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AdaptiveTimeStepping_impl.hpp
/*
Copyright 2024 Equinor ASA.
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_ADAPTIVE_TIME_STEPPING_IMPL_HPP
#define OPM_ADAPTIVE_TIME_STEPPING_IMPL_HPP
// Improve IDE experience
#ifndef OPM_ADAPTIVE_TIME_STEPPING_HPP
#include <config.h>
#include <opm/simulators/timestepping/AdaptiveTimeStepping.hpp>
#include <opm/simulators/timestepping/AdaptiveSimulatorTimer.hpp>
#endif
#include <dune/istl/istlexception.hh>
#include <opm/common/Exceptions.hpp>
#include <opm/common/ErrorMacros.hpp>
#include <opm/common/OpmLog/OpmLog.hpp>
#include <opm/grid/utility/StopWatch.hpp>
#include <opm/input/eclipse/Schedule/Tuning.hpp>
#include <opm/input/eclipse/Units/Units.hpp>
#include <opm/input/eclipse/Units/UnitSystem.hpp>
#include <opm/models/utils/parametersystem.hpp>
#include <opm/simulators/timestepping/EclTimeSteppingParams.hpp>
#include <algorithm>
#include <cassert>
#include <cmath>
#include <sstream>
#include <stdexcept>
#include <boost/date_time/posix_time/posix_time.hpp>
#include <fmt/format.h>
#include <fmt/ranges.h>
namespace Opm {
/*********************************************
* Public methods of AdaptiveTimeStepping
* ******************************************/
template<class TypeTag>
AdaptiveTimeStepping<TypeTag>::
AdaptiveTimeStepping(const UnitSystem& unit_system,
const SimulatorReport& report,
const double max_next_tstep,
const bool terminal_output
)
: time_step_control_{}
, restart_factor_{Parameters::Get<Parameters::SolverRestartFactor<Scalar>>()} // 0.33
, growth_factor_{Parameters::Get<Parameters::SolverGrowthFactor<Scalar>>()} // 2.0
, max_growth_{Parameters::Get<Parameters::SolverMaxGrowth<Scalar>>()} // 3.0
, max_time_step_{
Parameters::Get<Parameters::SolverMaxTimeStepInDays<Scalar>>() * 24 * 60 * 60} // 365.25
, min_time_step_{
unit_system.to_si(UnitSystem::measure::time,
Parameters::Get<Parameters::SolverMinTimeStep<Scalar>>())} // 1e-12;
, ignore_convergence_failure_{
Parameters::Get<Parameters::SolverContinueOnConvergenceFailure>()} // false;
, solver_restart_max_{Parameters::Get<Parameters::SolverMaxRestarts>()} // 10
, solver_verbose_{Parameters::Get<Parameters::SolverVerbosity>() > 0 && terminal_output} // 2
, timestep_verbose_{Parameters::Get<Parameters::TimeStepVerbosity>() > 0 && terminal_output} // 2
, suggested_next_timestep_{
(max_next_tstep <= 0 ? Parameters::Get<Parameters::InitialTimeStepInDays>()
: max_next_tstep) * 24 * 60 * 60} // 1.0
, full_timestep_initially_{Parameters::Get<Parameters::FullTimeStepInitially>()} // false
, timestep_after_event_{
Parameters::Get<Parameters::TimeStepAfterEventInDays<Scalar>>() * 24 * 60 * 60} // 1e30
, use_newton_iteration_{false}
, min_time_step_before_shutting_problematic_wells_{
Parameters::Get<Parameters::MinTimeStepBeforeShuttingProblematicWellsInDays>() * unit::day}
, report_(report)
{
init_(unit_system);
}
template<class TypeTag>
AdaptiveTimeStepping<TypeTag>::
AdaptiveTimeStepping(double max_next_tstep,
const Tuning& tuning,
const UnitSystem& unit_system,
const SimulatorReport& report,
const bool terminal_output
)
: time_step_control_{}
, restart_factor_{tuning.TSFCNV}
, growth_factor_{tuning.TFDIFF}
, max_growth_{tuning.TSFMAX}
, max_time_step_{tuning.TSMAXZ} // 365.25
, min_time_step_{tuning.TSMINZ} // 0.1;
, ignore_convergence_failure_{true}
, solver_restart_max_{Parameters::Get<Parameters::SolverMaxRestarts>()} // 10
, solver_verbose_{Parameters::Get<Parameters::SolverVerbosity>() > 0 && terminal_output} // 2
, timestep_verbose_{Parameters::Get<Parameters::TimeStepVerbosity>() > 0 && terminal_output} // 2
, suggested_next_timestep_{
max_next_tstep <= 0 ? Parameters::Get<Parameters::InitialTimeStepInDays>() * 24 * 60 * 60
: max_next_tstep} // 1.0
, full_timestep_initially_{Parameters::Get<Parameters::FullTimeStepInitially>()} // false
, timestep_after_event_{tuning.TMAXWC} // 1e30
, use_newton_iteration_{false}
, min_time_step_before_shutting_problematic_wells_{
Parameters::Get<Parameters::MinTimeStepBeforeShuttingProblematicWellsInDays>() * unit::day}
, report_(report)
{
init_(unit_system);
}
template<class TypeTag>
bool
AdaptiveTimeStepping<TypeTag>::
operator==(const AdaptiveTimeStepping<TypeTag>& rhs)
{
if (this->time_step_control_type_ != rhs.time_step_control_type_ ||
(this->time_step_control_ && !rhs.time_step_control_) ||
(!this->time_step_control_ && rhs.time_step_control_)) {
return false;
}
bool result = false;
switch (this->time_step_control_type_) {
case TimeStepControlType::HardCodedTimeStep:
result = castAndComp<HardcodedTimeStepControl>(rhs);
break;
