def calculatePartialMolarVolume(self,elementMolarAmounts,endmemberMassDensityLaws, epsilon, constituentToEndmembersConverter=None):
#print(elementMolarAmounts, epsilon)
# suspend all other phases
oc.setPhasesStatus(('* ',), phStat.Suspended)
oc.setPhasesStatus(tuple(self.__phasenames), phStat.Entered, 1.0)
# set pressure
oc.setPressure(self.__P)
# set temperature
oc.setTemperature(self.__T)
# evaluate volume
oc.setElementMolarAmounts(elementMolarAmounts)
oc.calculateEquilibrium(gmStat.Off)
exactVolume = self.__calculateVolume(oc.getPhasesAtEquilibrium().getPhaseConstituentComposition(),oc.getConstituentsDescription(),endmemberMassDensityLaws, constituentToEndmembersConverter)
# evaluate (elementwise) partial molar volume (approximation of first order volume derivative by a second-order finite difference formula)
partialMolarVolumes={}
for element in elementMolarAmounts:
# evaluate volume for n[element]+epsilone
modifiedElementMolarAmounts=elementMolarAmounts.copy()
modifiedElementMolarAmounts[element] += epsilon
#print(element, modifiedElementMolarAmounts)
oc.setElementMolarAmounts(modifiedElementMolarAmounts)
oc.calculateEquilibrium(gmStat.Off)
volumePlus = self.__calculateVolume(oc.getPhasesAtEquilibrium().getPhaseConstituentComposition(),oc.getConstituentsDescription(),endmemberMassDensityLaws, constituentToEndmembersConverter)
# evaluate volume for n[element]-epsilone
modifiedElementMolarAmounts[element] -= 2.0*epsilon
#print(element, modifiedElementMolarAmounts)
oc.setElementMolarAmounts(modifiedElementMolarAmounts)
oc.calculateEquilibrium(gmStat.Off)
volumeMinus = self.__calculateVolume(oc.getPhasesAtEquilibrium().getPhaseConstituentComposition(),oc.getConstituentsDescription(),endmemberMassDensityLaws, constituentToEndmembersConverter)
partialMolarVolumes[element]=(volumePlus-volumeMinus)/(2.0*epsilon)
# calculate approximate volume from partial volumes
approxVolume = 0.0
for element, molarAmount in oc.getPhasesAtEquilibrium().getPhaseElementComposition()[list(oc.getPhasesAtEquilibrium().getPhaseElementComposition())[0]].items():
approxVolume+=molarAmount*partialMolarVolumes[element]
return partialMolarVolumes,exactVolume,approxVolume
def calculateEquilibria(self, gmStat, setverb, T, P, x0):
# setting verbosity (True or False - default), if set to yes, in particular, when getters are called the returned values are displayed in a comprehensive way
oc.setVerbosity(setverb)
# set pressure
oc.setPressure(P)
# set temperature
oc.setTemperature(T)
# set initial molar amounts
oc.setElementMolarAmounts(x0)
#Equilibrium
if gmStat == 'Off':
oc.calculateEquilibrium(gmstat.Off)
elif gmStat == 'On':
oc.calculateEquilibrium(gmstat.On)
else:
raise ValueError(
'No suitable parameter for gmstat found: Choose from On/Off')
self.gibbs = oc.getGibbsEnergy()
self.mu = oc.getChemicalPotentials()
self.cd = oc.getConstituentsDescription()
self.mass = oc.getScalarResult('B')
phasesAtEquilibrium = oc.getPhasesAtEquilibrium()
self.pec = phasesAtEquilibrium.getPhaseElementComposition()
self.pcc = phasesAtEquilibrium.getPhaseConstituentComposition()
self.ps = phasesAtEquilibrium.getPhaseSites()
self.ma = phasesAtEquilibrium.getPhaseMolarAmounts()
def eqfunc(self, x, calc_value):
# setting verbosity (True or False - default), if set to yes, in particular, when getters are called the returned values are displayed in a comprehensive way
oc.setVerbosity(self.setverb)
# set pressure
oc.setPressure(self.P)
# set temperature
oc.setTemperature(self.T)
# set initial molar amounts
oc.setElementMolarAmounts(x)
#Equilibrium
oc.calculateEquilibrium(gmstat.Off)
if calc_value == 'gibbs':
self.eq_val = oc.getGibbsEnergy()
elif calc_value == 'mu':
self.eq_val = oc.getChemicalPotentials()
elif calc_value == 'cd':
self.eq_val = oc.getConstituentsDescription()
elif calc_value == 'mass':
self.eq_val = oc.getScalarResult('B')
elif calc_value == 'pec':
self.eq_val = oc.getPhasesAtEquilibrium(
).getPhaseElementComposition()
elif calc_value == 'pcc':
self.eq_val = oc.getPhasesAtEquilibrium(
).getPhaseConstituentComposition()
elif calc_value == 'ps':
self.eq_val = oc.getPhasesAtEquilibrium().getPhaseSites()
elif calc_value == 'ma':
self.eq_val = oc.getPhasesAtEquilibrium().getPhaseMolarAmounts()
return self.eq_val
def Gm_bulkphase(temperature, elementMolarAmounts):
# set temperature
oc.setTemperature(temperature)
oc.setElementMolarAmounts(elementMolarAmounts)
Gm_bulkphase = {}
Gm_bulkphase = oc.calculateEquilibrium(gmStat.On)
G = oc.getScalarResult('G')
phase_description = oc.getPhasesAtEquilibrium(
).getPhaseConstituentComposition()
chemicalpotential = oc.getComponentAssociatedResult('MU')
def phase(self, x, **kwargs):
"""
The string name of the phase in equilibrium at the conditions.
