Applying of genetic algorithm for optimizing methane combustion reactions

Abstract

PurposeThe aim of this paper is to find the optimal values of the reaction rates coefficients for the combustion of a methane/air mixture for a given reduced reaction mechanism which has a high appropriateness with full reaction mechanism.Design/methodology/approachA multi‐objective genetic algorithm (GA) was used to determine new reaction rate parameters (A's, β's, and Ea's in the non‐Arrhenius expressions). The employed multi‐objective structure of the GA allows for the incorporation of perfectly stirred reactor (PSR), laminar premixed flames, opposed flow diffusion flames, and homogeneous charge compression ignition (HCCI) engine data in the inversion process, thus enabling a greater confidence in the predictive capabilities of the reaction mechanisms obtained.FindingsThe results of this study demonstrate that the GA inversion process promises the ability to assess combustion behaviour for methane, where the reaction rate coefficients are not known. Moreover it is shown that GA can consider a confident method to be applied, straightforwardly, to the combustion chambers, in which complex reactions are occurred.Originality/valueIn this paper, GA is used in more complicated combustion models with fewer assumptions. Another consequence of this study is less CPU time in converging to final solutions.