// construct Jacobi matrix or residual vector
void DiscreteProblem::assemble(scalar *coeff_vec, SparseMatrix *mat, Vector *rhs, bool rhsonly) {
// number of equations in the system
int n_eq = space->get_n_eq();
// total number of unknowns
int ndof = Space::get_num_dofs(space);
// Copy coefficients from vector coeff_vec to elements.
if (coeff_vec != NULL) set_coeff_vector(coeff_vec, space);
// Reallocate the matrix and residual vector.
if (rhs != NULL) rhs->alloc(ndof);
// Zero the vector, which should be done by the appropriate implementation anyway.
if (rhs != NULL) rhs->zero();
if (mat != NULL)
{
mat->free();
mat->prealloc(ndof);
for(int i = 0; i < ndof; i++)
for(int j = 0; j< ndof; j++)
mat->pre_add_ij(i, j);
mat->alloc();
// Zero the matrix, which should be done by the appropriate implementation anyway.
mat->zero();
}
// process volumetric weak forms via an element loop
process_vol_forms(mat, rhs, rhsonly);
// process surface weak forms for the left boundary
process_surf_forms(mat, rhs, BOUNDARY_LEFT, rhsonly);
// process surface weak forms for the right boundary
process_surf_forms(mat, rhs, BOUNDARY_RIGHT, rhsonly);
// DEBUG: print Jacobi matrix
if(DEBUG_MATRIX) {
info("Jacobi matrix:");
for(int i=0; i<ndof; i++) {
for(int j=0; j<ndof; j++) {
info("%g ", mat->get(i, j));
}
}
}
// DEBUG: print residual vector
if(DEBUG_MATRIX && rhs != NULL) {
info("Residual:");
for(int i=0; i<ndof; i++) {
info("%g ", rhs->get(i));
}
}
}
// using coefficient array (no pss)
void Solution::set_coeff_vector(Space* space, scalar* coeffs, bool add_dir_lift)
{
// sanity check
if (space == NULL) error("Space == NULL in Solutin::set_coeff_vector().");
int ndof = Space::get_num_dofs(space);
// initialize precalc shapeset using the space's shapeset
Shapeset *shapeset = space->get_shapeset();
if (space->get_shapeset() == NULL) error("Space->shapeset == NULL in Solution::set_coeff_vector().");
PrecalcShapeset *pss = new PrecalcShapeset(shapeset);
if (pss == NULL) error("PrecalcShapeset could not be allocated in Solution::set_coeff_vector().");
set_coeff_vector(space, pss, coeffs, add_dir_lift);
delete pss;
}
void J_dot_vec_jfnk(DiscreteProblem *dp, Space *space, Vector* vec,
scalar* y_orig, Vector* f_orig,
Vector* J_dot_vec,
double jfnk_epsilon, int ndof, MatrixSolverType matrix_solver)
{
scalar* y_perturbed = new scalar[ndof];
Vector* f_perturbed = create_vector(matrix_solver);
for (int i = 0; i < ndof; i++)
y_perturbed[i] = y_orig[i] + jfnk_epsilon*vec->get(i);
// NULL stands for that we are not interested in the matrix, just the vector.
dp->assemble(y_perturbed, NULL, f_perturbed, true);
set_coeff_vector(y_orig, space);
for (int i = 0; i < ndof; i++) {
J_dot_vec->set(i,(f_perturbed->get(i) - f_orig->get(i))/jfnk_epsilon);
}
delete [] y_perturbed;
delete [] f_perturbed;
}
int main() {
// Time measurement.
TimePeriod cpu_time;
cpu_time.tick();
// Create coarse mesh, set Dirichlet BC, enumerate basis functions.
Space* space = new Space(A, B, NELEM, DIR_BC_LEFT, DIR_BC_RIGHT, P_INIT, NEQ);
// Enumerate basis functions, info for user.
int ndof = Space::get_num_dofs(space);
info("ndof: %d", ndof);
// Initialize the weak formulation.
WeakForm wf;
wf.add_matrix_form(jacobian);
wf.add_vector_form(residual);
// Initialize the FE problem.
bool is_linear = false;
DiscreteProblem *dp_coarse = new DiscreteProblem(&wf, space, is_linear);
// Newton's loop on coarse mesh.
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec_coarse = new double[Space::get_num_dofs(space)];
get_coeff_vector(space, coeff_vec_coarse);
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix_coarse = create_matrix(matrix_solver);
Vector* rhs_coarse = create_vector(matrix_solver);
Solver* solver_coarse = create_linear_solver(matrix_solver, matrix_coarse, rhs_coarse);
int it = 1;
while (1) {
// Obtain the number of degrees of freedom.
int ndof_coarse = Space::get_num_dofs(space);
// Assemble the Jacobian matrix and residual vector.
dp_coarse->assemble(coeff_vec_coarse, matrix_coarse, rhs_coarse);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs_coarse);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL_COARSE && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i=0; i < ndof_coarse; i++) rhs_coarse->set(i, -rhs_coarse->get(i));
// Solve the linear system.
if(!solver_coarse->solve())
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof_coarse; i++) coeff_vec_coarse[i] += solver_coarse->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec_coarse, space);
it++;
}
// Cleanup.
delete matrix_coarse;
delete rhs_coarse;
delete solver_coarse;
delete [] coeff_vec_coarse;
delete dp_coarse;
// DOF and CPU convergence graphs.
SimpleGraph graph_dof_est, graph_cpu_est;
SimpleGraph graph_dof_exact, graph_cpu_exact;
// Adaptivity loop:
int as = 1;
bool done = false;
do
{
info("---- Adaptivity step %d:", as);
// Construct globally refined reference mesh and setup reference space.
Space* ref_space = construct_refined_space(space);
// Initialize the FE problem.
bool is_linear = false;
DiscreteProblem* dp = new DiscreteProblem(&wf, ref_space, is_linear);
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix = create_matrix(matrix_solver);
Vector* rhs = create_vector(matrix_solver);
Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);
// Newton's loop on the fine mesh.
info("Solving on fine mesh:");
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec = new double[Space::get_num_dofs(ref_space)];
get_coeff_vector(ref_space, coeff_vec);
int it = 1;
while (1)
{
// Obtain the number of degrees of freedom.
int ndof = Space::get_num_dofs(ref_space);
// Assemble the Jacobian matrix and residual vector.
dp->assemble(coeff_vec, matrix, rhs);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(ref_space), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL_REF && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i = 0; i < ndof; i++) rhs->set(i, -rhs->get(i));
// Solve the linear system.
if(!solver->solve())
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec, ref_space);
it++;
}
// Starting with second adaptivity step, obtain new coarse
// mesh solution via projecting the fine mesh solution.
if(as > 1)
{
info("Projecting the fine mesh solution onto the coarse mesh.");
// Project the fine mesh solution (defined on space_ref) onto the coarse mesh (defined on space).