case TimeStepControlType::PIDAndIterationCount:
result = castAndComp<PIDAndIterationCountTimeStepControl>(rhs);
break;
case TimeStepControlType::SimpleIterationCount:
result = castAndComp<SimpleIterationCountTimeStepControl>(rhs);
break;
case TimeStepControlType::PID:
result = castAndComp<PIDTimeStepControl>(rhs);
break;
case TimeStepControlType::General3rdOrder:
result = castAndComp<General3rdOrderController>(rhs);
break;
}
return result &&
this->restart_factor_ == rhs.restart_factor_ &&
this->growth_factor_ == rhs.growth_factor_ &&
this->max_growth_ == rhs.max_growth_ &&
this->max_time_step_ == rhs.max_time_step_ &&
this->min_time_step_ == rhs.min_time_step_ &&
this->ignore_convergence_failure_ == rhs.ignore_convergence_failure_ &&
this->solver_restart_max_== rhs.solver_restart_max_ &&
this->solver_verbose_ == rhs.solver_verbose_ &&
this->full_timestep_initially_ == rhs.full_timestep_initially_ &&
this->timestep_after_event_ == rhs.timestep_after_event_ &&
this->use_newton_iteration_ == rhs.use_newton_iteration_ &&
this->min_time_step_before_shutting_problematic_wells_ ==
rhs.min_time_step_before_shutting_problematic_wells_;
}
template<class TypeTag>
void
AdaptiveTimeStepping<TypeTag>::
registerParameters()
{
registerEclTimeSteppingParameters<Scalar>();
detail::registerAdaptiveParameters();
}
template<class TypeTag>
template <class Solver>
SimulatorReport
AdaptiveTimeStepping<TypeTag>::
step(const SimulatorTimer& simulator_timer,
Solver& solver,
const bool is_event,
const TuningUpdateCallback& tuning_updater)
{
SubStepper<Solver> sub_stepper{
*this, simulator_timer, solver, is_event, tuning_updater,
};
return sub_stepper.run();
}
template<class TypeTag>
template<class Serializer>
void
AdaptiveTimeStepping<TypeTag>::
serializeOp(Serializer& serializer)
{
serializer(this->time_step_control_type_);
switch (this->time_step_control_type_) {
case TimeStepControlType::HardCodedTimeStep:
allocAndSerialize<HardcodedTimeStepControl>(serializer);
break;
case TimeStepControlType::PIDAndIterationCount:
allocAndSerialize<PIDAndIterationCountTimeStepControl>(serializer);
break;
case TimeStepControlType::SimpleIterationCount:
allocAndSerialize<SimpleIterationCountTimeStepControl>(serializer);
break;
case TimeStepControlType::PID:
allocAndSerialize<PIDTimeStepControl>(serializer);
break;
case TimeStepControlType::General3rdOrder:
allocAndSerialize<General3rdOrderController>(serializer);
break;
}
serializer(this->restart_factor_);
serializer(this->growth_factor_);
serializer(this->max_growth_);
serializer(this->max_time_step_);
serializer(this->min_time_step_);
serializer(this->ignore_convergence_failure_);
serializer(this->solver_restart_max_);
serializer(this->solver_verbose_);
serializer(this->timestep_verbose_);
serializer(this->suggested_next_timestep_);
serializer(this->full_timestep_initially_);
serializer(this->timestep_after_event_);
serializer(this->use_newton_iteration_);
serializer(this->min_time_step_before_shutting_problematic_wells_);
}
template<class TypeTag>
SimulatorReport&
AdaptiveTimeStepping<TypeTag>::
report()
{
return report_;
}
template<class TypeTag>
AdaptiveTimeStepping<TypeTag>
AdaptiveTimeStepping<TypeTag>::
serializationTestObjectHardcoded()
{
return serializationTestObject_<HardcodedTimeStepControl>();
}
template<class TypeTag>
AdaptiveTimeStepping<TypeTag>
AdaptiveTimeStepping<TypeTag>::
serializationTestObjectPID()
{
return serializationTestObject_<PIDTimeStepControl>();
}
template<class TypeTag>
AdaptiveTimeStepping<TypeTag>
AdaptiveTimeStepping<TypeTag>::
serializationTestObjectPIDIt()
{
return serializationTestObject_<PIDAndIterationCountTimeStepControl>();
}
template<class TypeTag>
AdaptiveTimeStepping<TypeTag>
AdaptiveTimeStepping<TypeTag>::
serializationTestObjectSimple()
{
return serializationTestObject_<SimpleIterationCountTimeStepControl>();
}
template<class TypeTag>
AdaptiveTimeStepping<TypeTag>
AdaptiveTimeStepping<TypeTag>::
serializationTestObject3rdOrder()
{
return serializationTestObject_<General3rdOrderController>();
}
template<class TypeTag>
void
AdaptiveTimeStepping<TypeTag>::
setSuggestedNextStep(const double x)
{
this->suggested_next_timestep_ = x;
}
template<class TypeTag>
double
AdaptiveTimeStepping<TypeTag>::
suggestedNextStep() const
{
return this->suggested_next_timestep_;
}
template<class TypeTag>
const TimeStepControlInterface&
AdaptiveTimeStepping<TypeTag>::
timeStepControl() const
{
return *this->time_step_control_;
}
template<class TypeTag>
void
AdaptiveTimeStepping<TypeTag>::
updateNEXTSTEP(double max_next_tstep)
{
// \Note Only update next suggested step if TSINIT was explicitly
// set in TUNING or NEXTSTEP is active.
