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// MFEM Example 6
//
// Compile with: make ex6
//
// Sample runs: ex6 -m ../data/square-disc.mesh -o 1
// ex6 -m ../data/square-disc.mesh -o 2
// ex6 -m ../data/square-disc-nurbs.mesh -o 2
// ex6 -m ../data/star.mesh -o 3
// ex6 -m ../data/escher.mesh -o 2
// ex6 -m ../data/fichera.mesh -o 2
// ex6 -m ../data/disc-nurbs.mesh -o 2
// ex6 -m ../data/ball-nurbs.mesh
// ex6 -m ../data/pipe-nurbs.mesh
// ex6 -m ../data/star-surf.mesh -o 2
// ex6 -m ../data/square-disc-surf.mesh -o 2
// ex6 -m ../data/amr-quad.mesh
//
// Description: This is a version of Example 1 with a simple adaptive mesh
// refinement loop. The problem being solved is again the Laplace
// equation -Delta u = 1 with homogeneous Dirichlet boundary
// conditions. The problem is solved on a sequence of meshes which
// are locally refined in a conforming (triangles, tetrahedrons)
// or non-conforming (quadrilateral, hexahedrons) manner according
// to a simple ZZ error estimator.
//
// The example demonstrates MFEM's capability to work with both
// conforming and nonconforming refinements, in 2D and 3D, on
// linear, curved and surface meshes. Interpolation of functions
// from coarse to fine meshes, as well as persistent GLVis
// visualization are also illustrated.
//
// We recommend viewing Example 1 before viewing this example.
#include "mfem.hpp"
#include <fstream>
#include <iostream>
using namespace std;
using namespace mfem;
int main(int argc, char *argv[])
{
// 1. Parse command-line options.
const char *mesh_file = "../data/star.mesh";
int order = 1;
bool visualization = 1;
OptionsParser args(argc, argv);
args.AddOption(&mesh_file, "-m", "--mesh",
"Mesh file to use.");
args.AddOption(&order, "-o", "--order",
"Finite element order (polynomial degree).");
args.AddOption(&visualization, "-vis", "--visualization", "-no-vis",
"--no-visualization",
"Enable or disable GLVis visualization.");
args.Parse();
if (!args.Good())
{
args.PrintUsage(cout);
return 1;
}
args.PrintOptions(cout);
// 2. Read the mesh from the given mesh file. We can handle triangular,
// quadrilateral, tetrahedral, hexahedral, surface and volume meshes with
// the same code.
Mesh mesh(mesh_file, 1, 1);
int dim = mesh.Dimension();
int sdim = mesh.SpaceDimension();
// 3. Since a NURBS mesh can currently only be refined uniformly, we need to
// convert it to a piecewise-polynomial curved mesh. First we refine the
// NURBS mesh a bit more and then project the curvature to quadratic Nodes.
if (mesh.NURBSext)
{
for (int i = 0; i < 2; i++)
{
mesh.UniformRefinement();
}
mesh.SetCurvature(2);
}
// 4. Define a finite element space on the mesh. The polynomial order is
// one (linear) by default, but this can be changed on the command line.
H1_FECollection fec(order, dim);
FiniteElementSpace fespace(&mesh, &fec);
// 5. As in Example 1, we set up bilinear and linear forms corresponding to
// the Laplace problem -\Delta u = 1. We don't assemble the discrete
// problem yet, this will be done in the main loop.
BilinearForm a(&fespace);
LinearForm b(&fespace);
ConstantCoefficient one(1.0);
ConstantCoefficient zero(0.0);
BilinearFormIntegrator *integ = new DiffusionIntegrator(one);
a.AddDomainIntegrator(integ);
b.AddDomainIntegrator(new DomainLFIntegrator(one));
// 6. The solution vector x and the associated finite element grid function
// will be maintained over the AMR iterations. We initialize it to zero.
GridFunction x(&fespace);
x = 0.0;
// 7. All boundary attributes will be used for essential (Dirichlet) BC.
