def createFluxDiagram(inputFile, chemkinFile, speciesDict, savePath=None, speciesPath=None, java=False, settings=None,
chemkinOutput='', centralSpecies=None, diffusionLimited=True, checkDuplicates=True):
"""
Generates the flux diagram based on a condition 'inputFile', chemkin.inp chemkinFile,
a speciesDict txt file, plus an optional chemkinOutput file.
"""
if speciesPath is None:
speciesPath = os.path.join(os.path.dirname(inputFile), 'species')
generateImages = True
else:
generateImages = False
rmg = loadRMGJob(inputFile, chemkinFile, speciesDict,
generateImages=generateImages, useJava=java, checkDuplicates=checkDuplicates)
if savePath is None:
savePath = os.path.join(rmg.outputDirectory, 'flux')
# if you have a chemkin output, then you only have one reactionSystem
if chemkinOutput:
outDir = os.path.join(savePath, '1')
try:
os.makedirs(outDir)
except OSError:
pass
print 'Extracting species concentrations and calculating reaction rates from chemkin output...'
time, coreSpeciesConcentrations, coreReactionRates, edgeReactionRates = loadChemkinOutput(chemkinOutput, rmg.reactionModel)
print 'Generating flux diagram for chemkin output...'
generateFluxDiagram(rmg.reactionModel, time, coreSpeciesConcentrations, coreReactionRates, outDir, centralSpecies, speciesPath, settings)
else:
# Generate a flux diagram video for each reaction system
for index, reactionSystem in enumerate(rmg.reactionSystems):
outDir = os.path.join(savePath, '{0:d}'.format(index+1))
try:
os.makedirs(outDir)
except OSError:
# Fail silently on any OS errors
pass
# Enable diffusion-limited rates
if diffusionLimited and isinstance(reactionSystem, LiquidReactor):
rmg.loadDatabase()
solventData = rmg.database.solvation.getSolventData(rmg.solvent)
diffusionLimiter.enable(solventData, rmg.database.solvation)
# If there is no termination time, then add one to prevent jobs from
# running forever
if not any([isinstance(term, TerminationTime) for term in reactionSystem.termination]):
reactionSystem.termination.append(TerminationTime((1e10,'s')))
print 'Conducting simulation of reaction system {0:d}...'.format(index+1)
time, coreSpeciesConcentrations, coreReactionRates, edgeReactionRates = simulate(rmg.reactionModel, reactionSystem, settings)
print 'Generating flux diagram for reaction system {0:d}...'.format(index+1)
generateFluxDiagram(rmg.reactionModel, time, coreSpeciesConcentrations, coreReactionRates, outDir,
centralSpecies, speciesPath, settings)
def createFluxDiagram(inputFile, chemkinFile, speciesDict, savePath=None, speciesPath=None, java=False, settings=None,
chemkinOutput='', centralSpecies=None, diffusionLimited=True):
"""
Generates the flux diagram based on a condition 'inputFile', chemkin.inp chemkinFile,
a speciesDict txt file, plus an optional chemkinOutput file.
"""
if speciesPath is None:
speciesPath = os.path.join(os.path.dirname(inputFile), 'species')
generateImages = True
else:
generateImages = False
rmg = loadRMGJob(inputFile, chemkinFile, speciesDict, generateImages=generateImages, useJava=java)
if savePath is None:
savePath = os.path.join(rmg.outputDirectory, 'flux')
# if you have a chemkin output, then you only have one reactionSystem
if chemkinOutput:
outDir = os.path.join(savePath, '1')
try:
os.makedirs(outDir)
except OSError:
pass
print 'Extracting species concentrations and calculating reaction rates from chemkin output...'
time, coreSpeciesConcentrations, coreReactionRates, edgeReactionRates = loadChemkinOutput(chemkinOutput, rmg.reactionModel)
print 'Generating flux diagram for chemkin output...'
