I'm trying to solve \begin{cases} - \Delta p=f \text{ in } \Omega\\ p=0 \text{ on } \partial \Omega \end{cases} with in $\Omega = [-1,1]^2$ by writing it as
\begin{cases} u + \nabla p=0 \\ -\operatorname{div}(u) = -f \\ p = 0 \text{ on } \partial \Omega \end{cases}
whose weak form is \begin{cases}(v,u) - (\operatorname{div}(v),p) = 0 \qquad \forall v \in V\\ -(\operatorname{div}(u),q) = -(f,q) \qquad \forall q \in Q\end{cases}
where $V=H^{\operatorname{div}}(\Omega)$ and $Q=L^2(\Omega)$.
To solve it, I decided to use the inf-sup stable couple $V_h=RT_0$ (for the velocity) and $Q=P_0$ for the pressure. The basis functions for $RT_0$ in the reference triangle $\hat{K}$ are $$\hat{\phi_1} = \sqrt{2}(\hat{x},\hat{y})$$ $$\hat{\phi_2} = (-1+\hat{x},\hat{y})$$ $$\hat{\phi_3} = (\hat{x},-1+\hat{y})$$
In terms of finite element matrices, we have a saddle point problem and the element matrices $A^K$ and $B^K$ ($K$ is a triangle) have components:
$$a_{ij}^K = \frac{1}{|\det(B_K)|}\int_{\hat{K}} [\text{sign}_i^K][ \text{sign}_j^K] B_K \hat{\phi_i} \cdot B_K \hat{\phi_j}$$
$$b_j^K=-\frac{1}{|\det(B_K)|} \int_{\hat{K}} [\text{sign}_j^K] \operatorname{div}(\hat{\phi_j})$$
where $B_K$ is the matrix in the classical affine mapping $F_K:\hat{K} \rightarrow K$, $F_K(\hat{\boldsymbol{x}}) = B_K \hat{\boldsymbol{x}} + \boldsymbol{b_K}$.
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I've been implementing this in MatLab for two days, but the **condition number of the whole saddle point system is infinite**.
- The boundary condition $p=0 \text{ on } \partial \Omega$ should be weakly imposed, so I did not change the matrix after the `assemble()` function. If that is correct, then the problem must be inside my `assemble()` function, in particular in the distribution of the entries of $B$. Since I have $1$ DoF per triangle for the pressure, I have a 3x1 vector for each element $K$.
I think the following code is really "didactic":
- here the inputs `p,t` are the result of the MatLab function `initmesh`, and `force` is a function handle with the forcing term.
- `RT_shapes` is a function that evaluates at the points the RT basis functions and also computes the divergence for each function (which happens to be a constant vector $[2 \sqrt{2},2,2]$)
- In my tests, I am assuming $f$ s.t. the solution is $(x^2-1)(y^2-1)$, which indeed satisfies homogeneous Dirichlet.
Do you spot any error in my reasoning? I really don't see it, and any hint is really welcome!
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function [A,B,F] = assemble(p,t,force)
[rspoints,qwgts] = GaussPoints(4);
np = size(p,2); %N points
nt = size(t,2); %N elements
A = sparse(np,np); %N_DoFs x N_DoFs
B = sparse(nt,np); % N_triangles x N_DoFs
F = zeros(nt,1);
for K=1:nt
l2g = t(1:3,K); %global node indices for element K
tmp = l2g([2 3 1]) - l2g([3 1 2]);
signs = tmp ./ abs(tmp);
x = p(1,l2g); %x coords
y = p(2,l2g); %y coords
BK = [x(2)-x(1), x(3)-x(1);y(2)-y(1),y(3)-y(1)];
bK = [x(1);y(1)];
detBK = det(BK);
detBK_inv = 1/(abs(detBK));
%% Loop over quadrature points
for q=1:length(qwgts)
r = rspoints(q,1); %x coordinate q-th quadrature point
s = rspoints(q,2); %y coordinate q-th quadrature point
[phi,divphi] = RT_shapes(r,s);
JxW=qwgts(q)*detBK/2.0;
physical_coords = BK*[r;s] + bK; %physical coordinates of the current quadrature points
xp = physical_coords(1);
yp = physical_coords(2);
val_rhs = -force(xp,yp)*1.0*JxW;
F(K) = F(K) + val_rhs;
for i=1:3
for j=1:3
val_A = signs(i)*signs(j)*detBK_inv* dot(BK*phi(:,i),BK*phi(:,j))*qwgts(q);
A(l2g(i),l2g(j)) = A(l2g(i),l2g(j)) + val_A;
end
val_B = - signs(i)* detBK_inv*divphi(i)*qwgts(q);
B(K,l2g(i)) = B(K, l2g(i)) + val_B;
end
end
end
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# EDIT
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@knl spotted a fatal typo in my code above, i.e. the indexing given by `l2g` was the one referred to vertex, not to triangle edges. I used a suitable routine, found in the appendix of the book by Larson-Bengzon, named `Tri2Edge` that numbers the edges of a triangle mesh.
