--- /dev/null
+<br>
+
+<i>This program was contributed by Bruno Turcksin and Damien Lebrun-Grandie.</i>
+
+<a name="Intro"></a>
+<h1>Introducion</h1>
+
+This program shows how to use Runge-Kutta methods to solve a time-dependent
+problem.
+
+<h3>Problem statement<h3>
+
+In this example, we solve the energy-integrated time-dependent diffusion
+approximation of the neutron transport equation (see step-28 for the
+time-independent multigroup diffusion). We assume that the medium is not
+fissible and therefore, the neutron flux satisfies the following equation:
+@f{eqnarray*}
+\frac{1}{v}\frac{\partial \phi(x,t)}{\partial t} = \nabla D(x) \nabla \phi(x,t)
+- \Sigma_a(x) \phi(x,t) + S(x,t)
+@f}
+augmented by appropriate boundary conditions. Here, $v$ is the velocity of
+neutrons, $D$ is the diffusion coefficient, $\Sigma_a$ is the <i>absorption
+cross section</i>, and $S$ is a source. Because we are only interested in the
+time dependence, we assume that $D$ and $\Sigma_a$ are constant. In this
+example, we are only interested in the error in time and thus, we are looking
+for a solution of the form:
+@f{eqnarray*}
+\phi(x,t) = A\sin(\omega t)(bx-x^2).
+@f}
+By using quadratic finite elements, we will not have any spatial error. We
+impose the following boundary conditions: homogeneous Dirichlet fo $x=0$ and
+$x=b$ and homogeneous Neumann conditions for $y=0$ and $y=b$. The source is
+given by:
+@f{eqnarray*}
+S=A\left(\frac{1}{v}\omega \cos(\omega t)(bx -x^2) + \sin(\omega t)
+\left(\Sigma_a (bx-x^2)+2D\right) \right).
+@f}
+Because the solution is a sine, we know that
+\f$\phi\left(x,\frac{\pi}{\omega}\right) = 0$. Therefore, we can easily
+compute the error at this time since it is simply the norm of the solution
+found.
+
+<h3>Runge-Kutta</h3>
+
+The Runke-Kutta methods implemented in deal.II assume that the equation to be
+solved can be written as:
+@f{eqnarray*}
+\frac{dy}{dt} = f(t,y).
+@f}
+When using finite elements, the previous equation becomes:
+@f{eqnarray*}
+M\frac{dy}{dt} = f(t,y),
+@f}
+where $M$ is the mass matrix. Therefore, we have:
+@f{eqnarray*}
+\frac{dy}{dt} = M^{-1}f(t,y).
+@f}
+Runke-Kutta methods can be written as:
+@f{eqnarray*}
+y_{n+1} = y_n + \sum_{i=1}^s b_i k_i
+@f}
+where
+@f{eqnarray*}
+k_i = h M^{-1} f(t_n+c_ih,y_n+\sum_{j=1}^sa_{ij}k_j)
+@f}
+with $a_{ij}$, $b_i$, and $c_i$ are known coefficient and $h$ is the time step
+used. The methods currently implemented in deal.II can be divided in three
+categories:
+<ol>
+<li> explicit Runge-Kutta
+<li> embedded (or adaptive) Runge-Kutta
+<li> implicit Runge-Kutta
+</ol>
+
+<h4>Explicit Runge-Kutta</h4>
+These methods that include for forward Euler, third order Runge-Kutta, and
+fourth order Runge-Kutta, require a function to evaluate $M^{-1}f(t,y). These
+methods become unstable when the time step chosen is too large.
+
+<h4>Embedded Runge-Kutta</h4>
+These methods include Heun-Euler, Bogacki-Shampine, Dormand-Prince (ode45 in
+Matlab), Fehlberg, and Cash-Karp. These methods use a low order method to
+estimate the error and decide if the time step needs to be refined or it can be
+coarsen. Only embedded explicit methods have been implemented so far.
