ExplicitTimeIntegrator.C

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//* This file is part of the MOOSE framework
//* https://mooseframework.inl.gov
//*
//* All rights reserved, see COPYRIGHT for full restrictions
//* https://github.com/idaholab/moose/blob/master/COPYRIGHT
//*
//* Licensed under LGPL 2.1, please see LICENSE for details
//* https://www.gnu.org/licenses/lgpl-2.1.html
 
// MOOSE includes
#include "ExplicitTimeIntegrator.h"
#include "NonlinearSystem.h"
#include "FEProblem.h"
#include "PetscSupport.h"
#include "KernelBase.h"
#include "DGKernelBase.h"
#include "ScalarKernelBase.h"
#include "FVElementalKernel.h"
#include "FVFluxKernel.h"
#include "NodalKernelBase.h"
 
// libMesh includes
#include "libmesh/enum_convergence_flags.h"
 
using namespace libMesh;
 
InputParameters
ExplicitTimeIntegrator::validParams()
{
  InputParameters params = TimeIntegrator::validParams();
 
  MooseEnum solve_type("consistent lumped lump_preconditioned", "consistent");
 
  params.addParam<MooseEnum>(
      "solve_type",
      solve_type,
      "The way to solve the system.  A 'consistent' solve uses the full mass matrix and actually "
      "needs to use a linear solver to solve the problem.  'lumped' uses a lumped mass matrix with "
      "a simple inversion - incredibly fast but may be less accurate.  'lump_preconditioned' uses "
      "the lumped mass matrix as a preconditioner for the 'consistent' solve");
 
  return params;
}
 
ExplicitTimeIntegrator::ExplicitTimeIntegrator(const InputParameters & parameters)
  : TimeIntegrator(parameters),
    MeshChangedInterface(parameters),
    _solve_type(getParam<MooseEnum>("solve_type")),
    _explicit_residual(addVector("explicit_residual", false, PARALLEL)),
    _solution_update(addVector("solution_update", true, PARALLEL)),
    _mass_matrix_diag_inverted(addVector("mass_matrix_diag_inverted", true, GHOSTED)),
    _ones(nullptr)
{
  _Ke_time_tag = _fe_problem.getMatrixTagID("TIME");
 
  // This effectively changes the default solve_type to LINEAR instead of PJFNK,
  // so that it is valid to not supply solve_type in the Executioner block:
  if (_nl)
    _fe_problem.solverParams(_nl->number())._type = Moose::ST_LINEAR;
 
  if (_solve_type == LUMPED || _solve_type == LUMP_PRECONDITIONED)
    _ones = addVector("ones", true, PARALLEL);
  // don't set any of the common SNES and KSP-related petsc options to prevent unused option
  // warnings
  Moose::PetscSupport::dontAddCommonSNESOptions(_fe_problem);
  Moose::PetscSupport::dontAddCommonKSPOptions(_fe_problem);
}
 
void
ExplicitTimeIntegrator::initialSetup()
{
  setupSolver();
 
  if (_nl)
  {
    std::unordered_set<unsigned int> vars_to_check;
    if (!_vars.empty())
      vars_to_check = _vars;
    else
      for (const auto i : make_range(_nl->nVariables()))
        vars_to_check.insert(i);
 
    const auto mass_matrix_tag_id = massMatrixTagID();
    std::set<TagID> matrix_tags = {mass_matrix_tag_id};
    auto fv_object_starting_query = _fe_problem.theWarehouse()
                                        .query()
                                        .template condition<AttribMatrixTags>(matrix_tags)
                                        .template condition<AttribSysNum>(_nl->number());
 
    for (const auto var_id : vars_to_check)
    {
      const auto & var_name = _nl->system().variable_name(var_id);
      const bool field_var = _nl->hasVariable(var_name);
      if (!field_var)
        mooseAssert(_nl->hasScalarVariable(var_name),
                    var_name << " should be either a field or scalar variable");
      if (field_var)
      {
        const auto & field_var = _nl->getVariable(/*tid=*/0, var_name);
        if (field_var.isFV())
        {
          std::vector<FVElementalKernel *> fv_elemental_kernels;
          auto var_query = fv_object_starting_query.clone().template condition<AttribVar>(var_id);
          auto var_query_clone = var_query.clone();
          var_query.template condition<AttribSystem>("FVElementalKernel")
              .queryInto(fv_elemental_kernels);
          if (fv_elemental_kernels.size())
            continue;
 
          std::vector<FVFluxKernel *> fv_flux_kernels;
          var_query_clone.template condition<AttribSystem>("FVFluxKernel")
              .queryInto(fv_flux_kernels);
          if (fv_flux_kernels.size())
            continue;
        }
        else
        {
          // We are a finite element variable
          if (_nl->getKernelWarehouse()
                  .getMatrixTagObjectWarehouse(mass_matrix_tag_id, 0)
                  .hasVariableObjects(var_id))
            continue;
          if (_nl->getDGKernelWarehouse()
                  .getMatrixTagObjectWarehouse(mass_matrix_tag_id, 0)
                  .hasVariableObjects(var_id))
            continue;
          if (_nl->getNodalKernelWarehouse()
                  .getMatrixTagObjectWarehouse(mass_matrix_tag_id, 0)
                  .hasVariableObjects(var_id))
            continue;
#ifdef MOOSE_KOKKOS_ENABLED
          if (_nl->getKokkosKernelWarehouse()
                  .getMatrixTagObjectWarehouse(mass_matrix_tag_id, 0)
                  .hasVariableObjects(var_id))
            continue;
          if (_nl->getKokkosNodalKernelWarehouse()
                  .getMatrixTagObjectWarehouse(mass_matrix_tag_id, 0)
                  .hasVariableObjects(var_id))
            continue;
#endif
        }
      }
      else if (_nl->getScalarKernelWarehouse()
                   .getMatrixTagObjectWarehouse(mass_matrix_tag_id, 0)
                   .hasVariableObjects(var_id))
        continue;
 
