def run():
from spitfire.chemistry.mechanism import ChemicalMechanismSpec
from spitfire.chemistry.reactors import HomogeneousReactor
import numpy as np
xml = abspath(join('tests', 'test_mechanisms', 'h2-burke.xml'))
mechanism = ChemicalMechanismSpec(cantera_xml=xml, group_name='h2-burke')
air = mechanism.stream(stp_air=True)
fuel = mechanism.stream('X', 'H2:1')
mix = mechanism.mix_for_equivalence_ratio(1.0, fuel, air)
mix.TP = 1200., 101325.
reactor_dict = {
'cp, adiabatic':
HomogeneousReactor(mechanism, mix, 'isobaric', 'adiabatic', 'closed'),
'cp, isothermal':
HomogeneousReactor(mechanism, mix, 'isobaric', 'isothermal', 'closed'),
'cv, adiabatic':
HomogeneousReactor(mechanism, mix, 'isochoric', 'adiabatic', 'closed'),
'cv, isothermal':
HomogeneousReactor(mechanism, mix, 'isochoric', 'isothermal', 'closed')
}
sol_dict = dict()
for r in reactor_dict:
output = reactor_dict[r].integrate_to_steady()
Y = np.array([
output['mass fraction ' + s].copy()
for s in mechanism.species_names
])
sol_dict[r] = (output.time_values.copy(), output['temperature'], Y)
return sol_dict
def run(num_procs):
from spitfire.chemistry.mechanism import ChemicalMechanismSpec
from spitfire.chemistry.tabulation import build_nonadiabatic_defect_steady_slfm_library
import spitfire.chemistry.analysis as sca
import numpy as np
test_xml = abspath(join('tests', 'test_mechanisms', 'h2-burke.xml'))
m = ChemicalMechanismSpec(cantera_xml=test_xml, group_name='h2-burke')
pressure = 101325.
air = m.stream(stp_air=True)
air.TP = 1200., pressure
fuel = m.stream('TPY', (300., pressure, 'H2:1'))
flamelet_specs = {
'mech_spec': m,
'oxy_stream': air,
'fuel_stream': fuel,
'grid_points': 34
}
l = build_nonadiabatic_defect_steady_slfm_library(
flamelet_specs,
verbose=False,
diss_rate_values=np.logspace(0, 1, 4),
integration_args={'transient_tolerance': 1e-10},
num_procs=num_procs)
l = sca.compute_specific_enthalpy(m, l)
l = sca.compute_isochoric_specific_heat(m, l)
l = sca.compute_isobaric_specific_heat(m, l)
l = sca.compute_density(m, l)
l = sca.compute_pressure(m, l)
l = sca.compute_viscosity(m, l)
return l
def run():
from spitfire.chemistry.mechanism import ChemicalMechanismSpec
from spitfire.chemistry.tabulation import build_adiabatic_eq_library, apply_mixing_model, PDFSpec
import spitfire.chemistry.analysis as sca
test_xml = abspath(join('tests', 'test_mechanisms', 'h2-burke.xml'))
m = ChemicalMechanismSpec(cantera_xml=test_xml, group_name='h2-burke')
pressure = 101325.
air = m.stream(stp_air=True)
air.TP = 1200., pressure
fuel = m.stream('TPY', (300., pressure, 'H2:1'))
flamelet_specs = {
'mech_spec': m,
'oxy_stream': air,
'fuel_stream': fuel,
'grid_points': 34
}
l = build_adiabatic_eq_library(flamelet_specs, verbose=False)
l = sca.compute_specific_enthalpy(m, l)
l = sca.compute_isochoric_specific_heat(m, l)
l = sca.compute_isobaric_specific_heat(m, l)
l = sca.compute_density(m, l)
l = sca.compute_pressure(m, l)
l = sca.compute_viscosity(m, l)
scaled_variance_values = np.linspace(0., 1., 5)
l_t = apply_mixing_model(l, {
'mixture_fraction':
PDFSpec(pdf='ClipGauss', scaled_variance_values=scaled_variance_values)
},
num_procs=1)
return l_t
def run():
from spitfire.chemistry.mechanism import ChemicalMechanismSpec
from spitfire.chemistry.tabulation import build_unreacted_library
import spitfire.chemistry.analysis as sca
test_xml = abspath(join('tests', 'test_mechanisms', 'h2-burke.xml'))
m = ChemicalMechanismSpec(cantera_xml=test_xml, group_name='h2-burke')
pressure = 101325.