OGProjection::project_global(space, ref_space, matrix_solver);
}
// Calculate element errors and total error estimate.
info("Calculating error estimate.");
double err_est_array[MAX_ELEM_NUM];
double err_est_rel = calc_err_est(NORM, space, ref_space, err_est_array) * 100;
// Report results.
info("ndof_coarse: %d, ndof_fine: %d, err_est_rel: %g%%",
Space::get_num_dofs(space), Space::get_num_dofs(ref_space), err_est_rel);
// Time measurement.
cpu_time.tick();
// If exact solution available, also calculate exact error.
if (EXACT_SOL_PROVIDED)
{
// Calculate element errors wrt. exact solution.
double err_exact_rel = calc_err_exact(NORM, space, exact_sol, NEQ, A, B) * 100;
// Info for user.
info("Relative error (exact) = %g %%", err_exact_rel);
// Add entry to DOF and CPU convergence graphs.
graph_dof_exact.add_values(Space::get_num_dofs(space), err_exact_rel);
graph_cpu_exact.add_values(cpu_time.accumulated(), err_exact_rel);
}
// Add entry to DOF and CPU convergence graphs.
graph_dof_est.add_values(Space::get_num_dofs(space), err_est_rel);
graph_cpu_est.add_values(cpu_time.accumulated(), err_est_rel);
// If err_est_rel too large, adapt the mesh.
if (err_est_rel < NEWTON_TOL_REF) done = true;
else
{
info("Adapting the coarse mesh.");
adapt(NORM, ADAPT_TYPE, THRESHOLD, err_est_array, space, ref_space);
}
as++;
// Plot meshes, results, and errors.
adapt_plotting(space, ref_space, NORM, EXACT_SOL_PROVIDED, exact_sol);
// Cleanup.
delete solver;
delete matrix;
delete rhs;
delete ref_space;
delete dp;
delete [] coeff_vec;
}
while (done == false);
info("Total running time: %g s", cpu_time.accumulated());
// Save convergence graphs.
graph_dof_est.save("conv_dof_est.dat");
graph_cpu_est.save("conv_cpu_est.dat");
graph_dof_exact.save("conv_dof_exact.dat");
graph_cpu_exact.save("conv_cpu_exact.dat");
return 0;
}
int main()
{
// Create space, set Dirichlet BC, enumerate basis functions.
Space* space = new Space(A, B, NELEM, DIR_BC_LEFT, DIR_BC_RIGHT, P_INIT, NEQ);
int ndof = Space::get_num_dofs(space);
info("ndof: %d", ndof);
// Initialize the weak formulation.
WeakForm wf;
wf.add_matrix_form(jacobian_vol);
wf.add_vector_form(residual_vol);
wf.add_vector_form_surf(0, residual_surf_right, BOUNDARY_RIGHT);
// Initialize the FE problem.
bool is_linear = false;
DiscreteProblem *dp = new DiscreteProblem(&wf, space, is_linear);
// Newton's loop.
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec = new double[Space::get_num_dofs(space)];
get_coeff_vector(space, coeff_vec);
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix = create_matrix(matrix_solver);
Vector* rhs = create_vector(matrix_solver);
Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);
int it = 1;
while (1) {
// Obtain the number of degrees of freedom.
int ndof = Space::get_num_dofs(space);
// Assemble the Jacobian matrix and residual vector.
dp->assemble(coeff_vec, matrix, rhs);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i=0; i<ndof; i++) rhs->set(i, -rhs->get(i));
// Solve the linear system.
if(!solver->solve())
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec, space);
it++;
}
// Plot the solution.
Linearizer l(space);
l.plot_solution("solution.gp");
// Plot the resulting space.
space->plot("space.gp");
info("Done.");
return 0;
}
int main()
{
// Time measurement.
TimePeriod cpu_time;
cpu_time.tick();
// Create coarse mesh, set Dirichlet BC, enumerate basis functions.
Space* space = new Space(A, B, NELEM, DIR_BC_LEFT, DIR_BC_RIGHT, P_INIT, NEQ);
// Enumerate basis functions, info for user.
int ndof = Space::get_num_dofs(space);
info("ndof: %d", ndof);
// Initialize the weak formulation.
WeakForm wf;
wf.add_matrix_form(jacobian);
wf.add_vector_form(residual);
double elem_errors[MAX_ELEM_NUM]; // This array decides what
// elements will be refined.
ElemPtr2 ref_elem_pairs[MAX_ELEM_NUM]; // To store element pairs from the
// FTR solution. Decides how
// elements will be hp-refined.
for (int i=0; i < MAX_ELEM_NUM; i++)
{
ref_elem_pairs[i][0] = new Element();
ref_elem_pairs[i][1] = new Element();
}
// DOF and CPU convergence graphs.
SimpleGraph graph_dof_exact, graph_cpu_exact;
/// Adaptivity loop:
int as = 1;
bool done = false;
do
{
info("---- Adaptivity step %d:", as);
// Initialize the FE problem.
bool is_linear = false;
DiscreteProblem *dp_coarse = new DiscreteProblem(&wf, space, is_linear);
// Newton's loop on coarse mesh.
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec_coarse = new double[Space::get_num_dofs(space)];
get_coeff_vector(space, coeff_vec_coarse);
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix_coarse = create_matrix(matrix_solver);
Vector* rhs_coarse = create_vector(matrix_solver);
Solver* solver_coarse = create_linear_solver(matrix_solver, matrix_coarse, rhs_coarse);
int it = 1;
while (1)
{
// Obtain the number of degrees of freedom.
int ndof_coarse = Space::get_num_dofs(space);
// Assemble the Jacobian matrix and residual vector.
dp_coarse->assemble(coeff_vec_coarse, matrix_coarse, rhs_coarse);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs_coarse);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL_COARSE && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i=0; i<ndof_coarse; i++) rhs_coarse->set(i, -rhs_coarse->get(i));
// Solve the linear system.
if(!solver_coarse->solve())
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof_coarse; i++) coeff_vec_coarse[i] += solver_coarse->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec_coarse, space);
it++;
}
// Cleanup.
delete matrix_coarse;
delete rhs_coarse;
delete solver_coarse;
delete [] coeff_vec_coarse;
delete dp_coarse;
// For every element perform its fast trial refinement (FTR),
// calculate the norm of the difference between the FTR
// solution and the coarse space solution, and store the
// error in the elem_errors[] array.
int n_elem = space->get_n_active_elem();
for (int i=0; i < n_elem; i++)
{
info("=== Starting FTR of Elem [%d].", i);
// Replicate coarse space including solution.