+
+<h4>Implicit Runge-Kutta</h4>
+These methods include backward Euler, implicit midpoint, Crank-Nicolson, and the
+two stages SDIRK. These methods require to evaluate $M^{-1}f(t,y)$ and
+$\left(I-\Delta t M^{-1} \frac{\partial f}{\partial Y}\right) = \left(M - \Delta
+t \frac{\partial f}{\partial y}\right)^{-1} M$. These methods are always stable.
+
+<h3>Remarks</h3>
+To simplify the problem, we solve the domain in two dimensional and the mesh is
+uniform (there is no need to adapt the mesh since we use quadratic finite
+elements and the exact solution is quadratic). Going from a two dimensional
+domain to a three dimensional domain is not very challenging. However if the
+mesh must be adapted, we cannot forget to:
+<ol>
+<li> project the solution to the new mesh when the mesh is changed. The mesh
+used should be the same at the beginning and at the end of the time step.
+<li> update the mass matrix and its inverse.
+</ol>
--- /dev/null
+/* ---------------------------------------------------------------------
+ * $Id: step-52.cc 30526 2013-08-29 20:06:27Z felix.gruber $
+ *
+ * Copyright (C) 2014 by the deal.II authors
+ *
+ * This file is part of the deal.II library.
+ *
+ * The deal.II library is free software; you can use it, redistribute
+ * it, and/or modify it under the terms of the GNU Lesser General
+ * Public License as published by the Free Software Foundation; either
+ * version 2.1 of the License, or (at your option) any later version.
+ * The full text of the license can be found in the file LICENSE at
+ * the top level of the deal.II distribution.
+ *
+ * ---------------------------------------------------------------------
+
+ *
+ * Authors: Damien Lebrun-Grandie, Bruno Turcksin, 2014
+ */
+
+// @sect3{Include files}
+
+// The first task as usal is to include the functionality of these well-known
+// deal.II library files and some C++ header files.
+#include <deal.II/base/function.h>
+#include <deal.II/base/quadrature_lib.h>
+
+#include <deal.II/grid/grid_generator.h>
+#include <deal.II/grid/tria_accessor.h>
+#include <deal.II/grid/tria_iterator.h>
+#include <deal.II/grid/tria_boundary_lib.h>
+#include <deal.II/grid/tria.h>
+#include <deal.II/grid/grid_out.h>
+
+#include <deal.II/dofs/dof_handler.h>
+#include <deal.II/dofs/dof_accessor.h>
+#include <deal.II/dofs/dof_tools.h>
+
+#include <deal.II/fe/fe_q.h>
+#include <deal.II/fe/fe_values.h>
+
+#include <deal.II/lac/constraint_matrix.h>
+#include <deal.II/lac/sparse_direct.h>
+
+#include <deal.II/numerics/vector_tools.h>
+#include <deal.II/numerics/data_out.h>
+
+#include <fstream>
+#include <iostream>
+#include <cmath>
+#include <map>
+
+// This is the only include file that is new: It includes all the Runge-Kutta
+// methods.
+#include <deal.II/base/time_stepping.h>
+
+
+// The next step is like in all previous tutorial programs: We put everything
+// into a namespace of its own and then import the deal.II classes and functions
+// into it.
+namespace Step52
+{
+ using namespace dealii;
+
+ // @sect3{Diffusion}
+
+ // Now, here comes the declaration of the main class.
+ class Diffusion
+ {
+ public:
+ Diffusion();
+
+ void run();
+
+ private:
+ // Create the sparsity_pattern and initialize system_matrix.
+ void setup_system();
+
+ // Assemble the part of the matrix of the system that does not depend on
+ // the time.
+ void assemble_system();
+
+ // Compute the intensity of the source at the given point.
