Reference documentation for deal.II version GIT 3d55da8fe8 2023-02-08 23:55:02+00:00
\(\newcommand{\dealvcentcolon}{\mathrel{\mathop{:}}}\) \(\newcommand{\dealcoloneq}{\dealvcentcolon\mathrel{\mkern-1.2mu}=}\) \(\newcommand{\jump}[1]{\left[\!\left[ #1 \right]\!\right]}\) \(\newcommand{\average}[1]{\left\{\!\left\{ #1 \right\}\!\right\}}\)
The 'Elastoplastic Torsion' code gallery program

This program was contributed by Salvador Flores <sflores@dim.uchile.cl>.
It comes without any warranty or support by its authors or the authors of deal.II.

This program is part of the deal.II code gallery and consists of the following files (click to inspect):

Annotated version of ElastoplasticTorsion.cc

/* ---------------------------------------------------------------------
*
* Copyright (C) 2010 - 2015 by the deal.II authors
* and Salvador Flores.
*
*
*
* This 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.
*
* ---------------------------------------------------------------------
*
* Author: Salvador Flores,
* Center for Mathematical Modelling,
* Universidad de Chile, 2015.
*/
/*
* This piece of software solves the elliptic p-laplacian
* boundary-value problems:
*
* Min {∫ 1/2 W(|Du|²)+ 1/p |Du|^p -fu : u=g on ∂S } (1)
* u
*
* for large values of p, which approximates (see Alvarez & Flores 2015)
*
* Min {∫ 1/2 W(|Du|²) -fu : |Du|<1 a.s. on S, u=g on ∂S }
* u
*
* By default W(t)=t and S=unit disk.
*
* Large portions of this code are borrowed from the deal.ii tutorials
*
* @ref step_15 "step-15" @ref step_29 "step-29".
*
* For further details see the technical report
* "Solving variational problems with uniform gradient bounds by p-Laplacian
* approximation: Elastoplastic torsion implementation using the deal.II
* library"
* available at the documentation and at http://www.dim.uchile.cl/~sflores.
*
*/

Include files

#include <typeinfo>
#include <fstream>
#include <iostream>

Open a namespace for this program and import everything from the dealii namespace into it.

namespace nsp
{
using namespace dealii;

class ParameterReader : public Subscriptor
{
public:
ParameterReader(ParameterHandler &);
void read_parameters(const std::string);
private:
void declare_parameters();
};

Constructor

ParameterReader::ParameterReader(ParameterHandler &paramhandler):
prm(paramhandler)
{}
void ParameterReader::declare_parameters()
{
prm.enter_subsection ("Global Parameters");
{
prm.declare_entry("p", "100",Patterns::Double(2.1),
"Penalization parameter");
prm.declare_entry("known_solution", "true",Patterns::Bool(),
"Whether the exact solution is known");
}
prm.leave_subsection ();
prm.enter_subsection ("Mesh & Refinement Parameters");
{
prm.declare_entry("Code for the domain", "0",Patterns::Integer(0,2),
"Number identifying the domain in which we solve the problem");
prm.declare_entry("No of initial refinements", "4",Patterns::Integer(0),
"Number of global mesh refinement steps applied to initial coarse grid");
prm.declare_entry("No of adaptive refinements", "8",Patterns::Integer(0),
"Number of global adaptive mesh refinements");
prm.declare_entry("top_fraction_of_cells", "0.25",Patterns::Double(0),
"refinement threshold");
prm.declare_entry("bottom_fraction_of_cells", "0.05",Patterns::Double(0),
"coarsening threshold");
}
prm.leave_subsection ();
prm.enter_subsection ("Algorithm Parameters");
{
prm.declare_entry("Descent_direction", "0",Patterns::Integer(0,1),
"0: Preconditioned descent, 1: Newton Method");
prm.declare_entry("init_p", "10",Patterns::Double(2),
"Initial p");
prm.declare_entry("delta_p", "50",Patterns::Double(0),
"increase of p");
prm.declare_entry("Max_CG_it", "1500",Patterns::Integer(1),
"Maximum Number of CG iterations");
prm.declare_entry("CG_tol", "1e-10",Patterns::Double(0),
"Tolerance for CG iterations");
prm.declare_entry("max_LS_it", "45",Patterns::Integer(1),
"Maximum Number of LS iterations");
prm.declare_entry("line_search_tolerence", "1e-6",Patterns::Double(0),
"line search tolerance constant (c1 in Nocedal-Wright)");
prm.declare_entry("init_step_length", "1e-2",Patterns::Double(0),
"initial step length in line-search");
prm.declare_entry("Max_inner", "800",Patterns::Integer(1),
"Maximum Number of inner iterations");
prm.declare_entry("eps", "1.0e-8",Patterns::Double(0),
"Threshold on norm of the derivative to declare optimality achieved");
prm.declare_entry("hi_eps", "1.0e-9",Patterns::Double(0),
"Threshold on norm of the derivative to declare optimality achieved in highly refined mesh");
prm.declare_entry("hi_th", "8",Patterns::Integer(0),
"Number of adaptive refinement before change convergence threshold");
}
prm.leave_subsection ();
}
void ParameterReader::read_parameters (const std::string parameter_file)
{
declare_parameters();
prm.parse_input (parameter_file);
}

The solution of the elastoplastic torsion problem on the unit disk with rhs=4.

