Pure Convection :

Summary Here we will present two methods for upwinding for the simplest convection problem. We will learn about Characteristics-Galerkin and Discontinuous-Galerkin Finite Element Methods.

Let \(\Omega\) be the unit disk centered at 0; consider the rotation vector field $$ \bm{u} = [u1,u2], \qquad u_1 = y,\quad u_2 = -x.$$ Pure convection by \(u\) is $$ \partial_t c + \bm{u}.\nabla c = 0 \hbox{ in }  \Omega\times(0,T)     c (t=0) = c ^0 \hbox{ in }  \Omega. $$ The exact solution \(c(x_t,t)\) at time \(t\) en point \(x_t\) is given by $$ c(x_t,t)=c^0(x,0) $$ where \(x_t\) is the particle path in the flow starting at point \(x\) at time \(0\). So \(x_t\) are solutions of $$ \dot{x_t} = u(x_t),   \vec , \quad\ x_{t=0} =x , \quad\mbox{where}\quad \dot{x_t} = \frac{~d ( t \mapsto x_t)}{~d t} $$ The ODE are reversible and we want the solution at point \(x\) at time \(t\) ( not at point \(x_t\)) the initial point is \(x_{-t}\), and we have $$ c(x,t)=c^0(x_{-t},0) $$ The game consists in solving the equation until \(T=2\pi\), that is for a full revolution and to compare the final solution with the initial one; they should be equal.

Solution by a Characteristics-Galerkin Method In FreeFem++ there is an operator called \tt convect([u1,u2],dt,c) which compute \( c\circ X\) with \(X\) is the convect field defined by \( X(x)= x_{dt}\) and where \(x_\tau\) is particule path in the steady state velocity field \(\bm{u}=[u1,u2]\) starting at point \(x\) at time \(\tau=0\), so \(x_\tau\) is solution of the following ODE: $$ \dot{x}_\tau = u(x_\tau),   \vec x_{\tau=0}=x. $$

When \(\bm{u}\) is piecewise constant; this is possible because \(x_\tau\) is then a polygonal curve which can be computed exactly and the solution exists always when \(u\) is divergence free; convect returns \(c(x_{df})=C\circ X\).


 // file convects.edp

 border C(t=0, 2*pi) { x=cos(t);  y=sin(t); };
 mesh Th = buildmesh(C(100));
 fespace Uh(Th,P1);
 Uh cold, c = exp(-10*((x-0.3)^2 +(y-0.3)^2));

 real dt = 0.17,t=0;
 Uh u1 = y, u2 = -x;
 for (int m=0; m<2*pi/dt ; m++) {
     t += dt;     cold=c;
     plot(c,cmm=" t="+t + ", min=" + c[].min + ", max=" +  c[].max);

Remark: 3D plots can be done by adding the qualifyer "dim=3" to the plot instruction.

The method is very powerful but has two limitations: a/ it is not conservative, b/ it may diverge in rare cases when \(|u|\) is too small due to quadrature error.

Solution by Discontinuous-Galerkin FEM

Discontinuous Galerkin methods take advantage of the discontinuities of \(c\) at the edges to build upwinding. There are may formulations possible. We shall implement here the so-called dual-\(P_1^{DC}\) formulation (see Ern[ern]): $$ \int_\Omega(\frac{c^{n+1}-c^n}{\delta t} +u\cdot\nabla c)w +\int_E(\alpha|n\cdot u|-\frac 12 n\cdot u)[c]w =\int_{E_\Gamma^-}|n\cdot u| cw   \forall w $$ where \(E\) is the set of inner edges and \(E_\Gamma^-\) is the set of boundary edges where \(u\cdot n<0\) (in our case there is no such edges). Finally \([c]\) is the jump of \(c\) across an edge with the convention that \(c^+\) refers to the value on the right of the oriented edge. Example[convects_end.edp]

 // file convects.edp
 fespace Vh(Th,P1dc);

 Vh w, ccold, v1 = y, v2 = -x, cc = exp(-10*((x-0.3)^2 +(y-0.3)^2));
 real u, al=0.5;  dt = 0.05;

 macro n() (N.x*v1+N.y*v2) // Macro without parameter 
 problem  Adual(cc,w) =
   + intalledges(Th)((1-nTonEdge)*w*(al*abs(n)-n/2)*jump(cc))
 //  - int1d(Th,C)((n<0)*abs(n)*cc*w)  // unused because cc=0 on $\partial\Omega^-$
   - int2d(Th)(ccold*w/dt);

 for ( t=0; t< 2*pi ; t+=dt)
   ccold=cc; Adual;
   plot(cc,fill=1,cmm="t="+t + ", min=" + cc[].min + ", max=" +  cc[].max);
 real [int] viso=[-0.2,-0.1,0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1,1.1];

Notice the new keywords, intalledges to integrate on all edges of all triangles \begin{equation} \mathtt{intalledges}(\mathtt{Th}) \equiv \sum_T\in\mathtt{Th}\int_\partial T \end{equation}

(so all internal edges are see two times ), nTonEdge which is one if the triangle has a boundary edge and zero otherwise, \tt jump to implement \([c]\). Results of both methods are shown on Figure [figconvect] with identical levels for the level line; this is done with the plot-modifier viso. #plotviso=

Notice also the macro where the parameter \(u\) is not used (but the syntax needs one) and which ends with a //; it simply replaces the name \tt n by \tt (N.x*v1+N.y*v2). As easily guessed \tt N.x,N.y is the normal to the edge.


