def test_storeConstantSpeciesNames(self):
"Test if (i) constant species names are stored in reactor attributes and (ii) if attributes are not mix/equal for multiple conditions generation"
c0 = {self.C2H5: 0.1, self.CH3: 0.1, self.CH4: 0.4, self.C2H6: 0.4}
Temp = 1000
#
#set up the liquid phase reactor 1
terminationConversion = []
terminationTime = None
sensitivity = []
sensitivityThreshold = 0.001
constantSpecies = ["CH4", "C2H6"]
rxnSystem1 = LiquidReactor(Temp, c0, terminationConversion,
sensitivity, sensitivityThreshold,
constantSpecies)
#set up the liquid phase reactor 2
constantSpecies = ["O2", "H2O"]
rxnSystem2 = LiquidReactor(Temp, c0, terminationConversion,
sensitivity, sensitivityThreshold,
constantSpecies)
for reactor in [rxnSystem1, rxnSystem2]:
self.assertIsNotNone(reactor.constSPCNames)
#check if Constant species are different in each liquid system
for spc in rxnSystem1.constSPCNames:
for spc2 in rxnSystem2.constSPCNames:
self.assertIsNot(
spc, spc2,
"Constant species declared in two different reactors seem mixed. Species \"{0}\" appears in both systems and should be."
.format(spc))
def testComputeFlux(self):
"""
Test the liquid batch reactor with a simple kinetic model.
"""
rxn1 = Reaction(
reactants=[self.C2H6, self.CH3],
products=[self.C2H5, self.CH4],
kinetics=Arrhenius(A=(686.375*6, 'm^3/(mol*s)'), n=4.40721, Ea=(7.82799, 'kcal/mol'), T0=(298.15, 'K'))
)
coreSpecies = [self.CH4, self.CH3, self.C2H6, self.C2H5]
edgeSpecies = []
coreReactions = [rxn1]
edgeReactions = []
c0 = {self.C2H5: 0.1, self.CH3: 0.1, self.CH4: 0.4, self.C2H6: 0.4}
rxnSystem = LiquidReactor(self.T, c0, 1, termination=[])
rxnSystem.initializeModel(coreSpecies, coreReactions, edgeSpecies, edgeReactions)
tlist = numpy.array([10**(i/10.0) for i in xrange(-130, -49)], numpy.float64)
# Integrate to get the solution at each time point
t, y, reactionRates, speciesRates = [], [], [], []
for t1 in tlist:
rxnSystem.advance(t1)
t.append(rxnSystem.t)
# You must make a copy of y because it is overwritten by DASSL at
# each call to advance()
y.append(rxnSystem.y.copy())
reactionRates.append(rxnSystem.coreReactionRates.copy())
speciesRates.append(rxnSystem.coreSpeciesRates.copy())
# Convert the solution vectors to numpy arrays
t = numpy.array(t, numpy.float64)
reactionRates = numpy.array(reactionRates, numpy.float64)
speciesRates = numpy.array(speciesRates, numpy.float64)
# Check that we're computing the species fluxes correctly
for i in xrange(t.shape[0]):
self.assertAlmostEqual(reactionRates[i, 0], speciesRates[i, 0], delta=1e-6*reactionRates[i, 0])
self.assertAlmostEqual(reactionRates[i, 0], -speciesRates[i, 1], delta=1e-6*reactionRates[i, 0])
self.assertAlmostEqual(reactionRates[i, 0], -speciesRates[i, 2], delta=1e-6*reactionRates[i, 0])
self.assertAlmostEqual(reactionRates[i, 0], speciesRates[i, 3], delta=1e-6*reactionRates[i, 0])
# Check that we've reached equilibrium
self.assertAlmostEqual(reactionRates[-1, 0], 0.0, delta=1e-2)
def liquidReactor(temperature,
initialConcentrations,
terminationConversion=None,
terminationTime=None,
sensitivity=None,
sensitivityThreshold=1e-3):
logging.debug('Found LiquidReactor reaction system')
T = Quantity(temperature)
for spec, conc in initialConcentrations.iteritems():
concentration = Quantity(conc)
# check the dimensions are ok
# convert to mol/m^3 (or something numerically nice? or must it be SI)
initialConcentrations[spec] = concentration.value_si
termination = []
if terminationConversion is not None:
for spec, conv in terminationConversion.iteritems():
termination.append(TerminationConversion(speciesDict[spec], conv))
if terminationTime is not None:
termination.append(TerminationTime(Quantity(terminationTime)))
if len(termination) == 0:
raise InputError(
'No termination conditions specified for reaction system #{0}.'.
format(len(rmg.reactionSystems) + 2))
sensitiveSpecies = []
if sensitivity:
for spec in sensitivity:
sensitiveSpecies.append(speciesDict[spec])
system = LiquidReactor(T, initialConcentrations, termination,
sensitiveSpecies, sensitivityThreshold)
rmg.reactionSystems.append(system)
def test_corespeciesRate(self):
"Test if a specific core species rate is equal to 0 over time"
c0={self.C2H5: 0.1, self.CH3: 0.1, self.CH4: 0.4, self.C2H6: 0.4}
rxn1 = Reaction(reactants=[self.C2H6,self.CH3], products=[self.C2H5,self.CH4], kinetics=Arrhenius(A=(686.375*6,'m^3/(mol*s)'), n=4.40721, Ea=(7.82799,'kcal/mol'), T0=(298.15,'K')))
coreSpecies = [self.CH4,self.CH3,self.C2H6,self.C2H5]
edgeSpecies = []
coreReactions = [rxn1]
edgeReactions = []
sensitivity=[]
terminationConversion = []
sensitivityThreshold=0.001
ConstSpecies = ["CH4"]
rxnSystem = LiquidReactor(self.T, c0, terminationConversion, sensitivity,sensitivityThreshold,ConstSpecies)
##The test regarding the writting of constantSPCindices from input file is check with the previous test.