generateFluxDiagram(rmg.reactionModel, time, coreSpeciesConcentrations, coreReactionRates, outDir, centralSpecies, speciesPath, settings)
else:
# Generate a flux diagram video for each reaction system
for index, reactionSystem in enumerate(rmg.reactionSystems):
outDir = os.path.join(savePath, '{0:d}'.format(index+1))
try:
os.makedirs(outDir)
except OSError:
# Fail silently on any OS errors
pass
# Enable diffusion-limited rates
if diffusionLimited and isinstance(reactionSystem, LiquidReactor):
rmg.loadDatabase()
solventData = rmg.database.solvation.getSolventData(rmg.solvent)
diffusionLimiter.enable(solventData, rmg.database.solvation)
# If there is no termination time, then add one to prevent jobs from
# running forever
if not any([isinstance(term, TerminationTime) for term in reactionSystem.termination]):
reactionSystem.termination.append(TerminationTime((1e10,'s')))
print 'Conducting simulation of reaction system {0:d}...'.format(index+1)
time, coreSpeciesConcentrations, coreReactionRates, edgeReactionRates = simulate(rmg.reactionModel, reactionSystem, settings)
print 'Generating flux diagram for reaction system {0:d}...'.format(index+1)
generateFluxDiagram(rmg.reactionModel, time, coreSpeciesConcentrations, coreReactionRates, outDir,
centralSpecies, speciesPath, settings)
def setUp(self):
"""
A function run before each unit test in this class.
"""
octyl_pri = Species(label="", thermo=NASA(polynomials=[
NASAPolynomial(coeffs=[-0.772759,0.093255,-5.84447e-05,1.8557e-08,-2.37127e-12,-3926.9,37.6131], Tmin=(298,'K'), Tmax=(1390,'K')),
NASAPolynomial(coeffs=[25.051,0.036948,-1.25765e-05,1.94628e-09,-1.12669e-13,-13330.1,-102.557], Tmin=(1390,'K'), Tmax=(5000,'K'))
],
Tmin=(298,'K'), Tmax=(5000,'K'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(577.856,'J/(mol*K)'),
comment="""Thermo library: JetSurF0.2"""), molecule=[Molecule(SMILES="[CH2]CCCCCCC")])
octyl_sec = Species(label="", thermo=NASA(polynomials=[
NASAPolynomial(coeffs=[-0.304233,0.0880077,-4.90743e-05,1.21858e-08,-8.87773e-13,-5237.93,36.6583], Tmin=(298,'K'), Tmax=(1383,'K')),
NASAPolynomial(coeffs=[24.9044,0.0366394,-1.2385e-05,1.90835e-09,-1.10161e-13,-14713.5,-101.345], Tmin=(1383,'K'), Tmax=(5000,'K'))
],
Tmin=(298,'K'), Tmax=(5000,'K'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(577.856,'J/(mol*K)'),
comment="""Thermo library: JetSurF0.2"""), molecule=[Molecule(SMILES="CC[CH]CCCCC")])
ethane = Species(label="", thermo=ThermoData(
Tdata=([300,400,500,600,800,1000,1500],'K'), Cpdata=([10.294,12.643,14.933,16.932,20.033,22.438,26.281],'cal/(mol*K)'), H298=(12.549,'kcal/mol'), S298=(52.379,'cal/(mol*K)'),
Cp0=(33.2579,'J/(mol*K)'), CpInf=(133.032,'J/(mol*K)'), comment="""Thermo library: CH"""),
molecule=[Molecule(SMILES="C=C")])
decyl = Species(label="", thermo=NASA(polynomials=[
NASAPolynomial(coeffs=[-1.31358,0.117973,-7.51843e-05,2.43331e-08,-3.17523e-12,-9689.68,43.501], Tmin=(298,'K'), Tmax=(1390,'K')),
NASAPolynomial(coeffs=[31.5697,0.0455818,-1.54995e-05,2.39711e-09,-1.3871e-13,-21573.8,-134.709], Tmin=(1390,'K'), Tmax=(5000,'K'))
],
Tmin=(298,'K'), Tmax=(5000,'K'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(719.202,'J/(mol*K)'),
comment="""Thermo library: JetSurF0.2"""), molecule=[Molecule(SMILES="[CH2]CCCCCCCCC")])
self.database = SolvationDatabase()
self.database.load(os.path.join(settings['database.directory'], 'solvation'))
self.solvent = 'octane'
diffusionLimiter.enable(self.database.getSolventData(self.solvent), self.database)
self.T = 298
self.uni_reaction = Reaction(reactants=[octyl_pri], products=[octyl_sec])
self.uni_reaction.kinetics = Arrhenius(A=(2.0, '1/s'), n=0, Ea=(0,'kJ/mol'))
self.bi_uni_reaction = Reaction(reactants=[octyl_pri, ethane], products=[decyl])
self.bi_uni_reaction.kinetics = Arrhenius(A=(1.0E-22, 'cm^3/molecule/s'), n=0, Ea=(0,'kJ/mol'))
self.intrinsic_rates = {
self.uni_reaction: self.uni_reaction.kinetics.getRateCoefficient(self.T, P=100e5),
self.bi_uni_reaction: self.bi_uni_reaction.kinetics.getRateCoefficient(self.T, P=100e5),
}
def setUp(self):
"""
A function run before each unit test in this class.
