def generateThermo(self):
"""
Generate the thermodynamic data for the species and fit it to the
desired heat capacity model (as specified in the `thermoClass`
attribute).
"""
if self.thermoClass.lower() not in ['wilhoit', 'nasa']:
raise Exception('Unknown thermodynamic model "{0}".'.format(
self.thermoClass))
species = self.species
logging.info('Generating {0} thermo model for {1}...'.format(
self.thermoClass, species))
Tlist = numpy.arange(10.0, 3001.0, 10.0, numpy.float64)
Cplist = numpy.zeros_like(Tlist)
H298 = 0.0
S298 = 0.0
conformer = self.species.conformer
for i in range(Tlist.shape[0]):
Cplist[i] += conformer.getHeatCapacity(Tlist[i])
H298 += conformer.getEnthalpy(298.) + conformer.E0.value_si
S298 += conformer.getEntropy(298.)
if not any([
isinstance(mode, (LinearRotor, NonlinearRotor))
for mode in conformer.modes
]):
# Monatomic species
linear = False
Nfreq = 0
Nrotors = 0
Cp0 = 2.5 * constants.R
CpInf = 2.5 * constants.R
else:
# Polyatomic species
linear = True if isinstance(conformer.modes[1],
LinearRotor) else False
Nfreq = len(conformer.modes[2].frequencies.value)
Nrotors = len(conformer.modes[3:])
Cp0 = (3.5 if linear else 4.0) * constants.R
CpInf = Cp0 + (Nfreq + 0.5 * Nrotors) * constants.R
wilhoit = Wilhoit()
if Nfreq == 0 and Nrotors == 0:
wilhoit.Cp0 = (Cplist[0], "J/(mol*K)")
wilhoit.CpInf = (Cplist[0], "J/(mol*K)")
wilhoit.B = (500., "K")
wilhoit.H0 = (0.0, "J/mol")
wilhoit.S0 = (0.0, "J/(mol*K)")
wilhoit.H0 = (H298 - wilhoit.getEnthalpy(298.15), "J/mol")
wilhoit.S0 = (S298 - wilhoit.getEntropy(298.15), "J/(mol*K)")
else:
wilhoit.fitToData(Tlist, Cplist, Cp0, CpInf, H298, S298, B0=500.0)
if self.thermoClass.lower() == 'nasa':
species.thermo = wilhoit.toNASA(Tmin=10.0, Tmax=3000.0, Tint=500.0)
else:
species.thermo = wilhoit
def generateThermo(self):
"""
Generate the thermodynamic data for the species and fit it to the
desired heat capacity model (as specified in the `thermoClass`
attribute).
"""
if self.thermoClass.lower() not in ['wilhoit', 'nasa']:
raise Exception('Unknown thermodynamic model "{0}".'.format(self.thermoClass))
species = self.species
logging.debug('Generating {0} thermo model for {1}...'.format(self.thermoClass, species))
if species.thermo is not None:
logging.info("Thermo already generated for species {}. Skipping thermo generation.".format(species))
return None
Tlist = np.arange(10.0, 3001.0, 10.0, np.float64)
Cplist = np.zeros_like(Tlist)
H298 = 0.0
S298 = 0.0
conformer = self.species.conformer
for i in range(Tlist.shape[0]):
Cplist[i] += conformer.getHeatCapacity(Tlist[i])
H298 += conformer.getEnthalpy(298.) + conformer.E0.value_si
S298 += conformer.getEntropy(298.)
if not any([isinstance(mode, (LinearRotor, NonlinearRotor)) for mode in conformer.modes]):
# Monatomic species
linear = False
Nfreq = 0
Nrotors = 0
Cp0 = 2.5 * constants.R
CpInf = 2.5 * constants.R
else:
# Polyatomic species
linear = True if isinstance(conformer.modes[1], LinearRotor) else False
Nfreq = len(conformer.modes[2].frequencies.value)
Nrotors = len(conformer.modes[3:])
Cp0 = (3.5 if linear else 4.0) * constants.R
CpInf = Cp0 + (Nfreq + 0.5 * Nrotors) * constants.R
wilhoit = Wilhoit()
if Nfreq == 0 and Nrotors == 0:
wilhoit.Cp0 = (Cplist[0],"J/(mol*K)")
wilhoit.CpInf = (Cplist[0],"J/(mol*K)")
wilhoit.B = (500.,"K")
wilhoit.H0 = (0.0,"J/mol")
wilhoit.S0 = (0.0,"J/(mol*K)")
wilhoit.H0 = (H298 -wilhoit.getEnthalpy(298.15), "J/mol")
wilhoit.S0 = (S298 - wilhoit.getEntropy(298.15),"J/(mol*K)")
else:
wilhoit.fitToData(Tlist, Cplist, Cp0, CpInf, H298, S298, B0=500.0)
if self.thermoClass.lower() == 'nasa':
species.thermo = wilhoit.toNASA(Tmin=10.0, Tmax=3000.0, Tint=500.0)
else:
species.thermo = wilhoit
Tlist = numpy.array([300.0,400.0,500.0,600.0,800.0,1000.0])
Cplist = numpy.array([24.2, 31.1, 36.9, 41.4, 48, 52.55])*4.184 #J/mol*K
H298 = 40.5*4184 #J/mol
S298 = 81.35*4.184 #J/mol*K
# Polyatomic species
linear = False
Nfreq = 30
Nrotors = 0
Cp0 = (3.5 if linear else 4.0) * constants.R
CpInf = Cp0 + (Nfreq + 0.5 * Nrotors) * constants.R
wilhoit = Wilhoit()
wilhoit.fitToData(Tlist, Cplist, Cp0, CpInf, H298, S298, B0=500.0)\
NASA_fit = wilhoit.toNASA(Tlist[0], Tlist[-1], Tint=500.0)
string = ''
f = open('chem.inp', 'a')
# Line 1
string += '{0:<16} '.format(SpeciesIdentifier)
if len(elementCounts) <= 4:
# Use the original Chemkin syntax for the element counts
for key, count in elementCounts.iteritems():
if isinstance(key, tuple):
symbol, isotope = key
chemkinName = getElement(symbol, isotope=isotope).chemkinName