rxnSystem.constSPCIndices=[0]
rxnSystem.initializeModel(coreSpecies, coreReactions, edgeSpecies, edgeReactions)
tlist = numpy.array([10**(i/10.0) for i in range(-130, -49)], numpy.float64)
# Integrate to get the solution at each time point
t = []; y = []; reactionRates = []; speciesRates = []
for t1 in tlist:
rxnSystem.advance(t1)
t.append(rxnSystem.t)
self.assertEqual(rxnSystem.coreSpeciesRates[0], 0,"Core species rate has to be equal to 0 for species hold constant. Here it is equal to {0}".format(rxnSystem.coreSpeciesRates[0]))
def test_jacobian(self):
"""
Unit test for the jacobian function:
Solve a reaction system and check if the analytical jacobian matches the finite difference jacobian
"""
coreSpecies = [self.CH4,self.CH3,self.C2H6,self.C2H5]
edgeSpecies = []
rxn1 = Reaction(reactants=[self.C2H6,self.CH3], products=[self.C2H5,self.CH4], kinetics=Arrhenius(A=(686.375*6,'m^3/(mol*s)'), n=4.40721, Ea=(7.82799,'kcal/mol'), T0=(298.15,'K')))
coreReactions = [rxn1]
edgeReactions = []
numCoreSpecies = len(coreSpecies)
rxnList = []
rxnList.append(Reaction(reactants=[self.C2H6], products=[self.CH3,self.CH3], kinetics=Arrhenius(A=(686.375*6,'1/s'), n=4.40721, Ea=(7.82799,'kcal/mol'), T0=(298.15,'K'))))
rxnList.append(Reaction(reactants=[self.CH3,self.CH3], products=[self.C2H6], kinetics=Arrhenius(A=(686.375*6,'m^3/(mol*s)'), n=4.40721, Ea=(7.82799,'kcal/mol'), T0=(298.15,'K'))))
rxnList.append(Reaction(reactants=[self.C2H6,self.CH3], products=[self.C2H5,self.CH4], kinetics=Arrhenius(A=(46.375*6,'m^3/(mol*s)'), n=3.40721, Ea=(6.82799,'kcal/mol'), T0=(298.15,'K'))))
rxnList.append(Reaction(reactants=[self.C2H5,self.CH4], products=[self.C2H6,self.CH3], kinetics=Arrhenius(A=(46.375*6,'m^3/(mol*s)'), n=3.40721, Ea=(6.82799,'kcal/mol'), T0=(298.15,'K'))))
rxnList.append(Reaction(reactants=[self.C2H5,self.CH4], products=[self.CH3,self.CH3,self.CH3], kinetics=Arrhenius(A=(246.375*6,'m^3/(mol*s)'), n=1.40721, Ea=(3.82799,'kcal/mol'), T0=(298.15,'K'))))
rxnList.append(Reaction(reactants=[self.CH3,self.CH3,self.CH3], products=[self.C2H5,self.CH4], kinetics=Arrhenius(A=(246.375*6,'m^6/(mol^2*s)'), n=1.40721, Ea=(3.82799,'kcal/mol'), T0=(298.15,'K'))))#
rxnList.append(Reaction(reactants=[self.C2H6,self.CH3,self.CH3], products=[self.C2H5,self.C2H5,self.H2], kinetics=Arrhenius(A=(146.375*6,'m^6/(mol^2*s)'), n=2.40721, Ea=(8.82799,'kcal/mol'), T0=(298.15,'K'))))
rxnList.append(Reaction(reactants=[self.C2H5,self.C2H5,self.H2], products=[self.C2H6,self.CH3,self.CH3], kinetics=Arrhenius(A=(146.375*6,'m^6/(mol^2*s)'), n=2.40721, Ea=(8.82799,'kcal/mol'), T0=(298.15,'K'))))
rxnList.append(Reaction(reactants=[self.C2H6,self.C2H6], products=[self.CH3,self.CH4,self.C2H5], kinetics=Arrhenius(A=(1246.375*6,'m^3/(mol*s)'), n=0.40721, Ea=(8.82799,'kcal/mol'), T0=(298.15,'K'))))
rxnList.append(Reaction(reactants=[self.CH3,self.CH4,self.C2H5], products=[self.C2H6,self.C2H6], kinetics=Arrhenius(A=(46.375*6,'m^6/(mol^2*s)'), n=0.10721, Ea=(8.82799,'kcal/mol'), T0=(298.15,'K'))))
for rxn in rxnList:
coreSpecies = [self.CH4,self.CH3,self.C2H6,self.C2H5,self.H2]
edgeSpecies = []
coreReactions = [rxn]
c0={self.CH4:0.2,self.CH3:0.1,self.C2H6:0.35,self.C2H5:0.15, self.H2:0.2}
rxnSystem0 = LiquidReactor(self.T, c0,termination=[])
rxnSystem0.initializeModel(coreSpecies, coreReactions, edgeSpecies, edgeReactions)
dydt0 = rxnSystem0.residual(0.0, rxnSystem0.y, numpy.zeros(rxnSystem0.y.shape))[0]
dN = .000001*sum(rxnSystem0.y)
dN_array = dN*numpy.eye(numCoreSpecies)
dydt = []
for i in xrange(numCoreSpecies):
rxnSystem0.y[i] += dN
dydt.append(rxnSystem0.residual(0.0, rxnSystem0.y, numpy.zeros(rxnSystem0.y.shape))[0])
rxnSystem0.y[i] -= dN # reset y to original y0
# Let the solver compute the jacobian
solverJacobian = rxnSystem0.jacobian(0.0, rxnSystem0.y, dydt0, 0.0)
# Compute the jacobian using finite differences
jacobian = numpy.zeros((numCoreSpecies, numCoreSpecies))
for i in xrange(numCoreSpecies):
for j in xrange(numCoreSpecies):
jacobian[i,j] = (dydt[j][i]-dydt0[i])/dN
self.assertAlmostEqual(jacobian[i,j], solverJacobian[i,j], delta=abs(1e-4*jacobian[i,j]))
def test_compute_flux(self):
"""
Test the liquid batch reactor with a simple kinetic model.