+ double get_source(double time,const Point<2> &point) const;
+
+ // Evaluate the diffusion equation \f$M^{-1}(f(t,y))\f$
+ Vector<double> evaluate_diffusion(const double time, const Vector<double> &y) const;
+
+ // Evaluate \f$\left(I-\tau M^{-1} \frac{\partial f(t,y)}{\partial y}\right)^{-1} =
+ // \left(M-\tau \frac{\partial f}{\partial y}\right)^{-1} M \f$
+ Vector<double> id_minus_tau_J_inverse(const double time, const double tau,
+ const Vector<double> &y);
+
+ // Output the results as vtu
+ void output_results(unsigned int time_step,TimeStepping::runge_kutta_method method) const;
+
+ // Driver for the explicit methods
+ void explicit_method(TimeStepping::runge_kutta_method method,
+ const unsigned int n_time_steps,
+ const double initial_time,
+ const double final_time);
+
+ // Driver for the implicit methods
+ void implicit_method(TimeStepping::runge_kutta_method method,
+ const unsigned int n_time_steps,
+ const double initial_time,
+ const double final_time);
+
+ // Driver for the embedded explicit methods. Returns the number of steps
+ // executed.
+ unsigned int embedded_explicit_method(TimeStepping::runge_kutta_method method,
+ const unsigned int n_time_steps,
+ const double initial_time,
+ const double final_time);
+
+
+ unsigned int fe_degree;
+
+ double diffusion_coefficient;
+ double absorption_xs;
+
+ Triangulation<2> triangulation;
+
+ FE_Q<2> fe;
+
+ DoFHandler<2> dof_handler;
+
+ ConstraintMatrix constraint_matrix;
+
+ SparsityPattern sparsity_pattern;
+
+ SparseMatrix<double> system_matrix;
+ SparseMatrix<double> mass_matrix;
+ SparseMatrix<double> mass_minus_tau_Jacobian;
+
+ SparseDirectUMFPACK inverse_mass_matrix;
+
+ Vector<double> solution;
+ };
+
+
+
+ // We choose quadratic finite elements so that there are no spatial error.
+ Diffusion::Diffusion()
+ :
+ fe_degree(2),
+ diffusion_coefficient(1./30.),
+ absorption_xs(1.),
+ fe(fe_degree),
+ dof_handler(triangulation)
+ {}
+
+
+
+ void Diffusion::setup_system()
+ {
+ dof_handler.distribute_dofs(fe);
+
+ // Create the constraint matrix.
+ VectorTools::interpolate_boundary_values(dof_handler,1,ZeroFunction<2>(),constraint_matrix);
+ constraint_matrix.close();
+
+ // Create the sparsity_pattern.
+ CompressedSparsityPattern c_sparsity(dof_handler.n_dofs());
+ DoFTools::make_sparsity_pattern(dof_handler,c_sparsity,constraint_matrix);
+ sparsity_pattern.copy_from(c_sparsity);
+
+ system_matrix.reinit(sparsity_pattern);
+ mass_matrix.reinit(sparsity_pattern);
+ mass_minus_tau_Jacobian.reinit(sparsity_pattern);
+ solution.reinit(dof_handler.n_dofs());
+ }
+
+
+
+ void Diffusion::assemble_system()
+ {
+ system_matrix = 0.;
+ mass_matrix = 0.;
+
+ const QGauss<2> quadrature_formula(fe_degree+1);
+
+ FEValues<2> fe_values(fe, quadrature_formula,
+ update_values | update_gradients | update_JxW_values);
+
+
+ const unsigned int dofs_per_cell = fe.dofs_per_cell;
+ const unsigned int n_q_points = quadrature_formula.size();
+
+ FullMatrix<double> cell_matrix (dofs_per_cell, dofs_per_cell);
+ FullMatrix<double> cell_mass_matrix (dofs_per_cell, dofs_per_cell);
+
+ std::vector<types::global_dof_index> local_dof_indices (dofs_per_cell);
+
+ typename DoFHandler<2>::active_cell_iterator
+ cell = dof_handler.begin_active(),
+ endc = dof_handler.end();
+
+ // Compute \f$-\int D \nabla b \cdot \nabla b - \int \Sigma_a b b\f$ and \f$\int b b\f$
+ for (; cell!=endc; ++cell)
+ {
+ cell_matrix = 0.;
+ cell_mass_matrix = 0.;
+
+ fe_values.reinit (cell);
+
+ for (unsigned int q_point=0; q_point<n_q_points; ++q_point)
+ for (unsigned int i=0; i<dofs_per_cell; ++i)
+ for (unsigned int j=0; j<dofs_per_cell; ++j)
+ {
+ cell_matrix(i,j) += ((-diffusion_coefficient * fe_values.shape_grad(i,q_point) *
+ fe_values.shape_grad(j,q_point) - absorption_xs *
+ fe_values.shape_value(i,q_point) * fe_values.shape_value(j,q_point)) *
+ fe_values.JxW(q_point));
+ cell_mass_matrix(i,j) += fe_values.shape_value(i,q_point) *
+ fe_values.shape_value(j,q_point) *
+ fe_values.JxW(q_point);
+ }
+
+ cell->get_dof_indices(local_dof_indices);
+
+ constraint_matrix.distribute_local_to_global(cell_matrix,local_dof_indices,system_matrix);
+ constraint_matrix.distribute_local_to_global(cell_mass_matrix,local_dof_indices,mass_matrix);
+ }
+
+ // Compute the inverse of the mass matrix.
