def test_plog(self):
gas1 = ct.Solution('pdep-test.cti')
species = ct.Species.listFromFile('pdep-test.cti')
r = ct.PlogReaction()
r.reactants = {'R1A': 1, 'R1B': 1}
r.products = {'P1': 1, 'H': 1}
r.rates = [
(0.01 * ct.one_atm, ct.Arrhenius(1.2124e13, -0.5779,
10872.7 * 4184)),
(1.0 * ct.one_atm, ct.Arrhenius(4.9108e28, -4.8507,
24772.8 * 4184)),
(10.0 * ct.one_atm, ct.Arrhenius(1.2866e44, -9.0246,
39796.5 * 4184)),
(100.0 * ct.one_atm,
ct.Arrhenius(5.9632e53, -11.529, 52599.6 * 4184))
]
gas2 = ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=species,
reactions=[r])
gas2.X = gas1.X = 'R1A:0.3, R1B:0.6, P1:0.1'
for P in [0.001, 0.01, 0.2, 1.0, 1.1, 9.0, 10.0, 99.0, 103.0]:
gas1.TP = gas2.TP = 900, P * ct.one_atm
self.assertNear(gas2.forward_rate_constants[0],
gas1.forward_rate_constants[0])
self.assertNear(gas2.net_rates_of_progress[0],
gas1.net_rates_of_progress[0])
def test_negative_A_falloff(self):
species = ct.Species.listFromFile('gri30.yaml')
r = ct.FalloffReaction('NH:1, NO:1', 'N2O:1, H:1')
r.low_rate = ct.Arrhenius(2.16e13, -0.23, 0)
r.high_rate = ct.Arrhenius(-8.16e12, -0.5, 0)
self.assertFalse(r.allow_negative_pre_exponential_factor)
with self.assertRaisesRegex(ct.CanteraError, 'pre-exponential'):
gas = ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=species,
reactions=[r])
r.allow_negative_pre_exponential_factor = True
# Should still fail because of mixed positive and negative A factors
with self.assertRaisesRegex(ct.CanteraError, 'pre-exponential'):
gas = ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=species,
reactions=[r])
r.low_rate = ct.Arrhenius(-2.16e13, -0.23, 0)
gas = ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=species,
reactions=[r])
self.assertLess(gas.forward_rate_constants, 0)
def setUpClass(cls):
ReactionTests.setUpClass()
param = cls._rate["low_P_rate_constant"]
low = ct.Arrhenius(param["A"], param["b"], param["Ea"])
param = cls._rate["high_P_rate_constant"]
high = ct.Arrhenius(param["A"], param["b"], param["Ea"])
cls._rate_obj = ct.LindemannRate(low=low, high=high, falloff_coeffs=[])
def setUpClass(cls):
ReactionTests.setUpClass()
param = cls._rate["low_P_rate_constant"]
low = ct.Arrhenius(param["A"], param["b"], param["Ea"])
param = cls._rate["high_P_rate_constant"]
high = ct.Arrhenius(param["A"], param["b"], param["Ea"])
param = cls._rate["Troe"]
data = [param["A"], param["T3"], param["T1"], param["T2"]]
cls._rate_obj = ct.TroeRate(low=low, high=high, falloff_coeffs=data)
def modify_surface_kinetics(surface, param_to_set):
"""changes a set of numerical parameters of a an Interface among following:
site_density, coverages, concentrations,
pre-exponential factor, temperature_exponent, activation_energy
"""
if not HAS_CANTERA:
raise SpectroChemPyException(
'Cantera is not available : please install it before continuing: \n'
'conda install -c cantera cantera')
# check some parameters
if type(surface) is not ct.composite.Interface:
raise ValueError('only implemented of ct.composite.Interface')
for param in param_to_set:
# check that param_to_change exists
try:
eval('surface.' + param)
except ValueError:
print('class {} has no \'{}\' attribute'.format(
type(surface), param))
raise
# if exists => sets its new value
# if the attribute is writable:
if param in ('site_density', 'coverages', 'concentrations'):
init_coverages = surface.coverages
exec('surface.' + param + '=' + str(param_to_set[param]))
if param == 'site_density':
# coverages must be reset
surface.coverages = init_coverages
# else use Cantera methods (or derived from cantera)
elif param.split('.')[-1] == 'pre_exponential_factor':
str_rate = 'surface.' + '.'.join(param.split('.')[-3:-1])
b, E = eval(str_rate + '.temperature_exponent,' + str_rate +
'.activation_energy ')
rxn = int(param.split('.')[0].split('[')[-1].split(']')[0])
modify_rate(surface, rxn, ct.Arrhenius(param_to_set[param], b, E))
elif param.split('.')[-1] == 'temperature_exponent':
str_rate = 'surface.' + '.'.join(param.split('.')[-3:-1])
A, E = eval(str_rate + 'pre_exponential_factor,' + str_rate +
'.activation_energy ')
rxn = int(param.split('.')[0].split('[')[-1].split(']')[0])
modify_rate(surface, rxn, ct.Arrhenius(A, param_to_set[param], E))
elif param.split('.')[-1] == 'activation_energy':
str_rate = 'surface.' + '.'.join(param.split('.')[-3:-1])
A, b = eval(str_rate + 'pre_exponential_factor,' + str_rate +
'.temperature_exponent')
rxn = int(param.split('.')[0].split('[')[-1].split(']')[0])
modify_rate(surface, rxn, ct.Arrhenius(A, b, param_to_set[param]))
return
def test_falloff(self):
r = ct.FalloffReaction('OH:2', 'H2O2:1')
r.high_rate = ct.Arrhenius(7.4e10, -0.37, 0.0)
r.low_rate = ct.Arrhenius(2.3e12, -0.9, -1700*1000*4.184)
r.falloff = ct.TroeFalloff((0.7346, 94, 1756, 5182))
r.efficiencies = {'AR':0.7, 'H2':2.0, 'H2O':6.0}
gas2 = ct.Solution(thermo='IdealGas', kinetics='GasKinetics',
species=self.species, reactions=[r])
gas2.TPX = self.gas.TPX
self.assertNear(gas2.forward_rate_constants[0],
self.gas.forward_rate_constants[20])
self.assertNear(gas2.net_rates_of_progress[0],
self.gas.net_rates_of_progress[20])
def setUpClass(cls):
ReactionTests.setUpClass()
if cls._legacy:
args = list(cls._rate.values())
cls._rate_obj = ct.Arrhenius(*args)
else:
cls._rate_obj = ct.ArrheniusRate(**cls._rate)
def test_interface(self):
surf_species = ct.Species.listFromFile('ptcombust.xml')
gas = ct.Solution('ptcombust.xml', 'gas')
surf1 = ct.Interface('ptcombust.xml', 'Pt_surf', [gas])
r1 = ct.InterfaceReaction()
r1.reactants = 'H(S):2'
r1.products = 'H2:1, PT(S):2'
r1.rate = ct.Arrhenius(3.7e20, 0, 67.4e6)
r1.coverage_deps = {'H(S)': (0, 0, -6e6)}
self.assertNear(r1.coverage_deps['H(S)'][2], -6e6)
surf2 = ct.Interface(thermo='Surface',
species=surf_species,
kinetics='interface',
reactions=[r1],
phases=[gas])
surf2.site_density = surf1.site_density
surf1.coverages = surf2.coverages = 'PT(S):0.7, H(S):0.3'
gas.TP = surf2.TP = surf1.TP
for T in [300, 500, 1500]:
gas.TP = surf1.TP = surf2.TP = T, 5 * ct.one_atm
self.assertNear(surf1.forward_rate_constants[1],
surf2.forward_rate_constants[0])
self.assertNear(surf1.net_rates_of_progress[1],
surf2.net_rates_of_progress[0])
def modify_reactions(
self,
coeffs,
rxnNums=[]): # Only works for Arrhenius equations currently
if not rxnNums: # if rxnNums does not exist, modify all
rxnNums = range(len(coeffs))
else:
if isinstance(
rxnNums,
(float, int)): # if single reaction given, run that one
rxnNums = [rxnNums]
for rxnNum in rxnNums:
rxn = self.gas.reaction(rxnNum)
if type(rxn) is ct.ElementaryReaction or type(
rxn) is ct.ThreeBodyReaction:
# Get current values
A = coeffs[rxnNum]['pre_exponential_factor']
b = coeffs[rxnNum]['temperature_exponent']
Ea = coeffs[rxnNum]['activation_energy']
# Update reaction rate
rxn.rate = ct.Arrhenius(A, b, Ea)
# elif type(rxn) is ct.PlogReaction:
# print(dir(rxn))
# print(rxn.rates[rxn_num])
# elif type(rxn) is ct.ChebyshevReaction:
# print(dir(rxn))
# print(rxn.rates[rxn_num])
else:
continue
self.gas.modify_reaction(rxnNum, rxn)
def fitness(indv):
tmp_parameters = indv.solution
tmp_reactions = R.copy()
for i in range(len(tmp_reactions)):
