- Ensure Proper Source Term Integration: Check that the source term is correctly added to the “b” vector.
- Check Boundary Conditions: Confirm that “DefineBoundaryLaplace5” applies the boundary conditions accurately for both equations.
- Verify Matrix Coefficients: Make sure that “DefineEquationLaplace4” accurately represents the discretized Poisson equation.
- Review Convergence Criteria: Adjust the tolerance and iteration count for the Poisson equation as needed.
- Test Solver Stability: Experiment with different initial guesses and consider using a more robust solver if necessary.
- Optimize Code: Use vectorization and efficient sparse matrix operations to enhance performance.
- Debugging: Use debugging tools to examine intermediate computations, especially after incorporating the source term.
- Assess Numerical Stability: Check if the discretization scheme requires modification for stability with the source term.
PDE solver I made for the laplace equation fails when I insert a poisson equation
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Hello all, I wrote a solver to the poisson equation, it actually works fine for the laplace equation (e.g, when the laplacian equals to 0), but it screws by a lot when the laplacian isn't equal to 0.
function Sol = LaplaceSolver(xLimit, yLimit, boundaryFunction, rectFunction, N_x, N_y,tol, LinearSolverType)
%% in this function we solve the Laplace Equation using Jacobi's method
%% first we define our grid
x_s = linspace(xLimit(1), xLimit(2), N_x);
y_s = linspace(yLimit(1), yLimit(2), N_y);
delta_x = x_s(2)-x_s(1);
delta_y = y_s(2)-y_s(1);
%% We essentially solve the linear system of equation Ax = b where:
%% b = boundary
%% A the matrix
%% we begin with the bottom layer
b = DefineBoundaryLaplace5(x_s,y_s, boundaryFunction, rectFunction);
%% Next we determine our system of equations
delta_x_sq = delta_x^2;
delta_y_sq = delta_y^2;
FiniteDifferenceEquationLaplace = DefineEquationLaplace4(N_x,N_y,delta_x_sq,delta_y_sq);
%% Finally we use the Jacobi's method to solve our (sparse) linear system of equation
xInitial = zeros(length(b),1);
switch LinearSolverType
case "Jacobi"
VectorSol = JacobiMethod(FiniteDifferenceEquationLaplace,b,xInitial, tol);
case "Gauss"
VectorSol = GaussSiedelMethod(FiniteDifferenceEquationLaplace,b,xInitial, tol);
case "SOR"
omega = 4 / (2 + sqrt(4 - (cos(pi / N_y) + cos(pi/N_x)^2)));
VectorSol = SORMethod(FiniteDifferenceEquationLaplace,b,xInitial,omega,tol);
case "ConjGrad"
VectorSol = ConjGrad(FiniteDifferenceEquationLaplace,b,tol);
case "weird"
VectorSol = Weirdy(b,tol)
end
%% and trully finally, we reshape our VectorSol into a matrix:
Sol = reshape(VectorSol, [N_x-2,N_y-2]);
end
The function DefineBoundaryLaplace5:
function b = DefineBoundaryLaplace5(x,y, boundaryFunction, rectFunction)
N_x = length(x);
N_y = length(y);
delta_x = x(2) - x(1);
delta_y = x(2) - x(1);
b = zeros((N_x-2),(N_y-2));
delta_x_sq = delta_x^2;
delta_y_sq = delta_y^2;
arr_x = 1:(N_x-2);
arr_y = 1:(N_y-2);
x_coeffs = 1;
y_coeffs = delta_x_sq / delta_y_sq;
rect_coeffs = delta_x_sq;
b(arr_x,arr_y) = rect_coeffs * rectFunction(x(arr_x+1), y(arr_y+1));
b(arr_x,1) = b(arr_x,1) + y_coeffs * boundaryFunction(x(arr_x+1), y(1))';
b(arr_x, N_y-2) = b(arr_x,N_y-2) + y_coeffs * boundaryFunction(x(arr_x+1), y(N_y))';
b(1, arr_y) = b(1,arr_y) + x_coeffs * boundaryFunction(x(1), y(arr_y+1));
