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_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_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)