# Domain decomposition

We present three classic examples of domain decomposition technique: first, Schwarz algorithm with overlapping, second Schwarz algorithm without overlapping (also call Shur complement), and last we show to use the conjugate gradient to solve the boundary problem of the Shur complement.

## Schwarz overlapping#

To solve

the Schwarz algorithm runs like this

where $\Gamma_i$ is the boundary of $\Omega_i$ and on the condition that $\Omega_1\cap\Omega_2\neq\emptyset$ and that $u_i$ are zero at iteration 1.

Here we take $\Omega_1$ to be a quadrangle, $\Omega_2$ a disk and we apply the algorithm starting from zero.

Fig. 25: The 2 overlapping mesh TH and th

Schwarz overlapping

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 // Parameters int inside = 2; //inside boundary int outside = 1; //outside boundary int n = 4; // Mesh border a(t=1, 2){x=t; y=0; label=outside;} border b(t=0, 1){x=2; y=t; label=outside;} border c(t=2, 0){x=t; y=1; label=outside;} border d(t=1, 0){x=1-t; y=t; label=inside;} border e(t=0, pi/2){x=cos(t); y=sin(t); label=inside;} border e1(t=pi/2, 2*pi){x=cos(t); y=sin(t); label=outside;} mesh th = buildmesh(a(5*n) + b(5*n) + c(10*n) + d(5*n)); mesh TH = buildmesh(e(5*n) + e1(25*n)); plot(th, TH, wait=true); //to see the 2 meshes // Fespace fespace vh(th, P1); vh u=0, v; fespace VH(TH, P1); VH U, V; // Problem int i = 0; problem PB (U, V, init=i, solver=Cholesky) = int2d(TH)( dx(U)*dx(V) + dy(U)*dy(V) ) + int2d(TH)( - V ) + on(inside, U=u) + on(outside, U=0) ; problem pb (u, v, init=i, solver=Cholesky) = int2d(th)( dx(u)*dx(v) + dy(u)*dy(v) ) + int2d(th)( - v ) + on(inside, u=U) + on(outside, u=0) ; // Calculation loop for (i = 0 ; i < 10; i++){ // Solve PB; pb; // Plot plot(U, u, wait=true); } 
Fig. 26: Isovalues of the solution at iteration 0 and iteration 9

## Schwarz non overlapping Scheme#

To solve

the Schwarz algorithm for domain decomposition without overlapping runs like this

Fig. 27: The two none overlapping mesh TH and th

Let introduce $\Gamma_i$ is common the boundary of $\Omega_1$ and $\Omega_2$ and $\Gamma_e^i= \p \Omega_i \setminus \Gamma_i$.

The problem find $\lambda$ such that $(u_1|_{\Gamma_i}=u_2|_{\Gamma_i})$ where $u_i$ is solution of the following Laplace problem:

To solve this problem we just make a loop with upgrading $\lambda$ with

\lambda = \lambda {\pm} \frac{(u_1-u_2)}{2}

where the sign $+$ or $-$ of ${\pm}$ is choose to have convergence.

Schwarz non-overlapping

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 // Parameters int inside = 2; int outside = 1; int n = 4; // Mesh border a(t=1, 2){x=t; y=0; label=outside;}; border b(t=0, 1){x=2; y=t; label=outside;}; border c(t=2, 0){x=t; y=1; label=outside;}; border d(t=1, 0){x=1-t; y=t; label=inside;}; border e(t=0, 1){x=1-t; y=t; label=inside;}; border e1(t=pi/2, 2*pi){x=cos(t); y=sin(t); label=outside;}; mesh th = buildmesh(a(5*n) + b(5*n) + c(10*n) + d(5*n)); mesh TH = buildmesh(e(5*n) + e1(25*n)); plot(th, TH, wait=true); // Fespace fespace vh(th, P1); vh u=0, v; vh lambda=0; fespace VH(TH, P1); VH U, V; // Problem int i = 0; problem PB (U, V, init=i, solver=Cholesky) = int2d(TH)( dx(U)*dx(V) + dy(U)*dy(V) ) + int2d(TH)( - V ) + int1d(TH, inside)( lambda*V ) + on(outside, U= 0 ) ; problem pb (u, v, init=i, solver=Cholesky) = int2d(th)( dx(u)*dx(v) + dy(u)*dy(v) ) + int2d(th)( - v ) + int1d(th, inside)( - lambda*v ) + on(outside, u=0) ; for (i = 0; i < 10; i++){ // Solve PB; pb; lambda = lambda - (u-U)/2; // Plot plot(U,u,wait=true); } // Plot plot(U, u); 
Fig. 26: Isovalues of the solution at iteration 0 and iteration 9 without overlapping

