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

Citation
Sd. Harris et al., The optimisation of reaction rate parameters for chemical kinetic modelling of combustion using genetic algorithms, COMPUT METH, 190(8-10), 2000, pp. 1065-1090
Citations number
18
Categorie Soggetti
Mechanical Engineering
Journal title
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
ISSN journal
00457825 → ACNP
Volume
190
Issue
8-10
Year of publication
2000
Pages
1065 - 1090
Database
ISI
SICI code
0045-7825(2000)190:8-10<1065:TOORRP>2.0.ZU;2-X
Abstract
A general inversion procedure for determining the optimum rate coefficients for chemical kinetic schemes based upon limited net species production dat a is presented. The objective of the optimisation process is to derive rate parameters such that the given net species production rates at various con ditions are simultaneously achieved by searching the parameter space of the rate coefficients in the generalised Arrhenius form of the reaction rate m echanisms. Thus, the goal is to both match the given net species production rates and subsequently ensure the accurate prediction of net species produ ction rates over a wide rang 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 pres ented here from our initial study are based upon the recovery of reaction r ate coefficients for hydrogen/nitrogen/oxygen flames, The successful identi fication of the reaction rate parameters which correspond to product specie s measurement data from a sequence of such experiments clearly suggests tha t the progression onto other chemical kinetic schemes and the optimisation of higher-order hydrocarbon schemes can now be realised. The results of thi s study therefore demonstrate that the genetic algorithm inversion process promises the ability to assess combustion behaviour for fuels where the rea ction rate coefficients are not known with any confidence and, subsequently , accurately predict emission characteristics, stable species concentration s and flame characterisation. Such predictive capabilities are of paramount importance in a wide variety of industries. (C) 2000 Elsevier Science S.A. All rights reserved.