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tamaas/src/bem/bem_gigi.cpp
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bem_gigi.cpp
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/**
*
* @author Guillaume Anciaux <guillaume.anciaux@epfl.ch>
*
* @section LICENSE
*
* Copyright (©) 2016 EPFL (Ecole Polytechnique Fédérale de
* Lausanne) Laboratory (LSMS - Laboratoire de Simulation en Mécanique des
* Solides)
*
* Tamaas is free software: you can 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 3 of the License, or (at your option) any
* later version.
*
* Tamaas is distributed in the hope that it will be useful, but WITHOUT ANY
* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
* A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more
* details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with Tamaas. If not, see <http://www.gnu.org/licenses/>.
*
*/
/* -------------------------------------------------------------------------- */
#include <vector>
#include "surface.hh"
#include "bem_gigi.hh"
#include <iostream>
#include <sstream>
#include <fstream>
#include <iomanip>
#include <sstream>
#include <cmath>
/* -------------------------------------------------------------------------- */
#define TIMER
#include "surface_timer.hh"
/* -------------------------------------------------------------------------- */
__BEGIN_TAMAAS__
Real BemGigi::computeEquilibrium(Real epsilon,
Real mean_displacement) {
this->computeSpectralInfluenceOverDisplacement();
Real Rold = 1.;
Real f = 1e300;
this->search_direction = 0.;
this->true_displacements =0;
this->true_displacements = mean_displacement;
this->computeGaps();
this->optimizeToMeanDisplacement(mean_displacement);
this->computeGaps();
convergence_iterations.clear();
nb_iterations = 0;
max_iterations =50;
Real R=0;
while (f> epsilon && nb_iterations++ < max_iterations) {
this->computeGaps();
this->functional->computeGradFU();
this->updateSearchDirection(R / Rold);
Rold = R;
Real alpha = this->computeOptimalStep();
std::cout << "alpha vaut "<< alpha<< std::endl;
this->old_displacements=this->true_displacements;
this->updateDisplacements(alpha);
this->computeGaps();
this->optimizeToMeanDisplacement(mean_displacement); //espace admissible
this->computeGaps();
this->computePressures(mean_displacement);
f=computeStoppingCriterion();
}
this->computePressures(mean_displacement);
return f;
}
/* -------------------------------------------------------------------------- */
Real BemGigi::computeStoppingCriterion() {
Real rho = this->functional->getParameter("rho");
Real surface_energy = this->functional->getParameter("surface_energy");
Real crit=0.;
//Real disp_norm = 0.;
UInt n = surface.size();
UInt size = n*n;
//#pragma omp parallel for reduction(+:crit, disp_norm)
#pragma omp parallel for reduction(+:crit)
for (UInt i = 0; i < size; ++i) {
crit += std::abs(this->gap(i)*(this->surface_tractions(i)+surface_energy/rho * exp(- (gap(i)) / rho)));
}
return crit;
}
/* -------------------------------------------------------------------------- */
/* -------------------------------------------------------------------------- */
void BemGigi::optimizeToMeanDisplacement(Real imposed_mean) {
Real target_value = imposed_mean - SurfaceStatistics::computeAverage(surface, 0);
UInt n = surface.size();
UInt size = n * n;
// Initial guesses for upper and lower bound
Real step_min = -10;
Real step_max = 10;
// Gaps for upper and lower bound
Real gap_min = positiveGapAverage(step_min);
Real gap_max = positiveGapAverage(step_max);
UInt max_expansion = 8;
// Expand bounds if necessary
for (UInt i = 0 ; gap_max < target_value && i < max_expansion ; i++, step_max *= 10)
gap_max = positiveGapAverage(step_max);
for (UInt i = 0 ; gap_min > target_value && i < max_expansion ; i++, step_min *= 10)
gap_min = positiveGapAverage(step_min);
Real g = 0.;
Real epsilon = 1e-12;
Real step = 0;
while (fabs(g - target_value) > epsilon) {
step = (step_min + step_max) / 2.;