"""
rxn1 = Reaction(reactants=[self.C2H6, self.CH3],
products=[self.C2H5, self.CH4],
kinetics=Arrhenius(A=(686.375 * 6, 'm^3/(mol*s)'),
n=4.40721,
Ea=(7.82799, 'kcal/mol'),
T0=(298.15, 'K')))
core_species = [self.CH4, self.CH3, self.C2H6, self.C2H5]
edge_species = []
core_reactions = [rxn1]
edge_reactions = []
c0 = {self.C2H5: 0.1, self.CH3: 0.1, self.CH4: 0.4, self.C2H6: 0.4}
rxn_system = LiquidReactor(self.T, c0, 1, termination=[])
rxn_system.initialize_model(core_species, core_reactions, edge_species,
edge_reactions)
tlist = np.array([10**(i / 10.0) for i in range(-130, -49)],
np.float64)
# Integrate to get the solution at each time point
t, y, reaction_rates, species_rates = [], [], [], []
for t1 in tlist:
rxn_system.advance(t1)
t.append(rxn_system.t)
# You must make a copy of y because it is overwritten by DASSL at
# each call to advance()
y.append(rxn_system.y.copy())
reaction_rates.append(rxn_system.core_reaction_rates.copy())
species_rates.append(rxn_system.core_species_rates.copy())
# Convert the solution vectors to np arrays
t = np.array(t, np.float64)
reaction_rates = np.array(reaction_rates, np.float64)
species_rates = np.array(species_rates, np.float64)
# Check that we're computing the species fluxes correctly
for i in range(t.shape[0]):
self.assertAlmostEqual(reaction_rates[i, 0],
species_rates[i, 0],
delta=1e-6 * reaction_rates[i, 0])
self.assertAlmostEqual(reaction_rates[i, 0],
-species_rates[i, 1],
delta=1e-6 * reaction_rates[i, 0])
self.assertAlmostEqual(reaction_rates[i, 0],
-species_rates[i, 2],
delta=1e-6 * reaction_rates[i, 0])
self.assertAlmostEqual(reaction_rates[i, 0],
species_rates[i, 3],
delta=1e-6 * reaction_rates[i, 0])
# Check that we've reached equilibrium
self.assertAlmostEqual(reaction_rates[-1, 0], 0.0, delta=1e-2)
def test_corespeciesRate(self):
"""
Test if a specific core species rate is equal to 0 over time.
"""
c0 = {self.C2H5: 0.1, self.CH3: 0.1, self.CH4: 0.4, self.C2H6: 0.4}
rxn1 = Reaction(
reactants=[self.C2H6, self.CH3],
products=[self.C2H5, self.CH4],
kinetics=Arrhenius(A=(686.375*6, 'm^3/(mol*s)'), n=4.40721, Ea=(7.82799, 'kcal/mol'), T0=(298.15, 'K'))
)
coreSpecies = [self.CH4, self.CH3, self.C2H6, self.C2H5]
edgeSpecies = []
coreReactions = [rxn1]
edgeReactions = []
sensitivity = []
terminationConversion = []
sensitivityThreshold = 0.001
ConstSpecies = ["CH4"]
rxnSystem = LiquidReactor(self.T, c0, terminationConversion, sensitivity, sensitivityThreshold, ConstSpecies)
# The test regarding the writing of constantSPCindices from input file is check with the previous test.
rxnSystem.constSPCIndices = [0]
rxnSystem.initializeModel(coreSpecies, coreReactions, edgeSpecies, edgeReactions)
tlist = numpy.array([10**(i/10.0) for i in range(-130, -49)], numpy.float64)
# Integrate to get the solution at each time point
t, y, reactionRates, speciesRates = [], [], [], []
for t1 in tlist:
rxnSystem.advance(t1)
t.append(rxnSystem.t)
self.assertEqual(rxnSystem.coreSpeciesRates[0], 0, "Core species rate has to be equal to 0 for species hold constant. Here it is equal to {0}".format(rxnSystem.coreSpeciesRates[0]))
def test_store_constant_species_names(self):
"""
Test if (i) constant species names are stored in reactor attributes and
(ii) if attributes are not mix/equal for multiple conditions generation.
"""
c0 = {self.C2H5: 0.1, self.CH3: 0.1, self.CH4: 0.4, self.C2H6: 0.4}
temp = 1000
# set up the liquid phase reactor 1
termination_conversion = []
termination_time = None
sensitivity = []
sensitivity_threshold = 0.001
constant_species = ["CH4", "C2H6"]
sens_conds = None
rxn_system1 = LiquidReactor(temp, c0, 4, termination_conversion,
sensitivity, sensitivity_threshold,
sens_conds, constant_species)
# set up the liquid phase reactor 2
constant_species = ["O2", "H2O"]
rxn_system2 = LiquidReactor(temp, c0, 4, termination_conversion,
sensitivity, sensitivity_threshold,
sens_conds, constant_species)
for reactor in [rxn_system1, rxn_system2]:
self.assertIsNotNone(reactor.const_spc_names)
# check if Constant species are different in each liquid system
for spc in rxn_system1.const_spc_names:
for spc2 in rxn_system2.const_spc_names:
self.assertIsNot(
spc, spc2,
'Constant species declared in two different reactors seem mixed. '
'Species "{0}" appears in both systems and should be.'.