"""
phasearray = self.eqfunc(x).Phase.sel(P=self.P, T=self.T, **kwargs)
return phasearray.values.flatten()
phasesAtEquilibrium=oc.getPhasesAtEquilibrium()
self.pec = phasesAtEquilibrium.getPhaseElementComposition()
self.pcc = phasesAtEquilibrium.getPhaseConstituentComposition()
self.ps = phasesAtEquilibrium.getPhaseSites()
self.ma = phasesAtEquilibrium.getPhaseMolarAmounts()
self.mu = oc.getChemicalPotentials()
self.cd = oc.getConstituentsDescription()
self.mass=oc.getScalarResult('B')
def run():
print(
'### test U-O coherent interface in the liquid miscibility gap ###\n')
# tdb filepath
tdbFile = os.environ['TDBDATA_PRIVATE'] + '/feouzr.tdb'
#tdbFile=os.environ['TDBDATA_PRIVATE']+'/NUCLEA-17_1_mod.TDB'
#tdbFile=os.environ['TDBDATA_PRIVATE']+'/NUCLEA-19_1_mod.TDB'
#tdbFile='tests/TAF_uzrofe_V10.TDB'
#tdbFile='tests/TAF_uzrofe_V10_only_liquid_UO.TDB'
# components
comps = ['O', 'U']
# mass density laws (from Barrachin2004)
constituentDensityLaws = {
'U1':
lambda T: 17270.0 - 1.358 * (T - 1408),
'ZR1':
lambda T: 6844.51 - 0.609898 * T + 2.05008E-4 * T**2 - 4.47829E-8 * T**
3 + 3.26469E-12 * T**4,
'O2U1':
lambda T: 8860.0 - 9.285E-1 * (T - 3120),
'O2ZR1':
lambda T: 5150 - 0.445 * (T - 2983),
'O1':
lambda T:
1.141 # set to meaningless value but ok as, no 'free' oxygen in the considered mixtures
}
constituentDensityLaws['U'] = constituentDensityLaws['U1']
constituentDensityLaws['ZR'] = constituentDensityLaws['ZR1']
constituentDensityLaws['O'] = constituentDensityLaws['O1']
# phase names
phasenames = ['LIQUID', 'LIQUID']
# pressure
P = 1E5
# Given initial alloy composition. x0 is the mole fraction of U.
x0 = [0.65]
