A Novel Approach to Mechanism Reduction Optimization for an Aviation Fuel/Air Reaction Mechanism Using a Genetic Algorithm

摘要

This study presents a novel multiobjective genetic-algorithm approach to produce a new reduced chemical kinetic reaction mechanism to simulate aviation fuel combustion under various operating conditions. The mechanism is used to predict the flame structure of an aviation fuel/O{sub}2/N{sub}2 flame in both spatially homogeneous and one-dimensional premixed combustion. Complex hydrocarbon fuels, such as aviation fuel, involve large numbers of reaction steps with many species. As all the reaction rate data are not well known, there is a high degree of uncertainty in the results obtained using these large detailed reaction mechanisms. In this study a genetic algorithm approach is employed for determining new reaction rate parameters for a reduced reaction mechanism for the combustion of aviation fuel-air mixtures. The genetic algorithm employed incorporates both perfectly stirred reactor and laminar premixed flame data in the inversion process, thus producing an efficient reaction mechanism. This study provides an optimized reduced aviation fuel-air reaction scheme whose performance in predicting experimental major species profiles and ignition delay times is not only an improvement on the starting reduced mechanism but also on the full mechanism.