \beta_2 \approx 7.853 β2≈7.853, β3≈10.996 \beta_3 \approx 10.996 β3≈10.996, …)
特征值:λn=Kμn4=K(βn/l)4 \lambda_n = K \mu_n^4 = K (\beta_n / l)^4 λn=Kμn4=K(βn/l)4
角频率:ωn=λn=K(βn/l)2 \omega_n = \sqrt{\lambda_n} = \sqrt{K} (\beta_n / l)^2 ωn=λn=K(βn/l)2
特征函数:
Xn(x)=sin(μnx)+bnsinh(μnx) X_n(x) = \sin(\mu_n x) + b_n \sinh(\mu_n x) Xn(x)=sin(μnx)+bnsinh(μnx)
其中 μn=βn/l \mu_n = \beta_n / l μn=βn/l,bn=−sin(βn)sinh(βn) b_n = -\dfrac{\sin(\beta_n)}{\sinh(\beta_n)} bn=−sinh(βn)sin(βn)
(b) 图形化求解频率方程
定义函数:
f(β)=coshβcosβ−1
f(\beta) = \cosh \beta \cos \beta - 1
f(β)=coshβcosβ−1
绘制 f(β) f(\beta) f(β) 的图像,其与 β \beta β 轴的交点 (βn,0) (\beta_n, 0) (βn,0) 给出频率 ωn=K(βn/l)2 \omega_n = \sqrt{K} (\beta_n / l)^2 ωn=K(βn/l)2。
- 根的位置:
β1≈4.730 \beta_1 \approx 4.730 β1≈4.730(在 π≈3.14 \pi \approx 3.14 π≈3.14 和 3π/2≈4.71 3\pi/2 \approx 4.71 3π/2≈4.71 之间),
β2≈7.853 \beta_2 \approx 7.853 β2≈7.853(在 2π≈6.28 2\pi \approx 6.28 2π≈6.28 和 5π/2≈7.85 5\pi/2 \approx 7.85 5π/2≈7.85 之间),
β3≈10.996 \beta_3 \approx 10.996 β3≈10.996(在 3π≈9.42 3\pi \approx 9.42 3π≈9.42 和 7π/2≈10.99 7\pi/2 \approx 10.99 7π/2≈10.99 之间)。
Python 绘图代码:
import numpy as np
import matplotlib.pyplot as pltbeta = np.linspace(0, 15, 1000)
f = np.cosh(beta) * np.cos(beta) - 1plt.figure(figsize=(10, 6))
plt.plot(beta, f, label=r'$f(\beta) = \cosh\beta \cos\beta - 1$')
plt.axhline(0, color='r', linestyle='--')
plt.scatter([4.730, 7.853, 10.996], [0, 0, 0], color='k') # 标记前三个根
plt.xlabel(r'$\beta$')
plt.ylabel(r'$f(\beta)$')
plt.title('图形化求解频率方程: $\cosh\beta \cos\beta = 1$')
plt.legend()
plt.grid(True)
plt.show()
© 特征函数正交性证明
特征值问题:X(4)=γX X^{(4)} = \gamma X X(4)=γX(γ=λ/K \gamma = \lambda / K γ=λ/K),边界条件:
X(0)=X′′(0)=0,X′′(l)=X′′′(l)=0
X(0) = X''(0) = 0, \quad X''(l) = X'''(l) = 0
X(0)=X′′(0)=0,X′′(l)=X′′′(l)=0
设 γm≠γn \gamma_m \neq \gamma_n γm=γn 对应特征函数 Xm,Xn X_m, X_n Xm,Xn:
∫0lXm(4)Xndx=γm∫0lXmXndx
\int_0^l X_m^{(4)} X_n dx = \gamma_m \int_0^l X_m X_n dx
∫0lXm(4)Xndx=γm∫0lXmXndx
分部积分:
∫0lXm(4)Xndx=[Xm′′′Xn−Xm′′Xn′+Xm′Xn′′−XmXn′′′]0l+∫0lXmXn(4)dx
