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| 1 | // -*- mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- | ||
| 2 | // vi: set et ts=4 sw=4 sts=4: | ||
| 3 | // | ||
| 4 | // SPDX-FileCopyrightInfo: Copyright © DuMux Project contributors, see AUTHORS.md in root folder | ||
| 5 | // SPDX-License-Identifier: GPL-3.0-or-later | ||
| 6 | // | ||
| 7 | // ## The main file (`main.cc`) | ||
| 8 | // [[content]] | ||
| 9 | // | ||
| 10 | // ### Included header files | ||
| 11 | // [[details]] includes | ||
| 12 | // [[exclude]] | ||
| 13 | // Some generic includes. | ||
| 14 | #include <config.h> | ||
| 15 | #include <ctime> | ||
| 16 | #include <iostream> | ||
| 17 | // [[/exclude]] | ||
| 18 | |||
| 19 | // These time measurements and parallel backend initialization | ||
| 20 | #include <dune/common/timer.hh> | ||
| 21 | #include <dumux/common/initialize.hh> | ||
| 22 | |||
| 23 | // The following headers include functionality related to property definition or retrieval, as well as | ||
| 24 | // the retrieval of input parameters specified in the input file or via the command line. | ||
| 25 | #include <dumux/common/properties.hh> | ||
| 26 | #include <dumux/common/parameters.hh> | ||
| 27 | |||
| 28 | // The following files contains the available linear solver backends and the assembler for the linear | ||
| 29 | // systems arising from finite volume discretizations (box-scheme, tpfa-approximation, mpfa-approximation). | ||
| 30 | #include <dumux/linear/istlsolvers.hh> | ||
| 31 | #include <dumux/linear/linearsolvertraits.hh> | ||
| 32 | #include <dumux/linear/linearalgebratraits.hh> | ||
| 33 | #include <dumux/assembly/fvassembler.hh> | ||
| 34 | #include <dumux/assembly/diffmethod.hh> // analytic or numeric differentiation | ||
| 35 | |||
| 36 | // The following class provides a convenient way of writing of dumux simulation results to VTK format. | ||
| 37 | #include <dumux/io/vtkoutputmodule.hh> | ||
| 38 | // The gridmanager constructs a grid from the information in the input or grid file. | ||
| 39 | // Many different Dune grid implementations are supported, of which a list can be found | ||
| 40 | // in `gridmanager.hh`. | ||
| 41 | #include <dumux/io/grid/gridmanager.hh> | ||
| 42 | |||
| 43 | // For both the single-phase and the tracer problem, `TypeTags` are defined, which collect | ||
| 44 | // the properties that are required for the simulation. These type tags are defined | ||
| 45 | // in the headers that we include here. For detailed information, please have a look | ||
| 46 | // at the documentation provided therein. | ||
| 47 | #include "properties_1p.hh" | ||
| 48 | #include "properties_tracer.hh" | ||
| 49 | // [[/details]] | ||
| 50 | // | ||
| 51 | |||
| 52 | // ### The main function | ||
| 53 | // We will now discuss the main program flow implemented within the `main` function. | ||
| 54 | // At the beginning of each program using Dune, an instance of `Dune::MPIHelper` has to | ||
| 55 | // be created. Moreover, we parse the run-time arguments from the command line and the | ||
| 56 | // input file: | ||
| 57 | // [[codeblock]] | ||
| 58 | 1 | int main(int argc, char** argv) try | |
| 59 | { | ||
| 60 | 1 | using namespace Dumux; | |
| 61 | |||
| 62 | // maybe initialize MPI and/or multithreading backend | ||
| 63 |
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1 | Dumux::initialize(argc, argv); |
| 64 | |||
| 65 | // parse command line arguments and input file | ||
| 66 |
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4 | Parameters::init(argc, argv); |
| 67 | // [[/codeblock]] | ||
| 68 | |||
| 69 | // We define convenience aliases for the type tags of the two problems. The type | ||
| 70 | // tags contain all the properties that are needed to define the model and the problem | ||
| 71 | // setup. Throughout the main file, we will obtain types defined for these type tags | ||
| 72 | // using the property system, i.e. with `GetPropType`. A more detailed documentation | ||
| 73 | // for the type tags and properties can be found in the documentation of the single-phase | ||
| 74 | // and the tracer transport setups, respectively. | ||
