def test_equilibrium_solver_approx_overload_3(setup, state_regression):
"""
An integration test that checks result's reproducibility of
the calculation of an equilibrium of a state using
EquilibriumSolver::approximate(ChemicalState& state, double T, double P, VectorConstRef be)
@param setup
a tuple that has some objects from problem setup
(system, problem)
"""
(system, problem) = setup
state = ChemicalState(system)
solver = EquilibriumSolver(system)
T = problem.temperature()
P = problem.pressure()
b = problem.elementAmounts()
solver.approximate(state, T, P, b)
exclude = ['pH [-]']
state_regression.check(state,
default_tol=dict(atol=1e-5, rtol=1e-14),
exclude=exclude)
def test_equilibrium_CH4_CO2_H2S_liq_gas(temperature, pressure,
num_regression):
"""
This test checks the capability of solving a ternary mixture with
@param Temperature
temperature in Kelvin which will be used to compute equilibrium
@param Pressure
pressure in bar which will be used to compute equilibrium
"""
db = Database("supcrt98.xml")
editor = ChemicalEditor(db)
eos_params = CubicEOSParams(
phase_identification_method=PhaseIdentificationMethod.
GibbsEnergyAndEquationOfStateMethod, )
editor.addGaseousPhase(["CH4(g)", "H2S(g)",
"CO2(g)"]).setChemicalModelPengRobinson(eos_params)
editor.addLiquidPhase(["CH4(liq)", "H2S(liq)", "CO2(liq)"
]).setChemicalModelPengRobinson(eos_params)
system = ChemicalSystem(editor)
problem = EquilibriumProblem(system)
problem.setTemperature(temperature, "K")
problem.setPressure(pressure, "bar")
problem.add("CH4(g)", 0.60, "mol")
problem.add("H2S(g)", 0.35, "mol")
problem.add("CO2(g)", 0.05, "mol")
solver = EquilibriumSolver(problem.system())
options = EquilibriumOptions()
options.hessian = GibbsHessian.Exact
options.nonlinear.max_iterations = 100
options.optimum.max_iterations = 200
options.optimum.ipnewton.step = StepMode.Conservative
solver.setOptions(options)
state = ChemicalState(system)
result = solver.solve(state, problem)
assert result.optimum.succeeded
species_amount = {
"CH4(g)": np.asarray([state.speciesAmount("CH4(g)")]),
"H2S(g)": np.asarray([state.speciesAmount("H2S(g)")]),
"CO2(g)": np.asarray([state.speciesAmount("CO2(g)")]),
"CH4(liq)": np.asarray([state.speciesAmount("CH4(liq)")]),
"H2S(liq)": np.asarray([state.speciesAmount("H2S(liq)")]),
"CO2(liq)": np.asarray([state.speciesAmount("CO2(liq)")]),
}
num_regression.check(species_amount)
def test_equilibrium_solver_solve_overload_2(setup, state_regression):
"""
An integration test that checks result's reproducibility of
the calculation of an equilibrium of a state using
EquilibriumSolver::solve(ChemicalState& state, const EquilibriumProblem& problem)
@param setup
a tuple that has some objects from problem setup
(system, problem)
"""
(system, problem) = setup
state = ChemicalState(system)
solver = EquilibriumSolver(system)
solver.solve(state, problem)
state_regression.check(state, default_tol=dict(atol=1e-5, rtol=1e-16))
def test_equilibrium_H2S_liq_gas(temperature, pressure, num_regression):
db = Database("supcrt98.xml")
editor = ChemicalEditor(db)
eos_params = CubicEOSParams(
model=CubicEOSModel.PengRobinson,
phase_identification_method=PhaseIdentificationMethod.
