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opm-simulators/opm/simulators/flow/BlackoilModelNldd.hpp
Atgeirr Flø Rasmussen 8e60fecb85 Add missing convergence metrics to domain convergence report.
2024-03-08 10:37:20 +01:00

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/*
Copyright 2013, 2015 SINTEF ICT, Applied Mathematics.
Copyright 2014, 2015 Dr. Blatt - HPC-Simulation-Software & Services
Copyright 2014, 2015 Statoil ASA.
Copyright 2015 NTNU
Copyright 2015, 2016, 2017 IRIS AS
This file is part of the Open Porous Media project (OPM).
OPM is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
OPM 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 General Public License for more details.
You should have received a copy of the GNU General Public License
along with OPM. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef OPM_BLACKOILMODEL_NLDD_HEADER_INCLUDED
#define OPM_BLACKOILMODEL_NLDD_HEADER_INCLUDED
#include <dune/common/timer.hh>
#include <opm/grid/common/SubGridPart.hpp>
#include <opm/simulators/aquifers/AquiferGridUtils.hpp>
#include <opm/simulators/flow/countGlobalCells.hpp>
#include <opm/simulators/flow/partitionCells.hpp>
#include <opm/simulators/flow/priVarsPacking.hpp>
#include <opm/simulators/flow/SubDomain.hpp>
#include <opm/simulators/linalg/extractMatrix.hpp>
#if COMPILE_BDA_BRIDGE
#include <opm/simulators/linalg/ISTLSolverBda.hpp>
#else
#include <opm/simulators/linalg/ISTLSolver.hpp>
#endif
#include <opm/simulators/timestepping/ConvergenceReport.hpp>
#include <opm/simulators/timestepping/SimulatorReport.hpp>
#include <opm/simulators/timestepping/SimulatorTimerInterface.hpp>
#include <opm/simulators/utils/ComponentName.hpp>
#include <fmt/format.h>
#include <algorithm>
#include <array>
#include <cassert>
#include <cmath>
#include <cstddef>
#include <filesystem>
#include <fstream>
#include <functional>
#include <iomanip>
#include <ios>
#include <memory>
#include <numeric>
#include <sstream>
#include <string>
#include <type_traits>
#include <utility>
#include <vector>
namespace Opm {
template<class TypeTag> class BlackoilModel;
/// A NLDD implementation for three-phase black oil.
template <class TypeTag>
class BlackoilModelNldd {
public:
using ElementContext = GetPropType<TypeTag, Properties::ElementContext>;
using FluidSystem = GetPropType<TypeTag, Properties::FluidSystem>;
using Grid = GetPropType<TypeTag, Properties::Grid>;
using Indices = GetPropType<TypeTag, Properties::Indices>;
using ModelParameters = BlackoilModelParameters<TypeTag>;
using Scalar = GetPropType<TypeTag, Properties::Scalar>;
using SolutionVector = GetPropType<TypeTag, Properties::SolutionVector>;
using BVector = typename BlackoilModel<TypeTag>::BVector;
using Domain = SubDomain<Grid>;
using ISTLSolverType = ISTLSolver<TypeTag>;
using Mat = typename BlackoilModel<TypeTag>::Mat;
static constexpr int numEq = Indices::numEq;
//! \brief The constructor sets up the subdomains.
//! \param model BlackOil model to solve for
//! \param param param Model parameters
//! \param compNames Names of the solution components
BlackoilModelNldd(BlackoilModel<TypeTag>& model)
: model_(model), rank_(model_.simulator().vanguard().grid().comm().rank())
{
// Create partitions.
const auto& [partition_vector, num_domains] = this->partitionCells();
// Scan through partitioning to get correct size for each.
std::vector<int> sizes(num_domains, 0);
for (const auto& p : partition_vector) {
++sizes[p];
}
// Set up correctly sized vectors of entity seeds and of indices for each partition.
using EntitySeed = typename Grid::template Codim<0>::EntitySeed;
std::vector<std::vector<EntitySeed>> seeds(num_domains);
std::vector<std::vector<int>> partitions(num_domains);
for (int domain = 0; domain < num_domains; ++domain) {
seeds[domain].resize(sizes[domain]);
partitions[domain].resize(sizes[domain]);
}
// Iterate through grid once, setting the seeds of all partitions.