Space *space_ref_local = space->replicate();
// Perform FTR of element 'i'
space_ref_local->reference_refinement(i, 1);
info("Elem [%d]: fine space created (%d DOF).",
i, space_ref_local->assign_dofs());
// Initialize the FE problem.
bool is_linear = false;
DiscreteProblem* dp = new DiscreteProblem(&wf, space_ref_local, is_linear);
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix = create_matrix(matrix_solver);
Vector* rhs = create_vector(matrix_solver);
Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);
// Newton's loop on the FTR space.
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec = new double[Space::get_num_dofs(space_ref_local)];
get_coeff_vector(space_ref_local, coeff_vec);
memset(coeff_vec, 0, Space::get_num_dofs(space_ref_local)*sizeof(double));
int it = 1;
while (1)
{
// Obtain the number of degrees of freedom.
int ndof = Space::get_num_dofs(space_ref_local);
// Assemble the Jacobian matrix and residual vector.
dp->assemble(coeff_vec, matrix, rhs);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space_ref_local), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL_REF && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i=0; i<ndof; i++) rhs->set(i, -rhs->get(i));
// Solve the linear system.
if(!solver->solve())
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec, space_ref_local);
it++;
}
// Cleanup.
delete matrix;
delete rhs;
delete solver;
delete dp;
delete [] coeff_vec;
// Print FTR solution (enumerated).
//Linearizer *lxx = new Linearizer(space_ref_local);
//char out_filename[255];
//sprintf(out_filename, "solution_ref_%d.gp", i);
//lxx->plot_solution(out_filename);
//delete lxx;
// Calculate norm of the difference between the coarse space
// and FTR solutions.
// NOTE: later we want to look at the difference in some quantity
// of interest rather than error in global norm.
double err_est_array[MAX_ELEM_NUM];
elem_errors[i] = calc_err_est(NORM, space, space_ref_local, err_est_array) * 100;
info("Elem [%d]: absolute error (est) = %g%%", i, elem_errors[i]);
// Copy the reference element pair for element 'i'.
// into the ref_elem_pairs[i][] array
Iterator *I = new Iterator(space);
Iterator *I_ref = new Iterator(space_ref_local);
Element *e, *e_ref;
while (1)
{
e = I->next_active_element();
e_ref = I_ref->next_active_element();
if (e->id == i)
{
e_ref->copy_into(ref_elem_pairs[e->id][0]);
// coarse element 'e' was split in space.
if (e->level != e_ref->level)
{
e_ref = I_ref->next_active_element();
e_ref->copy_into(ref_elem_pairs[e->id][1]);
}
break;
}
}
delete I;
delete I_ref;
delete space_ref_local;
}
// Time measurement.
cpu_time.tick();
// If exact solution available, also calculate exact error.
if (EXACT_SOL_PROVIDED)
{
// Calculate element errors wrt. exact solution.
double err_exact_rel = calc_err_exact(NORM, space, exact_sol, NEQ, A, B) * 100;
// Info for user.
info("Relative error (exact) = %g %%", err_exact_rel);
// Add entry to DOF and CPU convergence graphs.
graph_dof_exact.add_values(Space::get_num_dofs(space), err_exact_rel);
graph_cpu_exact.add_values(cpu_time.accumulated(), err_exact_rel);
}
// Calculate max FTR error.
double max_ftr_error = 0;
for (int i=0; i < space->get_n_active_elem(); i++)
{
if (elem_errors[i] > max_ftr_error) max_ftr_error = elem_errors[i];
}
info("Max FTR error = %g%%.", max_ftr_error);
// Decide whether the max. FTR error is sufficiently small.
if(max_ftr_error < TOL_ERR_FTR) break;
// debug
//if (as >= 1) break;
// Returns updated coarse space with the last solution on it.
adapt(NORM, ADAPT_TYPE, THRESHOLD, elem_errors, space, ref_elem_pairs);
// Plot spaces, results, and errors.
//adapt_plotting(space, ref_elem_pairs, NORM, EXACT_SOL_PROVIDED, exact_sol);
as++;
}
while (done == false);
info("Total running time: %g s", cpu_time.accumulated());
// Save convergence graphs.
graph_dof_exact.save("conv_dof_exact.dat");
graph_cpu_exact.save("conv_cpu_exact.dat");
// Test variable.
bool success = true;
info("ndof = %d.", Space::get_num_dofs(space));
if (Space::get_num_dofs(space) > 35) success = false;
if (success)
{
info("Success!");
return ERROR_SUCCESS;
}
else
{
info("Failure!");
return ERROR_FAILURE;
}
}
void compute_trajectory(Space *space, DiscreteProblem *dp)
{
info("alpha = (%g, %g, %g, %g), zeta = (%g, %g, %g, %g)",
alpha_ctrl[0], alpha_ctrl[1],
alpha_ctrl[2], alpha_ctrl[3], zeta_ctrl[0],
zeta_ctrl[1], zeta_ctrl[2], zeta_ctrl[3]);
// Newton's loop.
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec = new double[Space::get_num_dofs(space)];
get_coeff_vector(space, coeff_vec);
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix = create_matrix(matrix_solver);
Vector* rhs = create_vector(matrix_solver);
Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);
int it = 1;
while (1)
{
// Obtain the number of degrees of freedom.
int ndof = Space::get_num_dofs(space);
// Assemble the Jacobian matrix and residual vector.
dp->assemble(coeff_vec, matrix, rhs);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i=0; i<ndof; i++) rhs->set(i, -rhs->get(i));
// Solve the linear system.
if(!solver->solve())
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec, space);
it++;
}
// Cleanup.
delete matrix;
delete rhs;
delete solver;
delete [] coeff_vec;
}
int main()
{
// Create space.