+ inverse_mass_matrix.initialize(mass_matrix);
+ }
+
+
+
+ double Diffusion::get_source(double time,const Point<2> &point) const
+ {
+ const double pi = 3.14159265358979323846;
+ const double intensity = 10.;
+ const double frequency = pi/10.;
+ const double b = 5.;
+ const double x = point(0);
+ double source = 0.;
+
+ source = intensity*(frequency*std::cos(frequency*time)*(b*x-x*x) + std::sin(frequency*time) *
+ (absorption_xs*(b*x-x*x)+2.*diffusion_coefficient));
+
+ return source;
+ }
+
+
+
+ Vector<double> Diffusion::evaluate_diffusion(const double time, const Vector<double> &y) const
+ {
+ Vector<double> tmp(dof_handler.n_dofs());
+ tmp = 0.;
+ // Compute system_matrix*y
+ system_matrix.vmult(tmp,y);
+
+
+ // Compute the source term
+ const QGauss<2> quadrature_formula(fe_degree+1);
+
+ FEValues<2> fe_values(fe, quadrature_formula,
+ update_values | update_quadrature_points | update_JxW_values);
+
+
+ const unsigned int dofs_per_cell = fe.dofs_per_cell;
+ const unsigned int n_q_points = quadrature_formula.size();
+
+ Vector<double> cell_source(dofs_per_cell);
+
+ std::vector<types::global_dof_index> local_dof_indices (dofs_per_cell);
+
+ typename DoFHandler<2>::active_cell_iterator
+ cell = dof_handler.begin_active(),
+ endc = dof_handler.end();
+
+ for (; cell!=endc; ++cell)
+ {
+ cell_source = 0.;
+
+ fe_values.reinit (cell);
+
+ for (unsigned int q_point=0; q_point<n_q_points; ++q_point)
+ {
+ double source = get_source(time,fe_values.quadrature_point(q_point)) ;
+ for (unsigned int i=0; i<dofs_per_cell; ++i)
+ cell_source(i) += source * fe_values.shape_value(i,q_point) *
+ fe_values.JxW(q_point);
+ }
+
+ cell->get_dof_indices(local_dof_indices);
+
+ // Add the source term to the tmp vector.