// Note: owned cells only!
const auto& grid = model_.simulator().vanguard().grid();
std::vector<int> count(num_domains, 0);
const auto& gridView = grid.leafGridView();
const auto beg = gridView.template begin<0, Dune::Interior_Partition>();
const auto end = gridView.template end<0, Dune::Interior_Partition>();
int cell = 0;
for (auto it = beg; it != end; ++it, ++cell) {
const int p = partition_vector[cell];
seeds[p][count[p]] = it->seed();
partitions[p][count[p]] = cell;
++count[p];
}
assert(count == sizes);
// Create the domains.
for (int index = 0; index < num_domains; ++index) {
std::vector<bool> interior(partition_vector.size(), false);
for (int ix : partitions[index]) {
interior[ix] = true;
}
Dune::SubGridPart<Grid> view{grid, std::move(seeds[index])};
this->domains_.emplace_back(index,
std::move(partitions[index]),
std::move(interior),
std::move(view));
}
// Set up container for the local system matrices.
domain_matrices_.resize(num_domains);
// Set up container for the local linear solvers.
for (int index = 0; index < num_domains; ++index) {
// TODO: The ISTLSolver constructor will make
// parallel structures appropriate for the full grid
// only. This must be addressed before going parallel.
const auto& eclState = model_.simulator().vanguard().eclState();
FlowLinearSolverParameters loc_param;
loc_param.template init<TypeTag>(eclState.getSimulationConfig().useCPR());
// Override solver type with umfpack if small domain.
// Otherwise hardcode to ILU0
if (domains_[index].cells.size() < 200) {
loc_param.linsolver_ = "umfpack";
} else {
loc_param.linsolver_ = "ilu0";
loc_param.linear_solver_reduction_ = 1e-2;
}
loc_param.linear_solver_print_json_definition_ = false;
const bool force_serial = true;
domain_linsolvers_.emplace_back(model_.simulator(), loc_param, force_serial);
}
assert(int(domains_.size()) == num_domains);
}
//! \brief Called before starting a time step.
void prepareStep()
{
// Setup domain->well mapping.
model_.wellModel().setupDomains(domains_);
}
//! \brief Do one non-linear NLDD iteration.
template <class NonlinearSolverType>
SimulatorReportSingle nonlinearIterationNldd(const int iteration,
const SimulatorTimerInterface& timer,
NonlinearSolverType& nonlinear_solver)
{
// ----------- Set up reports and timer -----------
SimulatorReportSingle report;
Dune::Timer perfTimer;
model_.initialLinearization(report, iteration, nonlinear_solver.minIter(), nonlinear_solver.maxIter(), timer);
if (report.converged) {
return report;
}
// ----------- If not converged, do an NLDD iteration -----------
auto& solution = model_.simulator().model().solution(0);
auto initial_solution = solution;
auto locally_solved = initial_solution;
// ----------- Decide on an ordering for the domains -----------
const auto domain_order = this->getSubdomainOrder();
// ----------- Solve each domain separately -----------
DeferredLogger logger;
std::vector<SimulatorReportSingle> domain_reports(domains_.size());
for (const int domain_index : domain_order) {
const auto& domain = domains_[domain_index];
SimulatorReportSingle local_report;
try {
switch (model_.param().local_solve_approach_) {
case DomainSolveApproach::Jacobi:
solveDomainJacobi(solution, locally_solved, local_report, logger,
iteration, timer, domain);
break;
default:
case DomainSolveApproach::GaussSeidel:
solveDomainGaussSeidel(solution, locally_solved, local_report, logger,
iteration, timer, domain);
break;
}
}
catch (...) {
// Something went wrong during local solves.
local_report.converged = false;
}
// This should have updated the global matrix to be
// dR_i/du_j evaluated at new local solutions for
// i == j, at old solution for i != j.
if (!local_report.converged) {
// TODO: more proper treatment, including in parallel.
logger.debug(fmt::format("Convergence failure in domain {} on rank {}." , domain.index, rank_));
}
domain_reports[domain.index] = local_report;
}
// Communicate and log all messages.
auto global_logger = gatherDeferredLogger(logger, model_.simulator().vanguard().grid().comm());
global_logger.logMessages();
// Accumulate local solve data.