| 75 | 1 | using OnePTypeTag = Properties::TTag::IncompressibleTest; | |
| 76 | 1 | using TracerTypeTag = Properties::TTag::TracerTest; | |
| 77 | |||
| 78 | // #### Step 1: Create the grid | ||
| 79 | // The `GridManager` class creates the grid from information given in the input file. | ||
| 80 | // This can either be a grid file, or in the case of structured grids, one can specify the coordinates | ||
| 81 | // of the corners of the grid and the number of cells to be used to discretize each spatial direction. | ||
| 82 | // Here, we solve both the single-phase and the tracer problem on the same grid, and thus, | ||
| 83 | // the grid is only created once using the grid type defined by the `OnePTypeTag` of the single-phase problem. | ||
| 84 | // [[codeblock]] | ||
| 85 |
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2 | GridManager<GetPropType<OnePTypeTag, Properties::Grid>> gridManager; |
| 86 |
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2 | gridManager.init(); |
| 87 | |||
| 88 | // We compute on the leaf grid view. | ||
| 89 |
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1 | const auto& leafGridView = gridManager.grid().leafGridView(); |
| 90 | // [[/codeblock]] | ||
| 91 | |||
| 92 | // #### Step 2: Solving the single-phase problem | ||
| 93 | // First, a finite volume grid geometry is constructed from the grid that was created above. | ||
| 94 | // This builds the sub-control volumes (scv) and sub-control volume faces (scvf) for each element | ||
| 95 | // of the grid partition. | ||
| 96 | 1 | using GridGeometry = GetPropType<OnePTypeTag, Properties::GridGeometry>; | |
| 97 |
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2 | auto gridGeometry = std::make_shared<GridGeometry>(leafGridView); |
| 98 | |||
| 99 | // We now instantiate the problem, in which we define the boundary and initial conditions. | ||
| 100 | 1 | using OnePProblem = GetPropType<OnePTypeTag, Properties::Problem>; | |
| 101 |
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2 | auto problemOneP = std::make_shared<OnePProblem>(gridGeometry); |
| 102 | |||
| 103 | // The jacobian matrix (`A`), the solution vector (`p`) and the residual (`r`) make up the linear system. | ||
| 104 | 1 | using JacobianMatrix = GetPropType<OnePTypeTag, Properties::JacobianMatrix>; | |
| 105 | 1 | using SolutionVector = GetPropType<OnePTypeTag, Properties::SolutionVector>; | |
| 106 |
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2 | SolutionVector p(leafGridView.size(0)); |
| 107 | |||
| 108 |
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2 | auto A = std::make_shared<JacobianMatrix>(); |
| 109 |
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2 | auto r = std::make_shared<SolutionVector>(); |
| 110 | |||
| 111 | // The grid variables are used store variables (primary and secondary variables) on sub-control volumes and faces (volume and flux variables). | ||
| 112 | 1 | using OnePGridVariables = GetPropType<OnePTypeTag, Properties::GridVariables>; | |
| 113 |
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2 | auto onePGridVariables = std::make_shared<OnePGridVariables>(problemOneP, gridGeometry); |
| 114 |
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2 | onePGridVariables->init(p); |
| 115 | |||
| 116 | // We now instantiate the assembler class, assemble the linear system and solve it with the linear | ||
| 117 | // solver AMGCGIstlSolver (a conjugate gradient solver preconditioned by an algebraic multigrid). | ||
| 118 | // Besides that, the time needed for assembly and solve is measured and printed. | ||
| 119 | 1 | using OnePAssembler = FVAssembler<OnePTypeTag, DiffMethod::analytic>; | |
| 120 |
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2 | auto assemblerOneP = std::make_shared<OnePAssembler>(problemOneP, gridGeometry, onePGridVariables); |
| 121 |
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3 | assemblerOneP->setLinearSystem(A, r); // tell assembler to use our previously defined system |
| 122 | |||
| 123 | 1 | Dune::Timer timer; | |
| 124 |
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2 | Dune::Timer assemblyTimer; std::cout << "Assembling linear system ..." << std::flush; |