if tmp_reactions[i].reaction_type !=4:
tmp_reactions[i].rate = ct.Arrhenius(A = tmp_parameters[3*i], \
b = tmp_parameters[3*i+1], E = tmp_parameters[3*i+2])
else:
tmp_reactions[i].low_rate = ct.Arrhenius(A = tmp_parameters[3*i], \
b = tmp_parameters[3*i+1], E = tmp_parameters[3*i+2])
gas2 = ct.Solution(thermo='IdealGas', kinetics='GasKinetics',species=gas.species(),reactions=tmp_reactions)
gas2.TPX = temp, pres, 'CH4:1, O2:2'
r = ct.IdealGasConstPressureReactor(gas2)
sim = ct.ReactorNet([r])
states = ct.SolutionArray(gas2, extra=['t'])
try:
for t in np.arange(0, end_time, step_time):
sim.advance(t)
states.append(r.thermo.state, t=1000*t)
except:
return 1e8
max_delta = 0
index_temp = 0
for i in range(len(states.T)-2):
if(states.T[i+1] - states.T[i] > max_delta):
max_delta = states.T[i+1] - states.T[i]
index_temp = i
ignite_time_optimised = float(states.t[index_temp])
optimised_T = float(states.T[-1] )
optimised_CH4 = float(states('CH4').X[-1] )
optimised_O2 = float(states('O2').X[-1] )
optimised_CO2 = float(states('CO2').X[-1] )
optimised_H2O = float(states('H2O').X[-1] )
optimised_H = float(states('H').X[-1] )
optimised_OH = float(states('OH').X[-1] )
# return ((ignite_time_optimised - ignite_time_precise)/ignite_time_precise)**2\
# + ((optimised_T - precise_T)/precise_T)**2\
# + ((optimised_O2 - precise_O2)/precise_O2)**2\
# + ((optimised_CO2 - precise_CO2)/precise_CO2)**2\
# + ((optimised_H2O - precise_H2O)/precise_H2O)**2\
return 1e8*abs(ignite_time_optimised - ignite_time_precise) + abs(optimised_T - precise_T)
def test_arrhenius(self):
# test assigning Arrhenius rate
rate = ct.Arrhenius(self._rate["A"], self._rate["b"], self._rate["Ea"])
rxn = self.from_rate(None)
if self._legacy:
rxn.rate = rate
else:
with self.assertWarnsRegex(DeprecationWarning, "'Arrhenius' object is deprecated"):
rxn.rate = rate
self.check_rxn(rxn)
def test_arrhenius(self):
# test assigning Arrhenius rate
rate = ct.Arrhenius(self._rate["A"], self._rate["b"], self._rate["Ea"])
rxn = self._cls(equation=self._equation, kinetics=self.gas,
legacy=self._legacy, **self._kwargs)
if self._legacy:
rxn.rate = rate
else:
with self.assertWarnsRegex(DeprecationWarning, "'Arrhenius' object is deprecated"):
rxn.rate = rate
self.check_rxn(rxn)
def test_elementary(self):
r = ct.ElementaryReaction({'O':1, 'H2':1}, {'H':1, 'OH':1})
r.rate = ct.Arrhenius(3.87e1, 2.7, 6260*1000*4.184)
gas2 = ct.Solution(thermo='IdealGas', kinetics='GasKinetics',
species=self.species, reactions=[r])
gas2.TPX = self.gas.TPX
self.assertNear(gas2.forward_rate_constants[0],
self.gas.forward_rate_constants[2])
self.assertNear(gas2.net_rates_of_progress[0],
self.gas.net_rates_of_progress[2])
def test_modify_sticking(self):
gas = ct.Solution('ptcombust.xml', 'gas')
surf = ct.Interface('ptcombust.xml', 'Pt_surf', [gas])
surf.coverages = 'O(S):0.1, PT(S):0.5, H(S):0.4'
gas.TP = surf.TP
R = surf.reaction(2)
R.rate = ct.Arrhenius(0.25, 0, 0) # original sticking coefficient = 1.0
k1 = surf.forward_rate_constants[2]
surf.modify_reaction(2, R)
k2 = surf.forward_rate_constants[2]
self.assertNear(k1, 4*k2)
def test_negative_A(self):
species = ct.Species.listFromFile('gri30.cti')
r = ct.ElementaryReaction('NH:1, NO:1', 'N2O:1, H:1')
r.rate = ct.Arrhenius(-2.16e13, -0.23, 0)
self.assertFalse(r.allow_negative_pre_exponential_factor)
with self.assertRaises(Exception):
gas = ct.Solution(thermo='IdealGas', kinetics='GasKinetics',
species=species, reactions=[r])
r.allow_negative_pre_exponential_factor = True
gas = ct.Solution(thermo='IdealGas', kinetics='GasKinetics',
species=species, reactions=[r])
def test_threebody(self):
r = ct.ThreeBodyReaction()
r.reactants = {'O':1, 'H':1}
r.products = {'OH':1}
r.rate = ct.Arrhenius(5e11, -1.0, 0.0)
r.efficiencies = {'AR':0.7, 'H2':2.0, 'H2O':6.0}
gas2 = ct.Solution(thermo='IdealGas', kinetics='GasKinetics',
species=self.species, reactions=[r])
gas2.TPX = self.gas.TPX
self.assertNear(gas2.forward_rate_constants[0],
self.gas.forward_rate_constants[1])
self.assertNear(gas2.net_rates_of_progress[0],
self.gas.net_rates_of_progress[1])
def test_modify_third_body(self):
gas = ct.Solution('h2o2.xml')
gas.TPX = self.gas.TPX
R = self.gas.reaction(5)
A1 = R.rate.pre_exponential_factor
b1 = R.rate.temperature_exponent
T = gas.T
kf1 = gas.forward_rate_constants[5]
A2 = 1.7 * A1
b2 = b1 - 0.1
R.rate = ct.Arrhenius(A2, b2, 0.0)
gas.modify_reaction(5, R)
kf2 = gas.forward_rate_constants[5]
self.assertNear((A2 * T**b2) / (A1 * T**b1), kf2 / kf1)
def test_modify_elementary(self):
gas = ct.Solution('h2o2.xml')
gas.TPX = self.gas.TPX
R = self.gas.reaction(2)
A1 = R.rate.pre_exponential_factor
b1 = R.rate.temperature_exponent
Ta1 = R.rate.activation_energy / ct.gas_constant
T = gas.T
self.assertNear(A1*T**b1*np.exp(-Ta1/T), gas.forward_rate_constants[2])
A2 = 1.5 * A1
b2 = b1 + 0.1
Ta2 = Ta1 * 1.2
R.rate = ct.Arrhenius(A2, b2, Ta2 * ct.gas_constant)
gas.modify_reaction(2, R)
self.assertNear(A2*T**b2*np.exp(-Ta2/T), gas.forward_rate_constants[2])
def test_set_rates(self):
# test setter for property rates
other = [
{"P": 100., "A": 1.2124e+16, "b": -1., "Ea": 45491376.8},
{"P": 10000., "A": 4.9108e+31, "b": -2., "Ea": 103649395.2},
{"P": 1000000., "A": 1.2866e+47, "b": -3., "Ea": 166508556.0}]
rate = ct.PlogRate([(o["P"], ct.Arrhenius(o["A"], o["b"], o["Ea"]))
for o in other])
rates = rate.rates
self.assertEqual(len(rates), len(other))
for index, item in enumerate(rates):
P, rate = item
self.assertNear(P, other[index]["P"])
self.assertNear(rate.pre_exponential_factor, other[index]["A"])
self.assertNear(rate.temperature_exponent, other[index]["b"])
self.assertNear(rate.activation_energy, other[index]["Ea"])
def modify_reactions(
self,
coeffs,
rxnNums=[]): # Only works for Arrhenius equations currently
if not rxnNums: # if rxnNums does not exist, modify all
rxnNums = range(len(coeffs))
else:
if isinstance(
rxnNums,
(float, int)): # if single reaction given, run that one
rxnNums = [rxnNums]
for rxnNum in rxnNums:
rxn = self.gas.reaction(rxnNum)
rxnChanged = False
if type(rxn) is ct.ElementaryReaction or type(
rxn) is ct.ThreeBodyReaction:
for coefName in [
'activation_energy', 'pre_exponential_factor',
'temperature_exponent'
]:
if coeffs[rxnNum][coefName] != eval(
f'rxn.rate.{coefName}'):
rxnChanged = True
if rxnChanged: # Update reaction rate
A = coeffs[rxnNum]['pre_exponential_factor']
b = coeffs[rxnNum]['temperature_exponent']
Ea = coeffs[rxnNum]['activation_energy']
rxn.rate = ct.Arrhenius(A, b, Ea)
# elif type(rxn) is ct.PlogReaction:
# print(dir(rxn))
# print(rxn.rates[rxn_num])
# elif type(rxn) is ct.ChebyshevReaction:
# print(dir(rxn))
# print(rxn.rates[rxn_num])
else:
continue
if rxnChanged:
self.gas.modify_reaction(rxnNum, rxn)
time.sleep(
5E-3
) # Not sure if this is necessary, but it reduces strange behavior in incident shock reactor
def set_max_sticking_coeff(rxn, A=0.75):
"""
Fix the maximum sticking coefficient for the given reaction.
ToDo: currently this ignores n and Ea in an Arrhenius expression
and replaces with a uniform A value..
Also, doesn't yet actually update the kinetics object in Cantera memory.
