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Optimisation of Reaction Mechanisms for Aviation Fuels Using a Multi-objective Genetic Algorithm
Lionel Elliott1, Derek B. Ingham1, Adrian G. Kyne2, Nicolae S. Mera2, Mohamed Pourkashanian3, and Chritopher W. Wilson4
1Department of Applied Mathematics
University of Leeds
Leeds, LS2 9JT, UK
{lionel,amt6dbi}@amsta.leeds.ac.uk
2Centre for Computational Fluid Dynamics
Energy and Resources Research Institute
University of Leeds
Leeds, LS2 9JT, UK
{fueagk,fuensm}@sun.leeds.ac.uk
3Energy and Resources Research Institute
University of Leeds
Leeds, LS2 9JT, UK
fue6lib@sun.leeds.ac.uk
4Centre for Aerospace Technology
QinetiQ group plc
Cody Technology Park
Ively Road
Pyestock, Farnborough, Hants, GU14 0LS, UK
cwwilson1@qinetiq.com
Abstract. In this study a multi-objective genetic algorithm approach is developed for determining new reaction rate parameters for the combustion of kerosene/air mixtures. The multi-objective structure of the genetic algorithm employed allows for the incorporation of both perfectly stirred reactor and laminar premixed flame data into the inversion process, thus producing more efficient reaction mechanisms.
LNCS 2724, p. 2046 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003