| 125 |
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2 | assemblerOneP->assembleJacobianAndResidual(p); // assemble linear system around current solution |
| 126 |
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3 | assemblyTimer.stop(); std::cout << " took " << assemblyTimer.elapsed() << " seconds." << std::endl; |
| 127 | |||
| 128 | 2 | (*r) *= -1.0; // We want to solve `Ax = -r`. | |
| 129 | |||
| 130 | 1 | using OnePLinearSolver = AMGCGIstlSolver<LinearSolverTraits<GridGeometry>, LinearAlgebraTraitsFromAssembler<OnePAssembler>>; | |
| 131 |
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2 | Dune::Timer solverTimer; std::cout << "Solving linear system ..." << std::flush; |
| 132 |
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6 | auto onePLinearSolver = std::make_shared<OnePLinearSolver>(gridGeometry->gridView(), gridGeometry->dofMapper()); |
| 133 |
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4 | onePLinearSolver->solve(*A, p, *r); |
| 134 |
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3 | solverTimer.stop(); std::cout << " took " << solverTimer.elapsed() << " seconds." << std::endl; |
| 135 | |||
| 136 |
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2 | Dune::Timer updateTimer; std::cout << "Updating variables ..." << std::flush; |
| 137 |
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2 | onePGridVariables->update(p); // update grid variables to new pressure distribution |
| 138 |
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2 | updateTimer.elapsed(); std::cout << " took " << updateTimer.elapsed() << std::endl; |
| 139 | |||
| 140 | // The solution vector `p` now contains the pressure field, i.e.the solution to the single-phase | ||
| 141 | // problem defined in `problem_1p.hh`. Let us now write this solution to a VTK file using the Dune | ||
| 142 | // `VTKWriter`. Moreover, we add the permeability distribution to the writer. | ||
| 143 | // [[codeblock]] | ||
| 144 | 1 | using GridView = typename GridGeometry::GridView; | |
| 145 |
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2 | Dune::VTKWriter<GridView> onepWriter(leafGridView); |
| 146 |
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2 | onepWriter.addCellData(p, "p"); |
| 147 | |||
| 148 |
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3 | const auto& k = problemOneP->spatialParams().getKField(); // defined in spatialparams_1p.hh |
| 149 |
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2 | onepWriter.addCellData(k, "permeability"); // add permeability to writer |
| 150 |
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2 | onepWriter.write("1p"); // write the file "1p.vtk" |
| 151 | |||
| 152 | // print overall CPU time required for assembling and solving the 1p problem. | ||
| 153 | 1 | timer.stop(); | |
| 154 |
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1 | const auto& comm = leafGridView.comm(); |
| 155 |
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2 | std::cout << "Simulation took " << timer.elapsed() << " seconds on " |
| 156 | << comm.size() << " processes.\n" | ||
| 157 |
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4 | << "The cumulative CPU time was " << timer.elapsed()*comm.size() << " seconds.\n"; |
| 158 | // [[/codeblock]] | ||
| 159 | |||
| 160 | // #### Step 3: Computation of the volume fluxes | ||
| 161 | // We use the results of the 1p problem to calculate the volume fluxes across all sub-control volume | ||
| 162 | // faces of the discretization and store them in the vector `volumeFlux`. In order to do so, we iterate | ||
| 163 | // over all elements of the grid, and in each element compute the volume fluxes for all sub-control volume | ||
| 164 | // faces embedded in that element. | ||
| 165 | // [[codeblock]] | ||
| 166 | 1 | using Scalar = GetPropType<OnePTypeTag, Properties::Scalar>; // type for scalar values | |
| 167 |
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5 | std::vector<Scalar> volumeFlux(gridGeometry->numScvf(), 0.0); |
| 168 | |||
| 169 | 1 | using FluxVariables = GetPropType<OnePTypeTag, Properties::FluxVariables>; | |
| 170 | ✗ | auto upwindTerm = [](const auto& volVars) { return volVars.mobility(0); }; | |