// Transform input data to the format used by the "Space" constructor.
SpaceData *md = new SpaceData(verbose);
Space* space = new Space(md->N_macroel, md->interfaces, md->poly_orders, md->material_markers, md->subdivisions, N_GRP, N_SLN);
delete md;
// Enumerate basis functions, info for user.
int ndof = Space::get_num_dofs(space);
info("ndof: %d", ndof);
// Plot the space.
space->plot("space.gp");
// Initial approximation of the dominant eigenvalue.
double K_EFF = 1.0;
// Initial approximation of the dominant eigenvector.
double init_val = 1.0;
for (int g = 0; g < N_GRP; g++)
{
set_vertex_dofs_constant(space, init_val, g);
space->set_bc_right_dirichlet(g, flux_right_surf[g]);
}
// Initialize the weak formulation.
WeakForm wf(2);
wf.add_matrix_form(0, 0, jacobian_fuel_0_0, NULL, fuel);
wf.add_matrix_form(0, 0, jacobian_water_0_0, NULL, water);
wf.add_matrix_form(0, 1, jacobian_fuel_0_1, NULL, fuel);
wf.add_matrix_form(0, 1, jacobian_water_0_1, NULL, water);
wf.add_matrix_form(1, 0, jacobian_fuel_1_0, NULL, fuel);
wf.add_matrix_form(1, 0, jacobian_water_1_0, NULL, water);
wf.add_matrix_form(1, 1, jacobian_fuel_1_1, NULL, fuel);
wf.add_matrix_form(1, 1, jacobian_water_1_1, NULL, water);
wf.add_vector_form(0, residual_fuel_0, NULL, fuel);
wf.add_vector_form(0, residual_water_0, NULL, water);
wf.add_vector_form(1, residual_fuel_1, NULL, fuel);
wf.add_vector_form(1, residual_water_1, NULL, water);
wf.add_vector_form_surf(0, residual_surf_left_0, BOUNDARY_LEFT);
wf.add_vector_form_surf(1, residual_surf_left_1, BOUNDARY_LEFT);
// Initialize the FE problem.
bool is_linear = false;
DiscreteProblem *dp = new DiscreteProblem(&wf, space, is_linear);
Linearizer l(space);
char solution_file[32];
// Source iteration
int i;
int current_solution = 0, previous_solution = 1;
double K_EFF_old;
for (i = 0; i < Max_SI; i++)
{
// Plot the critical (i.e. steady-state) flux in the actual iteration.
sprintf(solution_file, "solution_%d.gp", i);
l.plot_solution(solution_file);
// Store the previous solution (used at the right-hand side).
for (int g = 0; g < N_GRP; g++)
copy_dofs(current_solution, previous_solution, space, g);
// Obtain the number of degrees of freedom.
int ndof = Space::get_num_dofs(space);
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec = new double[Space::get_num_dofs(space)];
get_coeff_vector(space, coeff_vec);
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix = create_matrix(matrix_solver);
Vector* rhs = create_vector(matrix_solver);
Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);
int it = 1;
while (1)
{
// Obtain the number of degrees of freedom.
int ndof = Space::get_num_dofs(space);
// Assemble the Jacobian matrix and residual vector.
dp->assemble(coeff_vec, matrix, rhs);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i=0; i<ndof; i++) rhs->set(i, -rhs->get(i));
// Solve the linear system.
if(!solver->solve())
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec, space);
it++;
}
// Cleanup.
delete matrix;
delete rhs;
delete solver;
delete [] coeff_vec;
// Update the eigenvalue.
K_EFF_old = K_EFF;
K_EFF = calc_total_reaction_rate(space, nSf, 0., 40.);
// Convergence test.
if (fabs(K_EFF - K_EFF_old)/K_EFF < TOL_SI) break;
// Normalize total neutron flux to one fission neutron.
multiply_dofs_with_constant(space, 1./K_EFF, current_solution);
if (verbose) info("K_EFF_%d = %.8f", i+1, K_EFF);
}
// Print the converged eigenvalue.
info("K_EFF = %.8f, err= %.8f%%", K_EFF, 100*(K_EFF-1));
// Plot the converged critical neutron flux.
sprintf(solution_file, "solution.gp");
l.plot_solution(solution_file);
// Comparison with analytical results (see the reference above).
double flux[N_GRP], J[N_GRP], R;
get_solution_at_point(space, 0.0, flux, J);
R = flux[0]/flux[1];
info("phi_fast/phi_therm at x=0 : %.4f, err = %.2f%%", R, 100*(R-2.5332)/2.5332);
get_solution_at_point(space, 40.0, flux, J);
R = flux[0]/flux[1];
info("phi_fast/phi_therm at x=40 : %.4f, err = %.2f%%", R, 100*(R-1.5162)/1.5162);
info("Done.");
return 0;
}
int main()
{
// Time measurement.
TimePeriod cpu_time;
cpu_time.tick();
// Create space, set Dirichlet BC, enumerate basis functions.
Space* space = new Space(A, B, NELEM, DIR_BC_LEFT, DIR_BC_RIGHT, P_INIT, NEQ, NEQ);
// Enumerate basis functions, info for user.
int ndof = Space::get_num_dofs(space);
info("ndof: %d", ndof);
// Initialize the weak formulation.
WeakForm wf(2);
wf.add_matrix_form(0, 0, jacobian_0_0);
wf.add_matrix_form(0, 1, jacobian_0_1);
wf.add_matrix_form(1, 0, jacobian_1_0);
wf.add_matrix_form(1, 1, jacobian_1_1);
wf.add_vector_form(0, residual_0);
wf.add_vector_form(1, residual_1);
// Initialize the FE problem.
bool is_linear = false;
DiscreteProblem *dp = new DiscreteProblem(&wf, space, is_linear);
// Newton's loop.