\int_0^l X_m^{(4)} X_n dx = \left[ X_m''' X_n - X_m'' X_n' + X_m' X_n'' - X_m X_n''' \right]_0^l + \int_0^l X_m X_n^{(4)} dx
∫0lXm(4)Xndx=[Xm′′′Xn−Xm′′Xn′+Xm′Xn′′−XmXn′′′]0l+∫0lXmXn(4)dx
边界条件下端点项为零:
γm∫0lXmXndx=γn∫0lXmXndx
\gamma_m \int_0^l X_m X_n dx = \gamma_n \int_0^l X_m X_n dx
γm∫0lXmXndx=γn∫0lXmXndx
(γm−γn)∫0lXmXndx=0
(\gamma_m - \gamma_n) \int_0^l X_m X_n dx = 0
(γm−γn)∫0lXmXndx=0
因 γm≠γn \gamma_m \neq \gamma_n γm=γn,有:
∫0lXm(x)Xn(x)dx=0
\int_0^l X_m(x) X_n(x) dx = 0
∫0lXm(x)Xn(x)dx=0
正交性成立(含零特征值模式)。
(d) 特征值简单性证明(奖励)
- 零特征值:一维特征空间(仅 X(x)=x X(x) = x X(x)=x)
- 正特征值:解空间由两个参数 (A,B) (A, B) (A,B) 描述,但两个边界条件通过频率方程关联,解空间一维,故特征值简单。
(e) 特征函数草图(奖励)
前几个特征函数(设 l=1,K=1 l=1, K=1 l=1,K=1):
- 零特征值:X0(x)=x X_0(x) = x X0(x)=x
- 非零特征值:
Xn(x)=sin(μnx)+bnsinh(μnx),bn=−sinβnsinhβn X_n(x) = \sin(\mu_n x) + b_n \sinh(\mu_n x), \quad b_n = -\frac{\sin \beta_n}{\sinh \beta_n} Xn(x)=sin(μnx)+bnsinh(μnx),bn=−sinhβnsinβn- β1≈4.730 \beta_1 \approx 4.730 β1≈4.730:b1≈−0.0276 b_1 \approx -0.0276 b1≈−0.0276
- β2≈7.853 \beta_2 \approx 7.853 β2≈7.853:b2≈−0.0004 b_2 \approx -0.0004 b2≈−0.0004
- β3≈10.996 \beta_3 \approx 10.996 β3≈10.996:b3≈−0.00001 b_3 \approx -0.00001 b3≈−0.00001
Python 绘图代码:
import numpy as np
import matplotlib.pyplot as pltl = 1
beta_roots = [4.730, 7.853, 10.996] # 前三个根
x = np.linspace(0, l, 100)plt.figure(figsize=(10, 6))# 零特征值
plt.plot(x, x, 'k-', label=r'$\lambda=0$: $X_0(x)=x$')# 非零特征值
for i, beta in enumerate(beta_roots):mu = beta / lb = -np.sin(beta) / np.sinh(beta)X = np.sin(mu * x) + b * np.sinh(mu * x)plt.plot(x, X, label=f'$n={i+1}$, $\\beta_{i+1} \\approx {beta}$')plt.title('左端简支、右端自由梁的特征函数')
plt.xlabel('$x$')
plt.ylabel('$X_n(x)$')
plt.legend()
plt.grid(True)
plt.show()
特征函数行为:
- X0(x) X_0(x) X0(x):线性函数(斜直线)
- X1(x) X_1(x) X1(x):类似正弦波,但右端因双曲项轻微上翘
- X2(x) X_2(x) X2(x):更接近标准正弦波(因 bn b_n bn 极小)
- X3(x) X_3(x) X3(x):几乎与 sin(3πx/l) \sin(3\pi x/l) sin(3πx/l) 重合
- 所有函数满足:
- 左端:X(0)=0 X(0)=0 X(0)=0, X′′(0)=0 X''(0)=0 X′′(0)=0
- 右端:X′′(l)=0 X''(l)=0 X′′(l)=0, X′′′(l)=0 X'''(l)=0 X′′′(l)=0
问题9:左端诺伊曼、右端奇异边界条件的波动方程
考虑波动方程:
utt−c2uxx=0,0<x<l
