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Automated mechanism reduction is important in enabling the use of kinetics data in engineering design. In this work, we report on a mechanism-reduction technique that serves as a practical tool for automated mechanism reduction when applied to engine-simulation, with particular focus on compression-ignition engines. For this application, a multi-zone engine model has been developed, which can capture the stratification in the engine due to crevice and boundary-layer cooling effects. The multi-zone model serves as the workhorse for the mechanism-reduction algorithm. The reduction process is designed to operate on model-solution data from a parametric matrix of runs, in which the multi-zone model is run under different conditions. A more accurate reduction can therefore be achieved while accounting for spatial variations in the engine, temporal variations over the compression cycle, and variations in operating conditions.

Detailed knowledge of hydrocarbon fuel combustion chemistry has grown tremendously in recent years. However, the gap between detailed chemistry and computational fluid dynamics (CFD) remains, because of the high cost of solving detailed chemistry in a large number of computational cells. This paper presents the results of applying a suite of techniques aimed at closing this gap. The techniques include use of a surrogate blend optimizer and a guided mechanism reduction methodology, as well as advanced methods for efficiently and accurately coupling the pre-reduced kinetic models with the multidimensional transport equations. The advanced methods include dynamic adaptive chemistry (DAC) and dynamic cell clustering (DCC) algorithms.