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec = new double[Space::get_num_dofs(space)];
get_coeff_vector(space, coeff_vec);
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix = create_matrix(matrix_solver);
Vector* rhs = create_vector(matrix_solver);
Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);
int it = 1;
bool success = false;
while (1)
{
// Obtain the number of degrees of freedom.
int ndof = Space::get_num_dofs(space);
// Assemble the Jacobian matrix and residual vector.
dp->assemble(coeff_vec, matrix, rhs);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i=0; i<ndof; i++) rhs->set(i, -rhs->get(i));
// Solve the linear system.
if(!(success = solver->solve()))
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec, space);
it++;
}
info("Total running time: %g s", cpu_time.accumulated());
// Test variable.
info("ndof = %d.", Space::get_num_dofs(space));
if (success)
{
info("Success!");
return ERROR_SUCCESS;
}
else
{
info("Failure!");
return ERROR_FAILURE;
}
}
// CG method adjusted for JFNK
// NOTE:
void jfnk_cg(DiscreteProblem *dp, Space *space,
double matrix_solver_tol, int matrix_solver_maxiter,
double jfnk_epsilon, double tol_jfnk, int jfnk_maxiter,
MatrixSolverType matrix_solver, bool verbose)
{
int ndof = Space::get_num_dofs(space);
// vectors for JFNK
Vector* f_orig = create_vector(matrix_solver);
scalar* y_orig = new scalar[ndof];
Vector* vec = create_vector(matrix_solver);
Vector* rhs = create_vector(matrix_solver);
// vectors for the CG method
Vector* r = create_vector(matrix_solver);
Vector* p = create_vector(matrix_solver);
Vector* J_dot_vec = create_vector(matrix_solver);
// fill vector y_orig using dof and coeffs arrays in elements
get_coeff_vector(space, y_orig);
// JFNK loop
int jfnk_iter_num = 1;
while (1) {
// construct residual vector f_orig corresponding to y_orig
// (f_orig stays unchanged through the entire CG loop)
// NULL stands for that we are not interested in the matrix, just the vector.
dp->assemble(y_orig, NULL, f_orig, true);
// calculate L2 norm of f_orig
double res_norm_squared = 0;
for(int i = 0; i < ndof; i++) res_norm_squared += f_orig->get(i)*f_orig->get(i);
// If residual norm less than 'tol_jfnk', break
if (verbose) {
info("Residual norm: %.15f", sqrt(res_norm_squared));
}
if(res_norm_squared < tol_jfnk*tol_jfnk) break;
if (verbose) {
info("JFNK iteration: %d", jfnk_iter_num);
}
// right-hand side is negative residual
// (rhs stays unchanged through the CG loop)
for(int i = 0; i < ndof; i++) rhs->set(i, -f_orig->get(i));
// beginning CG method
// r = rhs - A*vec0 (where the initial vector vec0 = 0)
for (int i=0; i < ndof; i++) r->set(i, rhs->get(i));
// p = r
for (int i=0; i < ndof; i++) p->set(i, r->get(i));
// CG loop
int iter_current = 0;
double tol_current_squared;
// initializing the solution vector with zero
for(int i = 0; i < ndof; i++) vec->set(i, 0);
while (1) {
J_dot_vec_jfnk(dp, space, p, y_orig, f_orig,
J_dot_vec, jfnk_epsilon, ndof, matrix_solver);
double r_times_r = vec_dot(r, r, ndof);
double alpha = r_times_r / vec_dot(p, J_dot_vec, ndof);
for (int i=0; i < ndof; i++) {
vec->set(i, vec->get(i) + alpha*p->get(i));
r->set(i, r->get(i) - alpha*J_dot_vec->get(i));
}
/*
// debug - output of solution vector
printf(" vec = ");
for (int i=0; i < ndof; i++) {
printf("%g ", vec[i]);
}
printf("\n");
*/
double r_times_r_new = vec_dot(r, r, ndof);
iter_current++;
tol_current_squared = r_times_r_new;
if (tol_current_squared < matrix_solver_tol*matrix_solver_tol
|| iter_current >= matrix_solver_maxiter) break;
double beta = r_times_r_new/r_times_r;
for (int i=0; i < ndof; i++) p->set(i, r->get(i) + beta*p->get(i));
}
// check whether CG converged
if (verbose) {
info("CG (JFNK) made %d iteration(s) (tol = %g)",
iter_current, sqrt(tol_current_squared));
}
if(tol_current_squared > matrix_solver_tol*matrix_solver_tol) {
error("CG (JFNK) did not converge.");
}
// updating vector y_orig by new solution which is in x
for(int i=0; i<ndof; i++) y_orig[i] = y_orig[i] + vec->get(i);
jfnk_iter_num++;
if (jfnk_iter_num >= jfnk_maxiter) {
error("JFNK did not converge.");
}
}
delete f_orig;
// copy updated vector y_orig to space
set_coeff_vector(y_orig, space);
}
int main()
{
// Time measurement.
TimePeriod cpu_time;
cpu_time.tick();
// Create coarse mesh, set Dirichlet BC, enumerate basis functions.
Space* space = new Space(A, B, NELEM, DIR_BC_LEFT, DIR_BC_RIGHT, P_INIT, NEQ);
// Enumerate basis functions, info for user.
int ndof = Space::get_num_dofs(space);
info("ndof: %d", ndof);
// Initialize the weak formulation.
WeakForm wf;
wf.add_matrix_form(jacobian);
wf.add_vector_form(residual);
// Initialize the FE problem.
bool is_linear = false;
DiscreteProblem *dp_coarse = new DiscreteProblem(&wf, space, is_linear);
if(JFNK == 0)
{
// Newton's loop on coarse mesh.
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec_coarse = new double[Space::get_num_dofs(space)];
get_coeff_vector(space, coeff_vec_coarse);
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix_coarse = create_matrix(matrix_solver);
Vector* rhs_coarse = create_vector(matrix_solver);
Solver* solver_coarse = create_linear_solver(matrix_solver, matrix_coarse, rhs_coarse);
int it = 1;
while (1)
{
// Obtain the number of degrees of freedom.
int ndof_coarse = Space::get_num_dofs(space);
// Assemble the Jacobian matrix and residual vector.
dp_coarse->assemble(coeff_vec_coarse, matrix_coarse, rhs_coarse);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs_coarse);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL_COARSE && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i = 0; i < ndof_coarse; i++) rhs_coarse->set(i, -rhs_coarse->get(i));
// Solve the linear system.
if(!solver_coarse->solve())
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof_coarse; i++) coeff_vec_coarse[i] += solver_coarse->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec_coarse, space);
it++;
}
// Cleanup.
delete matrix_coarse;
delete rhs_coarse;
delete solver_coarse;
delete [] coeff_vec_coarse;
}
else
jfnk_cg(dp_coarse, space, MATRIX_SOLVER_TOL, MATRIX_SOLVER_MAXITER,
JFNK_EPSILON, NEWTON_TOL_COARSE, NEWTON_MAX_ITER, matrix_solver);
// Cleanup.
delete dp_coarse;
// DOF and CPU convergence graphs.