+ constraint_matrix.distribute_local_to_global(cell_source,local_dof_indices,tmp);
+ }
+
+
+ Vector<double> value(dof_handler.n_dofs());
+ inverse_mass_matrix.vmult(value,tmp);
+
+ return value;
+ }
+
+
+
+ Vector<double> Diffusion::id_minus_tau_J_inverse(const double time, const double tau,
+ const Vector<double> &y)
+ {
+ Vector<double> tmp(dof_handler.n_dofs());
+ Vector<double> result(y);
+ SparseDirectUMFPACK inverse_mass_minus_tau_Jacobian;
+
+ mass_minus_tau_Jacobian.copy_from(mass_matrix);
+ mass_minus_tau_Jacobian.add(-tau,system_matrix);
+ inverse_mass_minus_tau_Jacobian.initialize(mass_minus_tau_Jacobian);
+ mass_matrix.vmult(tmp,y);
+ inverse_mass_minus_tau_Jacobian.vmult(result,tmp);
+
+ return result;
+ }
+
+
+
+ void Diffusion::output_results(unsigned int time_step,TimeStepping::runge_kutta_method method) const
+ {
+ std::string method_name;
+
+ switch (method)
+ {
+ case TimeStepping::FORWARD_EULER :
+ {
+ method_name = "forward_euler";
+ break;
+ }
+ case TimeStepping::RK_THIRD_ORDER :
+ {
+ method_name = "rk3";
+ break;
+ }
+ case TimeStepping::RK_CLASSIC_FOURTH_ORDER :
+ {
+ method_name = "rk4";
+ break;
+ }
+ case TimeStepping::BACKWARD_EULER :
+ {
+ method_name = "backward_euler";
+ break;
+ }
+ case TimeStepping::IMPLICIT_MIDPOINT :
+ {
+ method_name = "implicit_midpoint";
+ break;
+ }
+ case TimeStepping::SDIRK_TWO_STAGES :
+ {
+ method_name = "sdirk";
+ break;
+ }
+ case TimeStepping::HEUN_EULER :
+ {
+ method_name = "heun_euler";
+ break;
+ }
+ case TimeStepping::BOGACKI_SHAMPINE :
+ {
+ method_name = "bocacki_shampine";
+ break;
+ }
+ case TimeStepping::DOPRI :
+ {
+ method_name = "dopri";
+ break;
+ }
+ case TimeStepping::FEHLBERG :
+ {
+ method_name = "fehlberg";
+ break;
+ }
+ case TimeStepping::CASH_KARP :
+ {
+ method_name = "cash_karp";
+ break;
+ }
+ default :
+ {
+ break;
+ }
+ }
+
+ DataOut<2> data_out;
+
+ data_out.attach_dof_handler(dof_handler);
+ data_out.add_data_vector(solution, "flux");
+
+ data_out.build_patches();
+
+ const std::string filename = "solution-" + method_name + "-" +
+ Utilities::int_to_string (time_step, 3) +
+ ".vtu";
+ std::ofstream output(filename.c_str());
+ data_out.write_vtu(output);
+ }
+
+
+
+ void Diffusion::explicit_method(TimeStepping::runge_kutta_method method,
+ const unsigned int n_time_steps,
+ const double initial_time,
+ const double final_time)
+ {
+ const double time_step = (final_time-initial_time)/static_cast<double> (n_time_steps);
+ double time = initial_time;
+ solution = 0.;
+
+ TimeStepping::ExplicitRungeKutta<Vector<double> > explicit_runge_kutta(method);
+ output_results(0,method);
+ for (unsigned int i=0; i<n_time_steps; ++i)
+ {
+ // Because we use a member function, we need to bind this to the
+ // function.
+ time = explicit_runge_kutta.evolve_one_time_step(
+ std_cxx1x::bind(&Diffusion::evaluate_diffusion,this,std_cxx1x::_1,std_cxx1x::_2),
+ time,time_step,solution);
+
+ // We output the results every 10 time steps.
+ if ((i+1)%10==0)
+ output_results(i+1,method);
+ }
+ }
+
+
+
+ void Diffusion::implicit_method(TimeStepping::runge_kutta_method method,
+ const unsigned int n_time_steps,
+ const double initial_time,
+ const double final_time)
+ {
+ const double time_step = (final_time-initial_time)/static_cast<double> (n_time_steps);
+ double time = initial_time;
+ solution = 0.;
+
+ TimeStepping::ImplicitRungeKutta<Vector<double> > implicit_runge_kutta(method);
+ output_results(0,method);
+ for (unsigned int i=0; i<n_time_steps; ++i)
+ {
+ // Because we use a member function, we need to bind this to the
+ // function.