To solve $-\Delta u =f \;\mbox{in}\;\Omega=\Omega_1\cup\Omega_2\quad u|_\Gamma=0$ the Schwarz algorithm for domain decomposition without overlapping runs like this

Let introduce $\Gamma_i$ is common the boundary of $\Omega_1$ and $\Omega_2$ and $\Gamma_e^i= \p \Omega_i \setminus \Gamma_i$.

The problem find $\lambda$ such that $(u_1|_{\Gamma_i}=u_2|_{\Gamma_i})$ where $u_i$ is solution of the following Laplace problem:

The version of this example uses the Shur complement. The problem on the border is solved by a conjugate gradient method.

First, we construct the two domains

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 // Parameters int inside = 2; int outside = 1; int n = 4; // Mesh border Gamma1(t=1, 2){x=t; y=0; label=outside;} border Gamma2(t=0, 1){x=2; y=t; label=outside;} border Gamma3(t=2, 0){x=t; y=1; label=outside;} border GammaInside(t=1, 0){x=1-t; y=t; label=inside;} border GammaArc(t=pi/2, 2*pi){x=cos(t); y=sin(t); label=outside;} mesh Th1 = buildmesh(Gamma1(5*n) + Gamma2(5*n) + GammaInside(5*n) + Gamma3(5*n)); mesh Th2 = buildmesh(GammaInside(-5*n) + GammaArc(25*n)); plot(Th1, Th2); 

Now, define the finite element spaces:

 1 2 3 4 5 6 7 8 // Fespace fespace Vh1(Th1, P1); Vh1 u1, v1; Vh1 lambda; Vh1 p=0; fespace Vh2(Th2,P1); Vh2 u2, v2; 

Note

It is impossible to define a function just on a part of boundary, so the $\lambda$ function must be defined on the all domain $\Omega_1$ such as

 1 Vh1 lambda; 

The two Poisson's problems:

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 problem Pb1 (u1, v1, init=i, solver=Cholesky) = int2d(Th1)( dx(u1)*dx(v1) + dy(u1)*dy(v1) ) + int2d(Th1)( - v1 ) + int1d(Th1, inside)( lambda*v1 ) + on(outside, u1=0) ; problem Pb2 (u2, v2, init=i, solver=Cholesky) = int2d(Th2)( dx(u2)*dx(v2) + dy(u2)*dy(v2) ) + int2d(Th2)( - v2 ) + int1d(Th2, inside)( - lambda*v2 ) + on(outside, u2=0) ; 

And, we define a border matrix, because the $\lambda$ function is none zero inside the domain $\Omega_1$:

 1 2 varf b(u2, v2, solver=CG) = int1d(Th1, inside)(u2*v2); matrix B = b(Vh1, Vh1, solver=CG); 

The boundary problem function,

\lambda \longrightarrow \int_{\Gamma_i }(u_1-u_2) v_{1}
  1 2 3 4 5 6 7 8 9 10 // Boundary problem function func real[int] BoundaryProblem (real[int] &l){ lambda[] = l; //make FE function form l Pb1; Pb2; i++; //no refactorization i != 0 v1 = -(u1-u2); lambda[] = B*v1[]; return lambda[]; } 

Note

The difference between the two notations v1 and v1[] is: v1 is the finite element function and v1[] is the vector in the canonical basis of the finite element function v1.

 1 2 3 4 5 6 7 8 9 // Solve real cpu=clock(); LinearCG(BoundaryProblem, p[], eps=1.e-6, nbiter=100); //compute the final solution, because CG works with increment BoundaryProblem(p[]); //solve again to have right u1, u2 // Display & Plot cout << " -- CPU time schwarz-gc:" << clock()-cpu << endl; plot(u1, u2);