The international symposium on diagnostics and modeling of combustion in internal combustion engines
Online ISSN : 2424-2918
セッションID: A2-3
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Application of a Genetic Algorithm to the Optimization of Rate Constants in Chemical Reaction Submodels for Engine Combustion Simulation(Computation Technology)
Sang-kyu KIMKazuma ITODaisuke YOSHIHARATomoyuki WAKISAKA
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In order to numerically predict the combustion processes in homogeneous charge compression ignition (HCCI) engines and also conventional compression ignition engines with reasonable accuracy, practical chemical kinetic models have been explored. A genetic algorithm (GA) has been applied to the optimization of the rate constants in detailed kinetic models and also to the optimization of the model constants involved in the ignition and combustion models. By means of the present optimization method, a detailed kinetic model (592 reactions) for gasoline 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. A reduced reaction scheme (45 reactions) for dimethyl ether (DME) derived from Curran's detailed scheme has been proposed, 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 the modified eddy dissipation combustion model. Schreiber's five-step reaction scheme has been optimized for DME, and the combustion process in a DME injection diesel engine has been simulated considerably well by three-dimensional simulation using the GTT code, into which this optimized simple reaction scheme and the modified Reitz's combustion model with the optimized chemical characteristic time scale have been incorporated. As a result, the effectiveness of the present optimization method by means of GA has been confirmed.
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© 2004 一般社団法人 日本機械学会
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