"""
assert rxn.is_sticking_coefficient
if rxn.rate.pre_exponential_factor > A:
old_stick = rxn.rate
rate = ct.Arrhenius(A)
rxn.rate = rate
print(
f"Changed sticking coeff for {rxn.equation} from {old_stick!r} to {rxn.rate.pre_exponential_factor}"
)
raise NotImplementedError(
"Haven't updated the kinetics object in Cantera")
def residual(eta, k0, observations, measure_ind, tmaxes, temperatures,
pressures, initials, maxes, yields):
rstart = timeit.default_timer()
ret = 0
reactions = gas.reaction_equations()
k = k0 * 10**eta
if (gas.reaction_type(measure_ind) == 1):
newrate = ct.ElementaryReaction(gas.reactions()[measure_ind].reactants,
gas.reactions()[measure_ind].products)
newrate.rate = ct.Arrhenius(
k,
gas.reactions()[measure_ind].rate.temperature_exponent,
gas.reactions()[measure_ind].rate.activation_energy)
gas.modify_reaction(measure_ind, newrate)
if (gas.reaction_type(measure_ind) == 2):
newrate = ct.ThreeBodyReaction(
reactants=gas.reactions()[measure_ind].reactants,
products=gas.reactions()[measure_ind].products)
newrate.efficiencies = gas.reactions()[measure_ind].efficiencies
newrate.rate = ct.Arrhenius(
k,
gas.reactions()[measure_ind].rate.temperature_exponent,
gas.reactions()[measure_ind].rate.activation_energy)
gas.modify_reaction(measure_ind, newrate)
if (gas.reaction_type(measure_ind) == 4):
newrate = ct.FalloffReaction(
reactants=gas.reactions()[measure_ind].reactants,
products=gas.reactions()[measure_ind].products)
newrate.efficiencies = gas.reactions()[measure_ind].efficiencies
newrate.falloff = gas.reactions()[measure_ind].falloff
newrate.low_rate = ct.Arrhenius(
k,
gas.reactions()[measure_ind].low_rate.temperature_exponent,
gas.reactions()[measure_ind].low_rate.temperature_exponent,
gas.reactions()[measure_ind].low_rate.activation_energy)
newrate.high_rate = gas.reactions()[measure_ind].high_rate
gas.modify_reaction(measure_ind, newrate)
sys.stdout.flush()
for i in range(0, nmeasure):
states = runsim_nosense(tmaxes[i], temperatures[i], pressures[i],
initials[i])
for n in maxes:
lst1 = observations[i].X[:, n]
lst2 = states.X[:, n]
ind1 = np.array(np.where(np.sign(np.diff(lst1)) == -1))[0, 0]
if np.any(np.sign(np.diff(lst2)) == -1):
ind2 = np.array(np.where(np.sign(np.diff(lst2)) == -1))[0, 0]
else:
ind2 = len(lst2) - 1
ret += ((1.0 * ind2 / ind1 - 1)**2 +
(lst2[ind2] / lst1[ind1] - 1)**2) / nmeasure
if (outflag == 1):
print(temperatures[i], tmaxes[i], pressures[i] / ct.one_atm,
(1.0 * ind2 / ind1 - 1), (lst2[ind2] / lst1[ind1] - 1))
sys.stdout.flush()
for n in yields:
lst1 = observations[i].X[:, n]
lst2 = states.X[:, n]
ret += ((lst2[-1] / lst1[-1] - 1)**2) / nmeasure
if (outflag == 1):
print(temperatures[i], tmaxes[i], pressures[i] / ct.one_atm,
(lst2[-1] / lst1[-1] - 1))
sys.stdout.flush()
if (outflag == 1):
rstop = timeit.default_timer()
print('iter time: %f' % (rstop - rstart))
print('residual: ', ret)
print('x: ', eta)
sys.stdout.flush()
return np.sqrt(ret)
*removed,
sep=' ',
file=f)
f.close()
if (outflag == 1):
print(result)
sys.stdout.flush()
reactions = gas.reaction_equations()
if (gas.reaction_type(measure_ind) == 1):
newrate = ct.ElementaryReaction(
gas.reactions()[measure_ind].reactants,
gas.reactions()[measure_ind].products)
newrate.rate = ct.Arrhenius(
k,
gas.reactions()[measure_ind].rate.temperature_exponent,
gas.reactions()[measure_ind].rate.activation_energy)
gas.modify_reaction(measure_ind, newrate)
if (gas.reaction_type(measure_ind) == 2):
newrate = ct.ThreeBodyReaction(
reactants=gas.reactions()[measure_ind].reactants,
products=gas.reactions()[measure_ind].products)
newrate.efficiencies = gas.reactions()[measure_ind].efficiencies
newrate.rate = ct.Arrhenius(
k,
gas.reactions()[measure_ind].rate.temperature_exponent,
gas.reactions()[measure_ind].rate.activation_energy)
gas.modify_reaction(measure_ind, newrate)
if (gas.reaction_type(measure_ind) == 4):
newrate = ct.FalloffReaction(
reactants=gas.reactions()[measure_ind].reactants,
states('CO2').X,
'--',
label='Redeuced to {} reactions'.format(gas2.n_reactions))
plt.legend()
plt.xlabel('Time (ms)')
plt.ylabel('CO2 Mole Fraction')
import best_fit
tmp_reactions = R.copy()
tmp_parameters = best_fit.best_fit[-1][1]
print(len(tmp_reactions))
for i in range(len(tmp_reactions)):
if tmp_reactions[i].reaction_type != 4:
tmp_reactions[i].rate = ct.Arrhenius(A=tmp_parameters[3 * i],
b=tmp_parameters[3 * i + 1],
E=tmp_parameters[3 * i + 2])
else:
tmp_reactions[i].low_rate = ct.Arrhenius(A=tmp_parameters[3 * i],
b=tmp_parameters[3 * i + 1],
E=tmp_parameters[3 * i + 2])
gas2 = ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=gas.species(),
reactions=tmp_reactions)
gas2.TPX = temp, pres, 'CH4:1, O2:2'
r = ct.IdealGasConstPressureReactor(gas2)
sim = ct.ReactorNet([r])
states = ct.SolutionArray(gas2, extra=['t'])
def perturb_parameter_thisisthecomplicatedonethatdoesntwork(
self, parameter, new_value):
param_info = self.model_parameter_info[parameter]
reaction_number = param_info['reaction_number']
parameter_type = param_info['parameter_type']
print(parameter)
print(param_info)
reaction = self.gas.reaction(reaction_number)
print(reaction.rate)
rate = None
efficiencies = None
reactants = reaction.reactant_string
products = reaction.product_string
rtype = reaction.reaction_type
pressurestring = 'pressure'
HasFalloff = False
if pressurestring in parameter_type:
HasFalloff = True
if HasFalloff:
highrate = reaction.high_rate
lowrate = reaction.low_rate
if rtype == 4:
newreaction = ct.FalloffReaction(reactants=reactants,
products=products)
if rtype == 8:
newreaction = ct.ChemicallyActivatedReaction(
reactants=reactants, products=products)
else:
rate = reaction.rate
if rtype == 2:
newreaction = ct.ThreeBodyReaction(reactants=reactants,
products=products)
else:
newreaction = ct.ElementaryReaction(reactants=reactants,
products=products)
if parameter_type == 'A_factor':
old_A = rate.pre_exponential_factor
old_b = rate.temperature_exponent
old_E = rate.activation_energy
new_A = new_value
newreaction.rate = ct.Arrhenius(A=new_A, b=old_b, E=old_E)
if parameter_type == 'Energy':
old_A = rate.pre_exponential_factor
old_b = rate.temperature_exponent
old_E = rate.activation_energy
new_E = new_value
newreaction.rate = ct.Arrhenius(A=old_A, b=old_b, E=new_E)
if parameter_type == 'High_pressure_A':
rate = highrate
old_A = rate.pre_exponential_factor
old_b = rate.temperature_exponent
old_E = rate.activation_energy
new_A = new_value
newreaction.high_rate = ct.Arrhenius(A=new_A, b=old_b, E=old_E)
if parameter_type == 'High_pressure_E':
rate = highrate
old_A = rate.pre_exponential_factor
old_b = rate.temperature_exponent
old_E = rate.activation_energy
new_E = new_value
newreaction.high_rate = ct.Arrhenius(A=old_A, b=old_b, E=new_E)
if parameter_type == 'Low_pressure_A':
rate = lowrate
old_A = rate.pre_exponential_factor
old_b = rate.temperature_exponent
old_E = rate.activation_energy
new_A = new_value
newreaction.low_rate = ct.Arrhenius(A=new_A, b=old_b, E=old_E)
if parameter_type == 'Low_pressure_E':
rate = lowrate
old_A = rate.pre_exponential_factor
old_b = rate.temperature_exponent
old_E = rate.activation_energy
new_E = new_value
newreaction.low_rate = ct.Arrhenius(A=old_A, b=old_b, E=new_E)
self.gas.modify_reaction(reaction_number, newreaction)
if parameter_type == 'Efficiency':
efficiencies = copy.deepcopy(reaction.efficiencies)
species = param_info['species']
efficiencies[species] = new_value
reaction.efficiencies = efficiencies
return
def cti_write(x={},original_cti='',master_rxns='',master_index=[]):
if not original_cti:
raise Exception('Please provide a name for the original mechanism file and try again.')