+ time = implicit_runge_kutta.evolve_one_time_step(
+ std_cxx1x::bind(&Diffusion::evaluate_diffusion,this,std_cxx1x::_1,std_cxx1x::_2),
+ std_cxx1x::bind(&Diffusion::id_minus_tau_J_inverse,this,std_cxx1x::_1,std_cxx1x::_2,
+ std_cxx1x::_3),
+ time,time_step,solution);
+
+ // We output the results every 10 time steps.
+ if ((i+1)%10==0)
+ output_results(i+1,method);
+ }
+ }
+
+
+
+ unsigned int Diffusion::embedded_explicit_method(TimeStepping::runge_kutta_method method,
+ const unsigned int n_time_steps,
+ const double initial_time,
+ const double final_time)
+ {
+ double time_step = (final_time-initial_time)/static_cast<double> (n_time_steps);
+ double time = initial_time;
+ // Factor multiplying the current time step when the error is below the
+ // threshold.
+ const double coarsen_param = 1.2;
+ // Factor multiplying the current time step when the error is above the
+ // threshold.
+ const double refine_param = 0.8;
+ // Smallest time step acceptable.
+ const double min_delta = 1e-8;
+ // Largest time step acceptable.
+ const double max_delta = 10*time_step;
+ // Threshold above which the time step is refined.
+ const double refine_tol = 1e-1;
+ // Threshold below which the time step is coarsen.
+ const double coarsen_tol = 1e-5;
+ solution = 0.;
+
+ TimeStepping::EmbeddedExplicitRungeKutta<Vector<double> > embedded_explicit_runge_kutta(method,
+ coarsen_param,refine_param,min_delta,max_delta,refine_tol,coarsen_tol);
+ output_results(0,method);
+ unsigned int n_steps=0;
+ while (time<final_time)
+ {
+ // Choose the last time step to reach final_time.
+ if (time+time_step>final_time)
+ time_step = final_time-time;
+
+ // Because we use a member function, we need to bind this to the
+ // function.
+ time = embedded_explicit_runge_kutta.evolve_one_time_step(
+ std_cxx1x::bind(&Diffusion::evaluate_diffusion,this,std_cxx1x::_1,std_cxx1x::_2),
+ time,time_step,solution);
+
+ // We output the results every 10 time steps.
+ if ((n_steps+1)%10==0)
+ output_results(n_steps+1,method);
+
+ // Update the time step
+ time_step = embedded_explicit_runge_kutta.get_status().delta_t_guess;
+ ++n_steps;
+ }
+
+ return n_steps;
+ }
+
+
+
+ void Diffusion::run()
+ {
+ // Create the grid (a square [0,5]x[0,5]) and refine the mesh four times.
+ // The final gird has 16 times 16 cells, for a total of 256.
+ GridGenerator::hyper_cube(triangulation, 0., 5.);
+ triangulation.refine_global(4);
+
+ // Set the boundary indicator for x=0 and x=5 to 1
+ typename Triangulation<2>::active_cell_iterator
+ cell = triangulation.begin_active(),
+ endc = triangulation.end();
+
+ for (; cell!=endc; ++cell)
+ for (unsigned int f=0; f<GeometryInfo<2>::faces_per_cell; ++f)
+ if (cell->face(f)->at_boundary())
+ {
+ if ((cell->face(f)->center()[0]==0.) || (cell->face(f)->center()[0]==5.))