SimpleGraph graph_dof_est, graph_cpu_est;
SimpleGraph graph_dof_exact, graph_cpu_exact;
// Adaptivity loop:
int as = 1;
double ftr_errors[MAX_ELEM_NUM]; // This array decides what
// elements will be refined.
bool done = false;
do
{
info("---- Adaptivity step %d:", as);
// Construct globally refined reference mesh and setup reference space.
Space* ref_space = construct_refined_space(space);
// Initialize the FE problem.
bool is_linear = false;
DiscreteProblem* dp = new DiscreteProblem(&wf, ref_space, is_linear);
if(JFNK == 0)
{
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix = create_matrix(matrix_solver);
Vector* rhs = create_vector(matrix_solver);
Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);
// Newton's loop on the fine mesh.
info("Solving on fine mesh:");
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec = new double[Space::get_num_dofs(ref_space)];
get_coeff_vector(ref_space, coeff_vec);
int it = 1;
while (1)
{
// Obtain the number of degrees of freedom.
int ndof = Space::get_num_dofs(ref_space);
// Assemble the Jacobian matrix and residual vector.
dp->assemble(coeff_vec, matrix, rhs);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(ref_space), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL_REF && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i = 0; i < ndof; i++) rhs->set(i, -rhs->get(i));
// Solve the linear system.
if(!solver->solve())
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec, ref_space);
it++;
}
// Cleanup.
delete matrix;
delete rhs;
delete solver;
delete [] coeff_vec;
}
else
jfnk_cg(dp, ref_space, MATRIX_SOLVER_TOL, MATRIX_SOLVER_MAXITER,
JFNK_EPSILON, NEWTON_TOL_COARSE, NEWTON_MAX_ITER, matrix_solver);
// Cleanup.
delete dp;
// Starting with second adaptivity step, obtain new coarse
// mesh solution via projecting the fine mesh solution.
if(as > 1)
{
info("Projecting the fine mesh solution onto the coarse mesh.");
// Project the fine mesh solution (defined on space_ref) onto the coarse mesh (defined on space).
OGProjection::project_global(space, ref_space, matrix_solver);
}
double max_qoi_err_est = 0;
for (int i=0; i < space->get_n_active_elem(); i++)
{
if (GOAL_ORIENTED == 1)
{
// Use quantity of interest.
double qoi_est = quantity_of_interest(space, X_QOI);
double qoi_ref_est = quantity_of_interest(ref_space, X_QOI);
ftr_errors[i] = fabs(qoi_ref_est - qoi_est);
}
else
{
// Use global norm
double err_est_array[MAX_ELEM_NUM];
ftr_errors[i] = calc_err_est(NORM, space, ref_space, err_est_array);
}
// Info for user.
info("Elem [%d]: absolute error (est) = %g%%", i, ftr_errors[i]);
// Time measurement.
cpu_time.tick();
// Calculating maximum of QOI FTR error for plotting purposes
if (GOAL_ORIENTED == 1)
{
if (ftr_errors[i] > max_qoi_err_est)
max_qoi_err_est = ftr_errors[i];
}
else
{
double qoi_est = quantity_of_interest(space, X_QOI);
double qoi_ref_est = quantity_of_interest(ref_space, X_QOI);
double err_est = fabs(qoi_ref_est - qoi_est);
if (err_est > max_qoi_err_est)
max_qoi_err_est = err_est;
}
}
// Add entries to convergence graphs.
if (EXACT_SOL_PROVIDED)
{
double qoi_est = quantity_of_interest(space, X_QOI);
double u[MAX_EQN_NUM], dudx[MAX_EQN_NUM];
exact_sol(X_QOI, u, dudx);
double err_qoi_exact = fabs(u[0] - qoi_est);
// Info for user.
info("Relative error (exact) = %g %%", err_qoi_exact);
// Add entry to DOF and CPU convergence graphs.
graph_dof_exact.add_values(Space::get_num_dofs(space), err_qoi_exact);
graph_cpu_exact.add_values(cpu_time.accumulated(), err_qoi_exact);
}
// Add entry to DOF and CPU convergence graphs.
graph_dof_est.add_values(Space::get_num_dofs(space), max_qoi_err_est);
graph_cpu_est.add_values(cpu_time.accumulated(), max_qoi_err_est);
// Decide whether the max. FTR error in the quantity of interest
// is sufficiently small.
if(max_qoi_err_est < TOL_ERR_QOI) break;
// Returns updated coarse and fine meshes, with the last
// coarse and fine mesh solutions on them, respectively.
// The coefficient vectors and numbers of degrees of freedom
// on both meshes are also updated.
adapt(NORM, ADAPT_TYPE, THRESHOLD, ftr_errors, space, ref_space);
as++;
// Plot meshes, results, and errors.
adapt_plotting(space, ref_space, NORM, EXACT_SOL_PROVIDED, exact_sol);
// Cleanup.
delete ref_space;
}
while (done == false);
info("Total running time: %g s", cpu_time.accumulated());
// Save convergence graphs.
graph_dof_est.save("conv_dof_est.dat");
graph_cpu_est.save("conv_cpu_est.dat");
graph_dof_exact.save("conv_dof_exact.dat");
graph_cpu_exact.save("conv_cpu_exact.dat");
// Test variable.
bool success = true;
info("ndof = %d.", Space::get_num_dofs(space));
if (Space::get_num_dofs(space) > 150) success = false;
if (success)
{
info("Success!");
return ERROR_SUCCESS;
}
else
{
info("Failure!");
return ERROR_FAILURE;
}
}
int main()
{
// Create space.
// Transform input data to the format used by the "Space" constructor.
SpaceData *md = new SpaceData();
// Boundary conditions.
Hermes::vector<BCSpec *>DIR_BC_LEFT;
Hermes::vector<BCSpec *>DIR_BC_RIGHT;
for (int g = 0; g < N_GRP; g++)
{
DIR_BC_LEFT.push_back(new BCSpec(g,flux_left_surf[g]));
DIR_BC_RIGHT.push_back(new BCSpec(g,flux_right_surf[g]));
}
Space* space = new Space(md->N_macroel, md->interfaces, md->poly_orders, md->material_markers, md->subdivisions,
DIR_BC_LEFT, DIR_BC_RIGHT, N_GRP, N_SLN);
delete md;
// Enumerate basis functions, info for user.
int ndof = Space::get_num_dofs(space);
info("ndof: %d", ndof);
// Plot the space.
