 |
    |
An Informed Operator Based Genetic Algorithm for Tuning the Reaction Rate Parameters of Chemical Kinetics Mechanisms
Lionel Elliott1, Derek B. Ingham1, Adrian G. Kyne2, Nicolae S. Mera2, Mohamed Pourkashanian2, and Christopher W. Wilson3
1Department of Applied Mathematics, University of Leeds, Leeds, LS2 9JT, UK
lionel@amsta.leeds.ac.uk
amt6dbi@amsta.leeds.ac.uk
2Centre for Computational Fluid Dynamics, Energy and Resources Research Institute, University of Leeds, Leeds, LS2 9JT, UK
fueagk@sun.leeds.ac.uk
fuensm@sun.leeds.ac.uk
fue6lib@sun.leeds.ac.uk
3Department of Mechanical Engineering, Mappin Street, University of Sheffield, Sheffield, S1 3JD, UK
c.w.wilson@sheffield.ac.uk
Abstract. A reduced model technique based on a reduced number of numerical simulations at a subset of operating conditions for a perfectly stirred reactor is developed in order to increase the rate of convergence of a genetic algorithm (GA) used for determining new reaction rate parameters of chemical kinetics mechanisms. The genetic algorithm employed uses perfectly stirred reactor, laminar premixed flame and ignition delay time data in the inversion process in order to produce efficient reaction mechanisms that are valid for a wide range of combustion processes and various operating conditions.
LNCS 3103, p. 945 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2004