| 171 | |||
| 172 | // We iterate over all elements | ||
| 173 |
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5001 | for (const auto& element : elements(leafGridView)) |
| 174 | { | ||
| 175 | // Compute the element-local views on geometry, primary and secondary variables | ||
| 176 | // as well as variables needed for flux computations. | ||
| 177 | |||
| 178 | // This creates instances of the local views | ||
| 179 | 5000 | auto fvGeometry = localView(*gridGeometry); | |
| 180 | 10000 | auto elemVolVars = localView(onePGridVariables->curGridVolVars()); | |
| 181 | 7500 | auto elemFluxVars = localView(onePGridVariables->gridFluxVarsCache()); | |
| 182 | |||
| 183 | // we now have to bind the views to the current element | ||
| 184 | 2500 | fvGeometry.bind(element); | |
| 185 |
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2500 | elemVolVars.bind(element, fvGeometry, p); |
| 186 | 2500 | elemFluxVars.bind(element, fvGeometry, elemVolVars); | |
| 187 | |||
| 188 | // We calculate the volume fluxes for all sub-control volume faces except for Neumann boundary faces | ||
| 189 |
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15000 | for (const auto& scvf : scvfs(fvGeometry)) |
| 190 | { | ||
| 191 | // skip Neumann boundary faces | ||
| 192 |
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10300 | if (scvf.boundary() && problemOneP->boundaryTypes(element, scvf).hasNeumann()) |
| 193 | 100 | continue; | |
| 194 | |||
| 195 | // let the FluxVariables class do the flux computation. | ||
| 196 |
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9900 | FluxVariables fluxVars; |
| 197 |
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19800 | fluxVars.init(*problemOneP, element, fvGeometry, elemVolVars, scvf, elemFluxVars); |
| 198 |
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9900 | volumeFlux[scvf.index()] = fluxVars.advectiveFlux(0, upwindTerm); |
| 199 | } | ||
| 200 | } | ||
| 201 | // [[/codeblock]] | ||
| 202 | |||
| 203 | // #### Step 4: Solving the tracer transport problem | ||
| 204 | // First, we instantiate the tracer problem containing initial and boundary conditions, | ||
| 205 | // and pass to it the previously computed volume fluxes (see the documentation of the | ||
| 206 | // file `spatialparams_tracer.hh` for more details). | ||
| 207 | 1 | using TracerProblem = GetPropType<TracerTypeTag, Properties::Problem>; | |
| 208 |
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2 | auto tracerProblem = std::make_shared<TracerProblem>(gridGeometry); |
| 209 |
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3 | tracerProblem->spatialParams().setVolumeFlux(volumeFlux); |
| 210 | |||
| 211 | // We create and initialize the solution vector. In contrast to the steady-state single-phase problem, | ||
| 212 | // the tracer problem is transient, and the initial solution defined in the problem is applied to the | ||
| 213 | // solution vector. On the basis of this solution, we initialize then the grid variables. | ||
| 214 |
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2 | SolutionVector x(leafGridView.size(0)); |
| 215 |
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2 | tracerProblem->applyInitialSolution(x); |
| 216 |
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2 | auto xOld = x; |
| 217 | |||
| 218 | 1 | using GridVariables = GetPropType<TracerTypeTag, Properties::GridVariables>; | |
| 219 |
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2 | auto gridVariables = std::make_shared<GridVariables>(tracerProblem, gridGeometry); |
| 220 |
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2 | gridVariables->init(x); |
| 221 | |||
| 222 | // Let us now instantiate the time loop. Therefore, we read in some time loop parameters from the input file. | ||
| 223 | // The parameter `tEnd` defines the duration of the simulation, `dt` the initial time step size and `maxDt` the maximal time step size. | ||
| 224 | // Moreover, we define 10 check points in the time loop at which we will write the solution to vtk files. | ||
| 225 | // [[codeblock]] | ||
| 226 |
