def test_modify_thermo_invalid(self):
S = {sp.name: sp for sp in ct.Species.listFromFile('h2o2.xml')}
orig = S['H2']
thermo = orig.thermo
copy = ct.Species('foobar', orig.composition)
copy.thermo = thermo
with self.assertRaises(ct.CanteraError):
self.gas.modify_species(self.gas.species_index('H2'), copy)
copy = ct.Species('H2', {'H': 3})
copy.thermo = thermo
with self.assertRaises(ct.CanteraError):
self.gas.modify_species(self.gas.species_index('H2'), copy)
copy = ct.Species('H2', orig.composition)
copy.thermo = ct.ConstantCp(thermo.min_temp, thermo.max_temp,
thermo.reference_pressure,
[300, 123, 456, 789])
with self.assertRaises(ct.CanteraError):
self.gas.modify_species(self.gas.species_index('H2'), copy)
copy = ct.Species('H2', orig.composition)
copy.thermo = ct.NasaPoly2(thermo.min_temp + 200, thermo.max_temp,
thermo.reference_pressure, thermo.coeffs)
with self.assertRaises(ct.CanteraError):
self.gas.modify_species(self.gas.species_index('H2'), copy)
def modify_thermo(
self, multipliers): # Only works for NasaPoly2 (NASA 7) currently
for i in range(np.shape(self.gas.species_names)[0]):
S_initial = self.gas.species(i)
S = self.gas.species(i)
if type(S.thermo) is ct.NasaPoly2:
# Get current values
T_low = S_initial.thermo.min_temp
T_high = S_initial.thermo.max_temp
P_ref = S_initial.thermo.reference_pressure
coeffs = S_initial.thermo.coeffs
# Update thermo properties
coeffs[1:] *= multipliers[i]
S.thermo = ct.NasaPoly2(T_low, T_high, P_ref, coeffs)
# elif type(S.thermo) is ct.ShomatePoly2: continue
# elif type(S.thermo) is ct.NasaPoly1: continue
# elif type(S.thermo) is ct.Nasa9PolyMultiTempRegion: continue
# elif type(S.thermo) is ct.Nasa9Poly1: continue
# elif type(S.thermo) is ct.ShomatePoly: continue
else:
print("{:.s}'s thermo is type: {:s}".format(
self.gas.species_names[i], type(S.thermo)))
continue
self.gas.modify_species(i, S)
def test_create(self):
st = ct.NasaPoly2(300, 3500, 101325, self.h2o_coeffs)
for T in [300, 500, 900, 1200, 2000]:
self.gas.TP = T, 101325
self.assertNear(st.cp(T), self.gas.cp_mole)
self.assertNear(st.h(T), self.gas.enthalpy_mole)
self.assertNear(st.s(T), self.gas.entropy_mole)
def test_yaml_inconsistent_species(self):
gas = ct.Solution('h2o2.yaml', transport_model=None)
gas2 = ct.Solution('h2o2.yaml', transport_model=None)
gas2.name = 'modified'
# modify the NASA coefficients for one species
h2 = gas2.species('H2')
nasa_coeffs = h2.thermo.coeffs
nasa_coeffs[1] += 0.1
nasa_coeffs[8] += 0.1
h2.thermo = ct.NasaPoly2(h2.thermo.min_temp, h2.thermo.max_temp,
h2.thermo.reference_pressure, nasa_coeffs)
gas2.modify_species(gas2.species_index('H2'), h2)
with self.assertRaisesRegex(ct.CanteraError, "different definitions"):
gas.write_yaml('h2o2-error.yaml', phases=gas2)
def change_species_enthalpy(gas, species_name, dH):
"""
Find the species by name and change it's enthalpy by dH (in J/kmol)
"""
index = gas.species_index(species_name)
species = gas.species(index)
# dx is in fact (delta H / R). Note that R in cantera is 8314.462 J/kmol/K
dx = dH / ct.gas_constant
perturbed_coeffs = species.thermo.coeffs.copy()
perturbed_coeffs[6] += dx
perturbed_coeffs[13] += dx
species.thermo = ct.NasaPoly2(species.thermo.min_temp,
species.thermo.max_temp,
species.thermo.reference_pressure,
perturbed_coeffs)
gas.modify_species(index, species)
def calc_tig(self, species, dH):