// Putting the counts in a single array to avoid multiple
// comm.sum() calls. Keeping the named vars for readability.
std::array<int, 4> counts{ 0, 0, 0, static_cast<int>(domain_reports.size()) };
int& num_converged = counts[0];
int& num_converged_already = counts[1];
int& num_local_newtons = counts[2];
int& num_domains = counts[3];
{
SimulatorReportSingle rep;
for (const auto& dr : domain_reports) {
if (dr.converged) {
++num_converged;
if (dr.total_newton_iterations == 0) {
++num_converged_already;
}
}
rep += dr;
}
num_local_newtons = rep.total_newton_iterations;
local_reports_accumulated_ += rep;
}
if (model_.param().local_solve_approach_ == DomainSolveApproach::Jacobi) {
solution = locally_solved;
model_.simulator().model().invalidateAndUpdateIntensiveQuantities(/*timeIdx=*/0);
}
#if HAVE_MPI
// Communicate solutions:
// With multiple processes, this process' overlap (i.e. not
// owned) cells' solution values have been modified by local
// solves in the owning processes, and remain unchanged
// here. We must therefore receive the updated solution on the
// overlap cells and update their intensive quantities before
// we move on.
const auto& comm = model_.simulator().vanguard().grid().comm();
if (comm.size() > 1) {
const auto* ccomm = model_.simulator().model().newtonMethod().linearSolver().comm();
// Copy numerical values from primary vars.
ccomm->copyOwnerToAll(solution, solution);
// Copy flags from primary vars.
const std::size_t num = solution.size();
Dune::BlockVector<std::size_t> allmeanings(num);
for (std::size_t ii = 0; ii < num; ++ii) {
allmeanings[ii] = PVUtil::pack(solution[ii]);
}
ccomm->copyOwnerToAll(allmeanings, allmeanings);
for (std::size_t ii = 0; ii < num; ++ii) {
PVUtil::unPack(solution[ii], allmeanings[ii]);
}
// Update intensive quantities for our overlap values.
model_.simulator().model().invalidateAndUpdateIntensiveQuantitiesOverlap(/*timeIdx=*/0);
// Make total counts of domains converged.
comm.sum(counts.data(), counts.size());
}
#endif // HAVE_MPI
const bool is_iorank = this->rank_ == 0;
if (is_iorank) {
OpmLog::debug(fmt::format("Local solves finished. Converged for {}/{} domains. {} domains did no work. {} total local Newton iterations.\n",
num_converged, num_domains, num_converged_already, num_local_newtons));
}
// Finish with a Newton step.
// Note that the "iteration + 100" is a simple way to avoid entering
// "if (iteration == 0)" and similar blocks, and also makes it a little
// easier to spot the iteration residuals in the DBG file. A more sophisticated
// approach can be done later.
auto rep = model_.nonlinearIterationNewton(iteration + 100, timer, nonlinear_solver);
report += rep;
if (rep.converged) {
report.converged = true;
}
return report;
}
/// return the statistics if the nonlinearIteration() method failed
const SimulatorReportSingle& localAccumulatedReports() const
{
return local_reports_accumulated_;
}
void writePartitions(const std::filesystem::path& odir) const
{
const auto& elementMapper = this->model_.simulator().model().elementMapper();
const auto& cartMapper = this->model_.simulator().vanguard().cartesianIndexMapper();
const auto& grid = this->model_.simulator().vanguard().grid();
const auto& comm = grid.comm();
const auto nDigit = 1 + static_cast<int>(std::floor(std::log10(comm.size())));
std::ofstream pfile { odir / fmt::format("{1:0>{0}}", nDigit, comm.rank()) };
const auto p = this->reconstitutePartitionVector();
auto i = 0;
for (const auto& cell : elements(grid.leafGridView(), Dune::Partitions::interior)) {
pfile << comm.rank() << ' '
<< cartMapper.cartesianIndex(elementMapper.index(cell)) << ' '
<< p[i++] << '\n';
}
}
private:
//! \brief Solve the equation system for a single domain.
std::pair<SimulatorReportSingle, ConvergenceReport>
solveDomain(const Domain& domain,
const SimulatorTimerInterface& timer,
DeferredLogger& logger,
[[maybe_unused]] const int global_iteration,
const bool initial_assembly_required)
{
auto& modelSimulator = model_.simulator();
SimulatorReportSingle report;
Dune::Timer solveTimer;
solveTimer.start();
Dune::Timer detailTimer;
modelSimulator.model().newtonMethod().setIterationIndex(0);
// When called, if assembly has already been performed
// with the initial values, we only need to check
// for local convergence. Otherwise, we must do a local
// assembly.
int iter = 0;
if (initial_assembly_required) {
detailTimer.start();
modelSimulator.model().newtonMethod().setIterationIndex(iter);
// TODO: we should have a beginIterationLocal function()
// only handling the well model for now
modelSimulator.problem().wellModel().assembleDomain(modelSimulator.model().newtonMethod().numIterations(),
modelSimulator.timeStepSize(),
domain);
// Assemble reservoir locally.
report += this->assembleReservoirDomain(domain);
report.assemble_time += detailTimer.stop();
}
detailTimer.reset();
detailTimer.start();
std::vector<double> resnorms;
auto convreport = this->getDomainConvergence(domain, timer, 0, logger, resnorms);
if (convreport.converged()) {
// TODO: set more info, timing etc.