if not master_rxns and np.any(master_index):
raise Exception('Please provide a mechanism file for reactions analysed with master equation or leave master_index empty')
if master_rxns and not np.any(master_index):
raise Exception('Please provide master_index, a non-empty list of reaction numbers from original file which are analysed with master equation.')
if not master_rxns and not master_index:
master_index=np.ones(ct.Solution(original_cti).n_reactions,dtype=bool)
elif master_rxns and np.any(master_index):
temp=np.ones(ct.Solution(original_cti).n_reactions,dtype=bool)
for j in np.arange(len(master_index)):
temp[master_index[j]-1]=False
master_index=temp
lineList=[]
with open(original_cti) as f:
lineList=f.readlines()
done=False
count=0
while not done or count<len(lineList):
if 'Reaction data' in lineList[count] or 'Reaction Data' in lineList[count] or 'reaction data' in lineList[count]:
done=True
lineList=lineList[0:count-1]
else:count+=1
with open('tempcti.cti','w') as p:
p.writelines(lineList)
NewModel=ct.Solution('tempcti.cti')
original_mechanism=ct.Solution(original_cti)
master_count=0
if master_rxns:
master_reactions=ct.Solution(master_rxns)
for i in np.arange(original_mechanism.n_reactions):
if master_index[i]==True:
NewModel.add_reaction(original_mechanism.reaction(i))
elif master_index[i]==False:
NewModel.add_reaction(master_reactions.reaction(master_count))
master_count+=1
if x=={}:
for j in np.arange(original_mechanism.n_reactions):
if master_index[j]:
if 'ThreeBodyReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).rate=original_mechanism.reaction(j).rate
elif 'ElementaryReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).rate=original_mechanism.reaction(j).rate
elif 'FalloffReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).high_rate=original_mechanism.reaction(j).high_rate
NewModel.reaction(j).low_rate=original_mechanism.reaction(j).low_rate
if original_mechanism.reaction(j).falloff.type=='Troe':
NewModel.reaction(j).falloff=original_mechanism.reaction(j).falloff
if original_mechanism.reaction(j).falloff.type=='Sri':
NewModel.reaction(j).falloff=original_mechanism.reaction(j).falloff
elif 'ChemicallyActivatedReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).high_rate=original_mechanism.reaction(j).high_rate
NewModel.reaction(j).low_rate=original_mechanism.reaction(j).low_rate
if original_mechanism.reaction(j).falloff.type=='Troe':
NewModel.reaction(j).falloff=original_mechanism.reaction(j).falloff
if original_mechanism.reaction(j).falloff.type=='Sri':
NewModel.reaction(j).falloff=original_mechanism.reaction(j).falloff
elif 'PlogReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).rates=original_mechanism.reaction(j).rates
elif 'ChebyshevReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).set_parameters(original_mechanism.reaction(j).Tmin,original_mechanism.reaction(j).Tmax,original_mechanism.reaction(j).Pmin,original_mechanism.reaction(j).Pmax,original_mechanism.reaction(j).coeffs)
if x!={}:
for j in np.arange(original_mechanism.n_reactions):
if master_index[j]:
try:
if 'ThreeBodyReaction' in str(type(original_mechanism.reaction(j))):
A=original_mechanism.reaction(j).rate.pre_exponential_factor
n=original_mechanism.reaction(j).rate.temperature_exponent
Ea=original_mechanism.reaction(j).rate.activation_energy
NewModel.reaction(j).rate=ct.Arrhenius(A*np.exp(x['r'+str(j)]['A']),n+x['r'+str(j)]['n'],Ea+x['r'+str(j)]['Ea'])
elif 'ElementaryReaction' in str(type(original_mechanism.reaction(j))):
A=original_mechanism.reaction(j).rate.pre_exponential_factor
n=original_mechanism.reaction(j).rate.temperature_exponent
Ea=original_mechanism.reaction(j).rate.activation_energy
NewModel.reaction(j).rate=ct.Arrhenius(A*np.exp(x['r'+str(j)]['A']),n+x['r'+str(j)]['n'],Ea+x['r'+str(j)]['Ea'])
elif 'FalloffReaction' in str(type(original_mechanism.reaction(j))):
A=original_mechanism.reaction(j).high_rate.pre_exponential_factor
n=original_mechanism.reaction(j).high_rate.temperature_exponent
Ea=original_mechanism.reaction(j).high_rate.activation_energy
NewModel.reaction(j).high_rate=ct.Arrhenius(A*np.exp(x['r'+str(j)]['A']),n+x['r'+str(j)]['n'],Ea+x['r'+str(j)]['Ea'])
A=original_mechanism.reaction(j).low_rate.pre_exponential_factor
n=original_mechanism.reaction(j).low_rate.temperature_exponent
Ea=original_mechanism.reaction(j).low_rate.activation_energy
NewModel.reaction(j).low_rate=ct.Arrhenius(A*np.exp(x['r'+str(j)]['A']),n+x['r'+str(j)]['n'],Ea+x['r'+str(j)]['Ea'])
if original_mechanism.reaction(j).falloff.type=='Troe':
NewModel.reaction(j).falloff=original_mechanism.reaction(j).falloff
if original_mechanism.reaction(j).falloff.type=='Sri':
NewModel.reaction(j).falloff=original_mechanism.reaction(j).falloff
elif 'ChemicallyActivatedReaction' in str(type(original_mechanism.reaction(j))):
A=original_mechanism.reaction(j).high_rate.pre_exponential_factor
n=original_mechanism.reaction(j).high_rate.temperature_exponent
Ea=original_mechanism.reaction(j).high_rate.activation_energy
NewModel.reaction(j).high_rate=ct.Arrhenius(A*np.exp(x['r'+str(j)]['A']),n+x['r'+str(j)]['n'],Ea+x['r'+str(j)]['Ea'])
A=original_mechanism.reaction(j).low_rate.pre_exponential_factor
n=original_mechanism.reaction(j).low_rate.temperature_exponent
Ea=original_mechanism.reaction(j).low_rate.activation_energy
NewModel.reaction(j).low_rate=ct.Arrhenius(A*np.exp(x['r'+str(j)]['A']),n+x['r'+str(j)]['n'],Ea+x['r'+str(j)]['Ea'])
if original_mechanism.reaction(j).falloff.type=='Troe':
NewModel.reaction(j).falloff=original_mechanism.reaction(j).falloff
if original_mechanism.reaction(j).falloff.type=='Sri':
NewModel.reaction(j).falloff=original_mechanism.reaction(j).falloff
elif 'PlogReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).rates=original_mechanism.reaction(j).rates
elif 'ChebyshevReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).set_parameters(original_mechanism.reaction(j).Tmin,original_mechanism.reaction(j).Tmax,original_mechanism.reaction(j).Pmin,original_mechanism.reaction(j).Pmax,original_mechanism.reaction(j).coeffs)
except:
if 'ThreeBodyReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).rate=original_mechanism.reaction(j).rate
elif 'ElementaryReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).rate=original_mechanism.reaction(j).rate
elif 'FalloffReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).high_rate=original_mechanism.reaction(j).high_rate
NewModel.reaction(j).low_rate=original_mechanism.reaction(j).low_rate
if original_mechanism.reaction(j).falloff.type=='Troe':
NewModel.reaction(j).falloff=original_mechanism.reaction(j).falloff
if original_mechanism.reaction(j).falloff.type=='Sri':
NewModel.reaction(j).falloff=original_mechanism.reaction(j).falloff
elif 'ChemicallyActivatedReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).high_rate=original_mechanism.reaction(j).high_rate
NewModel.reaction(j).low_rate=original_mechanism.reaction(j).low_rate
if original_mechanism.reaction(j).falloff.type=='Troe':
NewModel.reaction(j).falloff=original_mechanism.reaction(j).falloff
if original_mechanism.reaction(j).falloff.type=='Sri':
NewModel.reaction(j).falloff=original_mechanism.reaction(j).falloff
elif 'PlogReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).rates=original_mechanism.reaction(j).rates
elif 'ChebyshevReaction' in str(type(original_mechanism.reaction(j))):
NewModel.reaction(j).set_parameters(original_mechanism.reaction(j).Tmin,original_mechanism.reaction(j).Tmax,original_mechanism.reaction(j).Pmin,original_mechanism.reaction(j).Pmax,original_mechanism.reaction(j).coeffs)