      mooseError("No objects contributing to the mass matrix were found for variable '",
                 var_name,
                 "'. Did you, e.g., forget a time derivative term?");
    }
  }
}
 
void
ExplicitTimeIntegrator::init()
{
  if (_nl && _fe_problem.solverParams(_nl->number())._type != Moose::ST_LINEAR)
    mooseError(
        "The chosen time integrator requires 'solve_type = LINEAR' in the Executioner block.");
}
 
void
ExplicitTimeIntegrator::preSolve()
{
}
 
void
ExplicitTimeIntegrator::meshChanged()
{
  setupSolver();
}
 
void
ExplicitTimeIntegrator::setupSolver()
{
  // Can only be done after the system is initialized
  if (_ones)
  {
    if (_solve_type == LUMPED || _solve_type == LUMP_PRECONDITIONED)
      *_ones = 1.;
  }
 
  if (_solve_type == CONSISTENT || _solve_type == LUMP_PRECONDITIONED)
    _linear_solver = LinearSolver<Number>::build(comm());
 
  if (_solve_type == LUMP_PRECONDITIONED)
  {
    _preconditioner = std::make_unique<LumpedPreconditioner>(*_mass_matrix_diag_inverted);
    _linear_solver->attach_preconditioner(_preconditioner.get());
    _linear_solver->init();
  }
 
  if (_solve_type == CONSISTENT || _solve_type == LUMP_PRECONDITIONED)
    Moose::PetscSupport::setLinearSolverDefaults(_fe_problem, *_linear_solver);
}
 
bool
ExplicitTimeIntegrator::performExplicitSolve(SparseMatrix<Number> & mass_matrix)
{
  bool converged = false;
 
  switch (_solve_type)
  {
    case CONSISTENT:
    {
      converged = solveLinearSystem(mass_matrix);
 
      break;
    }
    case LUMPED:
    {
      // Computes the sum of each row (lumping)
      // Note: This is actually how PETSc does it
      // It's not "perfectly optimal" - but it will be fast (and universal)
      mass_matrix.vector_mult(*_mass_matrix_diag_inverted, *_ones);
 
      // "Invert" the diagonal mass matrix
      _mass_matrix_diag_inverted->reciprocal();
 
      // Multiply the inversion by the RHS
      _solution_update->pointwise_mult(*_mass_matrix_diag_inverted, *_explicit_residual);
 
      // Check for convergence by seeing if there is a nan or inf
      auto sum = _solution_update->sum();
      converged = std::isfinite(sum);
 
      // The linear iteration count remains zero
      _n_linear_iterations = 0;
 
      break;
    }
    case LUMP_PRECONDITIONED:
    {
      mass_matrix.vector_mult(*_mass_matrix_diag_inverted, *_ones);
      _mass_matrix_diag_inverted->reciprocal();
 
      converged = solveLinearSystem(mass_matrix);
 
      break;
    }
    default:
      mooseError("Unknown solve_type in ExplicitTimeIntegrator.");
  }
 
  return converged;
}
 
bool
ExplicitTimeIntegrator::solveLinearSystem(SparseMatrix<Number> & mass_matrix)
{
  auto & es = _fe_problem.es();
 
  const auto num_its_and_final_tol =
      _linear_solver->solve(mass_matrix,
                            *_solution_update,
                            *_explicit_residual,
                            es.parameters.get<Real>("linear solver tolerance"),
                            es.parameters.get<unsigned int>("linear solver maximum iterations"));
 
  _n_linear_iterations += num_its_and_final_tol.first;
 
  const bool converged = checkLinearConvergence();
 
  return converged;
}
 
bool
ExplicitTimeIntegrator::checkLinearConvergence()
{
  auto reason = _linear_solver->get_converged_reason();
 
  switch (reason)
  {
    case CONVERGED_RTOL_NORMAL:
    case CONVERGED_ATOL_NORMAL:
    case CONVERGED_RTOL:
    case CONVERGED_ATOL:
    case CONVERGED_ITS:
    case CONVERGED_CG_NEG_CURVE:
    case CONVERGED_CG_CONSTRAINED:
    case CONVERGED_STEP_LENGTH:
    case CONVERGED_HAPPY_BREAKDOWN:
      return true;
    case DIVERGED_NULL:
    case DIVERGED_ITS:
    case DIVERGED_DTOL:
    case DIVERGED_BREAKDOWN:
    case DIVERGED_BREAKDOWN_BICG:
    case DIVERGED_NONSYMMETRIC:
    case DIVERGED_INDEFINITE_PC:
    case DIVERGED_NAN:
    case DIVERGED_INDEFINITE_MAT:
    case CONVERGED_ITERATING:
    case DIVERGED_PCSETUP_FAILED:
      return false;
    default:
      mooseError("Unknown convergence reason in ExplicitTimeIntegrator.");
  }
}