Detached flat flame stabilized at a stagnation point

This script simulates a lean hydrogen-oxygen flame stabilized in a strained flowfield at an axisymmetric stagnation point on a non-reacting surface. The solution begins with a flame attached to the inlet (burner), and the mass flow rate is progressively increased, causing the flame to detach and move closer to the surface.

This example illustrates use of the new ‘prune’ grid refinement parameter, which allows grid points to be removed if they are no longer required to resolve the solution. This is important here, since the flamefront moves as the mass flowrate is increased. Without using ‘prune’, a large number of grid points would be concentrated upstream of the flame, where the flamefront had been previously. (To see this, try setting prune to zero.)

Requires: cantera >= 3.0

Tags: Python combustion 1D flow premixed flame strained flame

from pathlib import Path
import cantera as ct


# parameter values
p = 0.05 * ct.one_atm  # pressure
tburner = 373.0  # burner temperature
tsurf = 500.0

# each mdot value will be solved to convergence, with grid refinement, and
# then that solution will be used for the next mdot
mdot = [0.06, 0.07, 0.08, 0.09, 0.1, 0.11, 0.12]  # kg/m^2/s

rxnmech = 'h2o2.yaml'  # reaction mechanism file
comp = 'H2:1.8, O2:1, AR:7'  # premixed gas composition

# The solution domain is chosen to be 20 cm
width = 0.2  # m

loglevel = 1  # amount of diagnostic output (0 to 5)

# Grid refinement parameters
ratio = 3
slope = 0.1
curve = 0.2
prune = 0.06

# Set up the problem
gas = ct.Solution(rxnmech)

# set state to that of the unburned gas at the burner
gas.TPX = tburner, p, comp

# Create the stagnation flow object with a non-reactive surface.  (To make the
# surface reactive, supply a surface reaction mechanism. See example
# catalytic_combustion.py for how to do this.)
sim = ct.ImpingingJet(gas=gas, width=width)

# set the mass flow rate at the inlet
sim.inlet.mdot = mdot[0]

# set the surface state
sim.surface.T = tsurf

sim.set_grid_min(1e-4)
sim.set_refine_criteria(ratio=ratio, slope=slope, curve=curve, prune=prune)

sim.set_initial_guess(products='equil')  # assume adiabatic equilibrium products
sim.show()

sim.solve(loglevel, auto=True)

output_path = Path() / "stagnation_flame_data"
output_path.mkdir(parents=True, exist_ok=True)

if "native" in ct.hdf_support():
    output = output_path / "stagnation_flame.h5"
else:
    output = output_path / "stagnation_flame.yaml"
output.unlink(missing_ok=True)

for m, md in enumerate(mdot):
    sim.inlet.mdot = md
    sim.solve(loglevel)
    sim.save(output, name=f"mdot-{m}", description=f"mdot = {md} kg/m2/s")

    # write the velocity, temperature, and mole fractions to a CSV file
    sim.save(output_path / f"stagnation_flame_{m}.csv", basis="mole", overwrite=True)

sim.show_stats()