"""
octyl_pri = Species(
label="",
thermo=NASA(polynomials=[
NASAPolynomial(coeffs=[
-0.772759, 0.093255, -5.84447e-05, 1.8557e-08,
-2.37127e-12, -3926.9, 37.6131
],
Tmin=(298, 'K'),
Tmax=(1390, 'K')),
NASAPolynomial(coeffs=[
25.051, 0.036948, -1.25765e-05, 1.94628e-09, -1.12669e-13,
-13330.1, -102.557
],
Tmin=(1390, 'K'),
Tmax=(5000, 'K'))
],
Tmin=(298, 'K'),
Tmax=(5000, 'K'),
Cp0=(33.2579, 'J/(mol*K)'),
CpInf=(577.856, 'J/(mol*K)'),
comment="""Thermo library: JetSurF0.2"""),
molecule=[Molecule(SMILES="[CH2]CCCCCCC")])
octyl_sec = Species(
label="",
thermo=NASA(polynomials=[
NASAPolynomial(coeffs=[
-0.304233, 0.0880077, -4.90743e-05, 1.21858e-08,
-8.87773e-13, -5237.93, 36.6583
],
Tmin=(298, 'K'),
Tmax=(1383, 'K')),
NASAPolynomial(coeffs=[
24.9044, 0.0366394, -1.2385e-05, 1.90835e-09, -1.10161e-13,
-14713.5, -101.345
],
Tmin=(1383, 'K'),
Tmax=(5000, 'K'))
],
Tmin=(298, 'K'),
Tmax=(5000, 'K'),
Cp0=(33.2579, 'J/(mol*K)'),
CpInf=(577.856, 'J/(mol*K)'),
comment="""Thermo library: JetSurF0.2"""),
molecule=[Molecule(SMILES="CC[CH]CCCCC")])
ethane = Species(label="",
thermo=ThermoData(
Tdata=([300, 400, 500, 600, 800, 1000,
1500], 'K'),
Cpdata=([
10.294, 12.643, 14.933, 16.932, 20.033,
22.438, 26.281
], 'cal/(mol*K)'),
H298=(12.549, 'kcal/mol'),
S298=(52.379, 'cal/(mol*K)'),
Cp0=(33.2579, 'J/(mol*K)'),
CpInf=(133.032, 'J/(mol*K)'),
comment="""Thermo library: CH"""),
molecule=[Molecule(SMILES="C=C")])
decyl = Species(label="",
thermo=NASA(polynomials=[
NASAPolynomial(coeffs=[
-1.31358, 0.117973, -7.51843e-05, 2.43331e-08,
-3.17523e-12, -9689.68, 43.501
],
Tmin=(298, 'K'),
Tmax=(1390, 'K')),
NASAPolynomial(coeffs=[
31.5697, 0.0455818, -1.54995e-05, 2.39711e-09,
-1.3871e-13, -21573.8, -134.709
],
Tmin=(1390, 'K'),
Tmax=(5000, 'K'))
],
Tmin=(298, 'K'),
Tmax=(5000, 'K'),
Cp0=(33.2579, 'J/(mol*K)'),
CpInf=(719.202, 'J/(mol*K)'),
comment="""Thermo library: JetSurF0.2"""),
molecule=[Molecule(SMILES="[CH2]CCCCCCCCC")])
acetone = Species(label="",
thermo=NASA(polynomials=[
NASAPolynomial(coeffs=[
3.75568, 0.0264934, -6.55661e-05,
1.94971e-07, -1.82059e-10, -27905.3, 9.0162
],
Tmin=(10, 'K'),
Tmax=(422.477, 'K')),
NASAPolynomial(coeffs=[
0.701289, 0.0344988, -1.9736e-05,
5.48052e-09, -5.92612e-13, -27460.6, 23.329
],
Tmin=(422.477, 'K'),
Tmax=(3000, 'K'))
],
Tmin=(10, 'K'),
Tmax=(3000, 'K'),
E0=(-232.025, 'kJ/mol'),
Cp0=(33.2579, 'J/(mol*K)'),
CpInf=(232.805, 'J/(mol*K)')),
molecule=[Molecule(SMILES="CC(=O)C")])
peracetic_acid = Species(label="",
thermo=NASA(polynomials=[
NASAPolynomial(coeffs=[
3.81786, 0.016419, 3.32204e-05,
-8.98403e-08, 6.63474e-11, -42057.8,
9.65245
],
Tmin=(10, 'K'),
Tmax=(354.579, 'K')),
NASAPolynomial(coeffs=[
2.75993, 0.0283534, -1.72659e-05,
5.08158e-09, -5.77773e-13, -41982.8,
13.6595
],
Tmin=(354.579, 'K'),
Tmax=(3000, 'K'))
],