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1 | const auto tEnd = getParam<Scalar>("TimeLoop.TEnd"); |
| 227 |
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1 | auto dt = getParam<Scalar>("TimeLoop.DtInitial"); |
| 228 |
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1 | const auto maxDt = getParam<Scalar>("TimeLoop.MaxTimeStepSize"); |
| 229 | |||
| 230 | // We instantiate the time loop. | ||
| 231 |
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2 | auto timeLoop = std::make_shared<CheckPointTimeLoop<Scalar>>(0.0, dt, tEnd); |
| 232 |
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2 | timeLoop->setMaxTimeStepSize(maxDt); |
| 233 |
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2 | timeLoop->setPeriodicCheckPoint(tEnd/10.0); |
| 234 | // [[/codeblock]] | ||
| 235 | |||
| 236 | // We create and initialize the assembler with a time loop for the transient problem. | ||
| 237 | // Within the time loop, we will use this assembler in each time step to assemble the linear system. | ||
| 238 | // As solver we use the ILUBiCGSTABIstlSolver (a bi-conjugate gradient solver preconditioned by an incomplete LU-factorization). | ||
| 239 | 1 | using TracerAssembler = FVAssembler<TracerTypeTag, DiffMethod::analytic, /*implicit=*/false>; | |
| 240 |
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2 | auto assembler = std::make_shared<TracerAssembler>(tracerProblem, gridGeometry, gridVariables, timeLoop, xOld); |
| 241 |
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3 | assembler->setLinearSystem(A, r); |
| 242 | |||
| 243 | 1 | using TracerLinearSolver = ILUBiCGSTABIstlSolver<LinearSolverTraits<GridGeometry>, LinearAlgebraTraitsFromAssembler<TracerAssembler>>; | |
| 244 |
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6 | auto tracerLinearSolver = std::make_shared<TracerLinearSolver>(gridGeometry->gridView(), gridGeometry->dofMapper()); |
| 245 | |||
| 246 | // The following lines of code initialize the vtk output module, add the velocity output facility | ||
| 247 | // and write out the initial solution. At each checkpoint, we will use the output module to write | ||
| 248 | // the solution of a time step into a corresponding vtk file. | ||
| 249 | // [[codeblock]] | ||
| 250 |
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4 | VtkOutputModule<GridVariables, SolutionVector> vtkWriter(*gridVariables, x, tracerProblem->name()); |
| 251 | |||
| 252 | // add model-specific output fields to the writer | ||
| 253 | 1 | using IOFields = GetPropType<TracerTypeTag, Properties::IOFields>; | |
| 254 |
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1 | IOFields::initOutputModule(vtkWriter); |
| 255 | |||
| 256 | // add velocity output facility | ||
| 257 | 1 | using VelocityOutput = GetPropType<TracerTypeTag, Properties::VelocityOutput>; | |
| 258 |
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3 | vtkWriter.addVelocityOutput(std::make_shared<VelocityOutput>(*gridVariables)); |
| 259 | |||
| 260 | // write initial solution | ||
| 261 |
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1 | vtkWriter.write(0.0); |
| 262 | // [[/codeblock]] | ||
| 263 | |||
| 264 | // ##### The time loop | ||
| 265 | // We start the time loop and solve a new time step as long as `tEnd` is not reached. In every time step, | ||
| 266 | // the problem is assembled and solved, the solution is updated, and when a checkpoint is reached the solution | ||
| 267 | // is written to a new vtk file. In addition, statistics related to CPU time, the current simulation time | ||
| 268 | // and the time step sizes used is printed to the terminal. | ||
| 269 | // [[codeblock]] | ||
| 270 |
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2 | timeLoop->start(); do |
| 271 | { | ||
| 272 | // Then the linear system is assembled. | ||
| 273 | 500 | Dune::Timer assembleTimer; | |
| 274 |
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1000 | assembler->assembleJacobianAndResidual(x); |
| 275 | 500 | assembleTimer.stop(); | |
| 276 | |||
| 277 | // We solve the linear system `A(xOld-xNew) = r`. | ||
| 278 | 500 | Dune::Timer solveTimer; | |
| 279 |
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1000 | SolutionVector xDelta(x); |
