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new_local_law.cc
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new_local_law.cc
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/**
* @file diffusion_dynamics_2d.cc
*
* @author Guillaume Anciaux <guillaume.anciaux@epfl.ch>
* @author Nicolas Richart <nicolas.richart@epfl.ch>
*
* @date creation: Sun May 01 2011
* @date last modification: Fri Mar 16 2018
*
* @brief Example of diffusion constitutive law
*
*
* @section LICENSE
*
* Copyright (©) 2015-2021 EPFL (Ecole Polytechnique Fédérale de Lausanne)
* Laboratory (LSMS - Laboratoire de Simulation en Mécanique des Solides)
*
* Akantu 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.
*
* Akantu 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 Akantu. If not, see <http://www.gnu.org/licenses/>.
*
*/
/* -------------------------------------------------------------------------- */
#include "poisson_model.hh"
/* -------------------------------------------------------------------------- */
#include <iostream>
/* -------------------------------------------------------------------------- */
using namespace akantu;
const UInt spatial_dimension = 1;
/* -------------------------------------------------------------------------- */
int main(int argc, char * argv[]) {
initialize("local_law.dat", argc, argv);
// create mesh
Mesh mesh(spatial_dimension);
mesh.read("bar.msh");
PoissonModel model(mesh);
// initialize everything
model.initFull();
// get stable time step
Real time_step = model.getStableTimeStep() * 0.1;
std::cout << "time step is:" << time_step << std::endl;
model.setTimeStep(time_step);
// boundary conditions
const Array<Real> & nodes = model.getFEEngine().getMesh().getNodes();
Array<bool> & boundary = model.getBlockedDOFs();
Array<Real> & concentration = model.getDof();
auto & external_flux_rate = model.getExternalDofRate();
external_flux_rate(0) = 1e-8;
std::cout << external_flux_rate;
model.setBaseName("new_local1d");
model.addDumpField("dof");
model.addDumpField("internal_dof_rate");
model.addDumpField("external_dof_rate");
model.dump();
// main loop
int max_steps = 15000;
for (int i = 0; i < max_steps; i++) {
model.solveStep();
if (i % 100 == 0)
model.dump();
std::cout << "Step " << i << "/" << max_steps << std::endl;
}
std::cout << "\n\n Stable Time Step is : " << time_step << "\n \n"
<< std::endl;
return 0;
}

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