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 test_qss_artificial(self):
"""Test using four species artificial model with QSS species from 2006 DRG paper.
# R \approx F / 1e3
"""
R1 = ct.Reaction.fromCti('''reaction('F => R', [1.0, 0.0, 0.0])''')
R2 = ct.Reaction.fromCti('''reaction('R => P', [1.0e3, 0.0, 0.0])''')
R3 = ct.Reaction.fromCti('''reaction('R => Pp', [1.0, 0.0, 0.0])''')
F = ct.Species('F', 'H:1')
R = ct.Species('R', 'H:1')
P = ct.Species('P', 'H:1')
Pp = ct.Species('Pp', 'H:1')
for sp in [F, R, P, Pp]:
sp.thermo = ct.ConstantCp(300, 1000, 101325, (300, 1.0, 1.0, 1.0))
model = ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=[F, R, P, Pp],
reactions=[R1, R2, R3])
state = 1000, ct.one_atm, [1., 1. / 1.e3, 0., 0.]
matrix = create_drg_matrix(state, model)
correct = np.array([[0, 1.0, 0, 0], [0.5, 0, 0.5, 0.5 * 1e-3],
[0, 1.0, 0, 0], [0, 1, 0, 0]])
assert np.allclose(correct, matrix, rtol=1e-3)
def test_pe_artificial(self):
"""Test using three species artificial model with PE reactions from 2006 DRG paper.
"""
R1 = ct.Reaction.fromCti('''reaction('F <=> R', [1.0e3, 0.0, 0.0])''')
R2 = ct.Reaction.fromCti('''reaction('R <=> P', [1.0, 0.0, 0.0])''')
F = ct.Species('F', 'H:1')
R = ct.Species('R', 'H:1')
P = ct.Species('P', 'H:1')
for sp in [F, R, P]:
sp.thermo = ct.ConstantCp(300, 1000, 101325, (300, 1.0, 1.0, 1.0))
model = ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=[F, R, P],
reactions=[R1, R2])
conc_R = 0.1
conc_F = ((1 + 1e-3) * conc_R - (1 / 2e3)) / (1 - (1 / 2e3))
conc_P = 1.0 - (conc_R + conc_F)
state = 1000, ct.one_atm, [conc_F, conc_R, conc_P]
matrix = create_drg_matrix(state, model)
correct = np.array([
[0, 1.0, 0],
[1. / 3., 0, 2. / 3.],
[0, 1.0, 0],
])
assert np.allclose(correct, matrix, rtol=1e-3)
def _get_cantera_element_mw_map(cls, ctsol: ct.Solution):
species_list = [
ct.Species(element_name, f'{element_name}: 1')
for element_name in ctsol.element_names
]
for i in range(len(species_list)):
species_list[i].thermo = ct.ConstantCp(300., 3000., 101325.,
(300., 0., 0., 1.e4))
element_only_ctsol = ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=species_list,
reactions=[])
return {
name: mw
for name, mw in zip(element_only_ctsol.species_names,
element_only_ctsol.molecular_weights)
}
def test_dormant_modes(self):
"""Test using three species artificial model with dormant modes from 2006 DRG paper.
"""
R1 = ct.Reaction.fromCti('''reaction('A <=> B', [1.0, 0.0, 0.0])''')
R2 = ct.Reaction.fromCti('''reaction('B <=> C', [1.0e-3, 0.0, 0.0])''')
A = ct.Species('A', 'H:1')
B = ct.Species('B', 'H:1')
C = ct.Species('C', 'H:1')
for sp in [A, B, C]:
sp.thermo = ct.ConstantCp(300, 1000, 101325, (300, 1.0, 1.0, 1.0))
model = ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=[A, B, C],
reactions=[R1, R2])
state = 1000, ct.one_atm, [1.0, 2.0, 1.0]
matrix = create_drg_matrix(state, model)
correct = np.array([
[0, 1.0, 0],
[1 / (1 + 1e-3), 0, 1e-3 / (1 + 1e-3)],
[0, 1.0, 0],
])
assert np.allclose(correct, matrix, rtol=1e-3)
conc_A = 1.370536
conc_B = 1.370480
conc_C = 1.258985
state = 1000, ct.one_atm, [conc_A, conc_B, conc_C]
matrix = create_drg_matrix(state, model)
correct = np.array([
[0, 1.0, 0],
[
abs(conc_A - conc_B) /
(abs(conc_A - conc_B) + 1e-3 * abs(conc_B - conc_C)), 0,
1e-3 * abs(conc_B - conc_C) /
(abs(conc_A - conc_B) + 1e-3 * abs(conc_B - conc_C))
],
[0, 1.0, 0],
])
assert np.allclose(correct, matrix, rtol=1e-3)
def test_csp_mech5(self):
"""Test of simple mech 5 from 2006 DRG paper.
"""
R1 = ct.Reaction.fromCti('''reaction('F => P', [1.0, 0.0, 0.0])''')
R2 = ct.Reaction.fromCti('''reaction('F => R', [1.0e-2, 0.0, 0.0])''')
R3 = ct.Reaction.fromCti('''reaction('R => P', [1.0e2, 0.0, 0.0])''')
F = ct.Species('F', 'H:1')
P = ct.Species('P', 'H:1')
R = ct.Species('R', 'H:1')
for sp in [F, P, R]:
sp.thermo = ct.ConstantCp(300, 1000, 101325, (300, 1.0, 1.0, 1.0))
model = ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=[F, P, R],
reactions=[R1, R2, R3])
state = 1000, ct.one_atm, [1.0, 1.0, 1.0e-4]
matrix = create_drg_matrix(state, model)
reached = trim_drg(matrix, ['F', 'P', 'R'], ['F'], 0.1)
assert check_equal(reached, ['F', 'P'])
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)
from spitfire import ChemicalMechanismSpec as Mechanism
import pickle
import cantera as ct
species_decl = list([
ct.Species('A', 'H:2'),
ct.Species('B', 'H:1'),
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',