if (max_next_tstep > 0) {
this->suggested_next_timestep_ = max_next_tstep;
}
}
template<class TypeTag>
void
AdaptiveTimeStepping<TypeTag>::
updateTUNING(double max_next_tstep, const Tuning& tuning)
{
this->restart_factor_ = tuning.TSFCNV;
this->growth_factor_ = tuning.TFDIFF;
this->max_growth_ = tuning.TSFMAX;
this->max_time_step_ = tuning.TSMAXZ;
updateNEXTSTEP(max_next_tstep);
this->timestep_after_event_ = tuning.TMAXWC;
}
/*********************************************
* Private methods of AdaptiveTimeStepping
* ******************************************/
template<class TypeTag>
template<class T, class Serializer>
void
AdaptiveTimeStepping<TypeTag>::
allocAndSerialize(Serializer& serializer)
{
if (!serializer.isSerializing()) {
this->time_step_control_ = std::make_unique<T>();
}
serializer(*static_cast<T*>(this->time_step_control_.get()));
}
template<class TypeTag>
template<class T>
bool
AdaptiveTimeStepping<TypeTag>::
castAndComp(const AdaptiveTimeStepping<TypeTag>& Rhs) const
{
const T* lhs = static_cast<const T*>(this->time_step_control_.get());
const T* rhs = static_cast<const T*>(Rhs.time_step_control_.get());
return *lhs == *rhs;
}
template<class TypeTag>
void
AdaptiveTimeStepping<TypeTag>::
maybeModifySuggestedTimeStepAtBeginningOfReportStep_(const double original_time_step,
bool is_event)
{
// init last time step as a fraction of the given time step
if (this->suggested_next_timestep_ < 0) {
this->suggested_next_timestep_ = this->restart_factor_ * original_time_step;
}
if (this->full_timestep_initially_) {
this->suggested_next_timestep_ = original_time_step;
}
// use seperate time step after event
if (is_event && this->timestep_after_event_ > 0) {
this->suggested_next_timestep_ = this->timestep_after_event_;
}
}
template<class TypeTag>
template<class Controller>
AdaptiveTimeStepping<TypeTag>
AdaptiveTimeStepping<TypeTag>::
serializationTestObject_()
{
AdaptiveTimeStepping<TypeTag> result;
result.restart_factor_ = 1.0;
result.growth_factor_ = 2.0;
result.max_growth_ = 3.0;
result.max_time_step_ = 4.0;
result.min_time_step_ = 5.0;
result.ignore_convergence_failure_ = true;
result.solver_restart_max_ = 6;
result.solver_verbose_ = true;
result.timestep_verbose_ = true;
result.suggested_next_timestep_ = 7.0;
result.full_timestep_initially_ = true;
result.use_newton_iteration_ = true;
result.min_time_step_before_shutting_problematic_wells_ = 9.0;
result.time_step_control_type_ = Controller::Type;
result.time_step_control_ =
std::make_unique<Controller>(Controller::serializationTestObject());
return result;
}
/*********************************************
* Protected methods of AdaptiveTimeStepping
* ******************************************/
template<class TypeTag>
void AdaptiveTimeStepping<TypeTag>::
init_(const UnitSystem& unitSystem)
{
std::tie(time_step_control_type_,
time_step_control_,
use_newton_iteration_) = detail::createController(unitSystem);
// make sure growth factor is something reasonable
if (this->growth_factor_ < 1.0) {
OPM_THROW(std::runtime_error,
"Growth factor cannot be less than 1.");
}
}
/************************************************
* Private class SubStepper public methods
************************************************/
template<class TypeTag>
template<class Solver>
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
SubStepper(AdaptiveTimeStepping<TypeTag>& adaptive_time_stepping,
const SimulatorTimer& simulator_timer,
Solver& solver,
const bool is_event,
const TuningUpdateCallback& tuning_updater)
: adaptive_time_stepping_{adaptive_time_stepping}
, simulator_timer_{simulator_timer}
, solver_{solver}
, is_event_{is_event}
, tuning_updater_{tuning_updater}
{
}
template<class TypeTag>
template<class Solver>
AdaptiveTimeStepping<TypeTag>&
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
getAdaptiveTimerStepper()
{
return adaptive_time_stepping_;
}
template<class TypeTag>
template<class Solver>
SimulatorReport
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
run()
{
#ifdef RESERVOIR_COUPLING_ENABLED
if (isReservoirCouplingSlave_() && reservoirCouplingSlave_().activated()) {
return runStepReservoirCouplingSlave_();
}
else if (isReservoirCouplingMaster_() && reservoirCouplingMaster_().activated()) {
return runStepReservoirCouplingMaster_();
}
else {
return runStepOriginal_();
}
#else
return runStepOriginal_();
#endif
}
/************************************************
* Private class SubStepper private methods
************************************************/
#ifdef RESERVOIR_COUPLING_ENABLED
template<class TypeTag>
template<class Solver>
bool
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
isReservoirCouplingMaster_() const
{
return this->solver_.model().simulator().reservoirCouplingMaster() != nullptr;
}
template<class TypeTag>
template<class Solver>
bool
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
isReservoirCouplingSlave_() const
{
return this->solver_.model().simulator().reservoirCouplingSlave() != nullptr;
}
#endif
template<class TypeTag>
template<class Solver>
void
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
maybeModifySuggestedTimeStepAtBeginningOfReportStep_(const double original_time_step)
{
this->adaptive_time_stepping_.maybeModifySuggestedTimeStepAtBeginningOfReportStep_(
original_time_step, this->is_event_
);
}
// The maybeUpdateTuning_() lambda callback is defined in SimulatorFullyImplicitBlackoil::runStep()
// It has to be called for each substep since TUNING might have been changed for next sub step due
// to ACTIONX (via NEXTSTEP) or WCYCLE keywords.