u_{tt} - c^2 u_{xx} = 0, \quad 0 < x < l
utt−c2uxx=0,0<x<l
边界条件:
- 左端(x=0 x=0 x=0):诺伊曼条件 ux(0,t)=0 u_x(0,t) = 0 ux(0,t)=0
- 右端(x=l x=l x=l):奇异条件 (ux+iαut)(l,t)=0 (u_x + i\alpha u_t)(l,t) = 0 (ux+iαut)(l,t)=0,其中 α∈R \alpha \in \mathbb{R} α∈R
(a) 分离变量
设解的形式为 u(x,t)=X(x)T(t) u(x,t) = X(x)T(t) u(x,t)=X(x)T(t)。代入波动方程:
XT′′−c2X′′T=0
X T'' - c^2 X'' T = 0
XT′′−c2X′′T=0
分离变量:
T′′c2T=X′′X=−λ
\frac{T''}{c^2 T} = \frac{X''}{X} = -\lambda
c2TT′′=XX′′=−λ
其中 λ \lambda λ 是分离常数(特征值)。得到两个常微分方程:
- 空间方程:X′′+λX=0 X'' + \lambda X = 0 X′′+λX=0
- 时间方程:T′′+c2λT=0 T'' + c^2 \lambda T = 0 T′′+c2λT=0
边界条件分离:
- 左端:ux(0,t)=X′(0)T(t)=0 u_x(0,t) = X'(0)T(t) = 0 ux(0,t)=X′(0)T(t)=0,因 T(t)≢0 T(t) \not\equiv 0 T(t)≡0,故 X′(0)=0 X'(0) = 0 X′(0)=0。
- 右端:(ux+iαut)(l,t)=X′(l)T(t)+iαX(l)T′(t)=0 (u_x + i\alpha u_t)(l,t) = X'(l)T(t) + i\alpha X(l)T'(t) = 0 (ux+iαut)(l,t)=X′(l)T(t)+iαX(l)T′(t)=0。
利用时间方程 T′′=−c2λT T'' = -c^2 \lambda T T′′=−c2λT,并假设 λ>0 \lambda > 0 λ>0(特征值实数且正),得 T′(t)=iσT(t) T'(t) = i \sigma T(t) T′(t)=iσT(t) 其中 σ=cλ \sigma = c \sqrt{\lambda} σ=cλ。代入右端条件:
X′(l)T(t)+iαX(l)(iσ)T(t)=T(t)[X′(l)−ασX(l)]=0 X'(l)T(t) + i\alpha X(l) (i \sigma) T(t) = T(t) \left[ X'(l) - \alpha \sigma X(l) \right] = 0 X′(l)T(t)+iαX(l)(iσ)T(t)=T(t)[X′(l)−ασX(l)]=0
因 T(t)≢0 T(t) \not\equiv 0 T(t)≡0,故:
X′(l)−αcλX(l)=0 X'(l) - \alpha c \sqrt{\lambda} X(l) = 0 X′(l)−αcλX(l)=0
其中 σ=cλ \sigma = c \sqrt{\lambda} σ=cλ。
综上,空间方程和边界条件为:
X′′+λX=0,X′(0)=0,X′(l)−αcλX(l)=0
X'' + \lambda X = 0, \quad X'(0) = 0, \quad X'(l) - \alpha c \sqrt{\lambda} X(l) = 0
X′′+λX=0,X′(0)=0,X′(l)−αcλX(l)=0
(b) 奇异特征值问题
空间方程的特征值问题为:
{X′′+λX=0,0<x<lX′(0)=0X′(l)−αcλX(l)=0
\begin{cases}
X'' + \lambda X = 0, & 0 < x < l \\
X'(0) = 0 \\
X'(l) - \alpha c \sqrt{\lambda} X(l) = 0
\end{cases}
⎩⎪⎨⎪⎧X′′+λX=0,X′(0)=0X′(l)−αcλX(l)=00<x<l
此问题为“奇异”因边界条件依赖于 λ \sqrt{\lambda} λ(含参数 λ \lambda λ)。
© 求解特征值问题
空间方程的通解为:
X(x)=Acos(λx)+Bsin(λx)
X(x) = A \cos(\sqrt{\lambda} x) + B \sin(\sqrt{\lambda} x)
X(x)=Acos(λx)+Bsin(λx)
应用边界条件:
- X′(0)=0 X'(0) = 0 X′(0)=0:
X′(x)=−Aλsin(λx)+Bλcos(λx) X'(x) = -A \sqrt{\lambda} \sin(\sqrt{\lambda} x) + B \sqrt{\lambda} \cos(\sqrt{\lambda} x) X′(x)=−Aλsin(λx)+Bλcos(λx)
X′(0)=Bλ=0 ⟹ B=0(因 λ>0) X'(0) = B \sqrt{\lambda} = 0 \implies B = 0 \quad (\text{因 } \lambda > 0) X′(0)=Bλ=0⟹B=0(因 λ>0)
故 X(x)=Acos(λx) X(x) = A \cos(\sqrt{\lambda} x) X(x)=Acos(λx)。 - X′(l)−αcλX(l)=0 X'(l) - \alpha c \sqrt{\lambda} X(l) = 0 X′(l)−αcλX(l)=0:
X′(l)=−Aλsin(λl),X(l)=Acos(λl) X'(l) = -A \sqrt{\lambda} \sin(\sqrt{\lambda} l), \quad X(l) = A \cos(\sqrt{\lambda} l) X′(l)=−Aλsin(λl),X(l)=Acos(λl)
代入:
−Aλsin(λl)−αcλAcos(λl)=0 -A \sqrt{\lambda} \sin(\sqrt{\lambda} l) - \alpha c \sqrt{\lambda} A \cos(\sqrt{\lambda} l) = 0 −Aλsin(λl)−αcλAcos(λl)=0
因 A≠0 A \neq 0 A=0 且 λ≠0 \sqrt{\lambda} \neq 0 λ=0,得:
sin(λl)+αccos(λl)=0 \sin(\sqrt{\lambda} l) + \alpha c \cos(\sqrt{\lambda} l) = 0 sin(λl)+αccos(λl)=0
即:
tan(λl)=−αc \tan(\sqrt{\lambda} l) = -\alpha c tan(λl)=−αc
令 β=λl \beta = \sqrt{\lambda} l β=λl,则:
tanβ=−γ,γ=αc \tan \beta = -\gamma, \quad \gamma = \alpha c tanβ=−γ,γ=αc
考虑 λ=0 \lambda = 0 λ=0:
- 空间方程 X′′=0 X'' = 0 X′′=0,通解 X(x)=a+bx X(x) = a + b x X(x)=a+bx。
- X′(0)=b=0 X'(0) = b = 0 X′(0)=b=0,故 X(x)=a X(x) = a X(x)=a。
- 右端条件:X′(l)−αc⋅0⋅X(l)=0−0=0 X'(l) - \alpha c \cdot 0 \cdot X(l) = 0 - 0 = 0 X′(l)−αc⋅0⋅X(l)=0−0=0,恒成立。
故 λ0=0 \lambda_0 = 0 λ0=0 是特征值,对应特征函数 X0(x)=1 X_0(x) = 1 X0(x)=1(常数)。
对于 λ>0 \lambda > 0 λ>0,方程 tanβ=−γ \tan \beta = -\gamma tanβ=−γ 有可数个正实根 βn>0 \beta_n > 0 βn>0(n=1,2,3,… n=1,2,3,\ldots n=1,2,3,…),满足:
βn=arctan(−γ)+nπ,n=1,2,3,…
\beta_n = \arctan(-\gamma) + n\pi, \quad n = 1,2,3,\ldots
βn=arctan(−γ)+nπ,n=1,2,3,…
(取使 βn>0 \beta_n > 0 βn>0 的根)。特征值为:
λn=(βnl)2
\lambda_n = \left( \frac{\beta_n}{l} \right)^2
λn=(lβn)2
对应特征函数:
Xn(x)=cos(βnxl)
X_n(x) = \cos\left( \frac{\beta_n x}{l} \right)
Xn(x)=cos(lβnx)
(d) 简单解 u(x,t)=X(x)T(t) u(x,t) = X(x)T(t) u(x,t)=X(x)T(t)
时间方程 T′′+c2λT=0 T'' + c^2 \lambda T = 0 T′′+c2λT=0 的解:
- 对 λn>0 \lambda_n > 0 λn>0(n≥1 n \geq 1 n≥1):
Tn(t)=Ancos(cβntl)+Bnsin(cβntl) T_n(t) = A_n \cos\left( \frac{c \beta_n t}{l} \right) + B_n \sin\left( \frac{c \beta_n t}{l} \right) Tn(t)=Ancos(lcβnt)+Bnsin(lcβnt)