format(spc))
def test_compute_derivative(self):
rxn_list = [
Reaction(reactants=[self.C2H6],
products=[self.CH3, self.CH3],
kinetics=Arrhenius(A=(686.375e6, '1/s'),
n=4.40721,
Ea=(7.82799, 'kcal/mol'),
T0=(298.15, 'K'))),
Reaction(reactants=[self.C2H6, self.CH3],
products=[self.C2H5, self.CH4],
kinetics=Arrhenius(A=(46.375 * 6, 'm^3/(mol*s)'),
n=3.40721,
Ea=(6.82799, 'kcal/mol'),
T0=(298.15, 'K'))),
Reaction(reactants=[self.C2H6, self.CH3, self.CH3],
products=[self.C2H5, self.C2H5, self.H2],
kinetics=Arrhenius(A=(146.375 * 6, 'm^6/(mol^2*s)'),
n=2.40721,
Ea=(8.82799, 'kcal/mol'),
T0=(298.15, 'K'))),
]
core_species = [self.CH4, self.CH3, self.C2H6, self.C2H5, self.H2]
edge_species = []
core_reactions = rxn_list
edge_reactions = []
num_core_species = len(core_species)
c0 = {
self.CH4: 0.2,
self.CH3: 0.1,
self.C2H6: 0.35,
self.C2H5: 0.15,
self.H2: 0.2
}
rxn_system0 = LiquidReactor(self.T, c0, 1, termination=[])
rxn_system0.initialize_model(core_species, core_reactions,
edge_species, edge_reactions)
dfdt0 = rxn_system0.residual(0.0, rxn_system0.y,
np.zeros(rxn_system0.y.shape))[0]
solver_dfdk = rxn_system0.compute_rate_derivative()
# print 'Solver d(dy/dt)/dk'
# print solver_dfdk
integration_time = 1e-8
model_settings = ModelSettings(tol_keep_in_edge=0,
tol_move_to_core=1,
tol_interrupt_simulation=0)
simulator_settings = SimulatorSettings()
rxn_system0.termination.append(TerminationTime(
(integration_time, 's')))
rxn_system0.simulate(core_species,
core_reactions, [], [], [], [],
model_settings=model_settings,
simulator_settings=simulator_settings)
y0 = rxn_system0.y
dfdk = np.zeros((num_core_species, len(rxn_list))) # d(dy/dt)/dk
c0 = {
self.CH4: 0.2,
self.CH3: 0.1,
self.C2H6: 0.35,
self.C2H5: 0.15,
self.H2: 0.2
}
for i in range(len(rxn_list)):
k0 = rxn_list[i].get_rate_coefficient(self.T)
rxn_list[i].kinetics.A.value_si = rxn_list[
i].kinetics.A.value_si * (1 + 1e-3)
dk = rxn_list[i].get_rate_coefficient(self.T) - k0
rxn_system = LiquidReactor(self.T, c0, 1, termination=[])
rxn_system.initialize_model(core_species, core_reactions,
edge_species, edge_reactions)
dfdt = rxn_system.residual(0.0, rxn_system.y,
np.zeros(rxn_system.y.shape))[0]
dfdk[:, i] = (dfdt - dfdt0) / dk
rxn_system.termination.append(
TerminationTime((integration_time, 's')))
model_settings = ModelSettings(tol_keep_in_edge=0,
tol_move_to_core=1,
tol_interrupt_simulation=0)
simulator_settings = SimulatorSettings()
rxn_system.simulate(core_species,
core_reactions, [], [], [], [],
model_settings=model_settings,
simulator_settings=simulator_settings)
rxn_list[i].kinetics.A.value_si = rxn_list[
i].kinetics.A.value_si / (1 + 1e-3) # reset A factor
for i in range(num_core_species):
for j in range(len(rxn_list)):
self.assertAlmostEqual(dfdk[i, j],
solver_dfdk[i, j],
delta=abs(1e-3 * dfdk[i, j]))
def test_jacobian(self):
"""
Unit test for the jacobian function:
Solve a reaction system and check if the analytical jacobian matches
the finite difference jacobian.
"""
core_species = [self.CH4, self.CH3, self.C2H6, self.C2H5, self.H2]
edge_species = []
num_core_species = len(core_species)
c0 = {
self.CH4: 0.2,
self.CH3: 0.1,
self.C2H6: 0.35,
self.C2H5: 0.15,
self.H2: 0.2
}
edge_reactions = []
rxn_list = [
Reaction(reactants=[self.C2H6],
products=[self.CH3, self.CH3],
kinetics=Arrhenius(A=(686.375 * 6, '1/s'),
n=4.40721,
Ea=(7.82799, 'kcal/mol'),
T0=(298.15, 'K'))),
Reaction(reactants=[self.CH3, self.CH3],
