def test_ion_profile(self):
reactants = 'CH4:0.216, O2:2'
p = ct.one_atm
Tin = 300
width = 0.03
# IdealGasMix object used to compute mixture properties
self.gas = ct.Solution('ch4_ion.cti')
self.gas.TPX = Tin, p, reactants
self.sim = ct.IonFlame(self.gas, width=width)
self.sim.set_refine_criteria(ratio=4, slope=0.8, curve=1.0)
# stage one
self.sim.solve(loglevel=0, auto=True)
# stage two
self.sim.solve(loglevel=0, stage=2, enable_energy=False)
# stage two
self.sim.solve(loglevel=0, stage=2, enable_energy=True)
#stage three
self.sim.solve(loglevel=0, stage=3, enable_energy=True)
# Regression test
self.assertNear(min(self.sim.E) / max(self.sim.E), -5.0765, 1e-3)
def test_ion_profile(self):
reactants = 'CH4:0.216, O2:2'
p = ct.one_atm
Tin = 300
width = 0.03
# IdealGasMix object used to compute mixture properties
self.gas = ct.Solution('ch4_ion.cti')
self.gas.TPX = Tin, p, reactants
self.sim = ct.IonFlame(self.gas, width=width)
self.sim.set_refine_criteria(ratio=4, slope=0.8, curve=1.0)
# Ionized species may require tighter absolute tolerances
self.sim.flame.set_steady_tolerances(Y=(1e-4, 1e-12))
self.sim.transport_model = 'Ion'
# stage one
self.sim.solve(loglevel=0, auto=True)
#stage two
self.sim.solve(loglevel=0, stage=2, enable_energy=True)
# Regression test
self.assertNear(max(self.sim.E), 131.9956, 1e-3)
import numpy as np
# Simulation parameters
p = ct.one_atm # pressure [Pa]
Tin = 300.0 # unburned gas temperature [K]
reactants = 'CH4:1, O2:2, N2:7.52' # premixed gas composition
width = 0.05 # m
loglevel = 1 # amount of diagnostic output (0 to 8)
# IdealGasMix object used to compute mixture properties, set to the state of the
# upstream fuel-air mixture
gas = ct.Solution('gri30_ion.xml')
gas.TPX = Tin, p, reactants
# Set up flame object
f = ct.IonFlame(gas, width=width)
f.set_refine_criteria(ratio=3, slope=0.06, curve=0.12)
f.show_solution()
# stage one
f.solve(loglevel=loglevel, auto=True)
# stage two
f.solve(loglevel=loglevel, stage=2, enable_energy=False)
f.solve(loglevel=loglevel, stage=2, enable_energy=True)
# stage three
f.solve(loglevel=loglevel, stage=3, enable_energy=True)
f.save('CH4_adiabatic.xml', 'mix', 'solution with mixture-averaged transport')
f.show_solution()