template <int dim>
class Solution : public Function<dim>
{
public:
Solution () : Function<dim>() {}
virtual double value (const Point<dim> &pto, const unsigned int component = 0) const;
virtual Tensor<1,dim> gradient (const Point<dim> &pto, const unsigned int component = 0) const;
};
template <int dim>
double Solution<dim>::value (const Point<dim> &pto,const unsigned int) const
{
double r=sqrt(pto.square());
if (r<0.5)
return -1.0*std::pow(r,2.0)+0.75;
else
return 1.0-r;
}
template <int dim>
Tensor<1,dim> Solution<dim>::gradient (const Point<dim> &pto,const unsigned int) const
{
double r=sqrt(pto.square());
if (r<0.5)
return -2.0*pto;
else
return -1.0*pto/r;
}
virtual Tensor< 1, dim, RangeNumberType > gradient(const Point< dim > &p, const unsigned int component=0) const
virtual RangeNumberType value(const Point< dim > &p, const unsigned int component=0) const
Definition: point.h:111
numbers::NumberTraits< Number >::real_type square() const
VectorizedArray< Number, width > sqrt(const ::VectorizedArray< Number, width > &x)
::VectorizedArray< Number, width > pow(const ::VectorizedArray< Number, width > &, const Number p)

/* Compute the Lagrange multiplier (as a derived quantity) */
template <int dim>
class ComputeMultiplier : public DataPostprocessor<dim>
{
private:
double p;
public:
ComputeMultiplier (double pe);
virtual
void compute_derived_quantities_scalar (
const std::vector< double > &,
const std::vector< Tensor< 1, dim > > &,
const std::vector< Tensor< 2, dim > > &,
const std::vector< Point< dim > > &,
const std::vector< Point< dim > > &,
std::vector< Vector< double > > &
) const;
virtual std::vector<std::string> get_names () const;
virtual
std::vector<DataComponentInterpretation::DataComponentInterpretation>
};
template <int dim>
ComputeMultiplier<dim>::ComputeMultiplier (double pe): p(pe)
{}
template <int dim>
void ComputeMultiplier<dim>::compute_derived_quantities_scalar(
const std::vector< double > & /*uh*/,
const std::vector< Tensor< 1, dim > > &duh,
const std::vector< Tensor< 2, dim > > & /*dduh*/,
const std::vector< Point< dim > > & /* normals*/,
const std::vector< Point< dim > > & /*evaluation_points*/,
std::vector< Vector< double > > &computed_quantities ) const
{
const unsigned int n_quadrature_points = duh.size();
for (unsigned int q=0; q<n_quadrature_points; ++q)
{
long double sqrGrad=duh[q]* duh[q]; //squared norm of the gradient
long double exponent=(p-2.0)/2*std::log(sqrGrad);
computed_quantities[q](0) = std::sqrt(sqrGrad); // norm of the gradient
computed_quantities[q](1)= std::exp(exponent); // multiplier
}
}
template <int dim>
std::vector<std::string>
ComputeMultiplier<dim>::get_names() const
{
std::vector<std::string> solution_names;
solution_names.push_back ("Gradient norm");
solution_names.push_back ("Lagrange multiplier");
return solution_names;
}
template <int dim>
ComputeMultiplier<dim>::get_needed_update_flags () const
{
}
template <int dim>
std::vector<DataComponentInterpretation::DataComponentInterpretation>
ComputeMultiplier<dim>:: get_data_component_interpretation () const
{
std::vector<DataComponentInterpretation::DataComponentInterpretation>
interpretation;
virtual std::vector< std::string > get_names() const =0
virtual UpdateFlags get_needed_update_flags() const =0
virtual std::vector< DataComponentInterpretation::DataComponentInterpretation > get_data_component_interpretation() const
UpdateFlags
@ update_gradients
Shape function gradients.

norm of the gradient

Lagrange multiplier

return interpretation;
}

template <int dim>
class ElastoplasticTorsion
{
public:
ElastoplasticTorsion (ParameterHandler &);
~ElastoplasticTorsion ();
void run ();
private:
void setup_system (const bool initial_step);
void assemble_system ();
bool solve (const int inner_it);
void init_mesh ();
void refine_mesh ();
void set_boundary_values ();
double phi (const double alpha) const;
bool checkWolfe(double &alpha, double &phi_alpha) const;
bool determine_step_length (const int inner_it);
void print_it_message (const int counter, bool ks);
void output_results (unsigned int refinement) const;
void format_convergence_tables();
void process_solution (const unsigned int cycle);
void process_multiplier (const unsigned int cycle,const int iter,double time);
double dual_error () const;
double dual_infty_error () const;
double W (double Du2) const;
double Wp (double Du2) const;
double G (double Du2) const;
DoFHandler<dim> dof_handler;
AffineConstraints<double> hanging_node_constraints;
SparsityPattern sparsity_pattern;
SparseMatrix<double> system_matrix;
ConvergenceTable convergence_table;
ConvergenceTable dual_convergence_table;
Vector<double> present_solution;
Vector<double> newton_update;
Vector<double> system_rhs;
Vector<double> grad_norm;
double step_length,phi_zero,phi_alpha,phip,phip_zero;
double old_step,old_phi_zero,old_phip;
double L2_error;
double H1_error;
double Linfty_error;
double dual_L1_error;
double dual_L_infty_error;
double p;
double line_search_tolerence; // c_1 in Nocedal & Wright
unsigned int dir_id;
std::string elements;
std::string Method;
};
/*******************************************************************************************/
Definition: fe_q.h:551
void run(const Iterator &begin, const typename identity< Iterator >::type &end, Worker worker, Copier copier, const ScratchData &sample_scratch_data, const CopyData &sample_copy_data, const unsigned int queue_length, const unsigned int chunk_size)
Definition: work_stream.h:474
const ::parallel::distributed::Triangulation< dim, spacedim > * triangulation