new_file=ctiw.write(NewModel)
return new_file
def run_single(self):
def chebyshev_zeros(da,*args):
i, m, k, gas, modified_rate, current_array=args
temp_r=gas.reactions()[i]
temp_array=copy.deepcopy(current_array)
temp_array[m,k]=current_array[m,k]+da
temp_r.set_parameters(temp_r.Tmin,temp_r.Tmax,temp_r.Pmin,temp_r.Pmax,temp_array)
#temp_r.coeffs[m,k]=gas.reactions()[i].coeffs[m,k]+da
gas.modify_reaction(i,temp_r)
adjusted_rate=gas.forward_rate_constants[i]
diff=adjusted_rate-modified_rate
return diff
gas=self.processor.solution
self.flame=ct.FreeFlame(gas,width=self.flame_width)
self.TPX=copy.deepcopy(gas.TPX)
self.flame.flame.set_steady_tolerances(default=self.tol_ss) #Set steady state tolerances
self.flame.flame.set_transient_tolerances(default=self.tol_ts) #Set transient tolerances
print('Running simulation at T = '+str(round(gas.T,5))+', P = '+str(round(gas.P,5))+'\nConditions: '+str(self.conditions))
if re.match('[aA]diabatic',self.thermalBoundary):
energycon = True
self.flame.energy_enabled = energycon
self.flame.transport_model = 'Multi'
self.flame.set_max_jac_age(10,10)
#self.flame.solve(self.loglevel,refine_grid=False)
self.flame.soret_enabled = self.soret
self.flame.set_refine_criteria(ratio=2.0,slope=0.01,curve=0.025)
#self.flame.transport_model = 'Multi'
self.flame.solve(self.loglevel,refine_grid=True)
self.forward_rates=self.flame.forward_rate_constants
self.net_rates=self.flame.net_rates_of_progress
self.reverse_rates=self.flame.reverse_rate_constants
gas.TPX=self.TPX
#self.flame.solve(self.loglevel,refine_grid=False)
# self.flame.solve(self.loglevel,refine_grid=False)
# self.flame.solve(self.loglevel,refine_grid=False)
# self.flame.solve(self.loglevel,refine_grid=False)
# self.flame.solve(self.loglevel,refine_grid=False)
# self.flame.solve(self.loglevel,refine_grid=False)
self.dk=0.01
if re.match('[Ff]lame [Ss]peed',self.flametype):
columns=['T_in','pressure']+list(self.conditions.keys())+['u0']
self.solution=pd.DataFrame(columns=columns)
for i in range(len(columns)):
if i==0:
self.solution['T_in']=[self.temperature]
elif i==1:
self.solution['pressure']=[self.pressure]
elif i>1 and i<len(columns)-1:
self.solution[columns[i]]=[self.conditions[columns[i]]]
elif i==len(columns)-1:
self.solution['u0']=[self.flame.u[0]]
elif re.match('[Aa]diabatic [Ff]lame',self.flametype):
self.solution=self.flame.X
columnNames=gas.species_names
tempdata=pd.DataFrame(columns=columnNames,data=self.flame.X)
print(tempdata)
if re.match('[Aa]diabatic [Ff]lame',self.flametype) and self.kineticSens==1 and bool(self.observables):
self.dk=0.01
#Calculate kinetic sensitivities
sensIndex = [self.flame.grid.tolist(),gas.reaction_equations(),self.observables]
S = np.zeros((len(self.flame.grid),gas.n_reactions,len(self.observables)))
#print(solution.X[solution.flame.component_index(observables[0])-4,len(f.grid)-1])
#a=solution.X[solution.flame.component_index(observables[0])-4,len(f.grid)-1]
for m in range(gas.n_reactions):
gas.set_multiplier(1.0)
gas.set_multiplier(1+self.dk,m)
self.flame.solve(loglevel=1,refine_grid=False)
for i in np.arange(len(self.observables)):
for k in np.arange(len(self.flame.grid)):
S[k,m,i]=np.log10(self.solution[self.flame.flame.component_index(self.observables[i])-4,k])-np.log10(self.flame.X[self.flame.flame.component_index(self.observables[i])-4,k])
#print(solution.X[solution.flame.component_index(observables[i])-4,k])
#print(f.X[f.flame.component_index(observables[i])-4,k])
S[k,m,i]=np.divide(S[k,m,i],np.log10(self.dk))
elif self.kineticSens==1 and bool(self.observables)==False and not re.match('[Ff]lame [Ss]peed',self.flametype):
raise Exception('Please supply a list of observables in order to run kinetic sensitivity analysis')
#gas.set_multiplier(1.0)
elif self.kineticSens==1 and re.match('[Ff]lame [Ss]peed',self.flametype):
#self.fsens = self.flame.get_flame_speed_reaction_sensitivities()
sensdict={}
nominal_u=self.flame.u[0]
for i in range(len(gas.reactions())):
equation_type=type(gas.reaction(i)).__name__
gas.TPX=self.TPX
if equation_type=='ElementaryReaction' or equation_type=='ThreeBodyReaction':
tempA=copy.deepcopy(gas.reaction(i).rate.pre_exponential_factor)
tempn=copy.deepcopy(gas.reaction(i).rate.temperature_exponent)
tempEa=copy.deepcopy(gas.reaction(i).rate.activation_energy)
#gas.reaction(i).rate=ct.Arrhenius(tempA*(1.0+self.dk),tempn,tempEa)
#gas.reaction(i).rate=ct.Arrhenius(tempA,tempn,tempEa)
temp_r=gas.reactions()[i]
temp_r.rate=ct.Arrhenius(tempA*(1.0+self.dk),tempn,tempEa)
gas.modify_reaction(i,temp_r)
print('Solving flame speed sensitivity with respect to Arrhenius parameters for reaction '+str(i))
#print(self.flame.gas.reaction(i).rate)
#print(tempA,tempn,tempEa)
if self.log_file:
with open(self.log_name,'a') as f:
f.write('Reaction '+str(i)+' Nominals: '+str(round(tempA,9))+', '+str(round(tempn,9))+', '+str(round(tempEa,9))+'\n')
f.write('Reaction '+str(i)+' Modified: '+str(round(gas.reaction(i).rate.pre_exponential_factor,9))+', '+str(round(tempn,9))+', '+str(round(tempEa,9))+'\n')
self.flame.solve(self.loglevel,refine_grid=False)
temp_u_A=copy.deepcopy(self.flame.u[0])
#print(temp_u_A)
if self.log_file:
with open(self.log_name,'a') as f:
f.write('Nominal u0: '+str(round(nominal_u,9))+'\n')
f.write('Modified A'+str(i) +' u0: '+str(round(temp_u_A,9))+'\n')
#gas.reaction(i).rate=ct.Arrhenius(tempA,tempn*(1.0+self.dk),tempEa)
#gas.reaction(i).rate=ct.Arrhenius(tempA,tempn,tempEa)
temp_r=gas.reactions()[i]
dn=0.00136059
temp_r.rate=ct.Arrhenius(tempA,tempn+dn,tempEa)
gas.modify_reaction(i,temp_r)
self.flame.solve(self.loglevel,refine_grid=False)
temp_u_n=copy.deepcopy(self.flame.u[0])
#gas.reaction(i).rate=ct.Arrhenius(tempA,tempn,tempEa*(1.0+self.dk))
#gas.reaction(i).rate=ct.Arrhenius(tempA,tempn,tempEa)
temp_r=gas.reactions()[i]
dEa=-14.9255*ct.gas_constant
temp_r.rate=ct.Arrhenius(tempA,tempn,tempEa+dEa)
gas.modify_reaction(i,temp_r)
self.flame.solve(self.loglevel,refine_grid=False)
temp_u_Ea=copy.deepcopy(self.flame.u[0])
tempChanges=np.array([temp_u_A,temp_u_n,temp_u_Ea])
nominals=nominal_u*np.ones(len(tempChanges))
nominal_df=pd.DataFrame(columns=['u0'])
nominal_df['u0']=nominals
tempChanges_df = pd.DataFrame(columns=['u0'])
tempChanges_df['u0'] = tempChanges
temp_sens=np.zeros(3)
temp_sens[0]=self.sensitivityCalculation(float(nominal_df['u0'][0]),float(tempChanges_df['u0'][0]),self.dk)
temp_sens[1]=self.sensitivityCalculation(float(nominal_df['u0'][1]),float(tempChanges_df['u0'][1]),dn)
temp_sens[2]=self.sensitivityCalculation(float(nominal_df['u0'][2]),float(tempChanges_df['u0'][2]),dEa)
sensdict['Reaction '+str(i)]=temp_sens
#gas.reaction(i).rate=ct.Arrhenius(tempA,tempn, tempEa)
temp_r=gas.reactions()[i]
temp_r.rate=ct.Arrhenius(tempA,tempn,tempEa)
gas.modify_reaction(i,temp_r)
elif equation_type=='FalloffReaction':
print('Solving flame speed sensitivity with respect to Arrhenius parameters for reaction '+str(i))
tempAl=copy.deepcopy(gas.reaction(i).low_rate.pre_exponential_factor)
tempnl=copy.deepcopy(gas.reaction(i).low_rate.temperature_exponent)
tempEal=copy.deepcopy(gas.reaction(i).low_rate.activation_energy)
tempAh=copy.deepcopy(gas.reaction(i).high_rate.pre_exponential_factor)
tempnh=copy.deepcopy(gas.reaction(i).high_rate.temperature_exponent)
tempEah=copy.deepcopy(gas.reaction(i).high_rate.activation_energy)
temp_r=gas.reactions()[i]
temp_r.low_rate=ct.Arrhenius(tempAl*(1.0+self.dk),tempnl,tempEal)
temp_r.high_rate=ct.Arrhenius(tempAh*(1.0+self.dk),tempnh,tempEah)
gas.modify_reaction(i,temp_r)
#self.flame.gas.reaction(i).low_rate=ct.Arrhenius(tempAl*(1.0+self.dk),tempnl,tempEal)