GibbsEnergyAndEquationOfStateMethod,
)
editor.addGaseousPhase(["H2S(g)"]).setChemicalModelCubicEOS(eos_params)
editor.addLiquidPhase(["H2S(liq)"]).setChemicalModelCubicEOS(eos_params)
system = ChemicalSystem(editor)
problem = EquilibriumProblem(system)
problem.setTemperature(temperature, "K")
problem.setPressure(pressure, "Pa")
problem.add("H2S(g)", 1.0, "mol")
solver = EquilibriumSolver(problem.system())
options = EquilibriumOptions()
options.hessian = GibbsHessian.Exact
options.nonlinear.max_iterations = 100
options.optimum.max_iterations = 200
options.optimum.ipnewton.step = StepMode.Conservative
options.optimum.tolerance = 1e-17
solver.setOptions(options)
state = ChemicalState(system)
result = solver.solve(state, problem)
assert result.optimum.succeeded
species_amounts = {
"H2S(g)": np.asarray([state.speciesAmount("H2S(g)")]),
"H2S(liq)": np.asarray([state.speciesAmount("H2S(liq)")]),
}
num_regression.check(species_amounts)
def test_equilibrium_solver_approx_overload_1(setup, state_regression):
"""
An integration test that checks result's reproducibility of
the calculation of an equilibrium of a state using
EquilibriumSolver::approximate(ChemicalState& state)
@param setup
a tuple that has some objects from problem setup
(system, problem)
"""
(system, problem) = setup
state = equilibrate(problem)
state.setTemperature(problem.temperature() + 10)
state.setPressure(problem.pressure() + 10)
solver = EquilibriumSolver(system)
solver.approximate(state)
state_regression.check(state, default_tol=dict(atol=1e-5, rtol=1e-16))
def test_equilibrium_solver_approx_overload_2(setup, num_regression):
"""
An integration test that checks result's reproducibility of
the calculation of an equilibrium of a state using
EquilibriumSolver::approximate(ChemicalState& state, const EquilibriumProblem& problem)
@param setup
a tuple that has some objects from problem setup
(system, problem)
"""
(system, problem) = setup
state = ChemicalState(system)
solver = EquilibriumSolver(system)
solver.approximate(state, problem)
stateDict = convert_reaktoro_state_to_dict(state)
num_regression.check(stateDict,
default_tolerance=dict(atol=1e-5, rtol=1e-16))
def test_CubicEOS_multiple_roots():
"""
This problem leads to the following CubicEOS roots
PR - Z1 = 1.00027728
Z2 = 0.0001655
Z3 = -0.0011024
since bmix = 1.635e-05 -> Z3 is an invalid root
and since Z3 < Z2 < Z1 -> Z2 is an invalid root.
Reaktoro should remove Z3, Z2 and proceed instead of removing only Z3 and
raising the exception "Logic error: it was expected Z roots of size 3, but
got: 2".
"""
database = Database("supcrt98.xml")
editor = ChemicalEditor(database)
editor.addAqueousPhaseWithElementsOf("H2O Fe(OH)2 Fe(OH)3 NH3")
editor.addGaseousPhaseWithElementsOf("NH3")
editor.addMineralPhase("Magnetite")
system = ChemicalSystem(editor)
state = ChemicalState(system)
solver = EquilibriumSolver(system)
temperature = 298.15
pressure = 1e5
b = [
3.0,
122.01687012,
1.0,
63.50843506,
0.0,
]
result = solver.approximate(state, temperature, pressure, b)
assert result.optimum.succeeded
# check that it doesn't raise an exception
state.properties()
def test_equilibrium_solver_solve_overload_3(setup, num_regression):
"""
An integration test that checks result's reproducibility of
the calculation of an equilibrium of a state using
EquilibriumSolver::solve(ChemicalState& state, double T, double P, VectorConstRef be)
@param setup
a tuple that has some objects from problem setup
(system, problem)
"""
(system, problem) = setup
state = ChemicalState(system)
solver = EquilibriumSolver(system)
solver.solve(state, problem.temperature(), problem.pressure(),
problem.elementAmounts())
stateDict = convert_reaktoro_state_to_dict(state)
num_regression.check(stateDict,
default_tolerance=dict(atol=1e-5, rtol=1e-16))
def test_equilibrium_solver_with_equilibrium_problem(
partition_with_inert_gaseous_phase, chemical_system):
problem = _create_equilibrium_problem(partition_with_inert_gaseous_phase)
state = _create_chemical_state(chemical_system)
# Compute equilibrium state; the amounts of CO2(g) and H2O(g) should remain the same
solver = EquilibriumSolver(chemical_system)
solver.setPartition(problem.partition())
solver.solve(state, problem)
# Assert the amounts of CO2(g) and H2O(g) are the same as initially set
assert state.speciesAmount('CO2(g)') == 1.0
assert state.speciesAmount('H2O(g)') == 0.001
def test_equilibrium_solver_with_chemical_state(
partition_with_inert_gaseous_phase, chemical_system):
state = _create_chemical_state(chemical_system)
# Compute equilibrium state; the amounts of CO2(g) and H2O(g) should remain the same
solver = EquilibriumSolver(chemical_system)