Boundary condition

template <int dim>
class BoundaryValues : public Function<dim>
{
public:
BoundaryValues () : Function<dim>() {}
virtual double value (const Point<dim> &p,
const unsigned int component = 0) const;
};
template <int dim>
double BoundaryValues<dim>::value (const Point<dim> &/*pto*/,
const unsigned int /*component*/) const
{

could be anything else (theory works provided |Dg|_infty < 1/2)

return 0.0;
/* A challenging BC leading to overdetermined problems
* it is regulated by the parameter 0<eta<1.
* eta closer to 1 leads to more difficult problems.
*
* double pii=numbers::PI;
* double theta=std::atan2(p[1],p[0])+pii;
* double eta=0.9;
*
* if (theta <= 0.5)
* return eta*(theta*theta);
* else if ((theta >0.5) & (theta<= pii-0.5))
* return eta*(theta-0.25);
* else if ((theta>pii-0.5)&(theta<= pii+0.5))
* return eta*(pii-0.75-(theta-(pii-0.5))*(theta-(pii+0.5)));
* else if ((theta>pii+0.5)&(theta<= 2*pii-0.5))
* return eta*((2*pii-theta)-0.25);
* else
* return eta*((theta-2*pii)*(theta-2*pii) );*/
}
/******************************************************************************/

Right-Hand Side

template <int dim>
class RightHandSide : public Function<dim>
{
public:
RightHandSide () : Function<dim>() {}
virtual double value (const Point<dim> &p,
const unsigned int component = 0) const;
};
template <int dim>
double RightHandSide<dim>::value (const Point<dim> &/*p*/,
const unsigned int /*component*/) const
{

set to constant = 4, for which explicit solution to compare exists could be anything

double return_value = 4.0;
return return_value;
}
/*******************************************************************/

The ElastoplasticTorsion class implementation

Constructor of the class

template <int dim>
ElastoplasticTorsion<dim>::ElastoplasticTorsion (ParameterHandler &param):
prm(param),
dof_handler (triangulation),
L2_error(1.0),
H1_error(1.0),
Linfty_error(1.0),
dual_L1_error(1.0),
dual_L_infty_error(1.0),
fe(2)
{
prm.enter_subsection ("Global Parameters");
p=prm.get_double("p");
prm.leave_subsection ();
prm.enter_subsection ("Algorithm Parameters");
line_search_tolerence=prm.get_double("line_search_tolerence");
dir_id=prm.get_integer("Descent_direction");
prm.leave_subsection ();
if (fe.degree==1)
elements="P1";
else elements="P2";
if (dir_id==0)
Method="Precond";
else
Method="Newton";
}
template <int dim>
ElastoplasticTorsion<dim>::~ElastoplasticTorsion ()
{
dof_handler.clear ();
}
/*****************************************************************************************/

print iteration message

template <int dim>
void ElastoplasticTorsion<dim>::print_it_message (const int counter, bool ks)
{
if (ks)
{
process_solution (counter);
std::cout << "iteration="<< counter+1 << " J(u_h)= "<< phi_zero << ", H1 error: "
<< H1_error <<", W0-1,infty error: "<< Linfty_error<< " J'(u_h)(w)= "<< phip
<< ", |J'(u_h)|= "<< system_rhs.l2_norm()<<std::endl;
}
else
{
std::cout << "iteration= " << counter+1 << " J(u_h)= "
<< phi_alpha << " J'(u_h)= "<< phip<<std::endl;
}
}
/*****************************************************************************************/

Convergence Tables

/*************************************************************/

formating

template <int dim>
void ElastoplasticTorsion<dim>::format_convergence_tables()
{
convergence_table.set_precision("L2", 3);
convergence_table.set_precision("H1", 3);
convergence_table.set_precision("Linfty", 3);
convergence_table.set_precision("function value", 3);
convergence_table.set_precision("derivative", 3);
dual_convergence_table.set_precision("dual_L1", 3);
dual_convergence_table.set_precision("dual_Linfty", 3);
dual_convergence_table.set_precision("L2", 3);
dual_convergence_table.set_precision("H1", 3);
dual_convergence_table.set_precision("Linfty", 3);
convergence_table.set_scientific("L2", true);
convergence_table.set_scientific("H1", true);
convergence_table.set_scientific("Linfty", true);
convergence_table.set_scientific("function value", true);
convergence_table.set_scientific("derivative", true);
dual_convergence_table.set_scientific("dual_L1", true);
dual_convergence_table.set_scientific("dual_Linfty", true);
dual_convergence_table.set_scientific("L2", true);
dual_convergence_table.set_scientific("H1", true);
dual_convergence_table.set_scientific("Linfty", true);
}
/****************************************/

fill-in entry for the solution

template <int dim>
void ElastoplasticTorsion<dim>::process_solution (const unsigned int it)
{
Vector<float> difference_per_cell (triangulation.n_active_cells());

compute L2 error (save to difference_per_cell)

VectorTools::integrate_difference (dof_handler,present_solution,
Solution<dim>(),difference_per_cell,QGauss<dim>(3),VectorTools::L2_norm);
L2_error = difference_per_cell.l2_norm();
void integrate_difference(const Mapping< dim, spacedim > &mapping, const DoFHandler< dim, spacedim > &dof, const InVector &fe_function, const Function< spacedim, typename InVector::value_type > &exact_solution, OutVector &difference, const Quadrature< dim > &q, const NormType &norm, const Function< spacedim, double > *weight=nullptr, const double exponent=2.)

compute H1 error (save to difference_per_cell)