#self.flame.gas.reaction(i).high_rate=ct.Arrhenius(tempAh*(1.0+self.dk),tempnh,tempEah)
self.flame.solve(self.loglevel,refine_grid=False)
temp_u_A=copy.deepcopy(self.flame.u[0])
temp_r=gas.reactions()[i]
dn=0.00136059
temp_r.low_rate=ct.Arrhenius(tempAl,tempnl+dn,tempEal)
temp_r.high_rate=ct.Arrhenius(tempAh,tempnh+dn,tempEah)
gas.modify_reaction(i,temp_r)
#self.flame.gas.reaction(i).low_rate=ct.Arrhenius(tempAl,tempnl*(1.0+self.dk),tempEal)
#self.flame.gas.reaction(i).high_rate=ct.Arrhenius(tempAh,tempnh*(1.0+self.dk),tempEah)
self.flame.solve(self.loglevel,refine_grid=False)
temp_u_n=copy.deepcopy(self.flame.u[0])
temp_r=gas.reactions()[i]
dEa=-14.9255*ct.gas_constant
temp_r.low_rate=ct.Arrhenius(tempAl,tempnl,tempEal+dEa)
temp_r.high_rate=ct.Arrhenius(tempAh,tempnh,tempEah+dEa)
gas.modify_reaction(i,temp_r)
#self.flame.gas.reaction(i).low_rate=ct.Arrhenius(tempAl,tempnl,tempEal*(1.0+self.dk))
#self.flame.gas.reaction(i).high_rate=ct.Arrhenius(tempAh,tempnh,tempEah*(1.0+self.dk))
self.flame.solve(self.loglevel,refine_grid=False)
temp_u_Ea=copy.deepcopy(self.flame.u[0])
tempChanges=np.array([temp_u_A,temp_u_n,temp_u_Ea])
nominals=nominal_u*np.ones(len(tempChanges))
nominal_df=pd.DataFrame(columns=['u0'])
nominal_df['u0']=nominals
tempChanges_df = pd.DataFrame(columns=['u0'])
tempChanges_df['u0'] = tempChanges
temp_sens=np.zeros(3)
temp_sens[0]=self.sensitivityCalculation(float(nominal_df['u0'][0]),float(tempChanges_df['u0'][0]),self.dk)
temp_sens[1]=self.sensitivityCalculation(float(nominal_df['u0'][1]),float(tempChanges_df['u0'][1]),dn)
temp_sens[2]=self.sensitivityCalculation(float(nominal_df['u0'][2]),float(tempChanges_df['u0'][2]),dEa)
sensdict['Reaction '+str(i)]=temp_sens
temp_r=gas.reactions()[i]
temp_r.low_rate=ct.Arrhenius(tempAl,tempnl,tempEal)
temp_r.high_rate=ct.Arrhenius(tempAh,tempnh,tempEah)
gas.modify_reaction(i,temp_r)
#self.flame.gas.reaction(i).low_rate=ct.Arrhenius(tempAl,tempnl, tempEal)
#self.flame.gas.reaction(i).high_rate=ct.Arrhenius(tempAh,tempnh, tempEah)
elif equation_type=='ChebyshevReaction':
#print('Chebyshev sensitivities not yet installed')
current_array=copy.deepcopy(gas.reaction(i).coeffs)
temp_u=np.zeros(np.shape(current_array))
sens=np.zeros(np.shape(current_array))
temp_gas=ct.Solution(self.processor.cti_path)
#temp_gas.TPX=gas.TPX
#temp_gas.TP=1500,gas.P
#temp_range=np.linspace(gas.reactions()[i].Tmin,gas.reactions()[i].Tmax,len(gas.reactions()[i].coeffs[:,0])+1)
temp_range=np.linspace(gas.reactions()[i].Tmin,gas.reactions()[i].Tmax,len(gas.reactions()[i].coeffs[:,0]))
#midpoints=np.zeros(len(temp_range)-1)
midpoints=copy.deepcopy(temp_range)
midpoints[0]=(temp_range[0]+temp_range[1])/2
midpoints[-1]=(temp_range[-1]+temp_range[-2])/2
#for j,T in enumerate(midpoints):
#midpoints[j]=(temp_range[j]+temp_range[j+1])/2.0
for m in range(len(current_array[:,0])):
for k in range(len(current_array[0,:])):
gas.TPX=self.TPX
temp_gas.TPX=gas.TPX
temp_gas.TP=midpoints[m],gas.P
current_rate=temp_gas.forward_rate_constants[i]
modified_rate=1.01*current_rate
print('Solving Chebyshev parameter sensitivity ['+str(m)+', '+str(k)+' for reaction ' +str(i))
print(temp_gas.TP)
temp_r=temp_gas.reactions()[i]
args=(i,m,k,temp_gas,modified_rate,current_array)
da=scipy.optimize.fsolve(chebyshev_zeros,current_array[m,k],args=args)
gas.TPX=self.TPX
print('Delta alpha '+str(m)+', '+str(k)+'= '+str(da))
#temp_r.coeffs=current_array
temp_r.set_parameters(temp_r.Tmin,temp_r.Tmax,temp_r.Pmin,temp_r.Pmax,current_array)
temp_current_array=copy.deepcopy(current_array)
temp_current_array[m,k]=current_array[m,k]+da
temp_r.set_parameters(temp_r.Tmin,temp_r.Tmax,temp_r.Pmin,temp_r.Pmax,temp_current_array)
gas.modify_reaction(i,temp_r)
self.flame.solve(self.loglevel,refine_grid=True)
temp_u[m,k]=copy.deepcopy(self.flame.u[0])
nominals=nominal_u*np.ones(np.shape(current_array))
sens[m,k]=self.sensitivityCalculation(nominals[m,k],temp_u[m,k],da)
temp_r=gas.reactions()[i]
temp_r.set_parameters(temp_r.Tmin,temp_r.Tmax,temp_r.Pmin,temp_r.Pmax,current_array)
gas.modify_reaction(i,temp_r)
sensdict['Reaction '+str(i)]=sens
self.fsens=sensdict
if self.kineticSens==1 and re.match('[Ff]lame [Ss]peed',self.flametype):
#numpyMatrixsksens = [dfs[dataframe].values for dataframe in range(len(dfs))]
#self.kineticSensitivities = np.dstack(numpyMatrixsksens)
#print(np.shape(self.kineticSensitivities))
#self.solution=data
return (self.solution,self.fsens)
elif self.kineticSens==1 and re.match('[Aa]diabatic [Ff]lame',self.flametype):
dfs = [pd.DataFrame() for x in range(len(self.observables))]
#print((pd.DataFrame(sens[0,:])).transpose())
#test=pd.concat([pd.DataFrame(),pd.DataFrame(sens[0,:]).transpose()])
#print(test)
#for k in range(len(self.observables)):
#dfs[k] = dfs[k].append(((pd.DataFrame(sens[k,:])).transpose()),ignore_index=True)
#dfs[k]=pd.concat([dfs[k],pd.DataFrame(sens[k,:]).transpose()])
#dfs[k]=pd.DataFrame(sens[k,:]).transpose()
#print(dfs)
numpyMatrixsksens = [dfs[dataframe].values for dataframe in range(len(dfs))]
self.kineticSensitivities = np.dstack(numpyMatrixsksens)
#print(np.shape(self.kineticSensitivities))
#self.solution=data
return (self.solution,self.kineticSensitivities)
elif self.kineticSens==0:
#numpyMatrixsksens = [dfs[dataframe].values for dataframe in range(len(dfs))]
return (self.solution,[])
else:
#self.solution=data
return (self.solution,[])
class TestElementary(utilities.CanteraTest):
_cls = ct.ElementaryReaction
_equation = 'H2 + O <=> H + OH'
_rate = {'A': 38.7, 'b': 2.7, 'Ea': 2.619184e+07}
_rate_obj = ct.Arrhenius(38.7, 2.7, 2.619184e+07)
_index = 2
_type = "elementary"
@classmethod
def setUpClass(cls):
utilities.CanteraTest.setUpClass()
cls.gas = ct.Solution('h2o2.xml')
cls.gas.X = 'H2:0.1, H2O:0.2, O2:0.7, O:1e-4, OH:1e-5, H:2e-5'
cls.gas.TP = 900, 2*ct.one_atm
cls.species = ct.Species.listFromFile('h2o2.xml')
def check_rxn(self, rxn):
ix = self._index
self.assertEqual(rxn.reaction_type, self._type)
self.assertNear(rxn.rate(self.gas.T), self.gas.forward_rate_constants[ix])
self.assertEqual(rxn.reactants, self.gas.reaction(ix).reactants)
self.assertEqual(rxn.products, self.gas.reaction(ix).products)
gas2 = ct.Solution(thermo='IdealGas', kinetics='GasKinetics',
species=self.species, reactions=[rxn])
gas2.TPX = self.gas.TPX
self.check_sol(gas2)
def check_sol(self, gas2):
ix = self._index
self.assertEqual(gas2.reaction_type_str(0), self._type)
self.assertNear(gas2.forward_rate_constants[0],
self.gas.forward_rate_constants[ix])
self.assertNear(gas2.net_rates_of_progress[0],
self.gas.net_rates_of_progress[ix])
def test_rate(self):
self.assertNear(self._rate_obj(self.gas.T), self.gas.forward_rate_constants[self._index])
def test_from_parts(self):
orig = self.gas.reaction(self._index)
rxn = self._cls(orig.reactants, orig.products)
rxn.rate = self._rate_obj
self.check_rxn(rxn)
def test_from_dict(self):
rxn = self._cls(equation=self._equation, rate=self._rate, kinetics=self.gas)
self.check_rxn(rxn)
def test_from_rate(self):
rxn = self._cls(equation=self._equation, rate=self._rate_obj, kinetics=self.gas)
self.check_rxn(rxn)
def test_add_rxn(self):
gas2 = ct.Solution(thermo='IdealGas', kinetics='GasKinetics',
species=self.species, reactions=[])
gas2.TPX = self.gas.TPX
rxn = self._cls(equation=self._equation, rate=self._rate_obj, kinetics=self.gas)
gas2.add_reaction(rxn)
self.check_sol(gas2)
def test_wrong_rate(self):
with self.assertRaises(TypeError):
rxn = self._cls(equation=self._equation, rate=[], kinetics=self.gas)
def test_no_rate(self):
rxn = self._cls(equation=self._equation, kinetics=self.gas)
self.assertNear(rxn.rate(self.gas.T), 0.)