report.converged = true;
return { report, convreport };
}
// We have already assembled for the first iteration,
// but not done the Schur complement for the wells yet.
detailTimer.reset();
detailTimer.start();
model_.wellModel().linearizeDomain(domain,
modelSimulator.model().linearizer().jacobian(),
modelSimulator.model().linearizer().residual());
const double tt1 = detailTimer.stop();
report.assemble_time += tt1;
report.assemble_time_well += tt1;
// Local Newton loop.
const int max_iter = model_.param().max_local_solve_iterations_;
const auto& grid = modelSimulator.vanguard().grid();
do {
// Solve local linear system.
// Note that x has full size, we expect it to be nonzero only for in-domain cells.
const int nc = grid.size(0);
BVector x(nc);
detailTimer.reset();
detailTimer.start();
this->solveJacobianSystemDomain(domain, x);
model_.wellModel().postSolveDomain(x, domain);
report.linear_solve_time += detailTimer.stop();
report.linear_solve_setup_time += model_.linearSolveSetupTime();
report.total_linear_iterations = model_.linearIterationsLastSolve();
// Update local solution. // TODO: x is still full size, should we optimize it?
detailTimer.reset();
detailTimer.start();
this->updateDomainSolution(domain, x);
report.update_time += detailTimer.stop();
// Assemble well and reservoir.
detailTimer.reset();
detailTimer.start();
++iter;
modelSimulator.model().newtonMethod().setIterationIndex(iter);
// TODO: we should have a beginIterationLocal function()
// only handling the well model for now
// Assemble reservoir locally.
modelSimulator.problem().wellModel().assembleDomain(modelSimulator.model().newtonMethod().numIterations(),
modelSimulator.timeStepSize(),
domain);
report += this->assembleReservoirDomain(domain);
report.assemble_time += detailTimer.stop();
// Check for local convergence.
detailTimer.reset();
detailTimer.start();
convreport = this->getDomainConvergence(domain, timer, iter, logger, resnorms);
// apply the Schur complement of the well model to the
// reservoir linearized equations
detailTimer.reset();
detailTimer.start();
model_.wellModel().linearizeDomain(domain,
modelSimulator.model().linearizer().jacobian(),
modelSimulator.model().linearizer().residual());
const double tt2 = detailTimer.stop();
report.assemble_time += tt2;
report.assemble_time_well += tt2;
} while (!convreport.converged() && iter <= max_iter);
modelSimulator.problem().endIteration();
report.converged = convreport.converged();
report.total_newton_iterations = iter;
report.total_linearizations = iter;
report.total_time = solveTimer.stop();
// TODO: set more info, timing etc.
return { report, convreport };
}
/// Assemble the residual and Jacobian of the nonlinear system.
SimulatorReportSingle assembleReservoirDomain(const Domain& domain)
{
// -------- Mass balance equations --------
model_.simulator().model().linearizer().linearizeDomain(domain);
return model_.wellModel().lastReport();
}
//! \brief Solve the linearized system for a domain.
void solveJacobianSystemDomain(const Domain& domain, BVector& global_x)
{
const auto& modelSimulator = model_.simulator();
Dune::Timer perfTimer;
perfTimer.start();
const Mat& main_matrix = modelSimulator.model().linearizer().jacobian().istlMatrix();
if (domain_matrices_[domain.index]) {
Details::copySubMatrix(main_matrix, domain.cells, *domain_matrices_[domain.index]);
} else {
domain_matrices_[domain.index] = std::make_unique<Mat>(Details::extractMatrix(main_matrix, domain.cells));
}
auto& jac = *domain_matrices_[domain.index];
auto res = Details::extractVector(modelSimulator.model().linearizer().residual(),
domain.cells);
auto x = res;
// set initial guess
global_x = 0.0;
x = 0.0;
auto& linsolver = domain_linsolvers_[domain.index];
linsolver.prepare(jac, res);
model_.linearSolveSetupTime() = perfTimer.stop();
linsolver.setResidual(res);
linsolver.solve(x);
Details::setGlobal(x, domain.cells, global_x);
}
/// Apply an update to the primary variables.
