[Python/Examples] Updated premixed counterflow twin flame example

Corrected method of calculating strain-rate, and added functionality to compute
consumption speed
This commit is contained in:
Santosh Shanbhogue 2016-07-24 22:39:09 -04:00 committed by Ray Speth
parent 791c9d1599
commit 1dc7071ba6

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@ -9,9 +9,50 @@ latter simulates a jet of reactants shooting into products.
import cantera as ct
import numpy as np
# Differentiation function for data that has variable grid spacing Used here to
# compute normal strain-rate
def derivative(x, y):
dydx = np.zeros(y.shape, y.dtype.type)
dx = np.diff(x)
dy = np.diff(y)
dydx[0:-1] = dy/dx
dydx[-1] = (y[-1] - y[-2])/(x[-1] - x[-2])
return dydx
def computeStrainRates(oppFlame):
# Compute the derivative of axial velocity to obtain normal strain rate
strainRates = derivative(oppFlame.grid, oppFlame.u)
# Obtain the location of the max. strain rate upstream of the pre-heat zone.
# This is the characteristic strain rate
maxStrLocation = abs(strainRates).argmax()
minVelocityPoint = oppFlame.u[:maxStrLocation].argmin()
# Characteristic Strain Rate = K
strainRatePoint = abs(strainRates[:minVelocityPoint]).argmax()
K = abs(strainRates[strainRatePoint])
return strainRates, strainRatePoint, K
def computeConsumptionSpeed(oppFlame):
Tb = max(oppFlame.T)
Tu = min(oppFlame.T)
rho_u = max(oppFlame.density)
integrand = oppFlame.heat_release_rate/oppFlame.cp
I = np.trapz(integrand, oppFlame.grid)
Sc = I/(Tb - Tu)/rho_u
return Sc
# This function is called to run the solver
def solveOpposedFlame(oppFlame, massFlux=0.12, loglevel=1,
ratio=3, slope=0.15, curve=0.25, prune=0.05):
ratio=2, slope=0.3, curve=0.3, prune=0.05):
"""
Execute this function to run the Oppposed Flow Simulation This function
takes a CounterFlowTwinPremixedFlame object as the first argument
@ -23,14 +64,15 @@ def solveOpposedFlame(oppFlame, massFlux=0.12, loglevel=1,
oppFlame.show_solution()
oppFlame.solve(loglevel, auto=True)
# Compute the strain rate, just before the flame. It also turns out to the
# maximum. This is the strain rate that computations comprare against, like
# when plotting Su vs. K
peakStrain = np.max(np.gradient(oppFlame.u, np.gradient(oppFlame.grid)))
return np.max(oppFlame.T), peakStrain
# Compute the strain rate, just before the flame. This is not necessarily
# the maximum We use the max. strain rate just upstream of the pre-heat zone
# as this is the strain rate that computations comprare against, like when
# plotting Su vs. K
strainRates, strainRatePoint, K = computeStrainRates(oppFlame)
return np.max(oppFlame.T), K, strainRatePoint
# Use the standard GRI3.0 Mechanism for CH4
# Select the reaction mechanism
gas = ct.Solution('gri30.cti')
# Create a CH4/Air premixed mixture with equivalence ratio=0.75, and at room
@ -39,26 +81,34 @@ 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
axial_velocity = 2.0 # 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
# Uncomment the following line to use a Multi-component formulation. Default is
# mixture-averaged
#oppFlame.transport_model = 'Multi'
# 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)
# Now run the solver. The solver returns the peak temperature, strain rate and
# the point which we ascribe to the characteristic strain rate.
print("Peak temperature: {0}".format(T))
print("Strain Rate: {0}".format(K))
(T, K, strainRatePoint) = solveOpposedFlame(oppFlame, massFlux, loglevel=1)
# You can plot/see all state space variables by calling oppFlame.foo where foo
# is T, Y[i], etc. The spatial variable (distance in meters) is in oppFlame.grid
# Thus to plot temperature vs distance, use oppFlame.grid and oppFlame.T
Sc = computeConsumptionSpeed(oppFlame)
print("Peak temperature: {0:.1f} K".format(T))
print("Strain Rate: {0:.1f} 1/s".format(K))
print("Consumption Speed: {0:.2f} cm/s".format(Sc*100))
oppFlame.write_csv("premixed_twin_flame.csv", quiet=False)