// Initialize the weak formulation.
WeakForm wf(2);
wf.add_matrix_form(0, 0, jacobian_mat1_0_0, NULL, mat1);
wf.add_matrix_form(0, 0, jacobian_mat2_0_0, NULL, mat2);
wf.add_matrix_form(0, 0, jacobian_mat3_0_0, NULL, mat3);
wf.add_matrix_form(0, 1, jacobian_mat1_0_1, NULL, mat1);
wf.add_matrix_form(0, 1, jacobian_mat2_0_1, NULL, mat2);
wf.add_matrix_form(0, 1, jacobian_mat3_0_1, NULL, mat3);
wf.add_matrix_form(1, 0, jacobian_mat1_1_0, NULL, mat1);
wf.add_matrix_form(1, 0, jacobian_mat2_1_0, NULL, mat2);
wf.add_matrix_form(1, 0, jacobian_mat3_1_0, NULL, mat3);
wf.add_matrix_form(1, 1, jacobian_mat1_1_1, NULL, mat1);
wf.add_matrix_form(1, 1, jacobian_mat2_1_1, NULL, mat2);
wf.add_matrix_form(1, 1, jacobian_mat3_1_1, NULL, mat3);
wf.add_vector_form(0, residual_mat1_0, NULL, mat1);
wf.add_vector_form(0, residual_mat2_0, NULL, mat2);
wf.add_vector_form(0, residual_mat3_0, NULL, mat3);
wf.add_vector_form(1, residual_mat1_1, NULL, mat1);
wf.add_vector_form(1, residual_mat2_1, NULL, mat2);
wf.add_vector_form(1, residual_mat3_1, NULL, mat3);
// Initialize the FE problem.
bool is_linear = false;
DiscreteProblem *dp = new DiscreteProblem(&wf, space, is_linear);
// Newton's loop.
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec = new double[Space::get_num_dofs(space)];
get_coeff_vector(space, coeff_vec);
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix = create_matrix(matrix_solver);
Vector* rhs = create_vector(matrix_solver);
Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);
int it = 1;
while (1)
{
// Obtain the number of degrees of freedom.
int ndof = Space::get_num_dofs(space);
// Assemble the Jacobian matrix and residual vector.
dp->assemble(coeff_vec, matrix, rhs);
#include "../../../hermes_common/solver/umfpack_solver.h"
CSCMatrix *mm = static_cast<CSCMatrix*>(matrix);
UMFPackVector *mv = static_cast<UMFPackVector*>(rhs);
FILE *fp = fopen("data.m", "wt");
mm->dump(fp, "A");
mv->dump(fp, "b");
fclose(fp);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i=0; i<ndof; i++) rhs->set(i, -rhs->get(i));
// Solve the linear system.
if(!solver->solve())
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec, space);
it++;
}
// Plot the solution.
Linearizer l(space);
l.plot_solution("solution.gp");
// Cleanup.
for(unsigned i = 0; i < DIR_BC_LEFT.size(); i++)
delete DIR_BC_LEFT[i];
DIR_BC_LEFT.clear();
for(unsigned i = 0; i < DIR_BC_RIGHT.size(); i++)
delete DIR_BC_RIGHT[i];
DIR_BC_RIGHT.clear();
delete matrix;
delete rhs;
delete solver;
delete[] coeff_vec;
delete dp;
delete space;
info("Done.");
return 0;
}
int main() {
// Three macroelements are defined above via the interfaces[] array.
// poly_orders[]... initial poly degrees of macroelements.
// material_markers[]... material markers of macroelements.
// subdivisions[]... equidistant subdivision of macroelements.
int poly_orders[N_MAT] = {P_init_inner, P_init_outer, P_init_reflector };
int material_markers[N_MAT] = {Marker_inner, Marker_outer, Marker_reflector };
int subdivisions[N_MAT] = {N_subdiv_inner, N_subdiv_outer, N_subdiv_reflector };
// Create space.
Space* space = new Space(N_MAT, interfaces, poly_orders, material_markers, subdivisions, N_GRP, N_SLN);
// Enumerate basis functions, info for user.
info("N_dof = %d", Space::get_num_dofs(space));
// Initial approximation: u = 1.
double K_EFF_old;
double init_val = 1.0;
set_vertex_dofs_constant(space, init_val, 0);
// Initialize the weak formulation.
WeakForm wf;
wf.add_matrix_form(jacobian_vol_inner, NULL, Marker_inner);
wf.add_matrix_form(jacobian_vol_outer, NULL, Marker_outer);
wf.add_matrix_form(jacobian_vol_reflector, NULL, Marker_reflector);
wf.add_vector_form(residual_vol_inner, NULL, Marker_inner);
wf.add_vector_form(residual_vol_outer, NULL, Marker_outer);
wf.add_vector_form(residual_vol_reflector, NULL, Marker_reflector);
wf.add_vector_form_surf(residual_surf_left, BOUNDARY_LEFT);
wf.add_matrix_form_surf(jacobian_surf_right, BOUNDARY_RIGHT);
wf.add_vector_form_surf(residual_surf_right, BOUNDARY_RIGHT);
// Initialize the FE problem.
bool is_linear = false;
DiscreteProblem *dp = new DiscreteProblem(&wf, space, is_linear);
// Source iteration (power method).
for (int i = 0; i < Max_SI; i++)
{
// Obtain fission source.
int current_solution = 0, previous_solution = 1;
copy_dofs(current_solution, previous_solution, space);
// Obtain the number of degrees of freedom.
int ndof = Space::get_num_dofs(space);
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec = new double[Space::get_num_dofs(space)];
get_coeff_vector(space, coeff_vec);
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix = create_matrix(matrix_solver);
Vector* rhs = create_vector(matrix_solver);
Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);
int it = 1;
while (1) {
// Obtain the number of degrees of freedom.
int ndof = Space::get_num_dofs(space);
// Assemble the Jacobian matrix and residual vector.
dp->assemble(matrix, rhs);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i=0; i<ndof; i++) rhs->set(i, -rhs->get(i));
// Solve the linear system.
if(!solver->solve())
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec, space);
it++;
}
// Cleanup.
delete matrix;
delete rhs;
delete solver;
delete [] coeff_vec;
// Update the eigenvalue.
