The code below solves the 1D heat equation that represents a rod whose ends are kept at zero temparature with initial condition 10*np.sin(np.pi*x).
How are the Dirichlet boundary conditions (zero temp at both ends) worked into this calculation? I was told the upper, lower rows of matrix A contain two non-zero elements, and the missing third element is the Dirichlet condition. But I do not understand by which mechanism this condition affects the calculation. With missing elements in A, how can u_{0} or u_{n} be zero?
The finite difference method below uses Crank-Nicholson.
import numpy as np
import scipy.linalg
# Number of internal points
N = 200
# Calculate Spatial Step-Size
h = 1/(N+1.0)
k = h/2
x = np.linspace(0,1,N+2)
x = x[1:-1] # get rid of the '0' and '1' at each end
# Initial Conditions
u = np.transpose(np.mat(10*np.sin(np.pi*x)))
# second derivative matrix
I2 = -2*np.eye(N)
E = np.diag(np.ones((N-1)), k=1)
D2 = (I2 + E + E.T)/(h**2)
I = np.eye(N)
TFinal = 1
NumOfTimeSteps = int(TFinal/k)
for i in range(NumOfTimeSteps):
# Solve the System: (I - k/2*D2) u_new = (I + k/2*D2)*u_old
A = (I - k/2*D2)
b = np.dot((I + k/2*D2), u)
u = scipy.linalg.solve(A, b)
Let's have a look at a simple example. We assume N = 3
, i.e. three inner points, but we will first also include the boundary points in the matrix D2
describing the approximate second derivatives:
1 / 1 -2 1 0 0 \
D2 = --- | 0 1 -2 1 0 |
h^2 \ 0 0 1 -2 1 /
The first line means the approximate second derivative at x_1
is 1/h^2 * (u_0 - 2*u_1 + u_2)
. We know that u_0 = 0
though, due to the homgeneous Dirichlet boundary conditions, so we can simply omit it from the equation, and e get the same result for the matrix
1 / 0 -2 1 0 0 \
D2 = --- | 0 1 -2 1 0 |
h^2 \ 0 0 1 -2 0 /
Since u_0
and u_{n+1}
are not real unknowns -- they are known to be zero -- we can completely drop them from the matrix, and we get
1 / 2 1 0 \
D2 = --- | 1 -2 1 |
h^2 \ 0 1 -2 /
The missing entries in the matrix really correspond to the fact that the boundary conditions are zero.