template<class TypeTag>
template<class Solver>
bool
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
maybeUpdateTuning_(double elapsed, double dt, int sub_step_number) const
{
return this->tuning_updater_(elapsed, dt, sub_step_number);
}
template<class TypeTag>
template<class Solver>
double
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
maxTimeStep_() const
{
return this->adaptive_time_stepping_.max_time_step_;
}
template <class TypeTag>
template <class Solver>
SimulatorReport
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
runStepOriginal_()
{
const auto elapsed = this->simulator_timer_.simulationTimeElapsed();
const auto original_time_step = this->simulator_timer_.currentStepLength();
const auto report_step = this->simulator_timer_.reportStepNum();
maybeUpdateTuning_(elapsed, original_time_step, report_step);
maybeModifySuggestedTimeStepAtBeginningOfReportStep_(original_time_step);
AdaptiveSimulatorTimer substep_timer{
this->simulator_timer_.startDateTime(),
original_time_step,
elapsed,
suggestedNextTimestep_(),
report_step,
maxTimeStep_()
};
SubStepIteration<Solver> substepIteration{*this, substep_timer, original_time_step, /*final_step=*/true};
return substepIteration.run();
}
#ifdef RESERVOIR_COUPLING_ENABLED
template <class TypeTag>
template <class Solver>
ReservoirCouplingMaster&
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
reservoirCouplingMaster_()
{
return *(this->solver_.model().simulator().reservoirCouplingMaster());
}
#endif
#ifdef RESERVOIR_COUPLING_ENABLED
template <class TypeTag>
template <class Solver>
ReservoirCouplingSlave&
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
reservoirCouplingSlave_()
{
return *(this->solver_.model().simulator().reservoirCouplingSlave());
}
#endif
#ifdef RESERVOIR_COUPLING_ENABLED
// Description of the reservoir coupling master and slave substep loop
// -------------------------------------------------------------------
// The master and slave processes attempts to reach the end of the report step using a series of substeps
// (also called timesteps). Each substep have an upper limit that is roughly determined by a combination
// of the keywords TUNING (through the TSINIT, TSMAXZ values), NEXSTEP, WCYCLE, and the start of the
// next report step (the last substep needs to coincide with this time). Note that NEXTSTEP can be
// updated from an ACTIONX keyword. Although, this comment focuses on the maximum substep limit,
// note that there is also a lower limit on the substep length. And the substep sizes will be adjusted
// automatically (or retried) based on the convergence behavior of the solver and other criteria.
//
// When using reservoir coupling, the upper limit on each substep is further limited to: a) not overshoot
// next report date of a slave reservoir, and b) to keep the flow rate of the slave groups within
// certain limits. To determine this potential further limitation on the substep, the following procedure
// is used at the beginning of each master substep:
// - First, the slaves sends the master the date of their next report step
// - The master receives the date of the next report step from the slaves
// - If necessary, the master computes a modified substep length based on the received dates
// TODO: explain how the substep is limited to keep the flow rate of the slave groups within certain
// limits. Since this is not implemented yet, this part of the procedure is not explained here.
//
// Then, after the master has determined the substep length using the above procedure, it sends it
// to the slaves. The slaves will now use the end of this substep as a fixed point (like a mini report
// step), that they will try to reach using a single substep or multiple substeps. The end of the
// substep received from the master will either conincide with the end of its current report step, or
// it will end before (it cannot not end after since the master has already adjusted the step to not
// exceed any report time in a slave). If the end of this substep is earlier in time than its next report
// date, the slave will enter a loop and wait for the master to send it a new substep.
// The loop is finished when the end of the received time step conincides with the end of its current
// report step.
template <class TypeTag>
template <class Solver>
SimulatorReport
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
runStepReservoirCouplingMaster_()
{
int iteration = 0;
const double original_time_step = this->simulator_timer_.currentStepLength();
double current_time{this->simulator_timer_.simulationTimeElapsed()};
double step_end_time = current_time + original_time_step;
auto current_step_length = original_time_step;
SimulatorReport report;
// The master needs to know which slaves have activated before it can start the substep loop
reservoirCouplingMaster_().maybeReceiveActivationHandshakeFromSlaves(current_time);
while (true) {
reservoirCouplingMaster_().receiveNextReportDateFromSlaves();
if (iteration == 0) {
maybeUpdateTuning_(current_time, current_step_length, /*substep=*/0);
}
current_step_length = reservoirCouplingMaster_().maybeChopSubStep(
current_step_length, current_time);
reservoirCouplingMaster_().sendNextTimeStepToSlaves(current_step_length);
if (iteration == 0) {
maybeModifySuggestedTimeStepAtBeginningOfReportStep_(current_step_length);
}
AdaptiveSimulatorTimer substep_timer{
this->simulator_timer_.startDateTime(),
/*stepLength=*/current_step_length,
/*elapsedTime=*/current_time,
/*timeStepEstimate=*/suggestedNextTimestep_(),
/*reportStep=*/this->simulator_timer_.reportStepNum(),
maxTimeStep_()
};
const bool final_step = ReservoirCoupling::Seconds::compare_gt_or_eq(
current_time + current_step_length, step_end_time
);
SubStepIteration<Solver> substepIteration{*this, substep_timer, current_step_length, final_step};
const auto sub_steps_report = substepIteration.run();
report += sub_steps_report;
current_time += current_step_length;
if (final_step) {
break;
}
iteration++;
}
return report;
}
#endif
#ifdef RESERVOIR_COUPLING_ENABLED
template <class TypeTag>
template <class Solver>
SimulatorReport
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
runStepReservoirCouplingSlave_()
{
int iteration = 0;
const double original_time_step = this->simulator_timer_.currentStepLength();
double current_time{this->simulator_timer_.simulationTimeElapsed()};