VectorTools::integrate_difference (dof_handler,present_solution,Solution<dim>(),
difference_per_cell,QGauss<dim>(3),VectorTools::H1_seminorm);
H1_error = difference_per_cell.l2_norm();

compute W1infty error (save to difference_per_cell)

const QTrapezoid<1> q_trapez;
const QIterated<dim> q_iterated (q_trapez, 5);
VectorTools::integrate_difference (dof_handler,present_solution,Solution<dim>(),
difference_per_cell,q_iterated,VectorTools::W1infty_seminorm);
Linfty_error = difference_per_cell.linfty_norm();
convergence_table.add_value("cycle", it);
convergence_table.add_value("p", p);
convergence_table.add_value("L2", L2_error);
convergence_table.add_value("H1", H1_error);
convergence_table.add_value("Linfty", Linfty_error);
convergence_table.add_value("function value", phi_alpha);
convergence_table.add_value("derivative", phip);
}
/***************************************/

fill-in entry for the multiplier

template <int dim>
void ElastoplasticTorsion<dim>::process_multiplier (const unsigned int cycle, const int iter,double time)
{
const unsigned int n_active_cells=triangulation.n_active_cells();
const unsigned int n_dofs=dof_handler.n_dofs();
dual_L1_error=dual_error();
dual_L_infty_error=dual_infty_error();
dual_convergence_table.add_value("cycle", cycle);
dual_convergence_table.add_value("p", p);
dual_convergence_table.add_value("iteration_number", iter);
dual_convergence_table.add_value("cpu_time", time);
dual_convergence_table.add_value("cells", n_active_cells);
dual_convergence_table.add_value("dofs", n_dofs);
dual_convergence_table.add_value("L2", L2_error);
dual_convergence_table.add_value("H1", H1_error);
dual_convergence_table.add_value("Linfty", Linfty_error);
dual_convergence_table.add_value("dual_L1", dual_L1_error);
dual_convergence_table.add_value("dual_Linfty", dual_L_infty_error);
}
/****************************************************************************************/
unsigned int n_active_cells(const internal::TriangulationImplementation::NumberCache< 1 > &c)
Definition: tria.cc:13763

ElastoplasticTorsion::setup_system unchanged from step-15

template <int dim>
void ElastoplasticTorsion<dim>::setup_system (const bool initial_step)
{
if (initial_step)
{
dof_handler.distribute_dofs (fe);
present_solution.reinit (dof_handler.n_dofs());
grad_norm.reinit (dof_handler.n_dofs());
lambda.reinit (dof_handler.n_dofs());
hanging_node_constraints.clear ();
hanging_node_constraints);
hanging_node_constraints.close ();
}
void make_hanging_node_constraints(const DoFHandler< dim, spacedim > &dof_handler, AffineConstraints< number > &constraints)

The remaining parts of the function

newton_update.reinit (dof_handler.n_dofs());
system_rhs.reinit (dof_handler.n_dofs());
DynamicSparsityPattern c_sparsity(dof_handler.n_dofs());
DoFTools::make_sparsity_pattern (dof_handler, c_sparsity);
hanging_node_constraints.condense (c_sparsity);
sparsity_pattern.copy_from(c_sparsity);
system_matrix.reinit (sparsity_pattern);
}
/***************************************************************************************/
/* the coeffcients W, W' and G defining the problem.
*
* Min_u \int W(|Du|^2) dx
*
* They must be consistent as G(s)=W'(s)+2s W''(s) for any s>0.
* recall that they receive the SQUARED gradient. */
template <int dim>
double ElastoplasticTorsion<dim>::W (double Du2) const
{
return Du2;
}
template <int dim>
double ElastoplasticTorsion<dim>::Wp (double /*Du2*/) const
{
return 1.0;
}
template <int dim>
double ElastoplasticTorsion<dim>::G (double /*Du2*/) const
{
return 1.0;
}
/***************************************************************************************/
template <int dim>
void ElastoplasticTorsion<dim>::assemble_system ()
{
const QGauss<dim> quadrature_formula(3);
const RightHandSide<dim> right_hand_side;
system_matrix = 0;
system_rhs = 0;
FEValues<dim> fe_values (fe, quadrature_formula,
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);
Vector<double> cell_rhs (dofs_per_cell);
std::vector<Tensor<1, dim> > old_solution_gradients(n_q_points);
std::vector<types::global_dof_index> local_dof_indices (dofs_per_cell);
cell = dof_handler.begin_active(),
endc = dof_handler.end();
for (; cell!=endc; ++cell)
{
cell_rhs = 0;
fe_values.reinit (cell);
fe_values.get_function_gradients(present_solution,
old_solution_gradients);
for (unsigned int q_point = 0; q_point < n_q_points; ++q_point)
{
long double coeff=0.0;
long double a=old_solution_gradients[q_point] * old_solution_gradients[q_point];
long double exponent=(p-2.0)/2*std::log(a);
coeff= std::exp( exponent);
for (unsigned int i=0; i<dofs_per_cell; ++i)
{
for (unsigned int j=0; j<dofs_per_cell; ++j)
{
if (dir_id==1)
{
cell_matrix(i, j) += fe_values.shape_grad(i, q_point) * fe_values.shape_grad(j, q_point)
* (G(a)+(p-1.0)*coeff) * fe_values.JxW(q_point);
}
else
{
cell_matrix(i, j) += fe_values.shape_grad(i, q_point) * fe_values.shape_grad(j, q_point)
* (Wp(a)+coeff)
* fe_values.JxW(q_point);
}
}
cell_rhs(i) -= ( fe_values.shape_grad(i, q_point)
* old_solution_gradients[q_point]
* (Wp(a)+coeff)
-right_hand_side.value(fe_values.quadrature_point(q_point))
*fe_values.shape_value(i, q_point)
)
* fe_values.JxW(q_point);
}
}
cell->get_dof_indices (local_dof_indices);
for (unsigned int i=0; i<dofs_per_cell; ++i)
{
for (unsigned int j=0; j<dofs_per_cell; ++j)
system_matrix.add (local_dof_indices[i],
local_dof_indices[j],
cell_matrix(i,j));
system_rhs(local_dof_indices[i]) += cell_rhs(i);
}
}
hanging_node_constraints.condense (system_matrix);
hanging_node_constraints.condense (system_rhs);
std::map<types::global_dof_index,double> boundary_values;
0,
boundary_values);
system_matrix,
newton_update,
system_rhs);
}
/********************************** Refine Mesh ****************************************/
typename ActiveSelector::active_cell_iterator active_cell_iterator
Definition: dof_handler.h:437
void make_sparsity_pattern(const DoFHandler< dim, spacedim > &dof_handler, SparsityPatternBase &sparsity_pattern, const AffineConstraints< number > &constraints=AffineConstraints< number >(), const bool keep_constrained_dofs=true, const types::subdomain_id subdomain_id=numbers::invalid_subdomain_id)
@ update_values
Shape function values.
@ update_JxW_values
Transformed quadrature weights.
@ update_quadrature_points
Transformed quadrature points.
void cell_matrix(FullMatrix< double > &M, const FEValuesBase< dim > &fe, const FEValuesBase< dim > &fetest, const ArrayView< const std::vector< double >> &velocity, const double factor=1.)
Definition: advection.h:75
void apply_boundary_values(const std::map< types::global_dof_index, number > &boundary_values, SparseMatrix< number > &matrix, Vector< number > &solution, Vector< number > &right_hand_side, const bool eliminate_columns=true)
Definition: matrix_tools.cc:76
void interpolate_boundary_values(const Mapping< dim, spacedim > &mapping, const DoFHandler< dim, spacedim > &dof, const std::map< types::boundary_id, const Function< spacedim, number > * > &function_map, std::map< types::global_dof_index, number > &boundary_values, const ComponentMask &component_mask=ComponentMask())
::VectorizedArray< Number, width > exp(const ::VectorizedArray< Number, width > &)