[figconvect] The rotated hill after one revolution, left with Characteristics-Galerkin, on the right with Discontinuous \(P_1\) Galerkin FEM.

Now if you think that DG is too slow try this

 // the same DG very much faster
 varf aadual(cc,w) = int2d(Th)((cc/dt+(v1*dx(cc)+v2*dy(cc)))*w)
         + intalledges(Th)((1-nTonEdge)*w*(al*abs(n)-n/2)*jump(cc));
 varf bbdual(ccold,w) =  - int2d(Th)(ccold*w/dt);
 matrix  AA= aadual(Vh,Vh);
 matrix BB = bbdual(Vh,Vh);
 set (AA,init=t,solver=sparsesolver);
 Vh rhs=0;
 for ( t=0; t< 2*pi ; t+=dt)
   rhs[] = BB* ccold[];
   cc[] = AA^-1*rhs[];
   plot(cc,fill=0,cmm="t="+t + ", min=" + cc[].min + ", max=" +  cc[].max);

Notice the new keyword set to specify a solver in this framework; the modifier init is used to tel the solver that the matrix has not changed (init=true), and the name parameter are the same that in problem definition (see. [defproblem]) .

Finite Volume Methods can also be handled with FreeFem++ but it requires programming. For instance the \(P_0-P_1\) Finite Volume Method of Dervieux et al associates to each \(P_0\) function \(c^1\) a \(P_0\) function \(c^0\) with constant value around each vertex \(q^i\) equal to \(c^1(q^i)\) on the cell \(\sigma_i\) made by all the medians of all triangles having \(q^i\) as vertex. Then upwinding is done by taking left or right values at the median: $$ \int_{\sigma_i}\frac 1{\delta t}({c^1}^{n+1}-{c^1}^n) + \int_{\partial\sigma_i}u\cdot n c^-=0    \forall i $$ It can be programmed as

 load "mat_dervieux";  // external module in C++ must be loaded
 border a(t=0, 2*pi){ x = cos(t); y = sin(t);  }
 mesh th = buildmesh(a(100));
 fespace Vh(th,P1);

 Vh vh,vold,u1 = y, u2 = -x;
 Vh v = exp(-10*((x-0.3)^2 +(y-0.3)^2)), vWall=0, rhs =0;

 real dt = 0.025;
 // qf1pTlump means mass lumping is used
 problem  FVM(v,vh) = int2d(th,qft=qf1pTlump)(v*vh/dt)
                   - int2d(th,qft=qf1pTlump)(vold*vh/dt)
       + int1d(th,a)(((u1*N.x+u2*N.y)<0)*(u1*N.x+u2*N.y)*vWall*vh)
 + rhs[] ;

 matrix A;

 for ( int t=0; t< 2*pi ; t+=dt){
   rhs[] = A * vold[] ; FVM;

the mass lumping parameter forces a quadrature formula with Gauss points at the vertices so as to make the mass matrix diagonal; the linear system solved by a conjugate gradient method for instance will then converge in one or two iterations.

The right hand side \tt rhs is computed by an external C++ function#externalC++function \tt MatUpWind0(...) which is programmed as

 // computes matrix a on a triangle for the Dervieux FVM
 int   fvmP1P0(double q[3][2], // the 3 vertices of a triangle T
               double u[2],   // convection velocity on T
               double c[3],   // the P1 function on T
               double a[3][3],// output matrix
               double where[3] ) // where>0 means we're on the boundary
   for(int i=0;i<3;i++) for(int j=0;j<3;j++) a[i][j]=0;

     for(int i=0;i<3;i++){
         int ip = (i+1)%3, ipp =(ip+1)%3;
        double unL =-((q[ip][1]+q[i][1]-2*q[ipp][1])*u[0]
         if(unL>0) { a[i][i] += unL; a[ip][i]-=unL;}
             else{ a[i][ip] += unL; a[ip][ip]-=unL;}
             unL=((q[ip][1]-q[i][1])*u[0] -(q[ip][0]-q[i][0])*u[1])/2;
             if(unL>0) { a[i][i]+=unL; a[ip][ip]+=unL;}
   return 1;

It must be inserted into a larger .cpp file, shown in Appendix A,

 which is the load module linked to FreeFem++.