double step_end_time = current_time + original_time_step;
SimulatorReport report;
while (true) {
reservoirCouplingSlave_().sendNextReportDateToMasterProcess();
const auto timestep = reservoirCouplingSlave_().receiveNextTimeStepFromMaster();
if (iteration == 0) {
maybeUpdateTuning_(current_time, original_time_step, /*substep=*/0);
maybeModifySuggestedTimeStepAtBeginningOfReportStep_(timestep);
}
AdaptiveSimulatorTimer substep_timer{
this->simulator_timer_.startDateTime(),
/*step_length=*/timestep,
/*elapsed_time=*/current_time,
/*time_step_estimate=*/suggestedNextTimestep_(),
this->simulator_timer_.reportStepNum(),
maxTimeStep_()
};
const bool final_step = ReservoirCoupling::Seconds::compare_gt_or_eq(
current_time + timestep, step_end_time
);
SubStepIteration<Solver> substepIteration{*this, substep_timer, timestep, final_step};
const auto sub_steps_report = substepIteration.run();
report += sub_steps_report;
current_time += timestep;
if (final_step) {
break;
}
iteration++;
}
return report;
}
#endif
template <class TypeTag>
template <class Solver>
double
AdaptiveTimeStepping<TypeTag>::SubStepper<Solver>::
suggestedNextTimestep_() const
{
return this->adaptive_time_stepping_.suggestedNextStep();
}
/************************************************
* Private class SubStepIteration public methods
************************************************/
template<class TypeTag>
template<class Solver>
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
SubStepIteration(SubStepper<Solver>& substepper,
AdaptiveSimulatorTimer& substep_timer,
const double original_time_step,
bool final_step)
: substepper_{substepper}
, substep_timer_{substep_timer}
, original_time_step_{original_time_step}
, final_step_{final_step}
, adaptive_time_stepping_{substepper.getAdaptiveTimerStepper()}
{
}
template <class TypeTag>
template <class Solver>
SimulatorReport
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
run()
{
auto& simulator = solver_().model().simulator();
auto& problem = simulator.problem();
// counter for solver restarts
int restarts = 0;
SimulatorReport report;
// sub step time loop
while (!this->substep_timer_.done()) {
// if we just chopped the timestep due to convergence i.e. restarts>0
// we dont want to update the next timestep based on Tuning
if (restarts == 0) {
maybeUpdateTuningAndTimeStep_();
}
const double dt = this->substep_timer_.currentStepLength();
if (timeStepVerbose_()) {
detail::logTimer(this->substep_timer_);
}
const auto substep_report = runSubStep_();
//Pass substep to eclwriter for summary output
problem.setSubStepReport(substep_report);
auto& full_report = adaptive_time_stepping_.report();
full_report += substep_report;
problem.setSimulationReport(full_report);
report += substep_report;
if (substep_report.converged || checkContinueOnUnconvergedSolution_(dt)) {
++this->substep_timer_; // advance by current dt
const int iterations = getNumIterations_(substep_report);
auto dt_estimate = timeStepControlComputeEstimate_(
dt, iterations, this->substep_timer_);
assert(dt_estimate > 0);
dt_estimate = maybeRestrictTimeStepGrowth_(dt, dt_estimate, restarts);
restarts = 0; // solver converged, reset restarts counter
maybeReportSubStep_(substep_report);
if (this->final_step_ && this->substep_timer_.done()) {
// if the time step is done we do not need to write it as this will be done
// by the simulator anyway.
}
else {
report.success.output_write_time += writeOutput_();
}
// set new time step length
setTimeStep_(dt_estimate);
report.success.converged = this->substep_timer_.done();
this->substep_timer_.setLastStepFailed(false);
}
else { // in case of no convergence or time step tolerance test failure
this->substep_timer_.setLastStepFailed(true);
checkTimeStepMaxRestartLimit_(restarts);
double new_time_step = restartFactor_() * dt;
if (substep_report.time_step_rejected) {
const double tol = Parameters::Get<Parameters::TimeStepControlTolerance>();
const double safetyFactor = Parameters::Get<Parameters::TimeStepControlSafetyFactor>();
const double temp_time_step = std::sqrt(safetyFactor * tol / solver_().model().relativeChange()) * dt;
if (temp_time_step < dt) { // added in case suggested time step is not a reduction
new_time_step = temp_time_step;
}
}
checkTimeStepMinLimit_(new_time_step);
bool wells_shut = false;
if (new_time_step > minTimeStepBeforeClosingWells_()) {
chopTimeStep_(new_time_step);
} else {
wells_shut = chopTimeStepOrCloseFailingWells_(new_time_step);
}
if (wells_shut) {
setTimeStep_(dt); // retry the old timestep
}
else {
restarts++; // only increase if no wells were shut
}
}
problem.setNextTimeStepSize(this->substep_timer_.currentStepLength());
}
updateSuggestedNextStep_();
return report;
}
/************************************************
* Private class SubStepIteration private methods
************************************************/
template<class TypeTag>
template<class Solver>
bool
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
checkContinueOnUnconvergedSolution_(double dt) const
{
const bool continue_on_uncoverged_solution = ignoreConvergenceFailure_() && dt <= minTimeStep_();
if (continue_on_uncoverged_solution && solverVerbose_()) {
// NOTE: This method is only called if the solver failed to converge.
const auto msg = fmt::format(
"Solver failed to converge but timestep {} is smaller or equal to {}\n"
"which is the minimum threshold given by option --solver-min-time-step\n",
dt, minTimeStep_()
);
OpmLog::problem(msg);
}
return continue_on_uncoverged_solution;
}
template<class TypeTag>
template<class Solver>
void
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
checkTimeStepMaxRestartLimit_(const int restarts) const
{
// If we have restarted (i.e. cut the timestep) too
// many times, we have failed and throw an exception.
if (restarts >= solverRestartMax_()) {
const auto msg = fmt::format(
"Solver failed to converge after cutting timestep {} times.", restarts
);
if (solverVerbose_()) {
OpmLog::error(msg);
}
// Use throw directly to prevent file and line
throw TimeSteppingBreakdown{msg};
}
}
template<class TypeTag>
template<class Solver>
void
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
checkTimeStepMinLimit_(const double new_time_step) const
{
using Meas = UnitSystem::measure;
// If we have restarted (i.e. cut the timestep) too
// much, we have failed and throw an exception.
