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mfem/examples/ex41b.cpp
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// MFEM Example 41
//
// Compile with: make ex41
//
// Sample runs: ex41 -o 2
// ex41 -o 2 -r 4
//
// Description: This example code demonstrates how to use MFEM to solve the
// Eikonal equation,
//
// |∇u| = 1 in Ω, u = g on ∂Ω.
//
// This example constructs a fast converging sequence,
//
// uₖ → u as k → \infty,
//
// by using in Newton's method to solve the sequence of nonlinear
// saddle-point problems
//
// Find qₖ ∈ H¹₀(Ω) and uₖ ∈ H¹₀(Ω) such that
// ( ϕₖ(|∇qₖ|) ∇qₖ , ∇w ) + ( ∇uₖ , ∇w ) = 0 ∀ w ∈ H¹₀(Ω)
// ( ∇qₖ , ∇v ) = ( -1 , v ) + ( ∇qₖ₋₁ , ∇v ) ∀ v ∈ H¹₀(Ω)
//
// where ϕₖ(s) = 1 / ( 1/αₖ + s² )^{1/2} and αₖ > 0.
#include "mfem.hpp"
#include <fstream>
#include <iostream>
using namespace std;
using namespace mfem;
class ZCoefficient : public VectorCoefficient
{
protected:
GridFunction *q;
real_t alpha;
public:
ZCoefficient(int vdim, GridFunction &q_, real_t alpha_ = 1.0)
: VectorCoefficient(vdim), q(&q_), alpha(alpha_) { }
virtual void Eval(Vector &V, ElementTransformation &T, const IntegrationPoint &ip);
};
class DZCoefficient : public MatrixCoefficient
{
protected:
GridFunction *q;
real_t alpha;
public:
DZCoefficient(int height, GridFunction &q_, real_t alpha_ = 1.0)
: MatrixCoefficient(height, true), q(&q_), alpha(alpha_) { }
virtual void Eval(DenseMatrix &K, ElementTransformation &T, const IntegrationPoint &ip);
};
int main(int argc, char *argv[])
{
// 1. Parse command-line options.
const char *mesh_file = "../data/star.mesh";
int order = 1;
int max_it = 5;
int ref_levels = 3;
real_t alpha = 1.0;
real_t tol = 1e-4;
bool visualization = true;
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(&ref_levels, "-r", "--refs",
"Number of h-refinements.");
args.AddOption(&max_it, "-mi", "--max-it",
"Maximum number of iterations");
args.AddOption(&tol, "-tol", "--tol",
"Stopping criteria based on the difference between"
"successive solution updates");
args.AddOption(&alpha, "-step", "--step",
"Step size alpha");
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 mesh file.
Mesh mesh(mesh_file, 1, 1);
int dim = mesh.Dimension();
int sdim = mesh.SpaceDimension();
// 3. Postprocess the mesh.
// 3A. Refine the mesh to increase the resolution.
for (int l = 0; l < ref_levels; l++)
{
mesh.UniformRefinement();
}
// 3B. Interpolate the geometry after refinement to control geometry error.
// NOTE: Minimum second-order interpolation is used to improve the accuracy.
int curvature_order = max(order,2);
mesh.SetCurvature(curvature_order);
// 4. Define the necessary finite element spaces on the mesh.
H1_FECollection H1fec(order, dim);
FiniteElementSpace H1fes(&mesh, &H1fec);
cout << "Number of dofs: "
<< H1fes.GetTrueVSize() * 2 << endl;
// 5. Determine the list of true (i.e., conforming) essential boundary dofs.
Array<int> ess_tdof_list;
if (mesh.bdr_attributes.Size())
{
Array<int> ess_bdr(mesh.bdr_attributes.Max());
ess_bdr = 1;
H1fes.GetEssentialTrueDofs(ess_bdr, ess_tdof_list);
}
else
{
ess_tdof_list.Append(0);
}
Array<int> offsets(3);
offsets[0] = 0;
offsets[1] = H1fes.GetVSize();
offsets[2] = H1fes.GetVSize();
offsets.PartialSum();
BlockVector x(offsets), rhs(offsets);
x = 0.0; rhs = 0.0;
// 6. Define an initial guess for the solution.
ConstantCoefficient neg_one(-1.0);
ConstantCoefficient zero(0.0);
// 7. Define the solution vectors as a finite element grid functions
// corresponding to the fespaces.