air = m.stream(stp_air=True)
air.TP = 1200., pressure
fuel = m.stream('TPY', (300., pressure, 'H2:1'))
flamelet_specs = {
'mech_spec': m,
'oxy_stream': air,
'fuel_stream': fuel,
'grid_points': 34
}
l = build_unreacted_library(flamelet_specs, verbose=False)
l = sca.compute_specific_enthalpy(m, l)
l = sca.compute_isochoric_specific_heat(m, l)
l = sca.compute_isobaric_specific_heat(m, l)
l = sca.compute_density(m, l)
l = sca.compute_pressure(m, l)
l = sca.compute_viscosity(m, l)
return l
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
import numpy as np
from spitfire.chemistry.flamelet import Flamelet
from spitfire.chemistry.mechanism import ChemicalMechanismSpec
m = ChemicalMechanismSpec(
cantera_xml='heptane-liu-hewson-chen-pitsch-highT.xml', group_name='gas')
pressure = 101325.
air = m.stream(stp_air=True)
air.TP = 298., pressure
fuel = m.stream('TPY', (488., pressure, 'NXC7H16:1'))
flamelet_specs = {
'mech_spec': m,
'pressure': pressure,
'oxy_stream': air,
'fuel_stream': fuel
}
def get_data(cpoint, ccoeff, npts):
z, dz = Flamelet._clustered_grid(npts, cpoint, ccoeff)
dz = np.hstack([dz, 1. - z[-2]])
return z, 1. / dz
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
Tmin = 200.
Tmax = int(np.max(solution_list) // 100 + 1) * 100
nt = t_list.size
ndof = solution_list.size // nt
nq = ndof // nx // ny
# m = ChemicalMechanismSpec(cantera_xml='ethylene-luo.xml', group_name='ethylene-luo')
# m = ChemicalMechanismSpec(cantera_xml='coh2-hawkes.xml', group_name='coh2-hawkes')
m = ChemicalMechanismSpec(cantera_xml='heptane-liu-hewson-chen-pitsch-highT.xml', group_name='gas')
variable = 'T'
pressure = 101325.
air = m.stream(stp_air=True)
air.TP = 300., pressure
# sg = m.stream('X', 'H2:1, CO:2')
sg = m.stream('X', 'H2:1, CO:1, CH4:1, CO2:1')
fuel2 = m.copy_stream(sg)
# fuel2.TP = 300., pressure
fuel2.TP = 400., pressure
# c2h4 = m.stream('X', 'C2H4:1')
eg = m.stream('X', 'CO2:1, H2O:1, CO:0.5, H2:0.001')
c7 = m.stream('X', 'NXC7H16:1')
# fuel1 = m.copy_stream(eg)
# fuel1.TP = 300., pressure
fuel1 = m.copy_stream(c7)
fuel1.TP = 485., pressure
fuel1_name = 'C7'
from mpl_toolkits.mplot3d import Axes3D
import mpl_toolkits.mplot3d as a3
from scipy.interpolate import RectBivariateSpline
# m = ChemicalMechanismSpec(cantera_xml='methane-lu30.xml', group_name='methane-lu30')
# m = ChemicalMechanismSpec(cantera_xml='h2-burke.xml', group_name='h2-burke')
# m = ChemicalMechanismSpec(cantera_xml='coh2-hawkes.xml', group_name='coh2-hawkes')
m = ChemicalMechanismSpec(
cantera_xml='heptane-liu-hewson-chen-pitsch-highT.xml', group_name='gas')
# m = ChemicalMechanismSpec(cantera_xml='dme-bhagatwala.xml', group_name='dme-bhagatwala')
# m = ChemicalMechanismSpec(cantera_xml='ethylene-luo.xml', group_name='ethylene-luo')
pressure = 101325.
print(m.n_species, m.n_reactions)
air = m.stream(stp_air=True)
air.TP = 300., pressure
n2 = m.stream('X', 'N2:1')
c7 = m.stream('X', 'NXC7H16:1')
# dme = m.stream('X', 'CH3OCH3:1')
# ch4 = m.stream('X', 'CH4:1')
# sg = m.stream('X', 'H2:1, CO:2')
sg = m.stream('X', 'H2:1, CO:1, CH4:1, CO2:1')
# eg = m.stream('X', 'CO2:1, H2O:1, CO:0.5, H2:0.001')
# c2h4 = m.stream('X', 'C2H4:1')
# fuel1 = m.mix_fuels_for_stoich_mixture_fraction(sg, n2, 0.1, air)
fuel1 = m.copy_stream(c7)
fuel1.TP = 485., pressure
# fuel1 = m.stream(stp_air=True)
# fuel1.TP = 1000., pressure
from spitfire.chemistry.mechanism import ChemicalMechanismSpec
from spitfire.time.integrator import Governor, NumberOfTimeSteps, FinalTime, Steady, SaveAllDataToList
from spitfire.time.methods import AdaptiveERK54CashKarp, ESDIRK64, BackwardEulerWithError
from spitfire.time.nonlinear import SimpleNewtonSolver
from spitfire.time.stepcontrol import PIController
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import Normalize
m = ChemicalMechanismSpec(cantera_xml='coh2-hawkes.xml',
group_name='coh2-hawkes')
print(m.n_species, m.n_reactions)
pressure = 101325.
