Application of a Genetic Algorithm to the Optimization of Rate Constants in Chemical Kinetic Models for Combustion Simulation of HCCI Engines

Abstract

For numerically predicting the combustion processes in homogeneous charge compression ignition (HCCI) engines, practical chemical kinetic models have been explored. A genetic algorithm (GA) has been applied to the optimization of the rate constants in detailed chemical kinetic models, and a detailed kinetic model (592 reactions) for gasoline reference fuels with arbitrary octane number between 60 and 100 has been obtained from the detailed reaction schemes for iso-octane and n-heptane proposed by Golovitchev. The ignition timing in a gasoline HCCI engine has been predicted reasonably well by zero-dimensional simulation using the CHEMKIN code with this detailed kinetic model. An original reduced reaction scheme (45 reactions) for dimethyl ether (DME) has been derived from Curran's detailed scheme, and the combustion process in a DME HCCI engine has been predicted reasonably well in a practical computation time by three-dimensional simulation using the authors' GTT code, which has been linked to the CHEMKIN subroutines with the proposed reaction scheme and also has adopted a modified eddy dissipation combustion model.

A reliable algorithm for calculating stoichiometry parameters in the hard modeling of spectrophotometric titration data

“…In 2005, Kim et al used a genetic algorithm to optimize the rate constants for a kinetic model of gasoline combustion employing 592 reactions; computation on a personal computer required 19.4 days. 29 A reduced scheme of 45 reactions for dimethyl ether combustion required 24 h. Using an algorithm to determine the stoichiometry of the chemical reactions themselves was not attempted.…”

“…Maeder et al explored the idea of extending their work with another genetic algorithm for the determination of the reaction mechanism itself but concluded that the strategy of nesting two genetic algorithms would be prohibitively expensive from a computational standpoint. In 2005, Kim et al used a genetic algorithm to optimize the rate constants for a kinetic model of gasoline combustion employing 592 reactions; computation on a personal computer required 19.4 days 29 . A reduced scheme of 45 reactions for dimethyl ether combustion required 24 h. Using an algorithm to determine the stoichiometry of the chemical reactions themselves was not attempted.…”

Optimization of Satellite Combination in Kinematic Positioning Mode with the Aid of Genetic Algorithm

“…The GA is a method based on a natural evaluation and it aims to search for a global optimum solution from the entire search space. The GA has been successfully applied in many practical applications (Allen and Karjalainen, 1999;Kim et al, 2005;Stomeo et al, 2006;Ran et al, 2010) and has recently been introduced to the field of GPS data processing (Xu et al, 2002;Wu et al, 2007;Mosavi and Divband, 2010;Liu et al, 2010). In this paper, the GA is proposed as a suitable method to optimize the combination of GPS satellites in kinematic positioning.…”