Note
Go to the end to download the full example code
Burner-stabilized flame with imposed temperature profile#
A burner-stabilized, premixed methane/air flat flame with multicomponent transport properties and a specified temperature profile.
Requires: cantera >= 3.0
from pathlib import Path
import numpy as np
import cantera as ct
parameter values
p = ct.one_atm # pressure
tburner = 373.7 # burner temperature
mdot = 0.04 # kg/m^2/s
comp = 'CH4:0.65, O2:1, N2:3.76' # premixed gas composition
# The solution domain is chosen to be 1 cm
width = 0.01 # m
loglevel = 1 # amount of diagnostic output (0 to 5)
refine_grid = True # 'True' to enable refinement
Create the gas object. This object will be used to evaluate all thermodynamic, kinetic, and transport properties
gas = ct.Solution('gri30.yaml')
# set its state to that of the unburned gas at the burner
gas.TPX = tburner, p, comp
# create the BurnerFlame object.
f = ct.BurnerFlame(gas=gas, width=width)
# set the mass flow rate at the burner
f.burner.mdot = mdot
Specify temperature vs. position data. For the purposes of this example, the data
is embedded directly. For more general use, the temperature profile should be stored
as a separate data file and read in, for example using np.genfromtxt.
zloc = np.array([
0. , 0.00015625, 0.00023437, 0.00039063, 0.00046875, 0.00050781,
0.00054688, 0.000625 , 0.00066406, 0.00070312, 0.00074219, 0.00078125,
0.00082031, 0.00085938, 0.00089844, 0.0009375 , 0.00101563, 0.00105469,
0.00109375, 0.00113281, 0.00117187, 0.00121094, 0.00125 , 0.00128906,
0.00132813, 0.00136719, 0.00140625, 0.00144531, 0.00148438, 0.00152344,
0.0015625 , 0.00160156, 0.00164062, 0.00171875, 0.00175781, 0.00179688,
0.00183594, 0.001875 , 0.00191406, 0.00195312, 0.00199219, 0.00203125,
0.00207031, 0.00210938, 0.00214844, 0.0021875 , 0.00222656, 0.00226562,
0.00230469, 0.00234375, 0.00238281, 0.00242187, 0.00246094, 0.0025 ,
0.00257813, 0.00265625, 0.00273437, 0.0028125 , 0.00289062, 0.00296875,
0.00304688, 0.003125 , 0.00328125, 0.0034375 , 0.00359375, 0.00375 ,
0.00390625, 0.0087 , 0.01
])
tvalues = np.array([
373.7 , 465.4070428, 510.4311676, 599.5552837, 643.8342938,
665.9335545, 688.0122338, 732.1284327, 754.1744755, 776.2170662,
798.2588757, 820.3020011, 842.348001 , 864.3979228, 886.4523159,
908.5112198, 952.6396629, 974.7018199, 996.7515831, 1018.777651 ,
1040.765863 , 1062.69948 , 1084.558639 , 1106.320078 , 1127.956918 ,
1149.438472 , 1170.730129 , 1191.793309 , 1212.585506 , 1233.060477 ,
1253.168589 , 1272.857384 , 1292.072391 , 1328.859767 , 1346.323998 ,
1363.101361 , 1379.147594 , 1394.425274 , 1408.905834 , 1422.569115 ,
1435.40408 , 1447.410648 , 1458.597668 , 1468.982722 , 1478.590978 ,
1487.453914 , 1495.607879 , 1503.092709 , 1509.950449 , 1516.224147 ,
1521.956853 , 1527.19079 , 1531.966722 , 1536.32348 , 1543.891739 ,
1550.203579 , 1555.480771 , 1559.908135 , 1563.637879 , 1566.794144 ,
1569.477867 , 1571.77099 , 1575.385829 , 1578.108169 , 1580.194856 ,
1581.820666 , 1583.106578 , 1589.51315 , 1589.578955
])
zloc /= max(zloc)
# set the temperature profile to the values read in
f.flame.set_fixed_temp_profile(zloc, tvalues)
show the initial estimate for the solution
f.show()
# don't solve the energy equation
f.energy_enabled = False
# first solve the flame with mixture-averaged transport properties
f.transport_model = 'mixture-averaged'
f.set_refine_criteria(ratio=3.0, slope=0.3, curve=1)
f.solve(loglevel, refine_grid)
if "native" in ct.hdf_support():
output = Path() / "flame_fixed_T.h5"
else:
output = Path() / "flame_fixed_T.yaml"
output.unlink(missing_ok=True)
f.save(output, name="mix", description="solution with mixture-averaged transport")
print('\n\n switching to multicomponent transport...\n\n')
f.transport_model = 'multicomponent'
f.set_refine_criteria(ratio=3.0, slope=0.1, curve=0.2)
f.solve(loglevel, refine_grid)
f.save(output, name="multi", description="solution with multicomponent transport")
# write the velocity, temperature, density, and mole fractions to a CSV file
f.save('flame_fixed_T.csv', basis="mole", overwrite=True)
f.show_stats()