# Composition step for searching initial interfacial equilibrium composition.
dx = 0.05
# Convergence criterion for loop on interfacial composition
epsilonX = 1E-5
# temperature range
Tmin = 2800.0
Tmax = 4400.0
Trange = np.linspace(Tmin, Tmax, num=60, endpoint=True)
#Tmin = 2800.0
#Tmax = 2900.0
#Trange = np.linspace(Tmin, Tmax, num=3, endpoint=True)
results = pd.DataFrame(columns=[
'temperature', 'n_phase1', 'n_phase2', 'xU_phase1', 'xU_phase2',
'xU_interface', 'sigma', 'VmU', 'VmO'
])
for T in Trange:
# calculate global equilibrium and retrieve associated chemical potentials
CoherentGibbsEnergy_OC.initOC(tdbFile, comps)
model = CoherentGibbsEnergy_OC(T, 1E5, phasenames)
mueq = model.chemicalpotential(x0)
phasesAtEquilibrium = oc.getPhasesAtEquilibrium()
phasesAtEquilibriumMolarAmounts = phasesAtEquilibrium.getPhaseMolarAmounts(
)
if (len(phasesAtEquilibriumMolarAmounts) == 1):
# it is possible that the miscibility gap has not been detected correctly (can happen when T increases)
#print(phasesAtEquilibriumMolarAmounts)
# ad hoc strategy: 1) calculate an equilibrium at lower temperature (hopefully finding the two phases)
# 2) redo the calculation at the target temperature afterwards without the grid minimizer
model = CoherentGibbsEnergy_OC(T - 300.0, 1E5, phasenames)
mueq = model.chemicalpotential(x0)
phasesAtEquilibrium = oc.getPhasesAtEquilibrium()
phasesAtEquilibriumMolarAmounts = phasesAtEquilibrium.getPhaseMolarAmounts(
)
#print(phasesAtEquilibriumMolarAmounts)
oc.setTemperature(T)
oc.calculateEquilibrium(gmStat.Off)
mueq = model.getChemicalPotentials()
phasesAtEquilibrium = oc.getPhasesAtEquilibrium()
phasesAtEquilibriumMolarAmounts = phasesAtEquilibrium.getPhaseMolarAmounts(
)
phasesAtEquilibriumElementCompositions = phasesAtEquilibrium.getPhaseElementComposition(
)
print(phasesAtEquilibriumMolarAmounts)
if (set(phasesAtEquilibriumMolarAmounts) == set(
['LIQUID#1', 'LIQUID_AUTO#2'])):
# Composition range for searching initial interfacial equilibrium composition
# calculated from the actual phase compositions
componentsWithLimits = comps[1:]
limit = [[1.0, 0.0] for each in componentsWithLimits]
for phase in phasesAtEquilibriumElementCompositions:
for element in phasesAtEquilibriumElementCompositions[phase]:
elementMolarFraction = phasesAtEquilibriumElementCompositions[
phase][element]
if element in componentsWithLimits:
limit[componentsWithLimits.index(element)][0] = min(
limit[componentsWithLimits.index(element)][0],
elementMolarFraction)
limit[componentsWithLimits.index(element)][1] = max(
limit[componentsWithLimits.index(element)][1],
elementMolarFraction)
limit = [[
each[0] + dx * (each[1] - each[0]),
each[1] - dx * (each[1] - each[0])
] for each in limit]
print('limits: ', limit)
notConverged = True
x = x0.copy()
# Iterate on interfacial molar composition
while (notConverged):
# Molar volumes of pure components evaluated at x
CoherentGibbsEnergy_OC.initOC(tdbFile, comps)
model = CoherentGibbsEnergy_OC(T, P, phasenames[0], False)
if ('TAF' in tdbFile):
functions = model.constantPartialMolarVolumeFunctions(
x, constituentDensityLaws, 1E-5,
constituentToEndmembersConverter)
else:
functions = model.constantPartialMolarVolumeFunctions(
x, constituentDensityLaws, 1E-5)
# calculate interfacial energy
sigma = SigmaCoherent_OC(T=T,
x0=x0,
db=tdbFile,
comps=comps,
phasenames=phasenames,
purevms=functions,
limit=limit,
dx=dx,
enforceGridMinimizerForLocalEq=False,
mueq=mueq)
print('at T=', T, ' sigma=', sigma.Interfacial_Energy.values,
'\n')
notConverged = np.abs(
x[0] - sigma.Interfacial_Composition.values[1]) > epsilonX
print('convergence: ', not notConverged, x[0],
sigma.Interfacial_Composition.values[1])
x[0] = sigma.Interfacial_Composition.values[1]
# Store result
if (np.abs(sigma.Interfacial_Energy.values) > 1E-6):
# store results in pandas dataframe
results = results.append(
{
'temperature':
T,
'n_phase1':
phasesAtEquilibriumMolarAmounts['LIQUID#1'],
'n_phase2':
phasesAtEquilibriumMolarAmounts['LIQUID_AUTO#2'],
'xU_phase1':
phasesAtEquilibriumElementCompositions['LIQUID#1']
['U'],
'xU_phase2':
phasesAtEquilibriumElementCompositions['LIQUID_AUTO#2']
['U'],
'xU_interface':
sigma.Interfacial_Composition.values[1],
'sigma':
sigma.Interfacial_Energy.values,
'VmU':
functions[1](T),
'VmO':
functions[0](T),
},
ignore_index=True)
else:
raise ValueError('wrong value discarded')
else:
print('at T=', T, ' out of the miscibility gap')
print('phases at equilibrium:', phasesAtEquilibriumMolarAmounts)
# write csv result file
results.to_csv('macro_liquidMG_UO_run.csv')
def run3(tdbFile, RUZr):
print(
'### test U-O-Zr-Fe coherent interface in the liquid miscibility gap ###\n'
)
# components
comps = ['O', 'U', 'ZR', 'FE']
# mass density laws (from Barrachin2004)
constituentDensityLaws = {
'U1':
lambda T: 17270.0 - 1.358 * (T - 1408),
'ZR1':
lambda T: 6844.51 - 0.609898 * T + 2.05008E-4 * T**2 - 4.47829E-8 * T**
3 + 3.26469E-12 * T**4,
'O2U1':
lambda T: 8860.0 - 9.285E-1 * (T - 3120),
'O2ZR1':
lambda T: 5150 - 0.445 * (T - 2983),
'FE1':
lambda T: 7030 - 0.88 * (T - 1808),
'NI1':
lambda T: 7900 - 1.19 * (T - 1728),
'CR1':
lambda T: 6290 - 0.72 * (T - 2178),
'O1':
lambda T:
1.141, # set to meaningless value but ok as, no 'free' oxygen in the considered mixtures
'FE1O1':
lambda T: 7030 - 0.88 * (
T - 1808
), # set to Fe value but ok as, almost no such component in the considered mixtures
'FE1O1_5':
lambda T: 7030 - 0.88 * (
T - 1808
), # set to Fe value but ok as, almost no such component in the considered mixtures
}
# phase names
phasenames = ['LIQUID', 'LIQUID']
