Selecting the optimum quasi-steady-state species for reduced chemical kinetic mechanisms using a genetic algorithm

Abstract

A genetic optimization algorithm has been applied to the selection of quasi-steady-state (QSS) species in reduced chemical kinetic mechanisms. The algorithm seeks to minimize the error between reduced and detailed chemistry for simple reactor calculations approximating conditions of interest for a computational fluid dynamics simulation. The genetic algorithm does not guarantee that the global optimum will be found, but much greater accuracy can be obtained than by choosing QSS species through a simple kinetic criterion or by human trial and error. The algorithm is demonstrated for methane–air combustion over a range of temperatures and stoichiometries and for homogeneous charge compression ignition engine combustion. The results are in excellent agreement with those predicted by the baseline mechanism. A factor of two reduction in the number of species was obtained for a skeletal mechanism that had already been greatly reduced from the parent detailed mechanism.