void updateDomainSolution(const Domain& domain, const BVector& dx)
{
auto& simulator = model_.simulator();
auto& newtonMethod = simulator.model().newtonMethod();
SolutionVector& solution = simulator.model().solution(/*timeIdx=*/0);
newtonMethod.update_(/*nextSolution=*/solution,
/*curSolution=*/solution,
/*update=*/dx,
/*resid=*/dx,
domain.cells); // the update routines of the black
// oil model do not care about the
// residual
// if the solution is updated, the intensive quantities need to be recalculated
simulator.model().invalidateAndUpdateIntensiveQuantities(/*timeIdx=*/0, domain);
}
//! \brief Get reservoir quantities on this process needed for convergence calculations.
std::pair<double, double> localDomainConvergenceData(const Domain& domain,
std::vector<Scalar>& R_sum,
std::vector<Scalar>& maxCoeff,
std::vector<Scalar>& B_avg,
std::vector<int>& maxCoeffCell)
{
const auto& modelSimulator = model_.simulator();
double pvSumLocal = 0.0;
double numAquiferPvSumLocal = 0.0;
const auto& model = modelSimulator.model();
const auto& problem = modelSimulator.problem();
const auto& modelResid = modelSimulator.model().linearizer().residual();
ElementContext elemCtx(modelSimulator);
const auto& gridView = domain.view;
const auto& elemEndIt = gridView.template end</*codim=*/0>();
IsNumericalAquiferCell isNumericalAquiferCell(gridView.grid());
for (auto elemIt = gridView.template begin</*codim=*/0>();
elemIt != elemEndIt;
++elemIt)
{
if (elemIt->partitionType() != Dune::InteriorEntity) {
continue;
}
const auto& elem = *elemIt;
elemCtx.updatePrimaryStencil(elem);
elemCtx.updatePrimaryIntensiveQuantities(/*timeIdx=*/0);
const unsigned cell_idx = elemCtx.globalSpaceIndex(/*spaceIdx=*/0, /*timeIdx=*/0);
const auto& intQuants = elemCtx.intensiveQuantities(/*spaceIdx=*/0, /*timeIdx=*/0);
const auto& fs = intQuants.fluidState();
const auto pvValue = problem.referencePorosity(cell_idx, /*timeIdx=*/0) *
model.dofTotalVolume(cell_idx);
pvSumLocal += pvValue;
if (isNumericalAquiferCell(elem))
{
numAquiferPvSumLocal += pvValue;
}
model_.getMaxCoeff(cell_idx, intQuants, fs, modelResid, pvValue,
B_avg, R_sum, maxCoeff, maxCoeffCell);
}
// compute local average in terms of global number of elements
const int bSize = B_avg.size();
for ( int i = 0; i<bSize; ++i )
{
B_avg[ i ] /= Scalar(domain.cells.size());
}
return {pvSumLocal, numAquiferPvSumLocal};
}
ConvergenceReport getDomainReservoirConvergence(const double reportTime,
const double dt,
const int iteration,
const Domain& domain,
DeferredLogger& logger,
std::vector<Scalar>& B_avg,
std::vector<Scalar>& residual_norms)
{
using Vector = std::vector<Scalar>;
const int numComp = numEq;
Vector R_sum(numComp, 0.0 );
Vector maxCoeff(numComp, std::numeric_limits<Scalar>::lowest() );
std::vector<int> maxCoeffCell(numComp, -1);
const auto [ pvSum, numAquiferPvSum]
= this->localDomainConvergenceData(domain, R_sum, maxCoeff, B_avg, maxCoeffCell);
auto cnvErrorPvFraction = computeCnvErrorPvLocal(domain, B_avg, dt);
cnvErrorPvFraction /= (pvSum - numAquiferPvSum);
// Default value of relaxed_max_pv_fraction_ is 0.03 and min_strict_cnv_iter_ is 0.
// For each iteration, we need to determine whether to use the relaxed CNV tolerance.
// To disable the usage of relaxed CNV tolerance, you can set the relaxed_max_pv_fraction_ to be 0.
const bool use_relaxed_cnv = cnvErrorPvFraction < model_.param().relaxed_max_pv_fraction_ &&
iteration >= model_.param().min_strict_cnv_iter_;
// Tighter bound for local convergence should increase the
// likelyhood of: local convergence => global convergence
const double tol_cnv = model_.param().local_tolerance_scaling_cnv_
* (use_relaxed_cnv ? model_.param().tolerance_cnv_relaxed_
: model_.param().tolerance_cnv_);
const bool use_relaxed_mb = iteration >= model_.param().min_strict_mb_iter_;
const double tol_mb = model_.param().local_tolerance_scaling_mb_
* (use_relaxed_mb ? model_.param().tolerance_mb_relaxed_ : model_.param().tolerance_mb_);
// Finish computation
std::vector<Scalar> CNV(numComp);
std::vector<Scalar> mass_balance_residual(numComp);
for (int compIdx = 0; compIdx < numComp; ++compIdx )
{
CNV[compIdx] = B_avg[compIdx] * dt * maxCoeff[compIdx];
mass_balance_residual[compIdx] = std::abs(B_avg[compIdx]*R_sum[compIdx]) * dt / pvSum;
residual_norms.push_back(CNV[compIdx]);
}
// Create convergence report.