if (new_time_step < minTimeStep_()) {
auto msg = fmt::format("Solver failed to converge after cutting timestep to ");
if (Parameters::Get<Parameters::EnableTuning>()) {
const UnitSystem& unit_system = solver_().model().simulator().vanguard().eclState().getDeckUnitSystem();
msg += fmt::format(
"{:.3E} {}\nwhich is the minimum threshold given by the TUNING keyword\n",
unit_system.from_si(Meas::time, minTimeStep_()),
unit_system.name(Meas::time)
);
}
else {
msg += fmt::format(
"{:.3E} DAYS\nwhich is the minimum threshold given by option --solver-min-time-step\n",
minTimeStep_() / 86400.0
);
}
if (solverVerbose_()) {
OpmLog::error(msg);
}
// Use throw directly to prevent file and line
throw TimeSteppingBreakdown{msg};
}
}
template<class TypeTag>
template<class Solver>
void
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
chopTimeStep_(const double new_time_step)
{
setTimeStep_(new_time_step);
if (solverVerbose_()) {
const auto msg = fmt::format("{}\nTimestep chopped to {} days\n",
this->cause_of_failure_,
unit::convert::to(this->substep_timer_.currentStepLength(), unit::day));
OpmLog::problem(msg);
}
}
template<class TypeTag>
template<class Solver>
bool
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
chopTimeStepOrCloseFailingWells_(const double new_time_step)
{
bool wells_shut = false;
// We are below the threshold, and will check if there are any
// wells that fails repeatedly (that means that it fails in the last three steps)
// we should close rather than chopping again.
// If we already have chopped the timestep two times that is
// new_time_step < minTimeStepBeforeClosingWells_()*restartFactor_()*restartFactor_()
// We also shut wells that fails only on this step.
const bool requireRepeatedFailures =
new_time_step > (minTimeStepBeforeClosingWells_() * restartFactor_() * restartFactor_());
const std::set<std::string> failing_wells =
detail::consistentlyFailingWells(solver_().model().stepReports(), requireRepeatedFailures);
if (failing_wells.empty()) {
// Found no wells to close, chop the timestep
chopTimeStep_(new_time_step);
} else {
// Close all consistently failing wells that are not under group control
std::vector<std::string> shut_wells;
for (const auto& well : failing_wells) {
const bool was_shut =
solver_().model().wellModel().forceShutWellByName(well,
this->substep_timer_.simulationTimeElapsed(),
/*dont_shut_grup_wells =*/ true);
if (was_shut) {
shut_wells.push_back(well);
}
}
// If no wells are closed we also try to shut wells under group control
if (shut_wells.empty()) {
for (const auto& well : failing_wells) {
const bool was_shut =
solver_().model().wellModel().forceShutWellByName(well,
this->substep_timer_.simulationTimeElapsed(),
/*dont_shut_grup_wells =*/ false);
if (was_shut) {
shut_wells.push_back(well);
}
}
}
// If still no wells are closed we must fall back to chopping again
if (shut_wells.empty()) {
chopTimeStep_(new_time_step);
} else {
wells_shut = true;
if (solverVerbose_()) {
const std::string msg =
fmt::format("\nProblematic well(s) were shut: {}"
"(retrying timestep)\n",
fmt::join(shut_wells, " "));
OpmLog::problem(msg);
}
}
}
return wells_shut;
}
template<class TypeTag>
template<class Solver>
boost::posix_time::ptime
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
currentDateTime_() const
{
return simulatorTimer_().currentDateTime();
}
template<class TypeTag>
template<class Solver>
int
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
getNumIterations_(const SimulatorReportSingle &substep_report) const
{
if (useNewtonIteration_()) {
return substep_report.total_newton_iterations;
}
else {
return substep_report.total_linear_iterations;
}
}
template<class TypeTag>
template<class Solver>
double
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
growthFactor_() const
{
return this->adaptive_time_stepping_.growth_factor_;
}
template<class TypeTag>
template<class Solver>
bool
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
ignoreConvergenceFailure_() const
{
return adaptive_time_stepping_.ignore_convergence_failure_;
}
template<class TypeTag>
template<class Solver>
double
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
maxGrowth_() const
{
return this->adaptive_time_stepping_.max_growth_;
}
template<class TypeTag>
template<class Solver>
void
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
maybeReportSubStep_(SimulatorReportSingle substep_report) const
{
if (timeStepVerbose_()) {
std::ostringstream ss;
substep_report.reportStep(ss);
OpmLog::info(ss.str());
}
}
template<class TypeTag>
template<class Solver>
double
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
maybeRestrictTimeStepGrowth_(const double dt, double dt_estimate, const int restarts) const
{
// limit the growth of the timestep size by the growth factor
dt_estimate = std::min(dt_estimate, double(maxGrowth_() * dt));
assert(dt_estimate > 0);
// further restrict time step size growth after convergence problems
if (restarts > 0) {
dt_estimate = std::min(growthFactor_() * dt, dt_estimate);
}
return dt_estimate;
}
// The maybeUpdateTuning_() lambda callback is defined in SimulatorFullyImplicitBlackoil::runStep()
// It has to be called for each substep since TUNING might have been changed for next sub step due
// to ACTIONX (via NEXTSTEP) or WCYCLE keywords.
template<class TypeTag>
template<class Solver>
void
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
maybeUpdateTuningAndTimeStep_()
{
// TODO: This function is currently only called if NEXTSTEP is activated from ACTIONX or
// if the WCYCLE keyword needs to modify the current timestep. So this method should rather
// be named maybeUpdateTimeStep_() or similar, since it should not update the tuning. However,
// the current definition of the maybeUpdateTuning_() callback is actually calling
// adaptiveTimeStepping_->updateTUNING(max_next_tstep, tuning) which is updating the tuning
// see SimulatorFullyImplicitBlackoil::runStep() for more details.