unchanged from step-15

template <int dim>
void ElastoplasticTorsion<dim>::refine_mesh ()
{
using FunctionMap = std::map<types::boundary_id, const Function<dim> *>;
Vector<float> estimated_error_per_cell (triangulation.n_active_cells());
FunctionMap(),
present_solution,
estimated_error_per_cell);
prm.enter_subsection ("Mesh & Refinement Parameters");
const double top_fraction=prm.get_double("top_fraction_of_cells");
const double bottom_fraction=prm.get_double("bottom_fraction_of_cells");
prm.leave_subsection ();
estimated_error_per_cell,
top_fraction, bottom_fraction);
triangulation.prepare_coarsening_and_refinement ();
SolutionTransfer<dim> solution_transfer(dof_handler);
solution_transfer.prepare_for_coarsening_and_refinement(present_solution);
triangulation.execute_coarsening_and_refinement();
dof_handler.distribute_dofs(fe);
Vector<double> tmp(dof_handler.n_dofs());
solution_transfer.interpolate(present_solution, tmp);
present_solution = tmp;
set_boundary_values ();
hanging_node_constraints.clear();
hanging_node_constraints);
hanging_node_constraints.close();
hanging_node_constraints.distribute (present_solution);
setup_system (false);
}
/*******************************************************************************************/
static void estimate(const Mapping< dim, spacedim > &mapping, const DoFHandler< dim, spacedim > &dof, const Quadrature< dim - 1 > &quadrature, const std::map< types::boundary_id, const Function< spacedim, typename InputVector::value_type > * > &neumann_bc, const InputVector &solution, Vector< float > &error, const ComponentMask &component_mask=ComponentMask(), const Function< spacedim > *coefficients=nullptr, const unsigned int n_threads=numbers::invalid_unsigned_int, const types::subdomain_id subdomain_id=numbers::invalid_subdomain_id, const types::material_id material_id=numbers::invalid_material_id, const Strategy strategy=cell_diameter_over_24)
void refine_and_coarsen_fixed_number(Triangulation< dim, spacedim > &triangulation, const Vector< Number > &criteria, const double top_fraction_of_cells, const double bottom_fraction_of_cells, const unsigned int max_n_cells=std::numeric_limits< unsigned int >::max())

Dump the norm of the gradient and the lagrange multiplier in vtu format for visualization

template <int dim>
void ElastoplasticTorsion<dim>::output_results (unsigned int counter) const
{

multiplier object contains both |Du| and lambda.

ComputeMultiplier<dim> multiplier(p);
DataOut<dim> data_out;
data_out.attach_dof_handler (dof_handler);
data_out.add_data_vector (present_solution, "solution");
data_out.add_data_vector (present_solution, multiplier);
data_out.build_patches ();
std::ostringstream p_str;
p_str << p<<"-cycle-"<<counter;
std::string str = p_str.str();
const std::string filename = "solution-" + str+".vtu";
std::ofstream output (filename.c_str());
data_out.write_vtu (output);
}
/********************************************************************************************/
void write_vtu(std::ostream &out) const
void attach_dof_handler(const DoFHandler< dim, spacedim > &)
void add_data_vector(const VectorType &data, const std::vector< std::string > &names, const DataVectorType type=type_automatic, const std::vector< DataComponentInterpretation::DataComponentInterpretation > &data_component_interpretation={})
virtual void build_patches(const unsigned int n_subdivisions=0)
Definition: data_out.cc:1063

unchanged from step-15

template <int dim>
void ElastoplasticTorsion<dim>::set_boundary_values ()
{
std::map<types::global_dof_index, double> boundary_values;
0,
BoundaryValues<dim>(),
boundary_values);
for (std::map<types::global_dof_index, double>::const_iterator
bp = boundary_values.begin();
bp != boundary_values.end(); ++bp)
present_solution(bp->first) = bp->second;
}
/****************************************************************************************/