| 280 |
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2000 | tracerLinearSolver->solve(*A, xDelta, *r); |
| 281 | 500 | solveTimer.stop(); | |
| 282 | |||
| 283 | // update the solution vector and the grid variables. | ||
| 284 | 500 | updateTimer.reset(); | |
| 285 | 500 | x -= xDelta; | |
| 286 |
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1000 | gridVariables->update(x); |
| 287 | 500 | updateTimer.stop(); | |
| 288 | |||
| 289 | // display the statistics of the actual time step. | ||
| 290 | 500 | const auto elapsedTot = assembleTimer.elapsed() + solveTimer.elapsed() + updateTimer.elapsed(); | |
| 291 | 500 | std::cout << "Assemble/solve/update time: " | |
| 292 |
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1000 | << assembleTimer.elapsed() << "(" << 100*assembleTimer.elapsed()/elapsedTot << "%)/" |
| 293 |
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1000 | << solveTimer.elapsed() << "(" << 100*solveTimer.elapsed()/elapsedTot << "%)/" |
| 294 |
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1000 | << updateTimer.elapsed() << "(" << 100*updateTimer.elapsed()/elapsedTot << "%)" |
| 295 |
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500 | << std::endl; |
| 296 | |||
| 297 | // Update the old solution with the one computed in this time step and move to the next one | ||
| 298 |
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500 | xOld = x; |
| 299 |
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1000 | gridVariables->advanceTimeStep(); |
| 300 |
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1000 | timeLoop->advanceTimeStep(); |
| 301 | |||
| 302 | // Write the Vtk output on check points. | ||
| 303 |
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1000 | if (timeLoop->isCheckPoint()) |
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30 | vtkWriter.write(timeLoop->time()); |
| 305 | |||
| 306 | // report statistics of this time step | ||
| 307 |
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1000 | timeLoop->reportTimeStep(); |
| 308 | |||
| 309 | // set the time step size for the next time step | ||
| 310 |
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1000 | timeLoop->setTimeStepSize(dt); |
| 311 | |||
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1000 | } while (!timeLoop->finished()); |
| 313 | // [[/codeblock]] | ||
| 314 | |||
| 315 | // The following piece of code prints a final status report of the time loop | ||
| 316 | // before the program is terminated. | ||
| 317 |
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2 | timeLoop->finalize(leafGridView.comm()); |
| 318 | |||
| 319 | 1 | return 0; | |
| 320 | } | ||
| 321 | // #### Exception handling | ||
| 322 | // In this part of the main file we catch and print possible exceptions that could | ||
| 323 | // occur during the simulation. | ||
| 324 | // [[details]] exception handler | ||
| 325 | // [[codeblock]] | ||
| 326 | // errors related to run-time parameters | ||
| 327 | ✗ | catch (Dumux::ParameterException &e) | |
| 328 | { | ||
| 329 | ✗ | std::cerr << std::endl << e << " ---> Abort!" << std::endl; | |
| 330 | ✗ | return 1; | |
| 331 | } | ||
| 332 | // errors related to the parsing of Dune grid files | ||
| 333 | ✗ | catch (Dune::DGFException & e) | |
| 334 | { | ||
| 335 | ✗ | std::cerr << "DGF exception thrown (" << e << | |
| 336 | "). Most likely, the DGF file name is wrong " | ||
| 337 | "or the DGF file is corrupted, " | ||
| 338 | "e.g. missing hash at end of file or wrong number (dimensions) of entries." | ||
| 339 | ✗ | << " ---> Abort!" << std::endl; | |
| 340 | ✗ | return 2; | |
| 341 | } | ||
| 342 | // generic error handling with Dune::Exception | ||
| 343 | ✗ | catch (Dune::Exception &e) | |
| 344 | { | ||
| 345 | ✗ | std::cerr << "Dune reported error: " << e << " ---> Abort!" << std::endl; | |
| 346 | ✗ | return 3; | |
| 347 | } | ||
| 348 | // other exceptions | ||
| 349 | ✗ | catch (...) | |
| 350 | { | ||
| 351 | ✗ | std::cerr << "Unknown exception thrown! ---> Abort!" << std::endl; | |
| 352 | ✗ | return 4; | |
| 353 | } | ||
| 354 | // [[/codeblock]] | ||
| 355 | // [[/details]] | ||
| 356 | // [[/content]] | ||
| 357 |