Tmin=(10, 'K'),
Tmax=(3000, 'K'),
E0=(-349.698, 'kJ/mol'),
Cp0=(33.2579, 'J/(mol*K)'),
CpInf=(199.547, 'J/(mol*K)')),
molecule=[Molecule(SMILES="CC(=O)OO")])
acetic_acid = Species(label="",
thermo=NASA(polynomials=[
NASAPolynomial(coeffs=[
3.97665, 0.00159915, 8.5542e-05,
-1.76486e-07, 1.20201e-10, -53911.5,
8.99309
],
Tmin=(10, 'K'),
Tmax=(375.616, 'K')),
NASAPolynomial(coeffs=[
1.57088, 0.0272146, -1.67357e-05,
5.01453e-09, -5.82273e-13, -53730.7,
18.2442
],
Tmin=(375.616, 'K'),
Tmax=(3000, 'K'))
],
Tmin=(10, 'K'),
Tmax=(3000, 'K'),
E0=(-448.245, 'kJ/mol'),
Cp0=(33.2579, 'J/(mol*K)'),
CpInf=(182.918, 'J/(mol*K)')),
molecule=[Molecule(SMILES="CC(=O)O")])
criegee = Species(label="",
thermo=NASA(polynomials=[
NASAPolynomial(coeffs=[
3.23876, 0.0679583, -3.35611e-05,
7.91519e-10, 3.13038e-12, -77986, 13.6438
],
Tmin=(10, 'K'),
Tmax=(1053.46, 'K')),
NASAPolynomial(coeffs=[
9.84525, 0.0536795, -2.86165e-05,
7.39945e-09, -7.48482e-13, -79977.6, -21.4187
],
Tmin=(1053.46, 'K'),
Tmax=(3000, 'K'))
],
Tmin=(10, 'K'),
Tmax=(3000, 'K'),
E0=(-648.47, 'kJ/mol'),
Cp0=(33.2579, 'J/(mol*K)'),
CpInf=(457.296, 'J/(mol*K)')),
molecule=[Molecule(SMILES="CC(=O)OOC(C)(O)C")])
self.database = SolvationDatabase()
self.database.load(
os.path.join(settings['database.directory'], 'solvation'))
self.solvent = 'octane'
diffusionLimiter.enable(self.database.getSolventData(self.solvent),
self.database)
self.T = 298
self.uni_reaction = Reaction(reactants=[octyl_pri],
products=[octyl_sec])
self.uni_reaction.kinetics = Arrhenius(A=(2.0, '1/s'),
n=0,
Ea=(0, 'kJ/mol'))
self.bi_uni_reaction = Reaction(reactants=[octyl_pri, ethane],
products=[decyl])
self.bi_uni_reaction.kinetics = Arrhenius(A=(1.0E-22,
'cm^3/molecule/s'),
n=0,
Ea=(0, 'kJ/mol'))
self.tri_bi_reaction = Reaction(
reactants=[acetone, peracetic_acid, acetic_acid],
products=[criegee, acetic_acid])
self.tri_bi_reaction.kinetics = Arrhenius(A=(1.07543e-11,
'cm^6/(mol^2*s)'),
n=5.47295,
Ea=(-38.5379, 'kJ/mol'))
self.intrinsic_rates = {
self.uni_reaction:
self.uni_reaction.kinetics.getRateCoefficient(self.T, P=100e5),
self.bi_uni_reaction:
self.bi_uni_reaction.kinetics.getRateCoefficient(self.T, P=100e5),
self.tri_bi_reaction:
self.tri_bi_reaction.kinetics.getRateCoefficient(self.T, P=100e5),
}
def simulate(rmg, diffusionLimited=True):
"""
Simulate the RMG job and run the sensitivity analysis if it is on, generating
output csv files
diffusionLimited=True implies that if it is a liquid reactor diffusion limitations will be enforced
otherwise they will not be in a liquid reactor
"""
util.makeOutputSubdirectory(rmg.outputDirectory, 'solver')
for index, reactionSystem in enumerate(rmg.reactionSystems):
if reactionSystem.sensitiveSpecies:
logging.info(
'Conducting simulation and sensitivity analysis of reaction system %s...'