ConvergenceReport report{reportTime};
using CR = ConvergenceReport;
for (int compIdx = 0; compIdx < numComp; ++compIdx) {
double res[2] = { mass_balance_residual[compIdx], CNV[compIdx] };
CR::ReservoirFailure::Type types[2] = { CR::ReservoirFailure::Type::MassBalance,
CR::ReservoirFailure::Type::Cnv };
double tol[2] = { tol_mb, tol_cnv };
for (int ii : {0, 1}) {
if (std::isnan(res[ii])) {
report.setReservoirFailed({types[ii], CR::Severity::NotANumber, compIdx});
logger.debug("NaN residual for " + model_.compNames().name(compIdx) + " equation.");
} else if (res[ii] > model_.param().max_residual_allowed_) {
report.setReservoirFailed({types[ii], CR::Severity::TooLarge, compIdx});
logger.debug("Too large residual for " + model_.compNames().name(compIdx) + " equation.");
} else if (res[ii] < 0.0) {
report.setReservoirFailed({types[ii], CR::Severity::Normal, compIdx});
logger.debug("Negative residual for " + model_.compNames().name(compIdx) + " equation.");
} else if (res[ii] > tol[ii]) {
report.setReservoirFailed({types[ii], CR::Severity::Normal, compIdx});
}
report.setReservoirConvergenceMetric(types[ii], compIdx, res[ii]);
}
}
// Output of residuals. If converged at initial state, log nothing.
const bool converged_at_initial_state = (report.converged() && iteration == 0);
if (!converged_at_initial_state) {
if (iteration == 0) {
// Log header.
std::string msg = fmt::format("Domain {} on rank {}, size {}, containing cell {}\n| Iter",
domain.index, this->rank_, domain.cells.size(), domain.cells[0]);
for (int compIdx = 0; compIdx < numComp; ++compIdx) {
msg += " MB(";
msg += model_.compNames().name(compIdx)[0];
msg += ") ";
}
for (int compIdx = 0; compIdx < numComp; ++compIdx) {
msg += " CNV(";
msg += model_.compNames().name(compIdx)[0];
msg += ") ";
}
logger.debug(msg);
}
// Log convergence data.
std::ostringstream ss;
ss << "| ";
const std::streamsize oprec = ss.precision(3);
const std::ios::fmtflags oflags = ss.setf(std::ios::scientific);
ss << std::setw(4) << iteration;
for (int compIdx = 0; compIdx < numComp; ++compIdx) {
ss << std::setw(11) << mass_balance_residual[compIdx];
}
for (int compIdx = 0; compIdx < numComp; ++compIdx) {
ss << std::setw(11) << CNV[compIdx];
}
ss.precision(oprec);
ss.flags(oflags);
logger.debug(ss.str());
}
return report;
}
ConvergenceReport getDomainConvergence(const Domain& domain,
const SimulatorTimerInterface& timer,
const int iteration,
DeferredLogger& logger,
std::vector<double>& residual_norms)
{
std::vector<Scalar> B_avg(numEq, 0.0);
auto report = this->getDomainReservoirConvergence(timer.simulationTimeElapsed(),
timer.currentStepLength(),
iteration,
domain,
logger,
B_avg,
residual_norms);
report += model_.wellModel().getDomainWellConvergence(domain, B_avg, logger);
return report;
}
//! \brief Returns subdomain ordered according to method and ordering measure.
std::vector<int> getSubdomainOrder()
{
const auto& modelSimulator = model_.simulator();
const auto& solution = modelSimulator.model().solution(0);
std::vector<int> domain_order(domains_.size());
std::iota(domain_order.begin(), domain_order.end(), 0);
if (model_.param().local_solve_approach_ == DomainSolveApproach::Jacobi) {
// Do nothing, 0..n-1 order is fine.
return domain_order;
} else if (model_.param().local_solve_approach_ == DomainSolveApproach::GaussSeidel) {
// Calculate the measure used to order the domains.
std::vector<double> measure_per_domain(domains_.size());
switch (model_.param().local_domain_ordering_) {
case DomainOrderingMeasure::AveragePressure: {
// Use average pressures to order domains.