const auto old_value = suggestedNextTimestep_();
if (this->substepper_.maybeUpdateTuning_(this->substep_timer_.simulationTimeElapsed(),
this->substep_timer_.currentStepLength(),
this->substep_timer_.currentStepNum()))
{
// Either NEXTSTEP and WCYCLE wants to change the current time step, but they cannot
// change the current time step directly. Instead, they change the suggested next time step
// by calling updateNEXTSTEP() via the maybeUpdateTuning() callback. We now need to update
// the current time step to the new suggested time step and reset the suggested time step
// to the old value.
setTimeStep_(suggestedNextTimestep_());
setSuggestedNextStep_(old_value);
}
}
template<class TypeTag>
template<class Solver>
double
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
minTimeStepBeforeClosingWells_() const
{
return this->adaptive_time_stepping_.min_time_step_before_shutting_problematic_wells_;
}
template<class TypeTag>
template<class Solver>
double
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
minTimeStep_() const
{
return this->adaptive_time_stepping_.min_time_step_;
}
template<class TypeTag>
template<class Solver>
double
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
restartFactor_() const
{
return this->adaptive_time_stepping_.restart_factor_;
}
template<class TypeTag>
template<class Solver>
SimulatorReportSingle
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
runSubStep_()
{
SimulatorReportSingle substep_report;
auto handleFailure = [this, &substep_report]
(const std::string& failure_reason, const std::exception& e, bool log_exception = true)
{
substep_report = solver_().failureReport();
this->cause_of_failure_ = failure_reason;
if (log_exception && solverVerbose_()) {
OpmLog::debug(std::string("Caught Exception: ") + e.what());
}
};
try {
substep_report = solver_().step(this->substep_timer_, &this->adaptive_time_stepping_.timeStepControl());
if (solverVerbose_()) {
// report number of linear iterations
OpmLog::debug("Overall linear iterations used: "
+ std::to_string(substep_report.total_linear_iterations));
}
}
catch (const TooManyIterations& e) {
handleFailure("Solver convergence failure - Iteration limit reached", e);
}
catch (const TimeSteppingBreakdown& e) {
handleFailure(e.what(), e);
}
catch (const ConvergenceMonitorFailure& e) {
handleFailure("Convergence monitor failure", e, /*log_exception=*/false);
}
catch (const LinearSolverProblem& e) {
handleFailure("Linear solver convergence failure", e);
}
catch (const NumericalProblem& e) {
handleFailure("Solver convergence failure - Numerical problem encountered", e);
}
catch (const std::runtime_error& e) {
handleFailure("Runtime error encountered", e);
}
catch (const Dune::ISTLError& e) {
handleFailure("ISTL error - Time step too large", e);
}
catch (const Dune::MatrixBlockError& e) {
handleFailure("Matrix block error", e);
}
return substep_report;
}
template<class TypeTag>
template<class Solver>
void
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
setTimeStep_(double dt_estimate)
{
this->substep_timer_.provideTimeStepEstimate(dt_estimate);
}
template<class TypeTag>
template<class Solver>
Solver&
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
solver_() const
{
return this->substepper_.solver_;
}
template<class TypeTag>
template<class Solver>
int
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
solverRestartMax_() const
{
return this->adaptive_time_stepping_.solver_restart_max_;
}
template<class TypeTag>
template<class Solver>
void
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
setSuggestedNextStep_(double step)
{
this->adaptive_time_stepping_.setSuggestedNextStep(step);
}
template <class TypeTag>
template <class Solver>
const SimulatorTimer&
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
simulatorTimer_() const
{
return this->substepper_.simulator_timer_;
}
template <class TypeTag>
template <class Solver>
bool
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
solverVerbose_() const
{
return this->adaptive_time_stepping_.solver_verbose_;
}
template<class TypeTag>
template<class Solver>
boost::posix_time::ptime
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
startDateTime_() const
{
return simulatorTimer_().startDateTime();
}
template <class TypeTag>
template <class Solver>
double
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
suggestedNextTimestep_() const
{
return this->adaptive_time_stepping_.suggestedNextStep();
}
template <class TypeTag>
template <class Solver>
double
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
timeStepControlComputeEstimate_(const double dt, const int iterations,
const AdaptiveSimulatorTimer& substepTimer) const
{
// create object to compute the time error, simply forwards the call to the model
const SolutionTimeErrorSolverWrapper<Solver> relative_change{solver_()};
return this->adaptive_time_stepping_.time_step_control_->computeTimeStepSize(
dt, iterations, relative_change, substepTimer);
}
template <class TypeTag>
template <class Solver>
bool
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
timeStepVerbose_() const
{
return this->adaptive_time_stepping_.timestep_verbose_;
}
// The suggested time step is the stepsize that will be used as a first try for
// the next sub step. It is updated at the end of each substep. It can also be
// updated by the TUNING or NEXTSTEP keywords at the beginning of each report step or
// at the beginning of each substep by the ACTIONX keyword (via NEXTSTEP), this is
// done by the maybeUpdateTuning_() method which is called at the beginning of each substep
// (and the begginning of each report step). Note that the WCYCLE keyword can also update the
// suggested time step via the maybeUpdateTuning_() method.