gas2 = ct.Solution(thermo='IdealGas', kinetics='GasKinetics',
species=self.species, reactions=[rxn])
gas2.TPX = self.gas.TPX
self.assertNear(gas2.forward_rate_constants[0], 0.)
self.assertNear(gas2.net_rates_of_progress[0], 0.)
def test_replace_rate(self):
rxn = self._cls(equation=self._equation, kinetics=self.gas)
rxn.rate = self._rate_obj
self.check_rxn(rxn)
def cti_write2(x={},
original_cti='',
master_rxns='',
master_index=[],
MP={},
working_directory='',
file_name=''):
#print(MP)
print(bool(x))
if not original_cti:
raise Exception(
'Please provide a name for the original mechanism file and try again.'
)
if not master_rxns and np.any(master_index):
raise Exception(
'Please provide a mechanism file for reactions analysed with master equation or leave master_index empty'
)
if master_rxns and not np.any(master_index):
raise Exception(
'Please provide master_index, a non-empty list of reaction numbers from original file which are analysed with master equation.'
)
if not master_rxns and not master_index:
master_index = np.ones(ct.Solution(original_cti).n_reactions,
dtype=bool)
elif master_rxns and np.any(master_index):
temp = np.ones(ct.Solution(original_cti).n_reactions, dtype=bool)
for j in np.arange(len(master_index)):
temp[master_index[j] - 1] = False
master_index = temp
lineList = []
with open(original_cti) as f:
lineList = f.readlines()
done = False
count = 0
while not done or count < len(lineList):
if 'Reaction data' in lineList[count] or 'Reaction Data' in lineList[
count] or 'reaction data' in lineList[count]:
done = True
lineList = lineList[0:count - 1]
else:
count += 1
with open('tempcti.cti', 'w') as p:
p.writelines(lineList)
NewModel = ct.Solution('tempcti.cti')
original_mechanism = ct.Solution(original_cti)
original_rxn_count = 0
master_rxn_eqs = []
if master_rxns:
with open(master_rxns) as f:
reactionsList = f.readlines()
lineList = lineList + reactionsList
with open('masterTemp.cti', 'w') as f:
f.writelines(lineList)
master_reactions = ct.Solution('masterTemp.cti')
master_rxn_eqs = master_reactions.reaction_equations()
original_rxn_eqs = []
for i in np.arange(original_mechanism.n_reactions):
if master_index[i]:
NewModel.add_reaction(original_mechanism.reaction(i))
original_rxn_count += 1
original_rxn_eqs.append(original_mechanism.reaction_equation(i))
# if 'FalloffReaction' in str(type(original_mechanism.reaction(i))):
# print(original_mechanism.reaction(i).high_rate)
# print(original_mechanism.reaction(i).low_rate)
if master_rxns:
for i in np.arange(master_reactions.n_reactions):
# print(master_reactions.reaction(i).rate)
NewModel.add_reaction(master_reactions.reaction(i))
#print(master_reactions.reaction(0).rate)
if x == {}:
for j in np.arange(original_rxn_count - 1):
#if master_index[j]:
#print(str(type(original_mechanism.reaction(j))),str(type(NewModel.reaction(j))))
if 'ThreeBodyReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).rate = NewModel.reaction(j).rate
elif 'ElementaryReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).rate = NewModel.reaction(j).rate
elif 'FalloffReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).high_rate = NewModel.reaction(j).high_rate
NewModel.reaction(j).low_rate = NewModel.reaction(j).low_rate
if NewModel.reaction(j).falloff.type == 'Troe':
NewModel.reaction(j).falloff = NewModel.reaction(j).falloff
if NewModel.reaction(j).falloff.type == 'Sri':
NewModel.reaction(j).falloff = NewModel.reaction(j).falloff
elif 'ChemicallyActivatedReaction' in str(
type(NewModel.reaction(j))):
NewModel.reaction(j).high_rate = NewModel.reaction(j).high_rate
NewModel.reaction(j).low_rate = NewModel.reaction(j).low_rate
if NewModel.reaction(j).falloff.type == 'Troe':
NewModel.reaction(j).falloff = NewModel.reaction(j).falloff
if NewModel.reaction(j).falloff.type == 'Sri':
NewModel.reaction(j).falloff = NewModel.reaction(j).falloff
elif 'PlogReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).rates = NewModel.reaction(j).rates
elif 'ChebyshevReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).set_parameters(
NewModel.reaction(j).Tmin,
NewModel.reaction(j).Tmax,
NewModel.reaction(j).Pmin,
NewModel.reaction(j).Pmax,
NewModel.reaction(j).coeffs)
#Rinv = 1/R #cal/mol*K
E = 1 #going test for energy
#T = 4184
#T= 4.186e3
T = ct.gas_constant
if x != {}:
for j in np.arange(original_rxn_count - 1):
#if master_index[j]:
try:
if 'ThreeBodyReaction' in str(type(NewModel.reaction(j))):
A = NewModel.reaction(j).rate.pre_exponential_factor
n = NewModel.reaction(j).rate.temperature_exponent
Ea = NewModel.reaction(j).rate.activation_energy
NewModel.reaction(j).rate = ct.Arrhenius(
A * np.exp(x['r' + str(j)]['A']),
n + x['r' + str(j)]['n'],
Ea + x['r' + str(j)]['Ea'] * T)
elif 'ElementaryReaction' in str(type(NewModel.reaction(j))):
A = NewModel.reaction(j).rate.pre_exponential_factor
n = NewModel.reaction(j).rate.temperature_exponent
Ea = NewModel.reaction(j).rate.activation_energy
NewModel.reaction(j).rate = ct.Arrhenius(
A * np.exp(x['r' + str(j)]['A']),
n + x['r' + str(j)]['n'],
Ea + x['r' + str(j)]['Ea'] * T)
elif 'FalloffReaction' in str(type(NewModel.reaction(j))):
A = NewModel.reaction(j).high_rate.pre_exponential_factor
n = NewModel.reaction(j).high_rate.temperature_exponent
Ea = NewModel.reaction(j).high_rate.activation_energy
NewModel.reaction(j).high_rate = ct.Arrhenius(
A * np.exp(x['r' + str(j)]['A']),
n + x['r' + str(j)]['n'],
Ea + x['r' + str(j)]['Ea'] * T)
A = NewModel.reaction(j).low_rate.pre_exponential_factor
n = NewModel.reaction(j).low_rate.temperature_exponent
Ea = NewModel.reaction(j).low_rate.activation_energy
NewModel.reaction(j).low_rate = ct.Arrhenius(
A * np.exp(x['r' + str(j)]['A']),
n + x['r' + str(j)]['n'],
Ea + x['r' + str(j)]['Ea'] * T)
if NewModel.reaction(j).falloff.type == 'Troe':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
if NewModel.reaction(j).falloff.type == 'Sri':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
elif 'ChemicallyActivatedReaction' in str(
type(NewModel.reaction(j))):
A = NewModel.reaction(j).high_rate.pre_exponential_factor
n = NewModel.reaction(j).high_rate.temperature_exponent
Ea = NewModel.reaction(j).high_rate.activation_energy
NewModel.reaction(j).high_rate = ct.Arrhenius(
A * np.exp(x['r' + str(j)]['A']),
n + x['r' + str(j)]['n'],
Ea + x['r' + str(j)]['Ea'] * T)
A = NewModel.reaction(j).low_rate.pre_exponential_factor
n = NewModel.reaction(j).low_rate.temperature_exponent
Ea = NewModel.reaction(j).low_rate.activation_energy
NewModel.reaction(j).low_rate = ct.Arrhenius(
A * np.exp(x['r' + str(j)]['A']),
n + x['r' + str(j)]['n'],
Ea + x['r' + str(j)]['Ea'] * T)
if NewModel.reaction(j).falloff.type == 'Troe':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
if NewModel.reaction(j).falloff.type == 'Sri':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
elif 'PlogReaction' in str(type(NewModel.reaction(j))):
for number, reactions in enumerate(
NewModel.reaction(j).rates):
A = NewModel.reaction(
j)[number][1].pre_exponential_factor
n = NewModel.reaction(
j)[number][1].temperature_exponent
Ea = NewModel.reaction(j)[number][1].activation_energy
NewModel.reaction(j)[number][1] = ct.Arrhenius(
A * np.exp(x['r' + str(j)]['A']),
n + x['r' + str(j)]['n'],
Ea + x['r' + str(j)]['Ea'] * T)
NewModel.reaction(j).rates = NewModel.reaction(j).rates
elif 'ChebyshevReaction' in str(
type(original_mechanism.reaction(j))):
NewModel.reaction(j).set_parameters(
NewModel.reaction(j).Tmin,
NewModel.reaction(j).Tmax,
NewModel.reaction(j).Pmin,
