def solve(self, phi, T, width, P):
gas = ct.Solution('h2o2.xml')
gas.TP = T, ct.one_atm
gas.set_equivalence_ratio(phi, 'H2', 'O2:1.0, AR:4.0')
sim = ct.CounterflowTwinPremixedFlame(gas=gas, width=width)
sim.set_refine_criteria(ratio=5, slope=0.6, curve=0.8, prune=0.1)
axial_velocity = 2.0
sim.reactants.mdot = gas.density * axial_velocity
sim.solve(loglevel=0, auto=True)
self.assertGreater(sim.T[-1], T + 100)
def __init__(self,
solution,
chemistry,
fuel,
oxidizer={
'O2': 1.,
'N2': 3.76
},
T=None):
self.chemistry = chemistry
gas = ct.Solution(chemistry, loglevel=0)
flame = ct.CounterflowTwinPremixedFlame(gas, width=0.1)
flame.restore(solution, loglevel=0)
PremixedFlameState.__init__(self, flame, fuel, oxidizer, T)
# Create a CH4/Air premixed mixture with equivalence ratio=0.75, and at room
# temperature and pressure.
gas.set_equivalence_ratio(0.75, 'CH4', {'O2': 1.0, 'N2': 3.76})
gas.TP = 300, ct.one_atm
# Set the velocity
axial_velocity = 0.25 # in m/s
# Domain half-width of 2.5 cm, meaning the whole domain is 5 cm wide
width = 0.025
# Done with initial conditions
# Compute the mass flux, as this is what the Flame object requires
massFlux = gas.density * axial_velocity # units kg/m2/s
# Create the flame object
oppFlame = ct.CounterflowTwinPremixedFlame(gas, width=width)
# Now run the solver
# The solver returns the peak temperature and strain rate. You can plot/see all
# state space variables by calling oppFlame.foo where foo is T, Y[i] or whatever
# The spatial variable (distance in meters) is in oppFlame.grid Thus to plot
# temperature vs distance, use oppFlame.grid and oppFlame.T
(T, K) = solveOpposedFlame(oppFlame, massFlux)
print("Peak temperature: {0}".format(T))
print("Strain Rate: {0}".format(K))
oppFlame.write_csv("premixed_twin_flame.csv", quiet=False)
def counterflow_twin_flame(gas, a=1000., solution=None, **kwargs):
# read kwargs
if 'transport' in kwargs.keys():
transport = kwargs['transport']
else:
transport = 'Mix'
if 'width' in kwargs.keys():
width = kwargs['width']
else:
width = 0.05
if 'loglevel' in kwargs.keys():
loglevel = kwargs['loglevel']
else:
# supress log output
loglevel = 0
# kwargs for flame solver
if 'ct_ratio' in kwargs.keys():
ct_ratio = kwargs['ct_ratio']
else:
ct_ratio = 2.
if 'ct_slope' in kwargs.keys():
ct_slope = kwargs['ct_slope']
else:
ct_slope = 0.2
if 'ct_curve' in kwargs.keys():
ct_curve = kwargs['ct_curve']
else:
ct_curve = 0.2
if 'ct_prune' in kwargs.keys():
ct_prune = kwargs['ct_prune']
else:
ct_prune = 0.1
if 'ct_max_grids' in kwargs.keys():
ct_max_grids = kwargs['ct_max_grids']
else:
ct_max_grids = 5000
# get inlet velocity based on the strain rate
# $a_1=\dfrac{2U_1}{L}\left(1+\dfrac{U_2\sqrt{\rho_2}}{U_1\sqrt{\rho_1}}\right)$
# $a_2=\dfrac{2U_2}{L}\left(1+\dfrac{U_1\sqrt{\rho_1}}{U_2\sqrt{\rho_2}}\right)$
# with $\rho_1 U_1^2 = \rho_2 U_2^2$
# $a_1=\dfrac{4U_1}{L}$ $a_2=\dfrac{4U_2}{L}$
# set stream 1 and 2 for unburnt and equilibrium status respectively
v = a * width / 4.
# mass rate
mass_flux = gas.density * v
# Create flame object
f = ct.CounterflowTwinPremixedFlame(gas=gas, width=width)
f.transport_model = transport
f.P = gas.P
f.reactants.mdot = mass_flux
f.set_refine_criteria(ratio=ct_ratio,
slope=ct_slope,
curve=ct_curve,
prune=ct_prune)
f.set_max_grid_points(f.flame, ct_max_grids)
# load saved case if presented
if solution is not None:
f.restore(solution, loglevel=loglevel)
# scaling of saved solution
solution_width = f.grid[-1] - f.grid[0]
width_factor = width / solution_width
solution_a = 4. * f.u[0] / solution_width
a_factor = a / solution_a
normalized_grid = f.grid / solution_width
u_factor = a_factor * width_factor
# update solution initialization following Fiala & Sattelmayer
f.flame.grid = normalized_grid * width
f.set_profile('u', normalized_grid, f.u * u_factor)
f.set_profile('V', normalized_grid, f.V * a_factor)
f.set_profile('lambda', normalized_grid, f.L * np.square(a_factor))
f.reactants.mdot = mass_flux
else:
f.set_initial_guess()
f.solve(loglevel=loglevel, auto=True)
return f