GridFunction u_gf, delta_q_gf;
delta_q_gf.MakeRef(&H1fes,x,offsets[0]);
u_gf.MakeRef(&H1fes,x,offsets[1]);
delta_q_gf = 0.0;
GridFunction q_old_gf(&H1fes);
GridFunction q_gf(&H1fes);
GridFunction u_old_gf(&H1fes);
q_old_gf = 0.0;
u_old_gf = 0.0;
// 8. Define the function coefficients for the solution and use them to
// initialize the initial guess
q_gf = 0.0;
q_old_gf = q_gf;
u_old_gf = u_gf;
char vishost[] = "localhost";
int visport = 19916;
socketstream sol_sock;
if (visualization)
{
sol_sock.open(vishost,visport);
sol_sock.precision(8);
}
// 10. Iterate
int k;
int total_iterations = 0;
real_t increment_u = 0.1;
for (k = 0; k < max_it; k++)
{
GridFunction u_tmp(&H1fes);
u_tmp = u_old_gf;
mfem::out << "\nOUTER ITERATION " << k+1 << endl;
ConstantCoefficient alpha_cf(alpha);
int j;
for ( j = 0; j < 5; j++)
{
total_iterations++;
LinearForm b0,b1;
b0.Update(&H1fes,rhs.GetBlock(0),0);
b1.Update(&H1fes,rhs.GetBlock(1),0);
ZCoefficient Z(sdim, q_gf, alpha);
DZCoefficient DZ(sdim, q_gf, alpha);
ScalarVectorProductCoefficient neg_Z(-1.0, Z);
b0.AddDomainIntegrator(new DomainLFGradIntegrator(neg_Z));
b0.Assemble();
GradientGridFunctionCoefficient grad_q_cf(&q_gf);
GradientGridFunctionCoefficient grad_q_old_cf(&q_old_gf);
VectorSumCoefficient grad_q_old_minus_q(grad_q_old_cf, grad_q_cf, 1.0, -1.0);
b1.AddDomainIntegrator(new DomainLFIntegrator(neg_one));
b1.AddDomainIntegrator(new DomainLFGradIntegrator(grad_q_old_minus_q));
b1.Assemble();
BilinearForm a00(&H1fes);
// a00.AddDomainIntegrator(new DiffusionIntegrator());
a00.AddDomainIntegrator(new DiffusionIntegrator(DZ));
a00.Assemble();
a00.EliminateVDofs(ess_tdof_list, mfem::Operator::DIAG_ZERO);
// a00.EliminateVDofs(ess_tdof_list,x.GetBlock(0),rhs.GetBlock(0),
// mfem::Operator::DIAG_ONE);
a00.Finalize();
SparseMatrix &A00 = a00.SpMat();
BilinearForm a10(&H1fes);
a10.AddDomainIntegrator(new DiffusionIntegrator());
a10.Assemble();
a10.EliminateVDofs(ess_tdof_list,x.GetBlock(0),rhs.GetBlock(1),
mfem::Operator::DIAG_ONE);
a10.Finalize();
SparseMatrix &A10 = a10.SpMat();
SparseMatrix *A01 = Transpose(A10);
// BlockOperator A(offsets);
// A.SetBlock(0,0,&A00);
// A.SetBlock(1,0,&A10);
// A.SetBlock(0,1,A01);
// BlockDiagonalPreconditioner prec(offsets);
// prec.SetDiagonalBlock(0,new GSSmoother(A00));
// prec.SetDiagonalBlock(1,new GSSmoother(A11));
// prec.owns_blocks = 1;
// GMRES(A,prec,rhs,x,0,10000,500,1e-12,0.0);
BlockMatrix A(offsets);
A.SetBlock(0,0,&A00);
A.SetBlock(0,1,A01);
A.SetBlock(1,0,&A10);
SparseMatrix * A_mono = A.CreateMonolithic();
UMFPackSolver umf(*A_mono);
umf.Mult(rhs,x);
delta_q_gf.MakeRef(&H1fes, x.GetBlock(0), 0);
u_gf.MakeRef(&H1fes, x.GetBlock(1), 0);
u_tmp -= u_gf;
real_t Newton_update_size = u_tmp.ComputeL2Error(zero);
u_tmp = u_gf;
real_t gamma = 1.0;
delta_q_gf *= gamma;
q_gf += delta_q_gf;
if (visualization)
{
sol_sock << "solution\n" << mesh << u_tmp << "window_title 'Discrete solution'"
// sol_sock << "solution\n" << mesh << q_gf << "window_title 'Discrete solution'"
// sol_sock << "solution\n" << mesh << u_gf << "window_title 'Discrete solution'"
<< flush;
mfem::out << "Newton_update_size = " << Newton_update_size << endl;
}
delete A01;
if (Newton_update_size < increment_u)
{
break;
}
}
u_tmp = u_gf;
u_tmp -= u_old_gf;
increment_u = u_tmp.ComputeL2Error(zero);
mfem::out << "Number of Newton iterations = " << j+1 << endl;
mfem::out << "Increment (|| uₕ - uₕ_prvs||) = " << increment_u << endl;
u_old_gf = u_gf;
q_old_gf = q_gf;
if (increment_u < tol || k == max_it-1)
{
break;
}
alpha *= 2.0;
}
mfem::out << "\n Outer iterations: " << k+1
<< "\n Total iterations: " << total_iterations
<< "\n Total dofs: " << H1fes.GetTrueVSize() * 2
<< endl;
return 0;
}
void ZCoefficient::Eval(Vector &V, ElementTransformation &T,
const IntegrationPoint &ip)
{
MFEM_ASSERT(q != NULL, "grid function is not set");
MFEM_ASSERT(alpha > 0, "alpha is not positive");
Vector gradq(vdim);
q->GetGradient(T,gradq);
real_t norm = gradq.Norml2();
real_t phi = 1.0 / sqrt(1.0/alpha + norm*norm);
V = gradq;
V *= phi;
}
void DZCoefficient::Eval(DenseMatrix &K, ElementTransformation &T,
const IntegrationPoint &ip)
{
MFEM_ASSERT(q != NULL, "grid function is not set");
MFEM_ASSERT(alpha > 0, "alpha is not positive");
Vector gradq(height);
q->GetGradient(T,gradq);
real_t norm = gradq.Norml2();
real_t phi = 1.0 / sqrt(1.0/alpha + norm*norm);
K = 0.0;
for (int i = 0; i < height; i++)
{
K(i,i) = phi;
for (int j = 0; j < height; j++)
{
K(i,j) -= gradq(i) * gradq(j) * pow(phi, 3);
}
}
}