COMPUTE \(\phi(\alpha)=J_p(u_h+\alpha w)\)

template <int dim>
double ElastoplasticTorsion<dim>::phi (const double alpha) const
{
double obj = 0.0;
const RightHandSide<dim> right_hand_side;
Vector<double> evaluation_point (dof_handler.n_dofs());
evaluation_point = present_solution; // copy of u_h
evaluation_point.add (alpha, newton_update); // u_{n+1}=u_n+alpha w_n
const QGauss<dim> quadrature_formula(3);
FEValues<dim> fe_values (fe, quadrature_formula,
const unsigned int dofs_per_cell = fe.dofs_per_cell;
const unsigned int n_q_points = quadrature_formula.size();
Vector<double> cell_residual (dofs_per_cell);
std::vector<Tensor<1, dim> > gradients(n_q_points);
std::vector<double> values(n_q_points);
std::vector<types::global_dof_index> local_dof_indices (dofs_per_cell);
cell = dof_handler.begin_active(),
endc = dof_handler.end();
for (; cell!=endc; ++cell)
{
fe_values.reinit (cell);
fe_values.get_function_gradients (evaluation_point, gradients);
fe_values.get_function_values (evaluation_point, values);
for (unsigned int q_point=0; q_point<n_q_points; ++q_point)
{
double Du2=gradients[q_point] * gradients[q_point]; // Du2=|Du|^2
double penalty;
if (Du2<1.0e-10)
penalty=0.0;
else
penalty=std::pow(Du2,p/2.0); // penalty=|Du|^p
active_cell_iterator begin_active(const unsigned int level=0) const
void cell_residual(Vector< double > &result, const FEValuesBase< dim > &fe, const std::vector< Tensor< 1, dim >> &input, const ArrayView< const std::vector< double >> &velocity, double factor=1.)
Definition: advection.h:131

obj+= 1/2 W(|Du|^2)+1/p |Du|^p -fu (see (1))

obj+=(
(0.5*W(Du2)+penalty/p)- right_hand_side.value(fe_values.quadrature_point(q_point))*values[q_point]
) * fe_values.JxW(q_point);
}
}
return obj;
}
/***************************************************************************************************/

Compute L^1 error norm of Lagrange Multiplier with respect to exact solution (cf. Alvarez & Flores, 2015)

template <int dim>
double ElastoplasticTorsion<dim>::dual_error () const
{
double obj = 0.0;
const QGauss<dim> quadrature_formula(3);
FEValues<dim> fe_values (fe, quadrature_formula,
const unsigned int dofs_per_cell = fe.dofs_per_cell;
const unsigned int n_q_points = quadrature_formula.size();
Vector<double> cell_residual (dofs_per_cell);
std::vector<Tensor<1, dim> > gradients(n_q_points);
std::vector<types::global_dof_index> local_dof_indices (dofs_per_cell);
cell = dof_handler.begin_active(),
endc = dof_handler.end();
for (; cell!=endc; ++cell)
{
fe_values.reinit (cell);
fe_values.get_function_gradients (present_solution, gradients);
for (unsigned int q_point=0; q_point<n_q_points; ++q_point)
{
double coeff=gradients[q_point] * gradients[q_point] ;
if (coeff<1.0e-15)
coeff=0.0;
else
coeff=std::pow(coeff,(p-2.0)/2.0); // |Du_p|^(p-2)
double r=std::sqrt(fe_values.quadrature_point(q_point).square());
double exact=0;
if (r>0.5)
exact= 2*r-1;
obj+=( std::abs(coeff-exact) ) * fe_values.JxW(q_point);
}
}
return obj;
}
/*******************************************************************************************/
::VectorizedArray< Number, width > abs(const ::VectorizedArray< Number, width > &)
::VectorizedArray< Number, width > sqrt(const ::VectorizedArray< Number, width > &)

Compute L^infinity error norm of Lagrange Multiplier with respect to exact solution (cf. Alvarez & Flores, 2015)

template <int dim>
double ElastoplasticTorsion<dim>::dual_infty_error () const
{
double obj = 0.0;
const QTrapezoid<1> q_trapez;
const QIterated<dim> quadrature_formula (q_trapez, 10);
FEValues<dim> fe_values (fe, quadrature_formula,
const unsigned int dofs_per_cell = fe.dofs_per_cell;
const unsigned int n_q_points = quadrature_formula.size();
Vector<double> cell_residual (dofs_per_cell);
std::vector<Tensor<1, dim> > gradients(n_q_points);
std::vector<types::global_dof_index> local_dof_indices (dofs_per_cell);
cell = dof_handler.begin_active(),
endc = dof_handler.end();
for (; cell!=endc; ++cell)
{
fe_values.reinit (cell);
fe_values.get_function_gradients (present_solution, gradients);
for (unsigned int q_point=0; q_point<n_q_points; ++q_point)
{
long double sqdGrad=gradients[q_point] * gradients[q_point] ;
double r=std::sqrt(fe_values.quadrature_point(q_point).square());
double exact=0;
if (r>0.5)
exact= 2*r-1.0;

compute |Du|^(p-2) as exp(p-2/2*log(Du^2))

long double exponent=(p-2.0)/2*std::log(sqdGrad);
long double coeff=std::exp(exponent);
if (std::abs(coeff-exact)>obj )
obj=std::abs(coeff-exact);
}
}
return obj;
}
/*****************************************************************************************/

check whether putative step-length satisfies sufficient decrease conditions

template <int dim>
bool ElastoplasticTorsion<dim>::checkWolfe(double &alpha, double &phi_alpha) const
{
if (phi_alpha< phi_zero+line_search_tolerence*phip*alpha )
return true;
else
return false;
}
/*****************************************************************************************/

