Nicolae S. Mera

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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(More)
In this study we develop a real coded genetic algorithm for the determination of the chemical reaction rates parameters (A's, b's and E's in the Arrhenius expression) for the hydrogen combustion in a perfectly stirred reactor (PSR). The algorithm is tested on a hydrogen/air mixture but it can be applied for other, more complex hydrocarbon fuels. The(More)
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(More)
Two efficient clustering-based genetic algorithms are developed for the optimisation of reaction rate parameters in chemical kinetic modelling. The genetic algorithms employed are used to determine new reaction rate coefficients for the combustion of four different fuel/air mixtures in a perfectly stirred reactor (PSR). The incorporation of clustering into(More)
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