products=[self.C2H6],
kinetics=Arrhenius(A=(686.375 * 6, 'm^3/(mol*s)'),
n=4.40721,
Ea=(7.82799, 'kcal/mol'),
T0=(298.15, 'K'))),
Reaction(reactants=[self.C2H6, self.CH3],
products=[self.C2H5, self.CH4],
kinetics=Arrhenius(A=(46.375 * 6, 'm^3/(mol*s)'),
n=3.40721,
Ea=(6.82799, 'kcal/mol'),
T0=(298.15, 'K'))),
Reaction(reactants=[self.C2H5, self.CH4],
products=[self.C2H6, self.CH3],
kinetics=Arrhenius(A=(46.375 * 6, 'm^3/(mol*s)'),
n=3.40721,
Ea=(6.82799, 'kcal/mol'),
T0=(298.15, 'K'))),
Reaction(reactants=[self.C2H5, self.CH4],
products=[self.CH3, self.CH3, self.CH3],
kinetics=Arrhenius(A=(246.375 * 6, 'm^3/(mol*s)'),
n=1.40721,
Ea=(3.82799, 'kcal/mol'),
T0=(298.15, 'K'))),
Reaction(reactants=[self.CH3, self.CH3, self.CH3],
products=[self.C2H5, self.CH4],
kinetics=Arrhenius(A=(246.375 * 6, 'm^6/(mol^2*s)'),
n=1.40721,
Ea=(3.82799, 'kcal/mol'),
T0=(298.15, 'K'))),
Reaction(reactants=[self.C2H6, self.CH3, self.CH3],
products=[self.C2H5, self.C2H5, self.H2],
kinetics=Arrhenius(A=(146.375 * 6, 'm^6/(mol^2*s)'),
n=2.40721,
Ea=(8.82799, 'kcal/mol'),
T0=(298.15, 'K'))),
Reaction(reactants=[self.C2H5, self.C2H5, self.H2],
products=[self.C2H6, self.CH3, self.CH3],
kinetics=Arrhenius(A=(146.375 * 6, 'm^6/(mol^2*s)'),
n=2.40721,
Ea=(8.82799, 'kcal/mol'),
T0=(298.15, 'K'))),
Reaction(reactants=[self.C2H6, self.C2H6],
products=[self.CH3, self.CH4, self.C2H5],
kinetics=Arrhenius(A=(1246.375 * 6, 'm^3/(mol*s)'),
n=0.40721,
Ea=(8.82799, 'kcal/mol'),
T0=(298.15, 'K'))),
Reaction(reactants=[self.CH3, self.CH4, self.C2H5],
products=[self.C2H6, self.C2H6],
kinetics=Arrhenius(A=(46.375 * 6, 'm^6/(mol^2*s)'),
n=0.10721,
Ea=(8.82799, 'kcal/mol'),
T0=(298.15, 'K'))),
]
# Analytical Jacobian for reaction 6
def jacobian_rxn6(c, kf, kr, s):
c1, c2, c3, c4 = c[s[1]], c[s[2]], c[s[3]], c[s[4]]
jaco = np.zeros((5, 5))
jaco[1, 1] = -4 * kf * c1 * c2
jaco[1, 2] = -2 * kf * c1 * c1
jaco[1, 3] = 4 * kr * c3 * c4
jaco[1, 4] = 2 * kr * c3 * c3
jaco[2, 1:] = 0.5 * jaco[1, 1:]
jaco[3, 1:] = -jaco[1, 1:]
jaco[4, 1:] = -0.5 * jaco[1, 1:]
return jaco
# Analytical Jacobian for reaction 7
def jacobian_rxn7(c, kf, kr, s):
c1, c2, c3, c4 = c[s[1]], c[s[2]], c[s[3]], c[s[4]]
jaco = np.zeros((5, 5))
jaco[1, 1] = -4 * kr * c1 * c2
jaco[1, 2] = -2 * kr * c1 * c1
jaco[1, 3] = 4 * kf * c3 * c4
jaco[1, 4] = 2 * kf * c3 * c3
jaco[2, 1:] = 0.5 * jaco[1, 1:]
jaco[3, 1:] = -jaco[1, 1:]
jaco[4, 1:] = -0.5 * jaco[1, 1:]
return jaco
for rxn_num, rxn in enumerate(rxn_list):
core_reactions = [rxn]
rxn_system0 = LiquidReactor(self.T, c0, 1, termination=[])
rxn_system0.initialize_model(core_species, core_reactions,
edge_species, edge_reactions)
dydt0 = rxn_system0.residual(0.0, rxn_system0.y,
np.zeros(rxn_system0.y.shape))[0]
dN = .000001 * sum(rxn_system0.y)
# Let the solver compute the jacobian
solver_jacobian = rxn_system0.jacobian(0.0, rxn_system0.y, dydt0,
0.0)
if rxn_num not in (6, 7):
dydt = []
for i in range(num_core_species):
rxn_system0.y[i] += dN
dydt.append(
rxn_system0.residual(0.0, rxn_system0.y,
np.zeros(rxn_system0.y.shape))[0])
rxn_system0.y[i] -= dN # reset y
# Compute the jacobian using finite differences
jacobian = np.zeros((num_core_species, num_core_species))
for i in range(num_core_species):
for j in range(num_core_species):
jacobian[i, j] = (dydt[j][i] - dydt0[i]) / dN
self.assertAlmostEqual(jacobian[i, j],
solver_jacobian[i, j],
delta=abs(1e-4 *
jacobian[i, j]))