MFEM_VERIFY(mesh.bdr_attributes.Size() > 0,
"Boundary attributes required in the mesh.");
Array<int> ess_bdr(mesh.bdr_attributes.Max());
ess_bdr = 1;
// 8. Connect to GLVis.
char vishost[] = "localhost";
int visport = 19916;
socketstream sol_sock;
if (visualization)
{
sol_sock.open(vishost, visport);
}
// 9. Set up an error estimator. Here we use the Zienkiewicz-Zhu estimator
// that uses the ComputeElementFlux method of the DiffusionIntegrator to
// recover a smoothed flux (gradient) that is subtracted from the element
// flux to get an error indicator. We need to supply the space for the
// smoothed flux: an (H1)^sdim (i.e., vector-valued) space is used here.
FiniteElementSpace flux_fespace(&mesh, &fec, sdim);
ZienkiewiczZhuEstimator estimator(*integ, x, flux_fespace);
estimator.SetAnisotropic();
// 10. A refiner selects and refines elements based on a refinement strategy.
// The strategy here is to refine elements with errors larger than a
// fraction of the maximum element error. Other strategies are possible.
// The refiner will call the given error estimator.
ThresholdRefiner refiner(estimator);
refiner.SetTotalErrorFraction(0.7);
// 11. The main AMR loop. In each iteration we solve the problem on the
// current mesh, visualize the solution, and refine the mesh.
const int max_dofs = 50000;
for (int it = 0; ; it++)
{
int cdofs = fespace.GetTrueVSize();
cout << "\nAMR iteration " << it << endl;
cout << "Number of unknowns: " << cdofs << endl;
// 12. Assemble the stiffness matrix and the right-hand side.
a.Assemble();
b.Assemble();
// 13. Set Dirichlet boundary values in the GridFunction x.
// Determine the list of Dirichlet true DOFs in the linear system.
Array<int> ess_tdof_list;
x.ProjectBdrCoefficient(zero, ess_bdr);
fespace.GetEssentialTrueDofs(ess_bdr, ess_tdof_list);
// 14. Create the linear system: eliminate boundary conditions, constrain
// hanging nodes and possibly apply other transformations. The system
// will be solved for true (unconstrained) DOFs only.
SparseMatrix A;
Vector B, X;
const int copy_interior = 1;
a.FormLinearSystem(ess_tdof_list, x, b, A, X, B, copy_interior);
#ifndef MFEM_USE_SUITESPARSE
// 15. Define a simple symmetric Gauss-Seidel preconditioner and use it to
// solve the linear system with PCG.
GSSmoother M(A);
PCG(A, M, B, X, 3, 200, 1e-12, 0.0);
#else
// 15. If MFEM was compiled with SuiteSparse, use UMFPACK to solve the
// the linear system.
UMFPackSolver umf_solver;
umf_solver.Control[UMFPACK_ORDERING] = UMFPACK_ORDERING_METIS;
umf_solver.SetOperator(A);
umf_solver.Mult(B, X);
#endif
// 16. After solving the linear system, reconstruct the solution as a
// finite element GridFunction. Constrained nodes are interpolated
// from true DOFs (it may therefore happen that x.Size() >= X.Size()).
a.RecoverFEMSolution(X, b, x);
// 17. Send solution by socket to the GLVis server.
if (visualization && sol_sock.good())
{
sol_sock.precision(8);
sol_sock << "solution\n" << mesh << x << flush;
}
if (cdofs > max_dofs)
{
cout << "Reached the maximum number of dofs. Stop." << endl;
break;
}
// 18. Call the refiner to modify the mesh. The refiner calls the error
// estimator to obtain element errors, then it selects elements to be
// refined and finally it modifies the mesh. The Stop() method can be
// used to determine if a stopping criterion was met.
refiner.Apply(mesh);
if (refiner.Stop())
{
cout << "Stopping criterion satisfied. Stop." << endl;
break;
}
// 19. Update the space to reflect the new state of the mesh. Also,
// interpolate the solution x so that it lies in the new space but
// represents the same function. This saves solver iterations later
// since we'll have a good initial guess of x in the next step.
// Internally, FiniteElementSpace::Update() calculates an
// interpolation matrix which is then used by GridFunction::Update().
fespace.Update();
x.Update();
// 20. Inform also the bilinear and linear forms that the space has
// changed.
a.Update();
b.Update();
}
return 0;
}