gas, r, net = self.setup_ignition_delay()
S = gas.species(species)
st = S.thermo
coeffs = st.coeffs
coeffs[[6, 13]] += dH / ct.gas_constant
snew = ct.NasaPoly2(st.min_temp, st.max_temp, st.reference_pressure, coeffs)
S.thermo = snew
gas.modify_species(gas.species_index(species), S)
t = []
T = []
while net.time < 0.6:
t.append(net.time)
T.append(r.thermo.T)
net.step()
T = np.array(T)
t = np.array(t)
To = T[0]
Tf = T[-1]
return (t[-1]*T[-1] - np.trapz(T,t)) / (T[-1] - T[0])
def change_species_enthalpy(self, species_name, dH):
"""
Find the species by name and change it's enthlapy by dH (in J/kmol)
"""
phase, index = self.find_species_phase_index(species_name)
species = phase.species(index)
print(f"Initial H(298) = {species.thermo.h(298)/1e6:.1f} kJ/mol")
dx = dH / ct.gas_constant
# 'dx' is in fact (delta H / R). Note that R in cantera is 8314.462 J/kmol
assert isinstance(species.thermo, ct.NasaPoly2)
# print(species.thermo.coeffs)
perturbed_coeffs = species.thermo.coeffs.copy()
perturbed_coeffs[6] += dx
perturbed_coeffs[13] += dx
species.thermo = ct.NasaPoly2(
species.thermo.min_temp,
species.thermo.max_temp,
species.thermo.reference_pressure,
perturbed_coeffs,
)
# print(species.thermo.coeffs)
phase.modify_species(index, species)
print(f"Modified H(298) = {species.thermo.h(298)/1e6:.1f} kJ/mol")
################################################################################
CO = ct.Species(name = 'CO')
coeffs = np.zeros(15)
coeffs[0] = T_mid
coeffs[1:8] = [ 3.57953347E+00, -6.10353680E-04, 1.01681433E-06,
9.07005884E-10, -9.04424499E-13, 0.00000000E+00,
3.50840928E+00]
coeffs[8:15] = [ 2.71518561E+00, 2.06252743E-03, -9.98825771E-07,
2.30053008E-10, -2.03647716E-14, 1.92213599E+02,
7.81868772E+00]
CO.thermo = ct.NasaPoly2(T_low = T_low ,
T_high = T_high ,
P_ref = P_ref ,
coeffs = coeffs )
################################################################################
# N2
################################################################################
N2 = ct.Species(name = 'N2')
coeffs = np.zeros(15)
coeffs[0] = T_mid
coeffs[1:8] = [ 3.29867700E+00, 1.40823990E-03, -3.96322180E-06,
5.64151480E-09, -2.44485400E-12, 0.00000000E+00,
3.95037200E+00]
coeffs[8:15] = [ 2.92663788E+00, 1.48797700E-03, -5.68476030E-07,
def test_coeffs(self):
st = ct.NasaPoly2(300, 3500, 101325, self.h2o_coeffs)
self.assertEqual(st.min_temp, 300)
self.assertEqual(st.max_temp, 3500)
self.assertEqual(st.reference_pressure, 101325)
self.assertArrayNear(self.h2o_coeffs, st.coeffs)
def test_invalid(self):
with self.assertRaises(ValueError):
# not enough coefficients
st = ct.NasaPoly2(300, 3500, 101325,
[1000.0, 3.03399249E+00, 2.17691804E-03])
def _build_cantera_solution(cls, gdata):
p_ref = gdata['ref_pressure']
species_list = list()
for s in gdata['species']:
spec = gdata['species'][s]
ctspec = ct.Species(
s, ','.join(
[f'{k}:{spec["atom_map"][k]}' for k in spec['atom_map']]))
if spec['cp'][0] == 'constant':
Tmin, Tmax, T0, h0, s0, cp = spec['cp'][1:]
ctspec.thermo = ct.ConstantCp(Tmin, Tmax, p_ref,
list([T0, h0, s0, cp]))
elif spec['cp'][0] == 'NASA7':
Tmin, Tmid, Tmax, low_coeffs, high_coeffs = spec['cp'][1:]
coeffs = [Tmid] + high_coeffs + low_coeffs
ctspec.thermo = ct.NasaPoly2(Tmin, Tmax, p_ref, coeffs)
species_list.append(ctspec)
reaction_list = list()
for rxn in gdata['reactions']:
type, reactants_stoich, products_stoich, reversible = rxn[:4]