# The forward finite difference is very unstable for reactions
# 6 and 7. Use Jacobians calculated by hand instead.
elif rxn_num == 6:
kforward = rxn.get_rate_coefficient(self.T)
kreverse = kforward / rxn.get_equilibrium_constant(self.T)
jacobian = jacobian_rxn6(c0, kforward, kreverse, core_species)
for i in range(num_core_species):
for j in range(num_core_species):
self.assertAlmostEqual(jacobian[i, j],
solver_jacobian[i, j],
delta=abs(1e-4 *
jacobian[i, j]))
elif rxn_num == 7:
kforward = rxn.get_rate_coefficient(self.T)
kreverse = kforward / rxn.get_equilibrium_constant(self.T)
jacobian = jacobian_rxn7(c0, kforward, kreverse, core_species)
for i in range(num_core_species):
for j in range(num_core_species):
self.assertAlmostEqual(jacobian[i, j],
solver_jacobian[i, j],
delta=abs(1e-4 *
jacobian[i, j]))
def test_compute_derivative(self):
rxnList = []
rxnList.append(Reaction(
reactants=[self.C2H6],
products=[self.CH3, self.CH3],
kinetics=Arrhenius(A=(686.375e6, '1/s'), n=4.40721, Ea=(7.82799, 'kcal/mol'), T0=(298.15, 'K'))
))
rxnList.append(Reaction(
reactants=[self.C2H6, self.CH3],
products=[self.C2H5, self.CH4],
kinetics=Arrhenius(A=(46.375*6, 'm^3/(mol*s)'), n=3.40721, Ea=(6.82799, 'kcal/mol'), T0=(298.15, 'K'))
))
rxnList.append(Reaction(
reactants=[self.C2H6, self.CH3, self.CH3],
products=[self.C2H5, self.C2H5, self.H2],
kinetics=Arrhenius(A=(146.375*6, 'm^6/(mol^2*s)'), n=2.40721, Ea=(8.82799, 'kcal/mol'), T0=(298.15, 'K'))
))
coreSpecies = [self.CH4, self.CH3, self.C2H6, self.C2H5, self.H2]
edgeSpecies = []
coreReactions = rxnList
edgeReactions = []
numCoreSpecies = len(coreSpecies)
c0 = {self.CH4: 0.2, self.CH3: 0.1, self.C2H6: 0.35, self.C2H5: 0.15, self.H2: 0.2}
rxnSystem0 = LiquidReactor(self.T, c0, 1, termination=[])
rxnSystem0.initializeModel(coreSpecies, coreReactions, edgeSpecies, edgeReactions)
dfdt0 = rxnSystem0.residual(0.0, rxnSystem0.y, numpy.zeros(rxnSystem0.y.shape))[0]
solver_dfdk = rxnSystem0.computeRateDerivative()
# print 'Solver d(dy/dt)/dk'
# print solver_dfdk
integrationTime = 1e-8
modelSettings = ModelSettings(toleranceKeepInEdge=0, toleranceMoveToCore=1, toleranceInterruptSimulation=0)
simulatorSettings = SimulatorSettings()
rxnSystem0.termination.append(TerminationTime((integrationTime, 's')))
rxnSystem0.simulate(coreSpecies, coreReactions, [], [], [], [],
modelSettings=modelSettings, simulatorSettings=simulatorSettings)
y0 = rxnSystem0.y
dfdk = numpy.zeros((numCoreSpecies, len(rxnList))) # d(dy/dt)/dk
c0 = {self.CH4: 0.2, self.CH3: 0.1, self.C2H6: 0.35, self.C2H5: 0.15, self.H2: 0.2}
for i in xrange(len(rxnList)):
k0 = rxnList[i].getRateCoefficient(self.T)
rxnList[i].kinetics.A.value_si = rxnList[i].kinetics.A.value_si*(1+1e-3)
dk = rxnList[i].getRateCoefficient(self.T) - k0
rxnSystem = LiquidReactor(self.T, c0, 1, termination=[])
rxnSystem.initializeModel(coreSpecies, coreReactions, edgeSpecies, edgeReactions)
dfdt = rxnSystem.residual(0.0, rxnSystem.y, numpy.zeros(rxnSystem.y.shape))[0]
dfdk[:, i] = (dfdt-dfdt0)/dk
rxnSystem.termination.append(TerminationTime((integrationTime, 's')))
modelSettings = ModelSettings(toleranceKeepInEdge=0, toleranceMoveToCore=1, toleranceInterruptSimulation=0)
simulatorSettings = SimulatorSettings()
rxnSystem.simulate(coreSpecies, coreReactions, [], [], [], [],
modelSettings=modelSettings, simulatorSettings=simulatorSettings)
rxnList[i].kinetics.A.value_si = rxnList[i].kinetics.A.value_si/(1+1e-3) # reset A factor
for i in xrange(numCoreSpecies):
for j in xrange(len(rxnList)):
self.assertAlmostEqual(dfdk[i, j], solver_dfdk[i, j], delta=abs(1e-3*dfdk[i, j]))
def test_jacobian(self):
"""
Unit test for the jacobian function:
Solve a reaction system and check if the analytical jacobian matches
the finite difference jacobian.
"""
coreSpecies = [self.CH4, self.CH3, self.C2H6, self.C2H5, self.H2]