% (index + 1))
else:
logging.info('Conducting simulation of reaction system %s...' %
(index + 1))
if rmg.saveSimulationProfiles:
reactionSystem.attach(
SimulationProfileWriter(rmg.outputDirectory, index,
rmg.reactionModel.core.species))
reactionSystem.attach(
SimulationProfilePlotter(rmg.outputDirectory, index,
rmg.reactionModel.core.species))
sensWorksheet = []
for spec in reactionSystem.sensitiveSpecies:
csvfilePath = os.path.join(
rmg.outputDirectory, 'solver',
'sensitivity_{0}_SPC_{1}.csv'.format(index + 1, spec.index))
sensWorksheet.append(csvfilePath)
pdepNetworks = []
for source, networks in rmg.reactionModel.networkDict.items():
pdepNetworks.extend(networks)
modelSettings = ModelSettings(toleranceKeepInEdge=0,
toleranceMoveToCore=1,
toleranceInterruptSimulation=1)
simulatorSettings = rmg.simulatorSettingsList[-1]
if isinstance(reactionSystem, LiquidReactor):
if diffusionLimited:
rmg.loadDatabase()
solventData = rmg.database.solvation.getSolventData(
rmg.solvent)
diffusionLimiter.enable(solventData, rmg.database.solvation)
# Store constant species indices
if reactionSystem.constSPCNames is not None:
reactionSystem.get_constSPCIndices(
rmg.reactionModel.core.species)
reactionSystem.simulate(
coreSpecies=rmg.reactionModel.core.species,
coreReactions=rmg.reactionModel.core.reactions,
edgeSpecies=rmg.reactionModel.edge.species,
edgeReactions=rmg.reactionModel.edge.reactions,
surfaceSpecies=[],
surfaceReactions=[],
pdepNetworks=pdepNetworks,
sensitivity=True if reactionSystem.sensitiveSpecies else False,
sensWorksheet=sensWorksheet,
modelSettings=modelSettings,
simulatorSettings=simulatorSettings,
)
if reactionSystem.sensitiveSpecies:
plotSensitivity(rmg.outputDirectory, index,
reactionSystem.sensitiveSpecies)
def simulate(rmg, diffusionLimited=True):
"""
Simulate the RMG job and run the sensitivity analysis if it is on, generating
output csv files
diffusionLimited=True implies that if it is a liquid reactor diffusion limitations will be enforced
otherwise they will not be in a liquid reactor
"""
util.makeOutputSubdirectory(rmg.outputDirectory, 'solver')
for index, reactionSystem in enumerate(rmg.reactionSystems):
if reactionSystem.sensitiveSpecies:
logging.info('Conducting simulation and sensitivity analysis of reaction system %s...' % (index+1))
else:
logging.info('Conducting simulation of reaction system %s...' % (index+1))
if rmg.saveSimulationProfiles:
reactionSystem.attach(SimulationProfileWriter(
rmg.outputDirectory, index, rmg.reactionModel.core.species))
reactionSystem.attach(SimulationProfilePlotter(
rmg.outputDirectory, index, rmg.reactionModel.core.species))
sensWorksheet = []
for spec in reactionSystem.sensitiveSpecies:
csvfilePath = os.path.join(rmg.outputDirectory, 'solver', 'sensitivity_{0}_SPC_{1}.csv'.format(index+1, spec.index))
sensWorksheet.append(csvfilePath)
pdepNetworks = []
for source, networks in rmg.reactionModel.networkDict.items():
pdepNetworks.extend(networks)
modelSettings = ModelSettings(toleranceKeepInEdge=0, toleranceMoveToCore=1, toleranceInterruptSimulation=1)
simulatorSettings = rmg.simulatorSettingsList[-1]
if isinstance(reactionSystem, LiquidReactor):
if diffusionLimited:
rmg.loadDatabase()
solventData = rmg.database.solvation.getSolventData(rmg.solvent)
diffusionLimiter.enable(solventData, rmg.database.solvation)
# Store constant species indices
if reactionSystem.constSPCNames is not None:
reactionSystem.get_constSPCIndices(rmg.reactionModel.core.species)
reactionSystem.simulate(
coreSpecies=rmg.reactionModel.core.species,
coreReactions=rmg.reactionModel.core.reactions,
edgeSpecies=rmg.reactionModel.edge.species,
edgeReactions=rmg.reactionModel.edge.reactions,
surfaceSpecies=[],
surfaceReactions=[],
pdepNetworks=pdepNetworks,
sensitivity=True if reactionSystem.sensitiveSpecies else False,
sensWorksheet=sensWorksheet,
modelSettings=modelSettings,
simulatorSettings=simulatorSettings,
)
if reactionSystem.sensitiveSpecies:
plotSensitivity(rmg.outputDirectory, index, reactionSystem.sensitiveSpecies)
def setUp(self):
"""
A function run before each unit test in this class.