Find a step-length satisfying sufficient decrease condition by line-search uses quadratic interpolation

template <int dim>
bool ElastoplasticTorsion<dim>::determine_step_length(const int inner_it)
{
unsigned int it=0;
bool done;
double alpha,nalpha;
prm.enter_subsection ("Algorithm Parameters");
const unsigned int max_LS_it=prm.get_integer("max_LS_it");
double init_SL=prm.get_double("init_step_length");
prm.leave_subsection ();
if (inner_it==0)
alpha=init_SL;
else
{
alpha=std::min(1.45*old_step*old_phip/phip,1.0);
}
phi_alpha=phi(alpha);
std::cerr << "Step length=" << alpha << ", Value= " << phi_alpha;

check if step-size satisfies sufficient decrease condition

done=checkWolfe(alpha,phi_alpha);
if (done)
std::cerr << " accepted" << std::endl;
else
std::cerr << " rejected" ;
while ((!done) & (it<max_LS_it))
{

new try obtained by quadratic interpolation

nalpha=-(phip*alpha*alpha)/(2*(phi_alpha-phi_zero-phip*alpha));
if (nalpha<1e-3*alpha || std::abs(nalpha-alpha)/alpha<1e-8)
nalpha=alpha/2;
else if ( phi_alpha-phi_zero>1e3*std::abs(phi_zero) )
nalpha=alpha/10;
alpha=nalpha;
phi_alpha=phi(alpha);
done=checkWolfe(alpha,phi_alpha);
if (done)
std::cerr << ", finished with steplength= "<< alpha<< ", fcn value= "<< phi_alpha<<std::endl;
it=it+1;
}
if (!done)
{
std::cerr << ", max. no. of iterations reached wiht steplength= "<< alpha
<< ", fcn value= "<< phi_alpha<<std::endl;
return false;
}
else
{
step_length=alpha;
return true;
}
}
/**************************************************************************************************/
SymmetricTensor< 2, dim, Number > e(const Tensor< 2, dim, Number > &F)

ElastoplasticTorsion::init_mesh()

template <int dim>
void ElastoplasticTorsion<dim>::init_mesh ()
{

get parameters

prm.enter_subsection ("Mesh & Refinement Parameters");
const int domain_id=prm.get_integer("Code for the domain");
const int init_ref=prm.get_integer("No of initial refinements");
prm.leave_subsection ();
if (domain_id==0)
{

For the unit disk around the origin

static const SphericalManifold<dim> boundary;
triangulation.set_manifold (0, boundary);
}
else if (domain_id==1)
{
void hyper_ball(Triangulation< dim > &tria, const Point< dim > &center=Point< dim >(), const double radius=1., const bool attach_spherical_manifold_on_boundary_cells=false)

For the unit square

}
else if (domain_id==2)
{
/* For Glowinski's domain
* ___ ___ __ 1
* | |__| | __ .8
* | |
* | |
* |__________| __ 0
*
* | | | |
* 0 .4 .6 1
*
*/
GridGenerator::hyper_rectangle(tria1, Point<2>(0.0,0.0), Point<2>(0.4,0.8));
GridGenerator::hyper_rectangle(tria2, Point<2>(0.0,0.8), Point<2>(0.4,1.0));
GridGenerator::hyper_rectangle(tria3, Point<2>(0.4,0.0), Point<2>(0.6,0.8));
GridGenerator::hyper_rectangle(tria4, Point<2>(0.6,0.0), Point<2>(1.0,0.8));
GridGenerator::hyper_rectangle(tria5, Point<2>(0.6,0.8), Point<2>(1.0,1.0));
GridGenerator::merge_triangulations (tria1, tria2, tria6);
GridGenerator::merge_triangulations (tria6, tria3, tria6);
GridGenerator::merge_triangulations (tria6, tria4, tria6);
}
void hyper_rectangle(Triangulation< dim, spacedim > &tria, const Point< dim > &p1, const Point< dim > &p2, const bool colorize=false)
void hyper_cube(Triangulation< dim, spacedim > &tria, const double left=0., const double right=1., const bool colorize=false)
void merge_triangulations(const Triangulation< dim, spacedim > &triangulation_1, const Triangulation< dim, spacedim > &triangulation_2, Triangulation< dim, spacedim > &result, const double duplicated_vertex_tolerance=1.0e-12, const bool copy_manifold_ids=false, const bool copy_boundary_ids=false)

perform initial refinements

triangulation.refine_global(init_ref);
}
/**************************************************************************************************/

ElastoplasticTorsion::solve(inner_it) Performs one inner iteration

template <int dim>
bool ElastoplasticTorsion<dim>::solve (const int inner_it)
{
prm.enter_subsection ("Algorithm Parameters");
const unsigned int max_CG_it=prm.get_integer("Max_CG_it");
const double CG_tol=prm.get_double("CG_tol");
prm.leave_subsection ();
SolverControl solver_control (max_CG_it,CG_tol);
SolverCG<> solver (solver_control);
PreconditionSSOR<> preconditioner;
preconditioner.initialize(system_matrix,0.25);
solver.solve (system_matrix, newton_update, system_rhs,
preconditioner);
hanging_node_constraints.distribute (newton_update);
/****** save current quantities for line-search **** */
void initialize(const MatrixType &A, const AdditionalData &parameters=AdditionalData())