# pressure
P = 1E5
# initial alloy compositions. x0 is the mole fractions of U, Zr, Fe.
read = pd.read_csv('tests/{0:2.1f}RUZr.csv'.format(RUZr),
delim_whitespace=True)
# Composition step for searching initial interfacial equilibrium composition.
#dx = 0.5
# Convergence criterion for loop on interfacial composition
epsilonX = 1E-4
# temperature range
T = 3000
# Trange = np.linspace(Tmin, Tmax, num=10, endpoint=True)
results = pd.DataFrame(columns=[
'temperature', 'n_phase1', 'n_phase2', 'xU_phase1', 'xU_phase2',
'xZr_phase1', 'xZr_phase2', 'xFe_phase1', 'xFe_phase2', 'xU_interface',
'xZr_interface', 'xFe_interface', 'sigma', 'VmU', 'VmZr', 'VmFe'
])
x = None
for ii in range(read.shape[0]):
x0 = [read['xU'][ii], read['xZr'][ii], read['xFe'][ii]]
print("*********({0:d}/{1:d})*********".format(ii + 1, read.shape[0]))
print("x0: ", x0)
# calculate global equilibrium and retrieve associated chemical potentials
CoherentGibbsEnergy_OC.initOC(tdbFile, comps)
oc.raw().pytqtgsw(4) # no merging of grid points
#oc.raw().pytqtgsw(23) # denser grid
model = CoherentGibbsEnergy_OC(T, 1E5, phasenames)
mueq = model.chemicalpotential(x0)
phasesAtEquilibrium = oc.getPhasesAtEquilibrium()
phasesAtEquilibriumMolarAmounts = phasesAtEquilibrium.getPhaseMolarAmounts(
)
if (len(phasesAtEquilibriumMolarAmounts) == 1):
# it is possible that the miscibility gap has not been detected correctly (can happen when T increases)
#print(phasesAtEquilibriumMolarAmounts)
# ad hoc strategy: 1) calculate an equilibrium at lower temperature (hopefully finding the two phases)
# 2) redo the calculation at the target temperature afterwards without the grid minimizer
model = CoherentGibbsEnergy_OC(2900, 1E5, phasenames)
mueq = model.chemicalpotential(x0)
phasesAtEquilibrium = oc.getPhasesAtEquilibrium()
phasesAtEquilibriumMolarAmounts = phasesAtEquilibrium.getPhaseMolarAmounts(
)
#print(phasesAtEquilibriumMolarAmounts)
oc.setTemperature(T)
oc.calculateEquilibrium(gmStat.Off)
mueq = model.getChemicalPotentials()
phasesAtEquilibrium = oc.getPhasesAtEquilibrium()
phasesAtEquilibriumMolarAmounts = phasesAtEquilibrium.getPhaseMolarAmounts(
)
phasesAtEquilibriumElementCompositions = phasesAtEquilibrium.getPhaseElementComposition(
)
print(phasesAtEquilibriumMolarAmounts)
if (set(phasesAtEquilibriumMolarAmounts) == set(
['LIQUID#1', 'LIQUID_AUTO#2'])):
# Composition range for searching initial interfacial equilibrium composition
# calculated from the actual phase compositions
componentsWithLimits = comps[1:]
#limit = [ [1.0, 0.0] for each in componentsWithLimits ]
#for phase in phasesAtEquilibriumElementCompositions:
#for element in phasesAtEquilibriumElementCompositions[phase]:
# elementMolarFraction = phasesAtEquilibriumElementCompositions[phase][element]
# if element in componentsWithLimits:
# limit[componentsWithLimits.index(element)][0] = min(limit[componentsWithLimits.index(element)][0], elementMolarFraction)
# limit[componentsWithLimits.index(element)][1] = max(limit[componentsWithLimits.index(element)][1], elementMolarFraction)
#limit = [ [each[0]+dx*(each[1]-each[0]), each[1]-dx*(each[1]-each[0])] for each in limit ]
bulkX = [[
phasesAtEquilibriumElementCompositions[phase][element]
for phase in phasesAtEquilibriumMolarAmounts
] for element in componentsWithLimits]
notConverged = True
if (x == None):
x = [
0.5 *
(phasesAtEquilibriumElementCompositions['LIQUID#1'][comp] +
phasesAtEquilibriumElementCompositions['LIQUID_AUTO#2']