"""
octyl_pri = Species(label="", thermo=NASA(polynomials=[
NASAPolynomial(coeffs=[-0.772759,0.093255,-5.84447e-05,1.8557e-08,-2.37127e-12,-3926.9,37.6131], Tmin=(298,'K'), Tmax=(1390,'K')),
NASAPolynomial(coeffs=[25.051,0.036948,-1.25765e-05,1.94628e-09,-1.12669e-13,-13330.1,-102.557], Tmin=(1390,'K'), Tmax=(5000,'K'))
],
Tmin=(298,'K'), Tmax=(5000,'K'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(577.856,'J/(mol*K)'),
comment="""Thermo library: JetSurF0.2"""), molecule=[Molecule(SMILES="[CH2]CCCCCCC")])
octyl_sec = Species(label="", thermo=NASA(polynomials=[
NASAPolynomial(coeffs=[-0.304233,0.0880077,-4.90743e-05,1.21858e-08,-8.87773e-13,-5237.93,36.6583], Tmin=(298,'K'), Tmax=(1383,'K')),
NASAPolynomial(coeffs=[24.9044,0.0366394,-1.2385e-05,1.90835e-09,-1.10161e-13,-14713.5,-101.345], Tmin=(1383,'K'), Tmax=(5000,'K'))
],
Tmin=(298,'K'), Tmax=(5000,'K'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(577.856,'J/(mol*K)'),
comment="""Thermo library: JetSurF0.2"""), molecule=[Molecule(SMILES="CC[CH]CCCCC")])
ethane = Species(label="", thermo=ThermoData(
Tdata=([300,400,500,600,800,1000,1500],'K'), Cpdata=([10.294,12.643,14.933,16.932,20.033,22.438,26.281],'cal/(mol*K)'), H298=(12.549,'kcal/mol'), S298=(52.379,'cal/(mol*K)'),
Cp0=(33.2579,'J/(mol*K)'), CpInf=(133.032,'J/(mol*K)'), comment="""Thermo library: CH"""),
molecule=[Molecule(SMILES="C=C")])
decyl = Species(label="", thermo=NASA(polynomials=[
NASAPolynomial(coeffs=[-1.31358,0.117973,-7.51843e-05,2.43331e-08,-3.17523e-12,-9689.68,43.501], Tmin=(298,'K'), Tmax=(1390,'K')),
NASAPolynomial(coeffs=[31.5697,0.0455818,-1.54995e-05,2.39711e-09,-1.3871e-13,-21573.8,-134.709], Tmin=(1390,'K'), Tmax=(5000,'K'))
],
Tmin=(298,'K'), Tmax=(5000,'K'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(719.202,'J/(mol*K)'),
comment="""Thermo library: JetSurF0.2"""), molecule=[Molecule(SMILES="[CH2]CCCCCCCCC")])
acetone = Species(label="", thermo=NASA(polynomials=[
NASAPolynomial(coeffs = [3.75568, 0.0264934, -6.55661e-05, 1.94971e-07, -1.82059e-10, -27905.3, 9.0162], Tmin = (10, 'K'), Tmax = (422.477, 'K')),
NASAPolynomial(coeffs = [0.701289, 0.0344988, -1.9736e-05, 5.48052e-09, -5.92612e-13, -27460.6, 23.329],Tmin = (422.477, 'K'),Tmax = (3000, 'K'))
],
Tmin = (10, 'K'), Tmax = (3000, 'K'), E0 = (-232.025, 'kJ/mol'), Cp0 = (33.2579, 'J/(mol*K)'), CpInf = (232.805, 'J/(mol*K)')),
molecule=[Molecule(SMILES="CC(=O)C")])
peracetic_acid = Species(label="", thermo=NASA(polynomials=[