Now, the following code is the last version.
- I'm using the indices of the edges to decide which entry of the matrices $A$ and $B$ has to be filled.
- Let $N_t$ the number of elements, and $N_e$ the number of edges. The matrix $A$ is a $N_e \times N_e$, while $B$ is a $N_e \times N_t$. The $F$ term in the rhs has size $N_t$.
- Again, homogeneous Dirichlet BC are assumed.
- Crucially, I noticed that in [my reference paper for the implementation][1], the formula $(8)$ for $b_j^K$ is not what they implemented, since if you go to the first snippet, you may see that they multiplied by `detJ` the entries of $B$, while in that formula they divide their divergence by `detJ`. I don't know why, but if I do not multiply by `detJ`, I obtain the correct solution, as can be seen by the following graph for the pressure, and the correct $L^2$ convergence for the pressure (order $1$, as I am using 1 DoF per triangle).
[![enter image description here][2]][2]
[![enter image description here][3]][3]
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function [A,B,F] = assemble(p,t,t2e,force)
[rspoints,qwgts] = GaussPoints(4);
nt = size(t,2); %N_triangles
ne = max(t2e(:)); %N_edges
A = sparse(ne,ne); %N_edges x N_edges
B = sparse(nt,ne); % N_triangles x N_edges
F = zeros(nt,1); %N_triangles
for K=1:nt
l2g = t(1:3,K); %global node indices for element K
edges = t2e(K,:);%global edges indices for element K
tmp = l2g([2 3 1]) - l2g([3 1 2]);
signs = tmp ./ abs(tmp);
x = p(1,l2g); %x coords
y = p(2,l2g); %y coords
BK = [x(2)-x(1), x(3)-x(1);y(2)-y(1),y(3)-y(1)];
bK = [x(1);y(1)];
detBK = det(BK);
detBK_inv = 1/abs(detBK);
%% Loop over quadrature points
for q=1:length(qwgts)
r = rspoints(q,1); %x coordinate q-th quadrature point
s = rspoints(q,2); %y coordinate q-th quadrature point
[phi,divphi] = RT_shapes(r,s);
JxW=qwgts(q)*detBK;
physical_coords = BK*[r;s] + bK; %physical coordinates of the current quadrature points
xp = physical_coords(1);
yp = physical_coords(2);
val_rhs = -force(xp,yp)*1.0*JxW;
F(K) = F(K) + val_rhs;
for i=1:3
for j=1:3
val_A = detBK_inv*dot(signs(i)*BK*phi(:,i),signs(j)*BK*phi(:,j))*qwgts(q);
A(edges(i),edges(j)) = A(edges(i),edges(j)) + val_A;
end
val_B = -signs(i)*divphi(i)*qwgts(q);
B(K,edges(i)) = B(K, edges(i)) + val_B;
end
end
end
[1]: https://www.siam.org/Portals/0/Publications/SIURO/Vol12/S01743.pdf
[2]: https://i.sstatic.net/imUpY.png
[3]: https://i.sstatic.net/7nKeI.png