g = positiveGapAverage(step);
if (g > target_value) step_max = step;
else if (g < target_value) step_min = step;
else {
step_max = step;
step_min = step;
}
}
step = (step_min + step_max) / 2.;
#pragma omp parallel for
for (UInt i = 0 ; i < size ; i++) {
gap(i) += step;
if (gap(i) < 0) gap(i) = 0;
true_displacements(i) = gap(i) + surface(i);
}
}
/* -------------------------------------------------------------------------- */
Real BemGigi::positiveGapAverage(Real shift) {
UInt n = surface.size();
Real res = 0;
#pragma omp parallel for reduction(+: res)
for (UInt i = 0 ; i < n * n ; i++) {
Real shifted_gap = gap(i) + shift;
res += shifted_gap * (shifted_gap > 0);
}
return res / (n * n);
}
/* -------------------------------------------------------------------------- */
void BemGigi::updateSearchDirection(Real factor) {
STARTTIMER("updateSearchDirection");
UInt n = surface.size();
UInt size = n*n;
const Surface<Real> & gradF = this->functional->getGradF();
#pragma omp parallel for
for (UInt i = 0; i < size; ++i) {
this->search_direction(i)= gradF(i);
}
STOPTIMER("updateSearchDirection");
}
/* -------------------------------------------------------------------------- */
Real BemGigi::computeOptimalStep() {
STARTTIMER("computeOptimalStep");
this->applyInverseInfluenceFunctions(search_direction, projected_direction);
UInt n = surface.size();
UInt size = n*n;
const Surface<Real> & gradF = this->functional->getGradF();
Real numerator = 0., denominator = 0.;
#pragma omp parallel for reduction(+: numerator, denominator)
for (UInt i = 0; i < size; ++i) {
numerator += gradF(i) * search_direction(i);
denominator += projected_direction(i) * search_direction(i);
}
Real alpha = numerator / denominator;
STOPTIMER("computeOptimalStep");
return alpha;
}
/* -------------------------------------------------------------------------- */
Real BemGigi::computeTau() {
return computeOptimalStep();
}
/* -------------------------------------------------------------------------- */
void BemGigi::updateDisplacements(Real alpha) {
STARTTIMER("updateDisplacements");
UInt n = surface.size();
UInt size = n*n;
#pragma omp parallel for
for (UInt i = 0; i < size; ++i) {
this->true_displacements(i) -= alpha*this->search_direction(i);
}
STOPTIMER("updateDisplacements");
}
/* -------------------------------------------------------------------------- */
void BemGigi::emptyOverlap() {
STARTTIMER("emptyoverlap");
UInt n = surface.size();
UInt size = n*n;
#pragma omp parallel for
for (UInt i = 0; i < size; ++i) {
if (gap(i) < 0)
this->true_displacements(i) = this->surface(i);
}
STOPTIMER("emptyoverlap");
}
/* -------------------------------------------------------------------------- */
void BemGigi::enforceMeanDisplacement(Real mean_displacement) {
STARTTIMER("enforceMeanDisplacement");
UInt n = surface.size();
UInt size = n*n;
Real moyenne_surface=SurfaceStatistics::computeAverage(this->surface, 0);
Real average = SurfaceStatistics::computeAverage(this->true_displacements, 0);
Real factor = (mean_displacement-moyenne_surface) / (average-moyenne_surface);
#pragma omp parallel for
for (UInt i = 0; i < size; ++i) {
this->true_displacements(i) = factor*(this->true_displacements(i)-this->surface(i)) +this->surface(i);
}
STOPTIMER("enforceMeanDisplacement");
}
/* -------------------------------------------------------------------------- */
void BemGigi::computePressures(Real mean_displacement) {
this->computeTractionsFromDisplacements();
UInt n = surface.size();
UInt size = n*n;
Real rho = this->functional->getParameter("rho");
Real surface_energy = this->functional->getParameter("surface_energy");
Real mini=3000;
for (UInt i = 0; i < size; ++i) {
if (gap(i)<rho){
if (this->surface_tractions(i)+surface_energy/rho <mini )
mini= this->surface_tractions(i)+surface_energy/rho ;
}
else
{ if (this->surface_tractions(i)<mini )
mini= this->surface_tractions(i) ;}
}
this->surface_tractions-=mini;
}
__END_TAMAAS__
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