[comp]) for comp in componentsWithLimits
]
# Iterate on interfacial molar composition
while (notConverged):
# Molar volumes of pure components evaluated at x
CoherentGibbsEnergy_OC.initOC(tdbFile, comps)
model = CoherentGibbsEnergy_OC(T, P, phasenames[0], False)
if ('TAF' in tdbFile):
functions = model.constantPartialMolarVolumeFunctions(
x, constituentDensityLaws, 1E-5,
constituentToEndmembersConverter)
else:
functions = model.constantPartialMolarVolumeFunctions(
x, constituentDensityLaws, 1E-5)
# calculate interfacial energy
sigma = SigmaCoherent_OC2(
T=T,
x0=x0,
db=tdbFile,
comps=comps,
phasenames=phasenames,
purevms=functions,
guess=x,
computeEquilibriumFunction=partial(
ComputeEquilibriumWithConstraints, bulkX=bulkX),
enforceGridMinimizerForLocalEq=False,
mueq=mueq)
print('at T=', T, ' sigma=', sigma.Interfacial_Energy.values,
'\n')
notConverged = np.linalg.norm(
x[:] - sigma.Interfacial_Composition.values[1:],
np.inf) > epsilonX
print('convergence: ', not notConverged, x[:],
sigma.Interfacial_Composition.values[1:])
x[:] = sigma.Interfacial_Composition.values[1:]
# store results in pandas dataframe
if (np.abs(sigma.Interfacial_Energy.values) > 1E-5):
print(sigma, "\n")
if (abs(
np.max(sigma.Partial_Interfacial_Energy.values) -
np.min(sigma.Partial_Interfacial_Energy.values)) >
1E-4):
print(np.min(sigma.Partial_Interfacial_Energy.values))
print(np.max(sigma.Partial_Interfacial_Energy.values))
raise ValueError('wrong value discarded')
results = results.append(
{
'temperature':
T,
'n_phase1':
phasesAtEquilibriumMolarAmounts['LIQUID#1'],
'n_phase2':
phasesAtEquilibriumMolarAmounts['LIQUID_AUTO#2'],
'xU_phase1':
phasesAtEquilibriumElementCompositions['LIQUID#1']
['U'],
'xU_phase2':
phasesAtEquilibriumElementCompositions['LIQUID_AUTO#2']
['U'],
'xZr_phase1':
phasesAtEquilibriumElementCompositions['LIQUID#1']
['ZR'],
'xZr_phase2':
phasesAtEquilibriumElementCompositions['LIQUID_AUTO#2']
['ZR'],
'xFe_phase1':
phasesAtEquilibriumElementCompositions['LIQUID#1']
['FE'],
'xFe_phase2':
phasesAtEquilibriumElementCompositions['LIQUID_AUTO#2']
['FE'],
'xU_interface':
sigma.Interfacial_Composition.values[1],
'xZr_interface':
sigma.Interfacial_Composition.values[2],
'xFe_interface':
sigma.Interfacial_Composition.values[3],
'sigma':
sigma.Interfacial_Energy.values,
'VmU':
functions[1](T),
'VmZr':
functions[2](T),
'VmFe':
functions[3](T),
'VmO':
functions[0](T),
},
ignore_index=True)
else:
raise ValueError('wrong value discarded')
else:
print('at T=', T, ' out of the miscibility gap')
print('phases at equilibrium:', phasesAtEquilibriumMolarAmounts)
# write csv result file
if ('TAF' in tdbFile):
results.to_csv(
'macro_liquidMG_UOZrFe_run3_TAFID_RUZR={0:2.1f}.csv'.format(RUZr))
else:
results.to_csv(
'macro_liquidMG_UOZrFe_run3_RUZR={0:2.1f}.csv'.format(RUZr))
def run2():
print(
'### test U-O coherent interface in the liquid miscibility gap ###\n')
# tdb filepath
#tdbFile=os.environ['TDBDATA_PRIVATE']+'/feouzr.tdb'
#tdbFile=os.environ['TDBDATA_PRIVATE']+'/NUCLEA-17_1_mod.TDB'
#tdbFile=os.environ['TDBDATA_PRIVATE']+'/NUCLEA-19_1_mod.TDB'
tdbFile = 'tests/TAF_uzrofe_V10.TDB'
# components
comps = ['O', 'U', 'ZR', 'FE']
# mass density laws (from Barrachin2004)
constituentDensityLaws = {
'U1':
lambda T: 17270.0 - 1.358 * (T - 1408),
'ZR1':
lambda T: 6844.51 - 0.609898 * T + 2.05008E-4 * T**2 - 4.47829E-8 * T**
3 + 3.26469E-12 * T**4,
'O2U1':
lambda T: 8860.0 - 9.285E-1 * (T - 3120),
