The optimisation of reaction rate parameters for chemical kinetic modelling of combustion using genetic algorithms Original Research Article

A general inversion procedure for determining the optimum rate coefficients for chemical kinetic schemes based upon limited net species production data is presented. The objective of the optimisation process is to derive rate parameters such that the given net species production rates at various conditions are simultaneously achieved by searching the parameter space of the rate coefficients in the generalised Arrhenius form of the reaction rate mechanisms. Thus, the goal is to both match the given net species production rates and subsequently ensure the accurate prediction of net species production rates over a wide range of conditions. We have retrieved the reaction rate data using an inversion technique whose minimisation process is based on the Darwinian principle of survival of the fittest which has inspired a class of algorithms known as genetic algorithms. The excellent results presented here from our initial study are based upon the recovery of reaction rate coefficients for hydrogen/nitrogen/oxygen flames. The successful identification of the reaction rate parameters which correspond to product species measurement data from a sequence of such experiments clearly suggests that the progression onto other chemical kinetic schemes and the optimisation of higher-order hydrocarbon schemes can now be realised. The results of this study therefore demonstrate that the genetic algorithm inversion process promises the ability to assess combustion behaviour for fuels where the reaction rate coefficients are not known with any confidence and, subsequently, accurately predict emission characteristics, stable species concentrations and flame characterisation. Such predictive capabilities are of paramount importance in a wide variety of industries.