The optimization of Arrhenius parameters for methane two-step reaction using machinelearning

The current concerns about the level of emission ofpollutants and their effects on the environmenthave made it important to predict the flow,temperature, concentration of species andemissions of various combustion systems for thedesign and improvement of combustion equipment.Experimental investigation of combustion isexpensive, and numerical simulation has been usedfor decades and has become a powerful tool forsimulating complex combustion processes. One ofthe common methods in combustion simulation isto use the Arrhenius equation. It should be notedthat the coefficients extracted from the Arrheniusequation can only be used for a certain range. If theequation with those coefficients is used in a rangeoutside the defined range, it will lead to a largeinaccuracy. Therefore, in order to reduce theseinaccuracies, the optimization of these coefficientshas been used using the methods of least squares,genetic algorithm and PSO algorithm according tothe two-step experimental data.

کلیدواژه ها:

Arrhenius equation ، chemical kinetics ، optimization ، artificial intelligence ، methane combustion