NASAPolynomial(coeffs = [3.81786, 0.016419, 3.32204e-05, -8.98403e-08, 6.63474e-11, -42057.8, 9.65245], Tmin = (10, 'K'), Tmax = (354.579, 'K')),
NASAPolynomial(coeffs = [2.75993, 0.0283534, -1.72659e-05, 5.08158e-09, -5.77773e-13, -41982.8, 13.6595], Tmin = (354.579, 'K'), Tmax = (3000, 'K'))
],
Tmin = (10, 'K'), Tmax = (3000, 'K'), E0 = (-349.698, 'kJ/mol'),Cp0 = (33.2579, 'J/(mol*K)'), CpInf = (199.547, 'J/(mol*K)')),
molecule=[Molecule(SMILES="CC(=O)OO")])
acetic_acid = Species(label="", thermo=NASA(polynomials=[
NASAPolynomial(coeffs = [3.97665, 0.00159915, 8.5542e-05, -1.76486e-07, 1.20201e-10, -53911.5, 8.99309], Tmin = (10, 'K'), Tmax = (375.616, 'K')),
NASAPolynomial(coeffs = [1.57088, 0.0272146, -1.67357e-05, 5.01453e-09, -5.82273e-13, -53730.7, 18.2442], Tmin = (375.616, 'K'), Tmax = (3000, 'K'))
],
Tmin = (10, 'K'), Tmax = (3000, 'K'), E0 = (-448.245, 'kJ/mol'), Cp0 = (33.2579, 'J/(mol*K)'), CpInf = (182.918, 'J/(mol*K)')),
molecule=[Molecule(SMILES="CC(=O)O")])
criegee = Species(label="", thermo=NASA(polynomials=[
NASAPolynomial(coeffs = [3.23876, 0.0679583, -3.35611e-05, 7.91519e-10, 3.13038e-12, -77986, 13.6438], Tmin = (10, 'K'), Tmax = (1053.46, 'K')),
NASAPolynomial(coeffs = [9.84525, 0.0536795, -2.86165e-05, 7.39945e-09, -7.48482e-13, -79977.6, -21.4187], Tmin = (1053.46, 'K'), Tmax = (3000, 'K'))
],
Tmin = (10, 'K'), Tmax = (3000, 'K'), E0 = (-648.47, 'kJ/mol'),Cp0 = (33.2579, 'J/(mol*K)'), CpInf = (457.296, 'J/(mol*K)')),
molecule=[Molecule(SMILES="CC(=O)OOC(C)(O)C")])
self.database = SolvationDatabase()
self.database.load(os.path.join(settings['database.directory'], 'solvation'))
self.solvent = 'octane'
diffusionLimiter.enable(self.database.getSolventData(self.solvent), self.database)
self.T = 298
self.uni_reaction = Reaction(reactants=[octyl_pri], products=[octyl_sec])
self.uni_reaction.kinetics = Arrhenius(A=(2.0, '1/s'), n=0, Ea=(0,'kJ/mol'))
self.bi_uni_reaction = Reaction(reactants=[octyl_pri, ethane], products=[decyl])
self.bi_uni_reaction.kinetics = Arrhenius(A=(1.0E-22, 'cm^3/molecule/s'), n=0, Ea=(0,'kJ/mol'))
self.tri_bi_reaction = Reaction(reactants=[acetone, peracetic_acid, acetic_acid],
products=[criegee, acetic_acid])
self.tri_bi_reaction.kinetics = Arrhenius(A=(1.07543e-11, 'cm^6/(mol^2*s)'), n=5.47295, Ea=(-38.5379, 'kJ/mol'))
self.intrinsic_rates = {
self.uni_reaction: self.uni_reaction.kinetics.getRateCoefficient(self.T, P=100e5),
self.bi_uni_reaction: self.bi_uni_reaction.kinetics.getRateCoefficient(self.T, P=100e5),
self.tri_bi_reaction: self.tri_bi_reaction.kinetics.getRateCoefficient(self.T, P=100e5),
}