Recall that phi(alpha)=J(u+alpha w)

old_step=step_length;
old_phi_zero=phi_zero;
phi_zero=phi(0); // phi(0)=J(u)
old_phip=phip;
phip=-1.0*(newton_update*system_rhs); //phi'(0)=J'(u) *w, rhs=-J'(u).
if (inner_it==0)
phip_zero=phip;
if (phip>0) // this should not happen, step back
{
std::cout << "Not a descent direction!" <<std::endl;
present_solution.add (-1.0*step_length, newton_update);
step_length=step_length/2;
phip=old_phip;
return false;
}
else
{
if (determine_step_length(inner_it))
{

update u_{n+1}=u_n+alpha w_n

present_solution.add (step_length, newton_update);
return true;
}
else return false;
}
}
/*************************************************************************************************************/

ElastoplasticTorsion::run

template <int dim>
{

get parameters

prm.enter_subsection ("Mesh & Refinement Parameters");
const int adapt_ref=prm.get_integer("No of adaptive refinements");
prm.leave_subsection ();
prm.enter_subsection ("Algorithm Parameters");
const int max_inner=prm.get_integer("Max_inner");
const double eps=prm.get_double("eps");
const double hi_eps=prm.get_double("hi_eps");
const int hi_th=prm.get_integer("hi_th");
const double init_p=prm.get_double("init_p");
const double delta_p=prm.get_double("delta_p");
prm.leave_subsection ();
prm.enter_subsection ("Global Parameters");
bool known_solution=prm.get_bool("known_solution");
double actual_p=prm.get_double("p");
prm.leave_subsection ();
/************************/

init Timer

Timer timer;
double ptime=0.0;
timer.start ();
Definition: timer.h:118
void start()
Definition: timer.cc:177

initalize mesh for the selected domain

init_mesh();

setup FE space

setup_system (true);
set_boundary_values ();

init counters

int global_it=0; // Total inner iterations (counting both loops)
int cycle=0; // Total outer iterations (counting both loops)
int refinement = 0; // Refinements performed (adaptive) = outer iterations 2nd loop

prepare to start first loop

p=init_p;
bool well_solved=true;
/***************************** First loop ***********************************/
/****************** Prepare initial condition using increasing p *************************/
while (p<actual_p) // outer iteration, increasing p.
{
std::cout <<"--Preparing initial condition with p="<<p<<" iter.= " << global_it<< " .-- "<< std::endl;
timer.restart();
for (int inner_iteration=0; inner_iteration<max_inner; ++inner_iteration,++global_it)
{
assemble_system ();
well_solved=solve (inner_iteration);
print_it_message (global_it, known_solution);
if (
((system_rhs.l2_norm()/std::sqrt(system_rhs.size()) <1e-4) & (cycle<1)) |
((system_rhs.l2_norm()/std::sqrt(system_rhs.size()) <1e-5) & (cycle>=1)) |
!well_solved
)
break;
}
ptime=timer.cpu_time();
if (well_solved)
output_results (cycle);
if (known_solution)
{
process_multiplier(cycle,global_it,ptime);
double cpu_time() const
Definition: timer.cc:236
void restart()
Definition: timer.h:897

dual_convergence_table.write_tex(dual_error_table_file);

}
refine_mesh();
cycle++;
p+=delta_p;
}
/*************************** first loop finished ********************/

prepare for second loop

p=actual_p;
well_solved=true;
/***************************** Second loop *********************************/
/**************************** Solve problem for target p *********************************/
std::cout << "============ Solving problem with p=" <<p << " ==================" << std::endl;
/***** Outer iteration - refining mesh ******************/
while ((cycle<adapt_ref) & well_solved)
{
timer.restart();

inner iteration

for (int inner_iteration=0; inner_iteration<max_inner; ++inner_iteration,++global_it)
{
assemble_system ();
well_solved=solve (inner_iteration);
print_it_message (global_it, known_solution);
if (
((system_rhs.l2_norm()/std::sqrt(system_rhs.size()) < eps) & (refinement<hi_th)) |
(( system_rhs.l2_norm()/ std::sqrt (system_rhs.size()) <hi_eps) | (!well_solved))
)
break;
}

inner iterations finished

ptime=timer.cpu_time();
if (well_solved)
output_results (cycle);

compute and display error, if the explicit solution is known

if (known_solution)
{
process_multiplier(cycle,global_it,ptime);
std::cout << "finished with H1 error: " << H1_error << ", dual error (L1): "
<< dual_L1_error << "dual error (L infty): "<<dual_L_infty_error <<std::endl;
}

update counters

++refinement;
++cycle;

refine mesh

std::cout << "******** Refined mesh " << cycle << " ********" << std::endl;
refine_mesh();
}// second loop

write convergence tables to file

if (known_solution)
{
format_convergence_tables();
std::string error_filename = "error"+Method+elements+".tex";
std::ofstream error_table_file(error_filename.c_str());
std::string dual_error_filename = "dual_error"+Method+elements+".tex";
std::ofstream dual_error_table_file(dual_error_filename.c_str());
convergence_table.write_tex(error_table_file);
dual_convergence_table.write_tex(dual_error_table_file);
}
}//run()
}//namespace
/**********************************************************************************************/

The main function

int main ()
{
try
{
using namespace dealii;
using namespace nsp;
ParameterReader param(prm);
param.read_parameters("EPT.prm");
ElastoplasticTorsion<2> ElastoplasticTorsionProblem(prm);
ElastoplasticTorsionProblem .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;
}
unsigned int depth_console(const unsigned int n)
Definition: logstream.cc:350
LogStream deallog
Definition: logstream.cc:37