fwd_pre_exp_value, fwd_temp_exponent, fwd_act_energy = rxn[4:7]
fwd_rate = ct.Arrhenius(fwd_pre_exp_value, fwd_temp_exponent,
fwd_act_energy)
if type == 'simple' or type == 'simple-special':
ctrxn = ct.ElementaryReaction(reactants_stoich,
products_stoich)
ctrxn.rate = fwd_rate
elif type == 'three-body' or type == 'three-body-special':
ctrxn = ct.ThreeBodyReaction(reactants_stoich, products_stoich)
ctrxn.rate = fwd_rate
ctrxn.efficiencies = rxn[7]
ctrxn.default_efficiency = rxn[8]
elif type == 'Lindemann' or type == 'Lindemann-special':
ctrxn = ct.FalloffReaction(reactants_stoich, products_stoich)
ctrxn.efficiencies = rxn[7]
ctrxn.default_efficiency = rxn[8]
flf_pre_exp_value, flf_temp_exponent, flf_act_energy = rxn[
9:12]
ctrxn.high_rate = fwd_rate
ctrxn.low_rate = ct.Arrhenius(flf_pre_exp_value,
flf_temp_exponent,
flf_act_energy)
ctrxn.falloff = ct.Falloff()
elif type == 'Troe' or type == 'Troe-special':
ctrxn = ct.FalloffReaction(reactants_stoich, products_stoich)
ctrxn.efficiencies = rxn[7]
ctrxn.default_efficiency = rxn[8]
flf_pre_exp_value, flf_temp_exponent, flf_act_energy = rxn[
9:12]
troe_params = rxn[12]
ctrxn.high_rate = fwd_rate
ctrxn.low_rate = ct.Arrhenius(flf_pre_exp_value,
flf_temp_exponent,
flf_act_energy)
if len(troe_params) == 4 and abs(troe_params[3]) < 1e-300:
ctrxn.falloff = ct.TroeFalloff(troe_params[:3])
else:
ctrxn.falloff = ct.TroeFalloff(troe_params)
if 'special' in type:
ctrxn.orders = rxn[-1]
ctrxn.reversible = reversible
reaction_list.append(ctrxn)
return ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=species_list,
reactions=reaction_list)
theta = theta_opt
Rxn1 = pt_s_ca.reaction(0)
if tog == 1:
i_o = a * w_Pt + b
else:
i_o = i_o_opt
Rxn1.rate = ct.Arrhenius(i_o, 0, 0)
pt_s_ca.modify_reaction(0, Rxn1)
O2 = naf_b_ca.species(naf_b_ca.species_index('O2(Naf)'))
O2_thermo = O2.thermo.coeffs
O2_thermo[[1, 8]] = np.array(
[3.28253784 + offset_opt, 3.782456360 + offset_opt])
O2.thermo = ct.NasaPoly2(200, 3500, ct.one_atm, fuel_coeffs)
naf_b_ca.modify_species(naf_b_ca.species_index('O2(Naf)'), O2)
# If running optimization w/ the 2-step reaction mechanism:
elif all([optimize == 1, rxn_mech == '2s']):
R_naf = R_naf_opt
theta = theta_opt
A = A_opt
i_o = i_o_opt
Rxn1 = pt_s_ca.reaction(0)
Rxn2 = pt_s_ca.reaction(1)
Rxn1.rate = ct.Arrhenius(A, 0, 0)
Rxn2.rate = ct.Arrhenius(i_o, 0, 0)
pt_s_ca.modify_reaction(0, Rxn1)
pt_s_ca.modify_reaction(1, Rxn2)
ct.Species('C', 'O:1'),
ct.Species('D', 'O:2'),
ct.Species('E', 'H:1, O:2'),
ct.Species('N', 'H:1, O:1')
])
species_dict = dict({'const': list(), 'nasa7': list()})
for i, s in enumerate(species_decl):
species_dict['const'].append(ct.Species(s.name, s.composition))
species_dict['const'][-1].thermo = ct.ConstantCp(
300., 3000., 101325., (300., 0., 0., float(i + 1) * 1.e4))
species_dict['nasa7'].append(ct.Species(s.name, s.composition))
coeffs = [
float(i + 1) * v
for v in [1.e0, 1.e-2, 1.e-4, 1.e-6, 1.e-8, 1.e-10, 1.e-12]
]
species_dict['nasa7'][-1].thermo = ct.NasaPoly2(
300., 3000., 101325., hstack([1200.] + coeffs + coeffs))
mechs = [('const',
Mechanism.from_solution(
ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=species_dict['const'],
reactions=[]))),
('nasa7',
Mechanism.from_solution(
ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=species_dict['nasa7'],
reactions=[])))]
tolerance = 1.e-14