edgeSpecies = []
numCoreSpecies = len(coreSpecies)
c0 = {self.CH4: 0.2, self.CH3: 0.1, self.C2H6: 0.35, self.C2H5: 0.15, self.H2: 0.2}
edgeReactions = []
rxnList = []
rxnList.append(Reaction(
reactants=[self.C2H6],
products=[self.CH3, self.CH3],
kinetics=Arrhenius(A=(686.375*6, '1/s'), n=4.40721, Ea=(7.82799, 'kcal/mol'), T0=(298.15, 'K'))
))
rxnList.append(Reaction(
reactants=[self.CH3, self.CH3],
products=[self.C2H6],
kinetics=Arrhenius(A=(686.375*6, 'm^3/(mol*s)'), n=4.40721, Ea=(7.82799, 'kcal/mol'), T0=(298.15, 'K'))
))
rxnList.append(Reaction(
reactants=[self.C2H6, self.CH3],
products=[self.C2H5, self.CH4],
kinetics=Arrhenius(A=(46.375*6, 'm^3/(mol*s)'), n=3.40721, Ea=(6.82799, 'kcal/mol'), T0=(298.15, 'K'))
))
rxnList.append(Reaction(
reactants=[self.C2H5, self.CH4],
products=[self.C2H6, self.CH3],
kinetics=Arrhenius(A=(46.375*6, 'm^3/(mol*s)'), n=3.40721, Ea=(6.82799, 'kcal/mol'), T0=(298.15, 'K'))
))
rxnList.append(Reaction(
reactants=[self.C2H5, self.CH4],
products=[self.CH3, self.CH3, self.CH3],
kinetics=Arrhenius(A=(246.375*6, 'm^3/(mol*s)'), n=1.40721, Ea=(3.82799, 'kcal/mol'), T0=(298.15, 'K'))
))
rxnList.append(Reaction(
reactants=[self.CH3, self.CH3, self.CH3],
products=[self.C2H5, self.CH4],
kinetics=Arrhenius(A=(246.375*6, 'm^6/(mol^2*s)'), n=1.40721, Ea=(3.82799, 'kcal/mol'), T0=(298.15, 'K'))
))
rxnList.append(Reaction(
reactants=[self.C2H6, self.CH3, self.CH3],
products=[self.C2H5, self.C2H5, self.H2],
kinetics=Arrhenius(A=(146.375*6, 'm^6/(mol^2*s)'), n=2.40721, Ea=(8.82799, 'kcal/mol'), T0=(298.15, 'K'))
))
rxnList.append(Reaction(
reactants=[self.C2H5, self.C2H5, self.H2],
products=[self.C2H6, self.CH3, self.CH3],
kinetics=Arrhenius(A=(146.375*6, 'm^6/(mol^2*s)'), n=2.40721, Ea=(8.82799, 'kcal/mol'), T0=(298.15, 'K'))
))
rxnList.append(Reaction(
reactants=[self.C2H6, self.C2H6],
products=[self.CH3, self.CH4, self.C2H5],
kinetics=Arrhenius(A=(1246.375*6, 'm^3/(mol*s)'), n=0.40721, Ea=(8.82799, 'kcal/mol'), T0=(298.15, 'K'))
))
rxnList.append(Reaction(
reactants=[self.CH3, self.CH4, self.C2H5],
products=[self.C2H6, self.C2H6],
kinetics=Arrhenius(A=(46.375*6, 'm^6/(mol^2*s)'), n=0.10721, Ea=(8.82799, 'kcal/mol'), T0=(298.15, 'K'))
))
# Analytical Jacobian for reaction 6
def jacobian_rxn6(c, kf, kr, s):
c1, c2, c3, c4 = c[s[1]], c[s[2]], c[s[3]], c[s[4]]
J = numpy.zeros((5, 5))
J[1, 1] = -4 * kf * c1 * c2
J[1, 2] = -2 * kf * c1 * c1
J[1, 3] = 4 * kr * c3 * c4
J[1, 4] = 2 * kr * c3 * c3
J[2, 1:] = 0.5 * J[1, 1:]
J[3, 1:] = -J[1, 1:]
J[4, 1:] = -0.5 * J[1, 1:]
return J
# Analytical Jacobian for reaction 7
def jacobian_rxn7(c, kf, kr, s):
c1, c2, c3, c4 = c[s[1]], c[s[2]], c[s[3]], c[s[4]]
J = numpy.zeros((5, 5))
J[1, 1] = -4 * kr * c1 * c2
J[1, 2] = -2 * kr * c1 * c1
J[1, 3] = 4 * kf * c3 * c4
J[1, 4] = 2 * kf * c3 * c3
J[2, 1:] = 0.5 * J[1, 1:]
J[3, 1:] = -J[1, 1:]
J[4, 1:] = -0.5 * J[1, 1:]
return J
for rxn_num, rxn in enumerate(rxnList):
coreReactions = [rxn]
rxnSystem0 = LiquidReactor(self.T, c0, 1, termination=[])
rxnSystem0.initializeModel(coreSpecies, coreReactions, edgeSpecies, edgeReactions)
dydt0 = rxnSystem0.residual(0.0, rxnSystem0.y, numpy.zeros(rxnSystem0.y.shape))[0]
dN = .000001*sum(rxnSystem0.y)
# Let the solver compute the jacobian
solverJacobian = rxnSystem0.jacobian(0.0, rxnSystem0.y, dydt0, 0.0)
if rxn_num not in (6, 7):
dydt = []
for i in xrange(numCoreSpecies):
rxnSystem0.y[i] += dN
dydt.append(rxnSystem0.residual(0.0, rxnSystem0.y, numpy.zeros(rxnSystem0.y.shape))[0])
rxnSystem0.y[i] -= dN # reset y
# Compute the jacobian using finite differences
jacobian = numpy.zeros((numCoreSpecies, numCoreSpecies))
for i in xrange(numCoreSpecies):
for j in xrange(numCoreSpecies):
jacobian[i, j] = (dydt[j][i]-dydt0[i])/dN
self.assertAlmostEqual(jacobian[i, j], solverJacobian[i, j], delta=abs(1e-4*jacobian[i, j]))
