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A methodology has been implemented to calculate local turbulent flame speeds for spark ignition engines accurately and on-the-fly in 3-D CFD modeling. The approach dynamically captures fuel effects, based on detailed chemistry calculations of laminar flame speeds. Accurately modeling flame propagation is critical to predicting heat release rates and emissions. Fuels used in spark ignition engines are increasingly complex, which necessitates the use of multi-component fuels or fuel surrogates for predictive simulation. Flame speeds of the individual components in these multi-component fuels may vary substantially, making it difficult to define flame speed values, especially for stratified mixtures. In addition to fuel effects, a wide range of local conditions of temperature, pressure, equivalence ratio and EGR are expected in spark ignition engines.

A detailed reaction mechanism for the combustion of biodiesel fuels has recently been developed by Westbrook and co-workers. This detailed mechanism involves 5037 species and 19990 reactions, which prohibits its direct use in computational fluid dynamic (CFD) applications. In the present work, various mechanism reduction methods included in the Reaction Workbench software were used to derive a semi-detailed biodiesel combustion mechanism, while maintaining the accuracy of the master mechanism for a desired set of engine conditions. The reduced combustion mechanism for a five-component biodiesel fuel was employed in the FORTÉ CFD simulation package to take advantage of advanced chemistry solver methodologies and advanced spray models. Simulations were performed for a Volvo D12C heavy diesel engine fueled by RME fuel using a 72° sector mesh. Predictions were validated against measured in-cylinder parameters and exhaust emission concentrations.

This study focuses on Lagrangian spray models that are commonly used in engine CFD simulations. In modeling sprays, droplet collision is one of the physical phenomena that must be accounted for. There are two main parts of droplet collision models for sprays - detecting colliding pairs of droplets and predicting the outcomes of these collisions. For the first part, we focus on the efficiency of the algorithm. We present an implementation of the arbitrary adaptive collision mesh model of Hou and Schmidt [1], and examine its efficiency in dealing with large simulations. Through theoretical analysis and numerical tests, we show that the computational cost of this model scales pseudo-linearly with respect to the number of parcels in the sprays. Regarding the second part, we examine the variations in existing phenomenological models used for predicting binary droplet collision outcomes. A quantitative accuracy metric is used to evaluate the models with respect to the experimental data set.