'O2ZR1':
lambda T: 5150 - 0.445 * (T - 2983),
'FE1':
lambda T: 7030 - 0.88 * (T - 1808),
'NI1':
lambda T: 7900 - 1.19 * (T - 1728),
'CR1':
lambda T: 6290 - 0.72 * (T - 2178),
'O1':
lambda T:
1.141, # set to meaningless value but ok as, no 'free' oxygen in the considered mixtures
'FE1O1':
lambda T: 7030 - 0.88 * (
T - 1808
), # set to Fe value but ok as, almost no such component in the considered mixtures
'FE1O1_5':
lambda T: 7030 - 0.88 * (
T - 1808
), # set to Fe value but ok as, almost no such component in the considered mixtures
}
constituentDensityLaws['U'] = constituentDensityLaws['U1']
constituentDensityLaws['ZR'] = constituentDensityLaws['ZR1']
constituentDensityLaws['O'] = constituentDensityLaws['O1']
constituentDensityLaws['FE'] = constituentDensityLaws['FE1']
# phase names
phasenames = ['LIQUID', 'LIQUID']
# pressure
P = 1E5
# Given initial alloy composition. x0 is the mole fractions of U, Zr, Fe.
# RU/Zr=0.60 CZr=0.3 xSteel=0.1
x0 = [0.1550142, 0.2583569, 0.1215864]
# Composition step for searching initial interfacial equilibrium composition.
#dx = 0.5
# Convergence criterion for loop on interfacial composition
epsilonX = 1E-5
inputs = pd.read_csv('macro_liquidMG_UOZrFe_run.csv')
results = pd.DataFrame(columns=[
'temperature', 'n_phase1', 'n_phase2', 'xU_phase1', 'xU_phase2',
'xZr_phase1', 'xZr_phase2', 'xFe_phase1', 'xFe_phase2', 'xU_interface',
'xZr_interface', 'xFe_interface', 'VmU', 'VmZr', 'VmFe', 'sigma'
])
x = None
for i, T in enumerate(inputs['temperature']):
# calculate global equilibrium and retrieve associated chemical potentials
CoherentGibbsEnergy_OC.initOC(tdbFile, comps)
oc.raw().pytqtgsw(4) # no merging of grid points
#oc.raw().pytqtgsw(23) # denser grid
model = CoherentGibbsEnergy_OC(T, 1E5, phasenames)
mueq = model.chemicalpotential(x0)
phasesAtEquilibrium = oc.getPhasesAtEquilibrium()
phasesAtEquilibriumMolarAmounts = phasesAtEquilibrium.getPhaseMolarAmounts(
)
if (len(phasesAtEquilibriumMolarAmounts) == 1):
# it is possible that the miscibility gap has not been detected correctly (can happen when T increases)
#print(phasesAtEquilibriumMolarAmounts)
# ad hoc strategy: 1) calculate an equilibrium at lower temperature (hopefully finding the two phases)
# 2) redo the calculation at the target temperature afterwards without the grid minimizer
model = CoherentGibbsEnergy_OC(2800.0, 1E5, phasenames)
mueq = model.chemicalpotential(x0)
phasesAtEquilibrium = oc.getPhasesAtEquilibrium()
phasesAtEquilibriumMolarAmounts = phasesAtEquilibrium.getPhaseMolarAmounts(
)
#print(phasesAtEquilibriumMolarAmounts)
oc.setTemperature(T)
oc.calculateEquilibrium(gmStat.Off)
mueq = model.getChemicalPotentials()
phasesAtEquilibrium = oc.getPhasesAtEquilibrium()
phasesAtEquilibriumMolarAmounts = phasesAtEquilibrium.getPhaseMolarAmounts(
)
phasesAtEquilibriumElementCompositions = phasesAtEquilibrium.getPhaseElementComposition(
)
print(phasesAtEquilibriumMolarAmounts)
print(phasesAtEquilibriumElementCompositions)
if (set(phasesAtEquilibriumMolarAmounts) == set(
['LIQUID#1', 'LIQUID_AUTO#2'])):
# Composition range for searching initial interfacial equilibrium composition
# calculated from the actual phase compositions
componentsWithLimits = comps[1:]
#limit = [ [1.0, 0.0] for each in componentsWithLimits ]
#for phase in phasesAtEquilibriumElementCompositions:
# for element in phasesAtEquilibriumElementCompositions[phase]:
# elementMolarFraction = phasesAtEquilibriumElementCompositions[phase][element]
# if element in componentsWithLimits:
# limit[componentsWithLimits.index(element)][0] = min(limit[componentsWithLimits.index(element)][0], elementMolarFraction)
# limit[componentsWithLimits.index(element)][1] = max(limit[componentsWithLimits.index(element)][1], elementMolarFraction)
#limit = [ [each[0]+dx*(each[1]-each[0]), each[1]-dx*(each[1]-each[0])] for each in limit ]
bulkX = [[
phasesAtEquilibriumElementCompositions[phase][element]
for phase in phasesAtEquilibriumMolarAmounts
] for element in componentsWithLimits]
if (x == None):
x = [
0.5 *
(phasesAtEquilibriumElementCompositions['LIQUID#1'][comp] +
phasesAtEquilibriumElementCompositions['LIQUID_AUTO#2']
[comp]) for comp in componentsWithLimits
]
#x = x0.copy()
# Molar volumes of pure components evaluated at x
functions = [
lambda _: inputs['VmO'][i], lambda _: inputs['VmU'][i],
lambda _: inputs['VmZr'][i], lambda _: inputs['VmFe'][i]
]
# calculate interfacial energy
sigma = SigmaCoherent_OC2(T=T,
x0=x0,
db=tdbFile,
comps=comps,
phasenames=phasenames,
purevms=functions,
guess=x,
computeEquilibriumFunction=partial(
ComputeEquilibriumWithConstraints,
bulkX=bulkX),
enforceGridMinimizerForLocalEq=False,
mueq=mueq)
print('at T=', T, ' sigma=', sigma.Interfacial_Energy.values, '\n')
x[:] = sigma.Interfacial_Composition.values[1:]
# Store result
if (np.abs(sigma.Interfacial_Energy.values) > 1E-6):
# store results in pandas dataframe
print(sigma, "\n")
results = results.append(
{
'temperature':
T,
'n_phase1':
phasesAtEquilibriumMolarAmounts['LIQUID#1'],
'n_phase2':
phasesAtEquilibriumMolarAmounts['LIQUID_AUTO#2'],
'xU_phase1':
phasesAtEquilibriumElementCompositions['LIQUID#1']
['U'],
'xU_phase2':
phasesAtEquilibriumElementCompositions['LIQUID_AUTO#2']
['U'],
'xZr_phase1':
phasesAtEquilibriumElementCompositions['LIQUID#1']
['ZR'],
'xZr_phase2':
phasesAtEquilibriumElementCompositions['LIQUID_AUTO#2']
['ZR'],
'xFe_phase1':
phasesAtEquilibriumElementCompositions['LIQUID#1']
['FE'],
'xFe_phase2':
phasesAtEquilibriumElementCompositions['LIQUID_AUTO#2']
['FE'],
'xU_interface':
sigma.Interfacial_Composition.values[1],
'xZr_interface':
sigma.Interfacial_Composition.values[2],
'xFe_interface':
sigma.Interfacial_Composition.values[3],
'sigma':
sigma.Interfacial_Energy.values,
'VmU':
functions[0](T),
'VmZr':
functions[1](T),
'VmFe':
functions[2](T),
},
ignore_index=True)
else:
print(sigma, "\n")
raise ValueError('wrong value discarded')
else:
print('at T=', T, ' out of the miscibility gap')
print('phases at equilibrium:', phasesAtEquilibriumMolarAmounts)
# write csv result file
results.to_csv('macro_liquidMG_UOZrFe_run2.csv')
oc.setPressure(1E5)
# set temperature
oc.setTemperature(2800)
## suspend all phases except the liquid one
oc.setPhasesStatus(('* ', ), phStat.Suspended)
oc.setPhasesStatus(('LIQUID', ), phStat.Entered)
oc.setElementMolarAmounts(x0)
# calculate equilibrium
oc.changeEquilibriumRecord('eq2')
oc.calculateEquilibrium(gmStat.Off)
# retrieving mu data
phasesAtEquilibrium = oc.getPhasesAtEquilibrium()
phaseConstituentComposition = phasesAtEquilibrium.getPhaseConstituentComposition(
)
mueq_inf = oc.getChemicalPotentials()
# calculate equilibrium with the grid-minimizer (equilibrium record = default equilibrium)
oc.changeEquilibriumRecord()
oc.calculateEquilibrium()
# retrieving mu data
phasesAtEquilibrium = oc.getPhasesAtEquilibrium()