b(N_x-2, arr_y) = b(N_x-2,arr_y) + x_coeffs * boundaryFunction(x(N_x), y(arr_y+1));
b = reshape(b, [(N_x-2)*(N_y-2),1]);
end
The function DefineEquationLaplace4:
function FiniteDifferenceLaplace = DefineEquationLaplace4(N_x,N_y,delta_x_sq,delta_y_sq)
FiniteDifferenceLaplace = cell((N_x-2) * (N_y-2),1);
L = CalcL(1,1,N_y);
x_coeff = -1;
y_coeff = -delta_x_sq / delta_y_sq;
Center_coeff = 2 * (delta_x_sq / delta_y_sq + 1);
FiniteDifferenceLaplace{L} = [Center_coeff,1, x_coeff,2, y_coeff,N_x-1]; %% bottom left
L = CalcL(N_x-2,1,N_y);
FiniteDifferenceLaplace{L} = [x_coeff,L-1,Center_coeff,L,y_coeff,L+(N_x-2)]; % bottom right
L = CalcL(1, N_y-2, N_y);
FiniteDifferenceLaplace{L} = [y_coeff,L-(N_x-2),Center_coeff,L,x_coeff,L+1]; % upper left
L = CalcL(N_x-2, N_y-2, N_y);
FiniteDifferenceLaplace{L} = [y_coeff,L-(N_x-2),x_coeff,L-1,Center_coeff,L]; % upper right
for i = 2:(N_x-3) % i iterates on x
L = CalcL(i,1,N_y); % bottom line
FiniteDifferenceLaplace{L} = [x_coeff,L-1,Center_coeff,L,x_coeff,L+1,y_coeff, L + (N_x-2)]; % bottom line
L = CalcL(i,N_y-2,N_y); % upper line
FiniteDifferenceLaplace{L} = [y_coeff, L - (N_x-2),x_coeff,L-1,Center_coeff,L,x_coeff,L+1]; % upper line
end
for j = 2:(N_x-3) % j iterates on y
L = CalcL(1,j,N_y); % left column
FiniteDifferenceLaplace{L} = [y_coeff,L-(N_x-2),Center_coeff,L,x_coeff,L+1,y_coeff, L + (N_x-2)]; % left line
L = CalcL(N_x-2,j,N_y); % upper line
FiniteDifferenceLaplace{L} = [y_coeff,L-(N_x-2),x_coeff,L-1,Center_coeff,L,y_coeff, L + (N_x-2)]; % right line
end
for i = 2:(N_x-3) % i iterates on x
for j = 2:(N_y-3) % j iterates on y
L = CalcL(i,j,N_y);
FiniteDifferenceLaplace{L} = [y_coeff,L - (N_x-2),x_coeff,L-1,Center_coeff,L,x_coeff,L+1,y_coeff, L + (N_x-2)]; % all other circumstances
end
end
end
end
And for instance, the Jacobi method which I use to iteratively solve the equation Ax = b:
function x = JacobiMethod(Matrix,b, xInitial, tol)
%% this function solves a sparse linear system of equations
%% it receives a cell array A{1},...,A{n}, each cell represents a line in
%% the matrix in the following way - A{1} = {A(1i1, i1),i1, A(1i2),i2, A1(i3),i3),...}
%% this is an efficent way to represent a sparse matrix, since we simply dont represent the zeros.
%% A = [[a1_i1, i1 , a_i2, i2, ], [ai_i, i,...]
N = length(xInitial);
x = zeros(N,1);
for i = 1:N
CurrLine = Matrix{i};
SumDotProduct = sum(CurrLine(1:2:length(CurrLine)) * xInitial(CurrLine(2:2:length(CurrLine))) );
diagonal_id = find(CurrLine(2:2:length(CurrLine)) == i);
a_ii = CurrLine(diagonal_id * 2 - 1);
SumDotProduct = SumDotProduct - a_ii * xInitial(i);
x(i) = ( -SumDotProduct + b(i)) / a_ii;
end
norm_to_check = max(abs(x - xInitial)) / max(abs(x));
if (norm_to_check < tol)
return
else
x = JacobiMethod(Matrix,b,x,tol);
end
end
Thanks in advance for anyone willing to help, and I will also appericate any other advises on how to make my code even more optimized (even though it runs pretty smooth when I use the Conj grad)
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回答(1 个)
UDAYA PEDDIRAJU
2024-1-15
Hi Matan,
To address the issue with poison equation solver you can try the following:
Additionally, you can refer to the following toolbox, that can solve the Poisson equation: https://www.mathworks.com/matlabcentral/fileexchange/38090-2d-poisson-equation.
I hope this helps!
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