for (const auto& domain : domains_) {
double press_sum = 0.0;
for (const int c : domain.cells) {
press_sum += solution[c][Indices::pressureSwitchIdx];
}
const double avgpress = press_sum / domain.cells.size();
measure_per_domain[domain.index] = avgpress;
}
break;
}
case DomainOrderingMeasure::MaxPressure: {
// Use max pressures to order domains.
for (const auto& domain : domains_) {
double maxpress = 0.0;
for (const int c : domain.cells) {
maxpress = std::max(maxpress, solution[c][Indices::pressureSwitchIdx]);
}
measure_per_domain[domain.index] = maxpress;
}
break;
}
case DomainOrderingMeasure::Residual: {
// Use maximum residual to order domains.
const auto& residual = modelSimulator.model().linearizer().residual();
const int num_vars = residual[0].size();
for (const auto& domain : domains_) {
double maxres = 0.0;
for (const int c : domain.cells) {
for (int ii = 0; ii < num_vars; ++ii) {
maxres = std::max(maxres, std::fabs(residual[c][ii]));
}
}
measure_per_domain[domain.index] = maxres;
}
break;
}
} // end of switch (model_.param().local_domain_ordering_)
// Sort by largest measure, keeping index order if equal.
const auto& m = measure_per_domain;
std::stable_sort(domain_order.begin(), domain_order.end(),
[&m](const int i1, const int i2){ return m[i1] > m[i2]; });
return domain_order;
} else {
throw std::logic_error("Domain solve approach must be Jacobi or Gauss-Seidel");
}
}
template<class GlobalEqVector>
void solveDomainJacobi(GlobalEqVector& solution,
GlobalEqVector& locally_solved,
SimulatorReportSingle& local_report,
DeferredLogger& logger,
const int iteration,
const SimulatorTimerInterface& timer,
const Domain& domain)
{
auto initial_local_well_primary_vars = model_.wellModel().getPrimaryVarsDomain(domain);
auto initial_local_solution = Details::extractVector(solution, domain.cells);
auto res = solveDomain(domain, timer, logger, iteration, false);
local_report = res.first;
if (local_report.converged) {
auto local_solution = Details::extractVector(solution, domain.cells);
Details::setGlobal(local_solution, domain.cells, locally_solved);
Details::setGlobal(initial_local_solution, domain.cells, solution);
model_.simulator().model().invalidateAndUpdateIntensiveQuantities(/*timeIdx=*/0, domain);
} else {
model_.wellModel().setPrimaryVarsDomain(domain, initial_local_well_primary_vars);
Details::setGlobal(initial_local_solution, domain.cells, solution);
model_.simulator().model().invalidateAndUpdateIntensiveQuantities(/*timeIdx=*/0, domain);
}
}
template<class GlobalEqVector>
void solveDomainGaussSeidel(GlobalEqVector& solution,
GlobalEqVector& locally_solved,
SimulatorReportSingle& local_report,
DeferredLogger& logger,
const int iteration,
const SimulatorTimerInterface& timer,
const Domain& domain)
{
auto initial_local_well_primary_vars = model_.wellModel().getPrimaryVarsDomain(domain);
auto initial_local_solution = Details::extractVector(solution, domain.cells);
auto res = solveDomain(domain, timer, logger, iteration, true);
local_report = res.first;
if (!local_report.converged) {
// We look at the detailed convergence report to evaluate
// if we should accept the unconverged solution.
const auto& convrep = res.second;
// We do not accept a solution if the wells are unconverged.
if (!convrep.wellFailed()) {
// Calculare the sums of the mb and cnv failures.
double mb_sum = 0.0;
double cnv_sum = 0.0;
for (const auto& rc : convrep.reservoirConvergence()) {
if (rc.type() == ConvergenceReport::ReservoirFailure::Type::MassBalance) {
mb_sum += rc.value();
} else if (rc.type() == ConvergenceReport::ReservoirFailure::Type::Cnv) {
cnv_sum += rc.value();
}
}
// If not too high, we overrule the convergence failure.
