Optimization of Genetic Algorithm Parameters for Determination of Kinetic Model Coefficients of Methane/Air Combustion

Development of kinetic model for new fuels requires optimization of rate parameters of chemical reactions and for this purpose, genetic algorithm (GA) has great capabilities. Since the GA population and breeding parameters (e.g. population, crossover probability, and mutation probability) deeply affect the approach to the optimum point and convergence rate toward it, in this paper the effects of those GA parameters in the optimization of a valid kinetic model for combustion of methane/air, as base mechanism, within perfectly stirred reactors studied and then by using statistical analysis the optimum GA parameters have been determined. The mutation probability has the greatest effect with the optimum value of 0.001and then population stands in the next place with optimum value of 16. In order to validate the optimized model, it was used in the simulation of a premixed flame where concentration profile of selected species match perfectly with those of the original model.