air = m.stream(stp_air=True)
air.TP = 300., pressure
synthesis_gas = m.stream('X', 'H2:1, CO:1')
exhaust_gas = m.stream('X', 'CO2:1, H2O:1, CO:0.5, H2:0.001')
fuel1 = m.copy_stream(synthesis_gas)
fuel1.TP = 1000., pressure
fuel2 = m.copy_stream(exhaust_gas)
fuel2.TP = 400., pressure
fuel1_name = 'SG'
fuel2_name = 'EG'
x_cp = m.stoich_mixture_fraction(fuel2, air)
y_cp = m.stoich_mixture_fraction(fuel1, air)
x_cp = x_cp if x_cp < 0.5 else 1. - x_cp
def test(self):
test_xml = abspath(join('tests', 'test_mechanisms', 'h2-burke.xml'))
m = ChemicalMechanismSpec(cantera_xml=test_xml, group_name='h2-burke')
pressure = 101325.
air = m.stream(stp_air=True)
air.TP = 300., pressure
fuel = m.stream('TPY', (300., pressure, 'H2:1'))
flamelet_specs = {'mech_spec': m, 'oxy_stream': air, 'fuel_stream': fuel, 'grid_points': 34}
slfm = build_adiabatic_slfm_library(flamelet_specs,
diss_rate_values=np.logspace(-1, 4, 40),
diss_rate_ref='stoichiometric',
include_extinguished=True,
verbose=False)
class LogMean1ParamPDF:
def __init__(self, sigma):
self._sigma = sigma
self._mu = 0.
self._s2pi = np.sqrt(2. * np.pi)
self._xt = np.logspace(-6, 6, 1000)
self._pdft = np.zeros_like(self._xt)
def get_pdf(self, x):
s = self._sigma
m = self._mu
return 1. / (x * s * self._s2pi) * np.exp(-(np.log(x) - m) * (np.log(x) - m) / (2. * s * s))
def set_mean(self, mean):
self._mu = np.log(mean) - 0.5 * self._sigma * self._sigma
self._pdft = self.get_pdf(self._xt)
def set_variance(self, variance):
pass
def set_scaled_variance(self, variance):
raise ValueError(
'cannot use set_scaled_variance on LogMean1ParamPDF, use direct variance values')
def integrate(self, interpolant):
ig = interpolant(self._xt) * self._pdft
return simpson(ig, x=self._xt)
lm_pdf = LogMean1ParamPDF(1.0)
mass_fracs = slfm.props
mass_fracs.remove('temperature')
slfm.remove(*mass_fracs)
slfm_l = apply_mixing_model(
slfm,
mixing_spec={}
)
slfm_t = apply_mixing_model(
slfm,
mixing_spec={'dissipation_rate_stoich': PDFSpec(pdf=lm_pdf, variance_values=np.array([1.]))}
)
slfm_t2 = apply_mixing_model(
slfm,
mixing_spec={'dissipation_rate_stoich': PDFSpec(pdf=lm_pdf, variance_values=np.array([1.])),
'mixture_fraction': 'delta'}
)
slfm_t3 = apply_mixing_model(
slfm,
mixing_spec={'dissipation_rate_stoich': PDFSpec(pdf=lm_pdf, variance_values=np.array([1.])),
'mixture_fraction': PDFSpec(pdf='delta')}
)
slfm_t4 = apply_mixing_model(
slfm,
mixing_spec={'dissipation_rate_stoich': 'delta',
'mixture_fraction': PDFSpec(pdf='delta')},
added_suffix='_avg'
)
slfm_tt1 = apply_mixing_model(
slfm_t,
mixing_spec={
'mixture_fraction_mean': PDFSpec(pdf='ClipGauss', scaled_variance_values=np.linspace(0, 1, 8))},
added_suffix=''
)
slfm_tt2 = apply_mixing_model(
slfm,
mixing_spec={'dissipation_rate_stoich': PDFSpec(pdf=lm_pdf, variance_values=np.array([1.])),
'mixture_fraction': PDFSpec(pdf='ClipGauss',
scaled_variance_values=np.linspace(0, 1, 8))}
)