def test_bips_setup_without_derivatives():
"""
This test takes into account the case where the BIPs are constants. In such a case, define
matrices for kT and kTT are not necessary since all entries would be zero. Thus, only k
should be defined.
"""
def bips_function(T):
k_00 = k_11 = k_22 = 0.0
k_01 = k_10 = 0.01
k_02 = k_20 = 0.50
k_12 = k_21 = 0.40
k = [
[k_00, k_01, k_02],
[k_10, k_11, k_12],
[k_20, k_21, k_22]
]
bips_values = BinaryInteractionParams(k)
return bips_values
T_dummy = 2.0
bips_expected = bips_function(T_dummy)
cubic_eos_params = CubicEOSParams(binary_interaction_values=bips_function)
bips_calculated = cubic_eos_params.binary_interaction_values(T_dummy)
assert_array_equal(bips_calculated.k, bips_expected.k)
assert len(bips_calculated.kT) == 0
assert len(bips_calculated.kTT) == 0
def test_bips_calculation_function():
"""
Test the wrapper for the function that calculates the BIPs for mixtures
modeled by a Cubic EOS. In this particular case, the BIPs depend on the
temperature.
"""
def bips_function(T):
k_00 = k_11 = k_22 = 0.0 * T
k_01 = k_10 = 0.01 * T
k_02 = k_20 = 0.50 * T
k_12 = k_21 = 0.40 * T
k = [
[k_00, k_01, k_02],
[k_10, k_11, k_12],
[k_20, k_21, k_22]
]
kT_00 = kT_11 = kT_22 = 0.0
kT_01 = kT_10 = 0.01
kT_02 = kT_20 = 0.50
kT_12 = kT_21 = 0.40
kT = [
[kT_00, kT_01, kT_02],
[kT_10, kT_11, kT_12],
[kT_20, kT_21, kT_22]
]
kTT_00 = kTT_11 = kTT_22 = 0.0
kTT_01 = kTT_10 = 0.0
kTT_02 = kTT_20 = 0.0
kTT_12 = kTT_21 = 0.0
kTT = [
[kTT_00, kTT_01, kTT_02],
[kTT_10, kTT_11, kTT_12],
[kTT_20, kTT_21, kTT_22]
]
bips_values = BinaryInteractionParams(k, kT, kTT)
return bips_values
T_dummy = 2.0
bips_expected = bips_function(T_dummy)
cubic_eos_params = CubicEOSParams(binary_interaction_values=bips_function)
bips_calculated = cubic_eos_params.binary_interaction_values(T_dummy)
assert_array_equal(bips_calculated.k, bips_expected.k)
assert_array_equal(bips_calculated.kT, bips_expected.kT)
assert_array_equal(bips_calculated.kTT, bips_expected.kTT)
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_CH4_liq_gas(temperature, pressure, num_regression):
db = Database("supcrt98.xml")
editor = ChemicalEditor(db)
eos_params = CubicEOSParams()
eos_params.phase_identification_method = PhaseIdentificationMethod.GibbsEnergyAndEquationOfStateMethod
editor.addGaseousPhase(["CH4(g)"]).setChemicalModelPengRobinson(eos_params)
editor.addLiquidPhase(["CH4(liq)"
]).setChemicalModelPengRobinson(eos_params)
system = ChemicalSystem(editor)
problem = EquilibriumProblem(system)
problem.setTemperature(temperature, "K")
problem.setPressure(pressure, "Pa")
problem.add("CH4(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 = {
"CH4(g)": np.asarray([state.speciesAmount("CH4(g)")]),
"CH4(liq)": np.asarray([state.speciesAmount("CH4(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)