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The objective of the present study is to analyze soot formation in diesel engine combustion by using multi-dimensional combustion simulations with a parallelized explicit ODE solver. Parallelized CHEMEQ2 was used to perform detailed chemical kinetics in KIVA-4 code. CHEMEQ2 is an explicit stiff ODE solver developed by Mott et al. which is known to be faster than traditional implicit ODE solvers, e.g., DVODE. In the present study, about eight times faster computation was achieved with CHEMEQ2 compared to DVODE when using a single thread. Further, by parallelizing CHEMEQ2 using OpenMP, the simulations could be run not only on calculation servers but also on desktop machines. The computation time decreases with the number of threads used. The parallelized CHEMEQ2 enabled combustion and emission characteristics, including detailed soot formation processes, to be predicted using KIVA-4 code with detailed chemical kinetics without the need for reducing the reaction mechanism.

Improvement of indicated thermal efficiency of internal combustion engines is required, and increasing the compression ratio is an effective solution. In this study, using a CAE analysis coupling a 0-dimensional combustion analysis and a 1-dimensional heat conduction analysis, the influence of compression ratio on indicated thermal efficiency and combustion was investigated. As a result, it was found that there was an optimal compression ratio that gave the best indicated thermal efficiency, because the increase of cooling loss caused by high compression was bigger than the increase of theoretical indicated thermal efficiency in some cases. Next, the influence of cooling loss reduction on the optimal compression ratio was investigated. It was found that indicated thermal efficiency improved by reducing cooling loss, because the compression ratio which made the best indicated thermal efficiency was shifted to higher compression ratio.

This study simulates soot formation processes in diesel combustion using a large eddy simulation (LES) model, based on a one-equation subgrid turbulent kinetic energy model. This approach was implemented in the KIVA4 code, and used to model diesel spray combustion within a constant volume chamber. The combustion model uses a direct integration approach with a fast explicit ordinary differential equation (ODE) solver, and is additionally parallelized using OpenMP. The soot mass production within each computation cell was determined using a phenomenological soot formation model developed by Waseda University. This model was combined with the LES code mentioned above, and included the following important steps: particle inception during which acenaphthylene (A2R5) grows irreversibly to form soot; surface growth with driven by reactions with C2H2; surface oxidation by OH radical and O2 attack; and particle coagulation.