const double acceptable_local_mb_sum = 1e-3;
const double acceptable_local_cnv_sum = 1.0;
if (mb_sum < acceptable_local_mb_sum && cnv_sum < acceptable_local_cnv_sum) {
local_report.converged = true;
logger.debug(fmt::format("Accepting solution in unconverged domain {} on rank {}.", domain.index, rank_));
logger.debug(fmt::format("Value of mb_sum: {} cnv_sum: {}", mb_sum, cnv_sum));
} else {
logger.debug("Unconverged local solution.");
}
} else {
logger.debug("Unconverged local solution with well convergence failures:");
for (const auto& wf : convrep.wellFailures()) {
logger.debug(to_string(wf));
}
}
}
if (local_report.converged) {
auto local_solution = Details::extractVector(solution, domain.cells);
Details::setGlobal(local_solution, domain.cells, locally_solved);
} else {
model_.wellModel().setPrimaryVarsDomain(domain, initial_local_well_primary_vars);
Details::setGlobal(initial_local_solution, domain.cells, solution);
model_.simulator().model().invalidateAndUpdateIntensiveQuantities(/*timeIdx=*/0, domain);
}
}
double computeCnvErrorPvLocal(const Domain& domain,
const std::vector<Scalar>& B_avg, double dt) const
{
double errorPV{};
const auto& simulator = model_.simulator();
const auto& model = simulator.model();
const auto& problem = simulator.problem();
const auto& residual = simulator.model().linearizer().residual();
for (const int cell_idx : domain.cells) {
const double pvValue = problem.referencePorosity(cell_idx, /*timeIdx=*/0) *
model.dofTotalVolume(cell_idx);
const auto& cellResidual = residual[cell_idx];
bool cnvViolated = false;
for (unsigned eqIdx = 0; eqIdx < cellResidual.size(); ++eqIdx) {
using std::fabs;
Scalar CNV = cellResidual[eqIdx] * dt * B_avg[eqIdx] / pvValue;
cnvViolated = cnvViolated || (fabs(CNV) > model_.param().tolerance_cnv_);
}
if (cnvViolated) {
errorPV += pvValue;
}
}
return errorPV;
}
decltype(auto) partitionCells() const
{
const auto& grid = this->model_.simulator().vanguard().grid();
using GridView = std::remove_cv_t<std::remove_reference_t<decltype(grid.leafGridView())>>;
using Element = std::remove_cv_t<std::remove_reference_t<typename GridView::template Codim<0>::Entity>>;
const auto& param = this->model_.param();
auto zoltan_ctrl = ZoltanPartitioningControl<Element>{};
zoltan_ctrl.domain_imbalance = param.local_domain_partition_imbalance_;
zoltan_ctrl.index =
[elementMapper = &this->model_.simulator().model().elementMapper()]
(const Element& element)
{
return elementMapper->index(element);
};
zoltan_ctrl.local_to_global =
[cartMapper = &this->model_.simulator().vanguard().cartesianIndexMapper()]
(const int elemIdx)
{
return cartMapper->cartesianIndex(elemIdx);
};
// Forming the list of wells is expensive, so do this only if needed.
const auto need_wells = param.local_domain_partition_method_ == "zoltan";
const auto wells = need_wells
? this->model_.simulator().vanguard().schedule().getWellsatEnd()
: std::vector<Well>{};
// If defaulted parameter for number of domains, choose a reasonable default.
constexpr int default_cells_per_domain = 1000;
const int num_cells = Opm::detail::countGlobalCells(grid);
const int num_domains = param.num_local_domains_ > 0
? param.num_local_domains_
: num_cells / default_cells_per_domain;
return ::Opm::partitionCells(param.local_domain_partition_method_,
num_domains,
grid.leafGridView(), wells, zoltan_ctrl);
}
std::vector<int> reconstitutePartitionVector() const
{
const auto& grid = this->model_.simulator().vanguard().grid();
auto numD = std::vector<int>(grid.comm().size() + 1, 0);
numD[grid.comm().rank() + 1] = static_cast<int>(this->domains_.size());
grid.comm().sum(numD.data(), numD.size());
std::partial_sum(numD.begin(), numD.end(), numD.begin());
auto p = std::vector<int>(grid.size(0));
auto maxCellIdx = std::numeric_limits<int>::min();
auto d = numD[grid.comm().rank()];
for (const auto& domain : this->domains_) {
for (const auto& cell : domain.cells) {
p[cell] = d;
if (cell > maxCellIdx) {
maxCellIdx = cell;
}
}
++d;
}
p.erase(p.begin() + maxCellIdx + 1, p.end());
return p;
}
BlackoilModel<TypeTag>& model_; //!< Reference to model
std::vector<Domain> domains_; //!< Vector of subdomains
std::vector<std::unique_ptr<Mat>> domain_matrices_; //!< Vector of matrix operator for each subdomain
std::vector<ISTLSolverType> domain_linsolvers_; //!< Vector of linear solvers for each domain
SimulatorReportSingle local_reports_accumulated_; //!< Accumulated convergence report for subdomain solvers
int rank_ = 0; //!< MPI rank of this process
};
} // namespace Opm
#endif // OPM_BLACKOILMODEL_NLDD_HEADER_INCLUDED
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