template <class TypeTag>
template <class Solver>
void
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
updateSuggestedNextStep_()
{
auto suggested_next_step = this->substep_timer_.currentStepLength();
if (! std::isfinite(suggested_next_step)) { // check for NaN
suggested_next_step = this->original_time_step_;
}
if (timeStepVerbose_()) {
std::ostringstream ss;
this->substep_timer_.report(ss);
ss << "Suggested next step size = "
<< unit::convert::to(suggested_next_step, unit::day) << " (days)" << std::endl;
OpmLog::debug(ss.str());
}
setSuggestedNextStep_(suggested_next_step);
}
template <class TypeTag>
template <class Solver>
bool
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
useNewtonIteration_() const
{
return this->adaptive_time_stepping_.use_newton_iteration_;
}
template <class TypeTag>
template <class Solver>
double
AdaptiveTimeStepping<TypeTag>::SubStepIteration<Solver>::
writeOutput_() const
{
time::StopWatch perf_timer;
perf_timer.start();
auto& problem = solver_().model().simulator().problem();
problem.writeOutput(true);
return perf_timer.secsSinceStart();
}
/************************************************
* Private class SolutionTimeErrorSolverWrapper
* **********************************************/
template<class TypeTag>
template<class Solver>
AdaptiveTimeStepping<TypeTag>::
SolutionTimeErrorSolverWrapper<Solver>::
SolutionTimeErrorSolverWrapper(const Solver& solver)
: solver_{solver}
{}
template<class TypeTag>
template<class Solver>
double AdaptiveTimeStepping<TypeTag>::SolutionTimeErrorSolverWrapper<Solver>::relativeChange() const
{
// returns: || u^n+1 - u^n || / || u^n+1 ||
return solver_.model().relativeChange();
}
} // namespace Opm
#endif // OPM_ADAPTIVE_TIME_STEPPING_IMPL_HPP
Opm::AdaptiveSimulatorTimer
Simulation timer for adaptive time stepping.
Definition AdaptiveSimulatorTimer.hpp:41
Opm::AdaptiveTimeStepping
Definition AdaptiveTimeStepping.hpp:78
Opm::AdaptiveTimeStepping::max_growth_
double max_growth_
factor that limits the maximum growth of a time step
Definition AdaptiveTimeStepping.hpp:252
Opm::AdaptiveTimeStepping::max_time_step_
double max_time_step_
maximal allowed time step size in days
Definition AdaptiveTimeStepping.hpp:253
Opm::AdaptiveTimeStepping::solver_verbose_
bool solver_verbose_
solver verbosity
Definition AdaptiveTimeStepping.hpp:257
Opm::AdaptiveTimeStepping::solver_restart_max_
int solver_restart_max_
how many restart of solver are allowed
Definition AdaptiveTimeStepping.hpp:256
Opm::AdaptiveTimeStepping::timestep_after_event_
double timestep_after_event_
suggested size of timestep after an event
Definition AdaptiveTimeStepping.hpp:261
Opm::AdaptiveTimeStepping::ignore_convergence_failure_
bool ignore_convergence_failure_
continue instead of stop when minimum time step is reached
Definition AdaptiveTimeStepping.hpp:255
Opm::AdaptiveTimeStepping::suggested_next_timestep_
double suggested_next_timestep_
suggested size of next timestep
Definition AdaptiveTimeStepping.hpp:259
Opm::AdaptiveTimeStepping::time_step_control_type_
TimeStepControlType time_step_control_type_
type of time step control object
Definition AdaptiveTimeStepping.hpp:248
Opm::AdaptiveTimeStepping::full_timestep_initially_
bool full_timestep_initially_
beginning with the size of the time step from data file
Definition AdaptiveTimeStepping.hpp:260
Opm::AdaptiveTimeStepping::step
SimulatorReport step(const SimulatorTimer &simulator_timer, Solver &solver, const bool is_event, const TuningUpdateCallback &tuning_updater)
step method that acts like the solver::step method in a sub cycle of time steps
Definition AdaptiveTimeStepping_impl.hpp:202
Opm::AdaptiveTimeStepping::growth_factor_
double growth_factor_
factor to multiply time step when solver recovered from failed convergence
Definition AdaptiveTimeStepping.hpp:251
Opm::AdaptiveTimeStepping::restart_factor_
double restart_factor_
factor to multiply time step with when solver fails to converge
Definition AdaptiveTimeStepping.hpp:250
Opm::AdaptiveTimeStepping::min_time_step_
double min_time_step_
minimal allowed time step size before throwing
Definition AdaptiveTimeStepping.hpp:254
Opm::AdaptiveTimeStepping::time_step_control_
TimeStepController time_step_control_
time step control object
Definition AdaptiveTimeStepping.hpp:249
Opm::AdaptiveTimeStepping::min_time_step_before_shutting_problematic_wells_
double min_time_step_before_shutting_problematic_wells_
< shut problematic wells when time step size in days are less than this
Definition AdaptiveTimeStepping.hpp:265
Opm::AdaptiveTimeStepping::timestep_verbose_
bool timestep_verbose_
timestep verbosity
Definition AdaptiveTimeStepping.hpp:258
Opm::AdaptiveTimeStepping::use_newton_iteration_
bool use_newton_iteration_
use newton iteration count for adaptive time step control
Definition AdaptiveTimeStepping.hpp:262
Opm::ReservoirCouplingMaster
Definition ReservoirCouplingMaster.hpp:35
Opm::ReservoirCouplingSlave
Definition ReservoirCouplingSlave.hpp:35
Opm::SimulatorTimer
Definition SimulatorTimer.hpp:39
Opm::TimeStepControlInterface
TimeStepControlInterface.
Definition TimeStepControlInterface.hpp:51
Opm
This file contains a set of helper functions used by VFPProd / VFPInj.
Definition blackoilbioeffectsmodules.hh:43
parametersystem.hpp
This file provides the infrastructure to retrieve run-time parameters.
Opm::Parameters::Get
auto Get(bool errorIfNotRegistered=true)
Retrieve a runtime parameter.
Definition parametersystem.hpp:187
Opm::ReservoirCoupling::Seconds::compare_gt_or_eq
static bool compare_gt_or_eq(double a, double b)
Determines if a is greater than b within the specified tolerance.
Definition ReservoirCoupling.cpp:120
Opm::SimulatorReportSingle
A struct for returning timing data from a simulator to its caller.
Definition SimulatorReport.hpp:34
Opm::SimulatorReport
Definition SimulatorReport.hpp:122