pyMechOpt: A Python toolbox for optimizing of reaction mechanisms

pyMechOpt can optimize the chemical reaction mechanism and reduce the difference with the detailed reaction mechanism.

Installation

It is recommended to install pyMechOpt in a newly created python environment.

Package	version
Cantera	>=3.00
Pymoo	>=0.6.0
pyDecision	>=4.5.8

After installing the above package, you can follow the following command to install pyMechOpt:

git clone https://github.com/disihan/pyMechOpt.git
pip install ./pyMechOpt

Usage

You can import modules by using the following code:

import numpy as np
import cantera as ct

from pyMechOpt.multi_obj import mo_problem      # For multi-objective
# from pyMechOpt.single_obj import so_problem   # For single-objective
# from pyMechOpt.line_search import ls_problem  # For line search method

Firstly, provide the mechanism that needs to be optimized and an accurate mechanism:

mech_detailed = 'mech/gri30.yaml'               # detailed mech
mech_reduced = 'mech/gri30-r45.yaml'            # reduced mech

Given the species to be optimized and the initial conditions:

spcs_int = ['CH4',
            'O2']
spcs_peak = ['CH2O',
            'CO',
            'CO2']

pressure = 1e05 * np.array([1, 1, 1, 100, 100, 100])
temperature = np.array([1000, 1000, 1000, 1000, 1000, 1000])
ratio = np.array([0.25, 1, 4, 0.25, 1, 4])

fuel = "CH4:1"
oxydizer = "O2:1"

Then you can start optimizing.

opt_prob = mo_problem(
    mech_detailed,
    mech_reduced,
    fuel,
    oxydizer,
    temperature,
    ratio,
    pressure,
    spcs_int,
    spcs_peak,
    range_input=0.1,
    weight=[1, 1, 1, 1],
    hist_dir="./hist_nsga3/",
    res_dir="./res_nsga3/",
)
opt_prob.calc_skip()
opt_prob.run(algorithm="NSGA3", max_gen=400, pop_size=200)