+ cell->face(f)->set_boundary_indicator(1);
+ else
+ cell->face(f)->set_boundary_indicator(0);
+ }
+
+ setup_system();
+
+ assemble_system();
+
+ unsigned int n_steps = 0;
+ const unsigned int n_time_steps = 200;
+ const double initial_time = 0.;
+ const double final_time = 10.;
+
+ // Use forward Euler
+ explicit_method(TimeStepping::FORWARD_EULER,n_time_steps,initial_time,final_time);
+ std::cout<<"Forward Euler error: "<<solution.l2_norm()<<std::endl;
+ // Use third order Runge-Kutta
+ explicit_method(TimeStepping::RK_THIRD_ORDER,n_time_steps,initial_time,final_time);
+ std::cout<<"Third order Runge-Kutta error: "<<solution.l2_norm()<<std::endl;
+ // Use fourth order Runge-Kutta
+ explicit_method(TimeStepping::RK_CLASSIC_FOURTH_ORDER,n_time_steps,initial_time,final_time);
+ std::cout<<"Fourth order Runge-Kutta error: "<<solution.l2_norm()<<std::endl;
+
+
+ // Use backward Euler
+ implicit_method(TimeStepping::BACKWARD_EULER,n_time_steps,initial_time,final_time);
+ std::cout<<"Backward Euler error: "<<solution.l2_norm()<<std::endl;
+ // Use implicit midpoint
+ implicit_method(TimeStepping::IMPLICIT_MIDPOINT,n_time_steps,initial_time,final_time);
+ std::cout<<"Implicit Midpoint error: "<<solution.l2_norm()<<std::endl;
+ // Use Crank-NICOLSON
+ implicit_method(TimeStepping::CRANK_NICOLSON,n_time_steps,initial_time,final_time);
+ std::cout<<"Crank-Nicolson error: "<<solution.l2_norm()<<std::endl;
+ // Use two stages SDIRK
+ implicit_method(TimeStepping::SDIRK_TWO_STAGES,n_time_steps,initial_time,final_time);
+ std::cout<<"SDIRK error: "<<solution.l2_norm()<<std::endl;
+
+
+ // Use Heun-Euler
+ n_steps = embedded_explicit_method(TimeStepping::HEUN_EULER,n_time_steps,initial_time,final_time);
+ std::cout<<"Heun-Euler error: "<<solution.l2_norm()<<std::endl;
+ std::cout<<"Number of steps done: "<<n_steps<<std::endl;
+ // Use Bogacki-Shampine
+ n_steps = embedded_explicit_method(TimeStepping::BOGACKI_SHAMPINE,n_time_steps,initial_time,final_time);
+ std::cout<<"Bogacki-Shampine error: "<<solution.l2_norm()<<std::endl;
+ std::cout<<"Number of steps done: "<<n_steps<<std::endl;
+ // Use Dopri
+ n_steps = embedded_explicit_method(TimeStepping::DOPRI,n_time_steps,initial_time,final_time);
+ std::cout<<"Dopri error: "<<solution.l2_norm()<<std::endl;
+ std::cout<<"Number of steps done: "<<n_steps<<std::endl;
+ // Use Fehlberg
+ n_steps = embedded_explicit_method(TimeStepping::FEHLBERG,n_time_steps,initial_time,final_time);
+ std::cout<<"Fehlberg error: "<<solution.l2_norm()<<std::endl;
+ std::cout<<"Number of steps done: "<<n_steps<<std::endl;
+ // Use Cash-Karp
+ n_steps = embedded_explicit_method(TimeStepping::CASH_KARP,n_time_steps,initial_time,final_time);
+ std::cout<<"Cash-Karp error: "<<solution.l2_norm()<<std::endl;
+ std::cout<<"Number of steps done: "<<n_steps<<std::endl;
+ }
+}
+
+
+
+// The following <code>main</code> function is similar to previous examples as
+// well, and need not be commented on.
+int main ()
+{
+ try
+ {
+ Step52::Diffusion diffusion;
+ diffusion.run();
+ }
+ catch (std::exception &exc)
+ {
+ std::cerr << std::endl << std::endl
+ << "----------------------------------------------------"
+ << std::endl;
+ std::cerr << "Exception on processing: " << std::endl
+ << exc.what() << std::endl
+ << "Aborting!" << std::endl
+ << "----------------------------------------------------"
+ << std::endl;
+ return 1;
+ }
+ catch (...)
+ {
+ std::cerr << std::endl << std::endl
+ << "----------------------------------------------------"
+ << std::endl;
+ std::cerr << "Unknown exception!" << std::endl
+ << "Aborting!" << std::endl
+ << "----------------------------------------------------"
+ << std::endl;
+ return 1;
+ };
+
+ return 0;
+}
projects / dealii-svn.git / commitdiff