NewModel.reaction(j).Pmax,
NewModel.reaction(j).coeffs)
except:
#print ('we are in the except statment in marks code',j)
if 'ThreeBodyReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).rate = NewModel.reaction(j).rate
elif 'ElementaryReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).rate = NewModel.reaction(j).rate
elif 'FalloffReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).high_rate = NewModel.reaction(
j).high_rate
NewModel.reaction(j).low_rate = NewModel.reaction(
j).low_rate
if NewModel.reaction(j).falloff.type == 'Troe':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
if NewModel.reaction(j).falloff.type == 'Sri':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
elif 'ChemicallyActivatedReaction' in str(
type(NewModel.reaction(j))):
NewModel.reaction(j).high_rate = NewModel.reaction(
j).high_rate
NewModel.reaction(j).low_rate = NewModel.reaction(
j).low_rate
if NewModel.reaction(j).falloff.type == 'Troe':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
if NewModel.reaction(j).falloff.type == 'Sri':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
elif 'PlogReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).rates = NewModel.reaction(j).rates
elif 'ChebyshevReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).set_parameters(
NewModel.reaction(j).Tmin,
NewModel.reaction(j).Tmax,
NewModel.reaction(j).Pmin,
NewModel.reaction(j).Pmax,
NewModel.reaction(j).coeffs)
if MP != {}:
print('insdie the MP if statment')
for j in np.arange(original_rxn_count, NewModel.n_reactions):
try:
if 'ThreeBodyReaction' in str(type(NewModel.reaction(j))):
A = NewModel.reaction(j).rate.pre_exponential_factor
n = NewModel.reaction(j).rate.temperature_exponent
Ea = NewModel.reaction(j).rate.activation_energy
NewModel.reaction(j).rate = ct.Arrhenius(
A * np.exp(MP['r' + str(j)]['A']),
n + MP['r' + str(j)]['n'],
Ea + MP['r' + str(j)]['Ea'] * E)
elif 'ElementaryReaction' in str(type(NewModel.reaction(j))):
A = NewModel.reaction(j).rate.pre_exponential_factor
n = NewModel.reaction(j).rate.temperature_exponent
Ea = NewModel.reaction(j).rate.activation_energy
NewModel.reaction(j).rate = ct.Arrhenius(
A * np.exp(MP['r' + str(j)]['A']),
n + MP['r' + str(j)]['n'],
Ea + MP['r' + str(j)]['Ea'] * E)
elif 'FalloffReaction' in str(type(NewModel.reaction(j))):
A = NewModel.reaction(j).high_rate.pre_exponential_factor
n = NewModel.reaction(j).high_rate.temperature_exponent
Ea = NewModel.reaction(j).high_rate.activation_energy
NewModel.reaction(j).high_rate = ct.Arrhenius(
A * np.exp(MP['r' + str(j)]['A']),
n + MP['r' + str(j)]['n'],
Ea + MP['r' + str(j)]['Ea'] * E)
A = NewModel.reaction(j).low_rate.pre_exponential_factor
n = NewModel.reaction(j).low_rate.temperature_exponent
Ea = NewModel.reaction(j).low_rate.activation_energy
NewModel.reaction(j).low_rate = ct.Arrhenius(
A * np.exp(MP['r' + str(j)]['A']),
n + MP['r' + str(j)]['n'],
Ea + MP['r' + str(j)]['Ea'] * E)
if NewModel.reaction(j).falloff.type == 'Troe':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
if NewModel.reaction(j).falloff.type == 'Sri':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
elif 'ChemicallyActivatedReaction' in str(
type(NewModel.reaction(j))):
A = NewModel.reaction(j).high_rate.pre_exponential_factor
n = NewModel.reaction(j).high_rate.temperature_exponent
Ea = NewModel.reaction(j).high_rate.activation_energy
NewModel.reaction(j).high_rate = ct.Arrhenius(
A * np.exp(MP['r' + str(j)]['A']),
n + MP['r' + str(j)]['n'],
Ea + MP['r' + str(j)]['Ea'] * E)
A = NewModel.reaction(j).low_rate.pre_exponential_factor
n = NewModel.reaction(j).low_rate.temperature_exponent
Ea = NewModel.reaction(j).low_rate.activation_energy
NewModel.reaction(j).low_rate = ct.Arrhenius(
A * np.exp(MP['r' + str(j)]['A']),
n + MP['r' + str(j)]['n'],
Ea + MP['r' + str(j)]['Ea'] * E)
if NewModel.reaction(j).falloff.type == 'Troe':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
if NewModel.reaction(j).falloff.type == 'Sri':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
elif 'PlogReaction' in str(type(NewModel.reaction(j))):
for number, reactions in enumerate(
NewModel.reaction(j).rates):
A = NewModel.reaction(
j)[number][1].pre_exponential_factor
n = NewModel.reaction(
j)[number][1].temperature_exponent
Ea = NewModel.reaction(j)[number][1].activation_energy
NewModel.reaction(j)[number][1] = ct.Arrhenius(
A * np.exp(MP['r' + str(j)]['A']),
n + MP['r' + str(j)]['n'],
Ea + MP['r' + str(j)]['Ea'] * E)
NewModel.reaction(j).rates = NewModel.reaction(j).rates
elif 'ChebyshevReaction' in str(
type(original_mechanism.reaction(j))):
NewModel.reaction(j).set_parameters(
NewModel.reaction(j).Tmin,
NewModel.reaction(j).Tmax,
NewModel.reaction(j).Pmin,
NewModel.reaction(j).Pmax,
NewModel.reaction(j).coeffs)
except:
print('we are in the except statment in marks code', j)
if 'ThreeBodyReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).rate = NewModel.reaction(j).rate
elif 'ElementaryReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).rate = NewModel.reaction(j).rate
elif 'FalloffReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).high_rate = NewModel.reaction(
j).high_rate
NewModel.reaction(j).low_rate = NewModel.reaction(
j).low_rate
if NewModel.reaction(j).falloff.type == 'Troe':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
if NewModel.reaction(j).falloff.type == 'Sri':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
elif 'ChemicallyActivatedReaction' in str(
type(NewModel.reaction(j))):
NewModel.reaction(j).high_rate = NewModel.reaction(
j).high_rate
NewModel.reaction(j).low_rate = NewModel.reaction(
j).low_rate
if NewModel.reaction(j).falloff.type == 'Troe':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
if NewModel.reaction(j).falloff.type == 'Sri':
NewModel.reaction(j).falloff = NewModel.reaction(
j).falloff
elif 'PlogReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).rates = NewModel.reaction(j).rates
elif 'ChebyshevReaction' in str(type(NewModel.reaction(j))):
NewModel.reaction(j).set_parameters(
NewModel.reaction(j).Tmin,
NewModel.reaction(j).Tmax,
NewModel.reaction(j).Pmin,
NewModel.reaction(j).Pmax,
NewModel.reaction(j).coeffs)
new_file = ctiw.write(NewModel,
cwd=working_directory,
file_name=file_name,
original_cti=original_cti)
#tab
return new_file, original_rxn_eqs, master_rxn_eqs
same Blowers-Masel parameters can have different forward rate constants.
The first plot generated shows how the rate constant changes with respect to temperature
for elementary and Blower-Masel reactions. The second plot shows the activation energy
change of a Blowers-Masel reaction with respect to the delta enthalpy of the reaction.
Requires: cantera >= 2.6.0, matplotlib >= 2.0
"""
import cantera as ct
import numpy as np
import matplotlib.pyplot as plt
#Create an elementary reaction O+H2<=>H+OH
r1 = ct.ElementaryReaction({'O': 1, 'H2': 1}, {'H': 1, 'OH': 1})
r1.rate = ct.Arrhenius(3.87e1, 2.7, 6260 * 1000 * 4.184)
#Create a Blowers-Masel reaction O+H2<=>H+OH
r2 = ct.BlowersMaselReaction({'O': 1, 'H2': 1}, {'H': 1, 'OH': 1})
r2.rate = ct.BlowersMasel(3.87e1, 2.7, 6260 * 1000 * 4.184, 1e9)
#Create a Blowers-Masel reaction with same parameters with r2
#reaction equation is H+CH4<=>CH3+H2
r3 = ct.BlowersMaselReaction({'H': 1, 'CH4': 1}, {'CH3': 1, 'H2': 1})
r3.rate = ct.BlowersMasel(3.87e1, 2.7, 6260 * 1000 * 4.184, 1e9)
gas = ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=ct.Solution('gri30.yaml').species(),
reactions=[r1, r2, r3])