# The forward finite difference is very unstable for reactions
# 6 and 7. Use Jacobians calculated by hand instead.
elif rxn_num == 6:
kforward = rxn.getRateCoefficient(self.T)
kreverse = kforward / rxn.getEquilibriumConstant(self.T)
jacobian = jacobian_rxn6(c0, kforward, kreverse, coreSpecies)
for i in xrange(numCoreSpecies):
for j in xrange(numCoreSpecies):
self.assertAlmostEqual(jacobian[i, j], solverJacobian[i, j], delta=abs(1e-4*jacobian[i, j]))
elif rxn_num == 7:
kforward = rxn.getRateCoefficient(self.T)
kreverse = kforward / rxn.getEquilibriumConstant(self.T)
jacobian = jacobian_rxn7(c0, kforward, kreverse, coreSpecies)
for i in xrange(numCoreSpecies):
for j in xrange(numCoreSpecies):
self.assertAlmostEqual(jacobian[i, j], solverJacobian[i, j], delta=abs(1e-4*jacobian[i, j]))
def liquidReactor(temperature,
initialConcentrations,
terminationConversion=None,
nSimsTerm = 4,
terminationTime=None,
terminationRateRatio=None,
sensitivity=None,
sensitivityThreshold=1e-3,
sensitivityTemperature=None,
sensitivityConcentrations=None,
constantSpecies=None):
logging.debug('Found LiquidReactor reaction system')
if not isinstance(temperature,list):
T = Quantity(temperature)
else:
if len(temperature) != 2:
raise InputError('Temperature and pressure ranges can either be in the form of (number,units) or a list with 2 entries of the same format')
T = [Quantity(t) for t in temperature]
for spec,conc in initialConcentrations.iteritems():
if not isinstance(conc,list):
concentration = Quantity(conc)
# check the dimensions are ok
# convert to mol/m^3 (or something numerically nice? or must it be SI)
initialConcentrations[spec] = concentration.value_si
else:
if len(conc) != 2:
raise InputError("Concentration values must either be in the form of (number,units) or a list with 2 entries of the same format")
initialConcentrations[spec] = [Quantity(conc[0]),Quantity(conc[1])]
if not isinstance(temperature,list) and all([not isinstance(x,list) for x in initialConcentrations.itervalues()]):
nSimsTerm=1
termination = []
if terminationConversion is not None:
for spec, conv in terminationConversion.iteritems():
termination.append(TerminationConversion(speciesDict[spec], conv))
if terminationTime is not None:
termination.append(TerminationTime(Quantity(terminationTime)))
if terminationRateRatio is not None:
termination.append(TerminationRateRatio(terminationRateRatio))
if len(termination) == 0:
raise InputError('No termination conditions specified for reaction system #{0}.'.format(len(rmg.reactionSystems)+2))
sensitiveSpecies = []
if sensitivity:
for spec in sensitivity:
sensitiveSpecies.append(speciesDict[spec])
##chatelak: check the constant species exist
if constantSpecies is not None:
logging.debug(' Generation with constant species:')
for constantSpecie in constantSpecies:
logging.debug(" {0}".format(constantSpecie))
if not speciesDict.has_key(constantSpecie):
raise InputError('Species {0} not found in the input file'.format(constantSpecie))
if not isinstance(T,list):
sensitivityTemperature = T
if not any([isinstance(x,list) for x in initialConcentrations.itervalues()]):
sensitivityConcentrations = initialConcentrations
if sensitivityConcentrations is None or sensitivityTemperature is None:
sensConditions = None
else:
sensConditions = sensitivityConcentrations
sensConditions['T'] = Quantity(sensitivityTemperature).value_si
system = LiquidReactor(T, initialConcentrations, nSimsTerm, termination, sensitiveSpecies, sensitivityThreshold, sensConditions, constantSpecies)
rmg.reactionSystems.append(system)
def test_compute_derivative(self):
rxnList = []
rxnList.append(Reaction(reactants=[self.C2H6], products=[self.CH3,self.CH3], kinetics=Arrhenius(A=(686.375e6,'1/s'), n=4.40721, Ea=(7.82799,'kcal/mol'), T0=(298.15,'K'))))
rxnList.append(Reaction(reactants=[self.C2H6,self.CH3], products=[self.C2H5,self.CH4], kinetics=Arrhenius(A=(46.375*6,'m^3/(mol*s)'), n=3.40721, Ea=(6.82799,'kcal/mol'), T0=(298.15,'K'))))
rxnList.append(Reaction(reactants=[self.C2H6,self.CH3,self.CH3], products=[self.C2H5,self.C2H5,self.H2], kinetics=Arrhenius(A=(146.375*6,'m^6/(mol^2*s)'), n=2.40721, Ea=(8.82799,'kcal/mol'), T0=(298.15,'K'))))
coreSpecies = [self.CH4,self.CH3,self.C2H6,self.C2H5, self.H2]
edgeSpecies = []
coreReactions = rxnList
edgeReactions = []
numCoreSpecies = len(coreSpecies)
c0={self.CH4:0.2,self.CH3:0.1,self.C2H6:0.35,self.C2H5:0.15, self.H2:0.2}
rxnSystem0 = LiquidReactor(self.T, c0,termination=[])
rxnSystem0.initializeModel(coreSpecies, coreReactions, edgeSpecies, edgeReactions)
dfdt0 = rxnSystem0.residual(0.0, rxnSystem0.y, numpy.zeros(rxnSystem0.y.shape))[0]
solver_dfdk = rxnSystem0.computeRateDerivative()
#print 'Solver d(dy/dt)/dk'
#print solver_dfdk
integrationTime = 1e-8
rxnSystem0.termination.append(TerminationTime((integrationTime,'s')))
rxnSystem0.simulate(coreSpecies, coreReactions, [], [], 0, 1, 0)
y0 = rxnSystem0.y
dfdk = numpy.zeros((numCoreSpecies,len(rxnList))) # d(dy/dt)/dk
c0={self.CH4:0.2,self.CH3:0.1,self.C2H6:0.35,self.C2H5:0.15, self.H2:0.2}
for i in xrange(len(rxnList)):
k0 = rxnList[i].getRateCoefficient(self.T)
rxnList[i].kinetics.A.value_si = rxnList[i].kinetics.A.value_si*(1+1e-3)
dk = rxnList[i].getRateCoefficient(self.T) - k0
rxnSystem = LiquidReactor(self.T, c0,termination=[])
rxnSystem.initializeModel(coreSpecies, coreReactions, edgeSpecies, edgeReactions)
dfdt = rxnSystem.residual(0.0, rxnSystem.y, numpy.zeros(rxnSystem.y.shape))[0]
dfdk[:,i]=(dfdt-dfdt0)/dk
rxnSystem.termination.append(TerminationTime((integrationTime,'s')))
rxnSystem.simulate(coreSpecies, coreReactions, [], [], 0, 1, 0)
rxnList[i].kinetics.A.value_si = rxnList[i].kinetics.A.value_si/(1+1e-3) # reset A factor
for i in xrange(numCoreSpecies):
for j in xrange(len(rxnList)):
self.assertAlmostEqual(dfdk[i,j], solver_dfdk[i,j], delta=abs(1e-3*dfdk[i,j]))