phaseConstituentComposition = phasesAtEquilibrium.getPhaseConstituentComposition(
)
mueq = oc.getChemicalPotentials()
# Use of molarVolume class
def run_TAFID():
print(
'### test U-O coherent interface in the liquid miscibility gap ###\n')
# tdb filepath
tdbFile = os.environ['TDBDATA_PRIVATE'] + '/feouzr.tdb'
# tdbFile=os.environ['TDBDATA_PRIVATE']+'/NUCLEA-17_1_mod.TDB'
# tdbFile='tests/TAF_uzrofe_V10.TDB'
# components
comps = ['O', 'U']
# mass density laws (from Barrachin2004)
constituentDensityLaws = {
'U1':
lambda T: 17270.0 - 1.358 * (T - 1408),
'ZR1':
lambda T: 6844.51 - 0.609898 * T + 2.05008E-4 * T**2 - 4.47829E-8 * T**
3 + 3.26469E-12 * T**4,
'O2U1':
lambda T: 8860.0 - 9.285E-1 * (T - 3120),
'O2ZR1':
lambda T: 5150 - 0.445 * (T - 2983),
'O1':
lambda T:
1.141 # set to meaningless value but ok as, no 'free' oxygen in the considered mixtures
}
constituentDensityLaws['U'] = constituentDensityLaws['U1']
constituentDensityLaws['ZR'] = constituentDensityLaws['ZR1']
constituentDensityLaws['O'] = constituentDensityLaws['O1']
# phase names
phasenames = ['LIQUID#1', 'LIQUID#2']
# pressure & temp
P = 1E5
T = 3200
# Given initial alloy composition. x0 is the mole fraction of U.
x0min = [0.5]
x0max = [0.7]
x0range = np.linspace(x0min[0], x0max[0], num=20, endpoint=True)
# Composition step for searching initial interfacial equilibrium composition.
dx = 0.05
results_1 = pd.DataFrame(
columns=['X_U', 'n_phase1', 'n_phase2', 'mu_U', 'mu_O'])
for x0 in x0range:
# Molar volumes of pure components evaluated at x0 and kept constant afterwards
CoherentGibbsEnergy_OC.initOC(tdbFile, comps)
model = CoherentGibbsEnergy_OC(T, P, phasenames[0], False)
# # functions=model.constantPartialMolarVolumeFunctions(x0, constituentDensityLaws, 1E-5, constituentToEndmembersConverter)
functions = model.constantPartialMolarVolumeFunctions(
[x0], constituentDensityLaws, 1E-5)
# calculate global equilibrium and retrieve associated chemical potentials
model = CoherentGibbsEnergy_OC(T, 1E5, phasenames)
mueq = model.chemicalpotential([x0])
print('mu_U= ', mueq[1])
phasesAtEquilibrium = oc.getPhasesAtEquilibrium()
phasesAtEquilibriumMolarAmounts = phasesAtEquilibrium.getPhaseMolarAmounts(
)
phasesAtEquilibriumElementCompositions = phasesAtEquilibrium.getPhaseElementComposition(
)
print(phasesAtEquilibriumMolarAmounts)
if (set(phasesAtEquilibriumMolarAmounts) == set(
['LIQUID#1', 'LIQUID_AUTO#2'])):
# Composition range for searching initial interfacial equilibrium composition
# calculated from the actual phase compositions
componentsWithLimits = comps[1:]
limit = [[1.0, 0.0] for each in componentsWithLimits]
for phase in phasesAtEquilibriumElementCompositions:
for element in phasesAtEquilibriumElementCompositions[phase]:
elementMolarFraction = phasesAtEquilibriumElementCompositions[
phase][element]
if element in componentsWithLimits:
limit[componentsWithLimits.index(element)][0] = min(
limit[componentsWithLimits.index(element)][0],
elementMolarFraction)
limit[componentsWithLimits.index(element)][1] = max(
limit[componentsWithLimits.index(element)][1],
elementMolarFraction)
limit = [[each[0] + dx, each[1] - dx] for each in limit]
print('limits: ', limit)
# store results in pandas dataframe
results_1 = results_1.append(
{
'X_U': x0,
'n_phase1': phasesAtEquilibriumMolarAmounts['LIQUID#1'],
'n_phase2':
phasesAtEquilibriumMolarAmounts['LIQUID_AUTO#2'],
'mu_U': mueq[1],
'mu_O': mueq[0],
},
ignore_index=True)
results_1.to_csv('UO_muvsx_TAFID.csv')