简单解:
un(x,t)=cos(βnxl)[Ancos(cβntl)+Bnsin(cβntl)] u_n(x,t) = \cos\left( \frac{\beta_n x}{l} \right) \left[ A_n \cos\left( \frac{c \beta_n t}{l} \right) + B_n \sin\left( \frac{c \beta_n t}{l} \right) \right] un(x,t)=cos(lβnx)[Ancos(lcβnt)+Bnsin(lcβnt)] - 对 λ0=0 \lambda_0 = 0 λ0=0:
T0′′=0 T_0'' = 0 T0′′=0,解 T0(t)=C0+D0t T_0(t) = C_0 + D_0 t T0(t)=C0+D0t。
右端边界条件:ux+iαut=0+iαD0 u_x + i\alpha u_t = 0 + i\alpha D_0 ux+iαut=0+iαD0。设为零:
iαD0=0 ⟹ D0=0(若 α≠0) i\alpha D_0 = 0 \implies D_0 = 0 \quad (\text{若 } \alpha \neq 0) iαD0=0⟹D0=0(若 α=0)
故 T0(t)=C0 T_0(t) = C_0 T0(t)=C0(常数),简单解:
u0(x,t)=C0 u_0(x,t) = C_0 u0(x,t)=C0
(若 α=0 \alpha = 0 α=0,则 T0(t)=C0+D0t T_0(t) = C_0 + D_0 t T0(t)=C0+D0t,解为 u0(x,t)=C0+D0t u_0(x,t) = C_0 + D_0 t u0(x,t)=C0+D0t,但假设 α≠0 \alpha \neq 0 α=0)。
综上,简单解为:
- u0(x,t)=C0 u_0(x,t) = C_0 u0(x,t)=C0(常数模式)
- un(x,t)=cos(βnxl)[Ancos(cβntl)+Bnsin(cβntl)] u_n(x,t) = \cos\left( \frac{\beta_n x}{l} \right) \left[ A_n \cos\left( \frac{c \beta_n t}{l} \right) + B_n \sin\left( \frac{c \beta_n t}{l} \right) \right] un(x,t)=cos(lβnx)[Ancos(lcβnt)+Bnsin(lcβnt)](振动模式,n≥1 n \geq 1 n≥1)
其中 βn \beta_n βn 是 tanβ=−αc \tan \beta = -\alpha c tanβ=−αc 的正实根。
\boxed{
\begin{aligned}
&\text{(a) 分离变量:} \
&u(x,t) = X(x)T(t) \implies \
&X’’ + \lambda X = 0, \quad T’’ + c^2 \lambda T = 0 \
&\text{边界条件:} X’(0) = 0, \quad X’(l) - \alpha c \sqrt{\lambda} X(l) = 0 \
\
&\text{(b) 奇异特征值问题:} \
&\begin{cases}
X’’ + \lambda X = 0, & 0 < x < l \
X’(0) = 0 \
X’(l) - \alpha c \sqrt{\lambda} X(l) = 0
\end{cases} \
\
&\text{© 求解:} \
&\lambda_0 = 0, \quad X_0(x) = 1 \
&\lambda_n = \left( \frac{\beta_n}{l} \right)^2, \quad X_n(x) = \cos\left( \frac{\beta_n x}{l} \right), \quad n=1,2,3,\ldots \
&\text{其中 } \beta_n > 0 \text{ 满足 } \tan \beta_n = -\alpha c \
\
&\text{(d) 简单解:} \
&u_0(x,t) = C_0 \quad (\text{常数解}) \
&u_n(x,t) = \cos\left( \frac{\beta_n x}{l} \right) \left[ A_n \cos\left( \frac{c \beta_n t}{l} \right) + B_n \sin\left( \frac{c \beta_n t}{l} \right) \right], \quad n=1,2,3,\ldots
\end{aligned}
}