K_EFF_old = K_EFF;
K_EFF = calc_fission_yield(space);
info("K_EFF_%d = %f", i, K_EFF);
if (fabs(K_EFF - K_EFF_old)/K_EFF < TOL_SI) break;
}
// Plot the critical (i.e. steady-state) neutron flux.
Linearizer l(space);
l.plot_solution("solution.gp");
// Normalize so that the absolute neutron flux generates 320 Watts of energy
// (note that, using the symmetry condition at the origin, we've solved for
// flux only in the right half of the reactor).
normalize_to_power(space, 320/2.);
// Plot the solution and space.
l.plot_solution("solution_320W.gp");
space->plot("space.gp");
info("K_EFF = %f", K_EFF);
info("Done.");
return 0;
}
int main()
{
// Create space.
// Transform input data to the format used by the "Space" constructor.
SpaceData *md = new SpaceData();
Space* space = new Space(md->N_macroel, md->interfaces, md->poly_orders, md->material_markers, md->subdivisions, N_GRP, N_SLN);
delete md;
// Enumerate basis functions, info for user.
int ndof = Space::get_num_dofs(space);
info("ndof: %d", ndof);
// Plot the space.
space->plot("space.gp");
for (int g = 0; g < N_GRP; g++)
{
space->set_bc_left_dirichlet(g, flux_left_surf[g]);
space->set_bc_right_dirichlet(g, flux_right_surf[g]);
}
// Initialize the weak formulation.
WeakForm wf(2);
wf.add_matrix_form(0, 0, jacobian_mat1_0_0, NULL, mat1);
wf.add_matrix_form(0, 0, jacobian_mat2_0_0, NULL, mat2);
wf.add_matrix_form(0, 0, jacobian_mat3_0_0, NULL, mat3);
wf.add_matrix_form(0, 1, jacobian_mat1_0_1, NULL, mat1);
wf.add_matrix_form(0, 1, jacobian_mat2_0_1, NULL, mat2);
wf.add_matrix_form(0, 1, jacobian_mat3_0_1, NULL, mat3);
wf.add_matrix_form(1, 0, jacobian_mat1_1_0, NULL, mat1);
wf.add_matrix_form(1, 0, jacobian_mat2_1_0, NULL, mat2);
wf.add_matrix_form(1, 0, jacobian_mat3_1_0, NULL, mat3);
wf.add_matrix_form(1, 1, jacobian_mat1_1_1, NULL, mat1);
wf.add_matrix_form(1, 1, jacobian_mat2_1_1, NULL, mat2);
wf.add_matrix_form(1, 1, jacobian_mat3_1_1, NULL, mat3);
wf.add_vector_form(0, residual_mat1_0, NULL, mat1);
wf.add_vector_form(0, residual_mat2_0, NULL, mat2);
wf.add_vector_form(0, residual_mat3_0, NULL, mat3);
wf.add_vector_form(1, residual_mat1_1, NULL, mat1);
wf.add_vector_form(1, residual_mat2_1, NULL, mat2);
wf.add_vector_form(1, residual_mat3_1, NULL, mat3);
// Initialize the FE problem.
bool is_linear = false;
DiscreteProblem *dp = new DiscreteProblem(&wf, space, is_linear);
// Newton's loop.
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec = new double[Space::get_num_dofs(space)];
get_coeff_vector(space, coeff_vec);
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix = create_matrix(matrix_solver);
Vector* rhs = create_vector(matrix_solver);
Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);
int it = 1;
while (1)
{
// Obtain the number of degrees of freedom.
int ndof = Space::get_num_dofs(space);
// Assemble the Jacobian matrix and residual vector.
dp->assemble(coeff_vec, matrix, rhs);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i=0; i<ndof; i++) rhs->set(i, -rhs->get(i));
// Solve the linear system.
if(!solver->solve())
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec, space);
it++;
}
// Plot the solution.
Linearizer l(space);
l.plot_solution("solution.gp");
info("Done.");
return 0;
}
int main()
{
// Create space, set Dirichlet BC, enumerate basis functions.
Space* space = new Space(A, B, NELEM, DIR_BC_LEFT, DIR_BC_RIGHT, P_INIT, NEQ);
int ndof = Space::get_num_dofs(space);
info("ndof: %d", ndof);
// Initialize the weak formulation.
WeakForm wf;
wf.add_matrix_form(jacobian);
wf.add_vector_form(residual);
// Initialize the FE problem.
DiscreteProblem *dp = new DiscreteProblem(&wf, space);
// Allocate coefficient vector.
double *coeff_vec = new double[ndof];
memset(coeff_vec, 0, ndof*sizeof(double));
// Set up the solver, matrix, and rhs according to the solver selection.
SparseMatrix* matrix = create_matrix(matrix_solver);
Vector* rhs = create_vector(matrix_solver);
Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);
// Time stepping loop.
double current_time = 0.0;
while (current_time < T_FINAL)
{
// Newton's loop.
// Fill vector coeff_vec using dof and coeffs arrays in elements.
get_coeff_vector(space, coeff_vec);
int it = 1;
while (true)
{
// Assemble the Jacobian matrix and residual vector.
dp->assemble(coeff_vec, matrix, rhs);
// Calculate the l2-norm of residual vector.
double res_l2_norm = get_l2_norm(rhs);
// Info for user.
info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);
// If l2 norm of the residual vector is within tolerance, then quit.
// NOTE: at least one full iteration forced
// here because sometimes the initial
// residual on fine mesh is too small.
if(res_l2_norm < NEWTON_TOL && it > 1) break;
// Multiply the residual vector with -1 since the matrix
// equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
for(int i=0; i<ndof; i++) rhs->set(i, -rhs->get(i));
// Solve the linear system.
if(!solver->solve())
error ("Matrix solver failed.\n");
// Add \deltaY^{n+1} to Y^n.
for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];
// If the maximum number of iteration has been reached, then quit.
if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
// Copy coefficients from vector y to elements.
set_coeff_vector(coeff_vec, space);
it++;
}
// Plot the solution.
Linearizer l(space);
char filename[100];
sprintf(filename, "solution_%g.gp", current_time);
l.plot_solution(filename);
info("Solution %s written.", filename);
current_time += TAU;
}
// Plot the resulting space.
space->plot("space.gp");
// Cleaning
delete dp;
delete rhs;
delete solver;
delete[] coeff_vec;
delete space;
delete matrix;
info("Done.");
return 0;
}