solver.setPartition(partition_with_inert_gaseous_phase)
# Set the amounts of H2O(l) and CO2(aq)
state.setSpeciesMass('H2O(l)', 55, 'kg')
state.setSpeciesAmount('CO2(aq)', 1, 'mol')
# Check inert elements are taken care of when solving with state input
solver.solve(state)
# Assert the amounts of CO2(g) and H2O(g) are the same as initially set
assert state.speciesAmount('CO2(g)') == 1.0
assert state.speciesAmount('H2O(g)') == 0.001
def test_different_results(state_regression):
from reaktoro import ChemicalEditor, ChemicalState, ChemicalSystem, Database, EquilibriumProblem, EquilibriumSolver, Partition
database = Database('supcrt07.xml')
editor = ChemicalEditor(database)
aqueous_elements = ["C", "Ca", "Cl", "Fe", "H", "Na", "O", "S", "Ba", "Sr"]
aqueous_phase = editor.addAqueousPhaseWithElements(aqueous_elements)
assert aqueous_phase.name() == 'Aqueous'
mineral_species = [
"Anhydrite", "Barite", "Calcite", "Celestite", "Siderite", "Pyrrhotite"
]
for mineral in mineral_species:
editor.addMineralPhase(mineral)
gaseous_species = ["CO2(g)", "H2S(g)", "CH4(g)"]
editor.addGaseousPhase(gaseous_species)
chemical_system = ChemicalSystem(editor)
element_index = {
e.name(): index
for index, e in enumerate(chemical_system.elements())
}
species_index = {
s.name(): index
for index, s in enumerate(chemical_system.species())
}
phase_index = {
p.name(): index
for index, p in enumerate(chemical_system.phases())
}
reaktoro_case = get_reaktoro_case()
equilibrium_problem = EquilibriumProblem(chemical_system)
equilibrium_problem.setTemperature(reaktoro_case.temperature_in_K)
equilibrium_problem.setPressure(reaktoro_case.pressure_in_Pa)
partition = Partition(chemical_system)
partition.setInertPhases([phase_index['Gaseous']])
equilibrium_problem.setPartition(partition)
chemical_state = ChemicalState(chemical_system)
for name, index, molar_amount in reaktoro_case.species_amounts:
assert index == species_index[name]
chemical_state.setSpeciesAmount(index, molar_amount)
equilibrium_problem.addState(chemical_state)
solver = EquilibriumSolver(chemical_system)
solver.setPartition(partition)
result = solver.solve(chemical_state, equilibrium_problem)
assert result.optimum.succeeded
state_regression.check(chemical_state,
default_tol=dict(atol=1e-5, rtol=1e-14))
def test_equilibrium_CH4_H2S_CO2_H2O_liq_gas_aq(temperature, pressure,
num_regression):
"""
This test checks the capability of solving a system that has CH4, H2S,
CO2, H2O with
@param Temperature
temperature in Kelvin which will be used to compute equilibrium
@param Pressure
pressure in bar which will be used to compute equilibrium
"""
db = Database("supcrt98.xml")
editor = ChemicalEditor(db)
eos_params = CubicEOSParams(
phase_identification_method=PhaseIdentificationMethod.
GibbsEnergyAndEquationOfStateMethod, )
editor.addAqueousPhase(["CO2(aq)", "H2S(aq)", "H2O(l)"])
editor.addGaseousPhase(["CH4(g)", "CO2(g)", "H2S(g)",
"H2O(g)"]).setChemicalModelCubicEOS(eos_params)
editor.addLiquidPhase(["CH4(liq)", "CO2(liq)", "H2S(liq)",
"H2O(liq)"]).setChemicalModelCubicEOS(eos_params)
system = ChemicalSystem(editor)
problem = EquilibriumProblem(system)
problem.setTemperature(temperature, "K")
problem.setPressure(pressure, "bar")
problem.add("H2O(g)", 0.50, "mol")
problem.add("CO2(g)", 0.05, "mol")
problem.add("H2S(g)", 0.40, "mol")
problem.add("CH4(g)", 0.05, "mol")
# This is a workaround to avoid an Eigen assertion when in Debug:
# `DenseBase::resize() does not actually allow to resize.`, triggered by `y(iee) = optimum_state.y * RT;`
problem.add("Z", 1e-15, "mol")
solver = EquilibriumSolver(problem.system())
options = EquilibriumOptions()
options.hessian = GibbsHessian.Exact
options.nonlinear.max_iterations = 100
options.optimum.max_iterations = 200
options.optimum.ipnewton.step = StepMode.Conservative
options.optimum.tolerance = 1e-14
solver.setOptions(options)
state = ChemicalState(system)
result = solver.solve(state, problem)
assert result.optimum.succeeded
species_amount = {
"CO2(aq)": np.asarray([state.speciesAmount("CO2(g)")]),
"H2S(aq)": np.asarray([state.speciesAmount("H2S(aq)")]),
"H2O(l)": np.asarray([state.speciesAmount("H2O(l)")]),
"CH4(g)": np.asarray([state.speciesAmount("CH4(g)")]),
"CO2(g)": np.asarray([state.speciesAmount("CO2(g)")]),
"H2S(g)": np.asarray([state.speciesAmount("H2S(g)")]),
"H2O(g)": np.asarray([state.speciesAmount("H2O(g)")]),
"CH4(liq)": np.asarray([state.speciesAmount("CH4(liq)")]),
"CO2(liq)": np.asarray([state.speciesAmount("CO2(liq)")]),
"H2S(liq)": np.asarray([state.speciesAmount("H2S(liq)")]),
"H2O(liq)": np.asarray([state.speciesAmount("H2O(liq)")]),
}
num_regression.check(species_amount)
