Enhancement of engine simulation using LES turbulence modeling and advanced numerical schemes

The goal of this study is to develop advanced numerical models and algorithms to improve the accuracy of engine spray combustion simulation. This study developed a large eddy simulation (LES) turbulence model and adaptive mesh refinement (AMR) algorithms to enhance the accuracy and computational efficiency of engine simulation. The LES approach for turbulence modeling is advantageous over the traditional Reynolds Averaged Navier Stokes (RANS) approach due to its capability to obtain more detailed flow information by resolving large-scale structures which are strongly geometry dependent. The current LES approach used a one-equation, non-viscosity, dynamic structure model for the sub-grid stress tensor and also used a gradient method for the sub-grid scalar fluxes. The LES implementation was validated by comparing the predicted spray penetrations and structures in a non-evaporating diesel spray. The present LES model, when coupled with spray breakup and detailed chemistry models, were able to predict the overall cylinder pressure history, heat release rate data, and the trends of NOx and soot emissions with respect to different injection timings and EGR levels in a heavy-duty diesel engine. Results also indicated that the LES model could predict the unsteadiness of in-cylinder flows and have the potential to provide more detailed flow structures compared to the RANS model. AMR algorithms were also developed to improve transient engine spray simulation. It is known that inadequate spatial resolution can cause inaccuracy in spray simulation using the stochastic Lagrangian particle approach due to the over-estimated diffusion and inappropriate liquid-gas phase coupling. Dynamic local mesh refinement, adaptive to fuel spray and vapor gradients, was developed to increase the grid resolution in the spray region. AMR was parallelized using the MPI library and various strategies were also adopted in order to improve the computational efficiency, including timestep control, reduction in search of the neighboring cells on the processor boundaries, and re-initialization of data at each adaptation. The AMR implementation was validated by comparing the predicted spray penetrations and structures. It was found that a coarse mesh using AMR could produce the same results as those using a uniformly fine mesh with substantially reduced computer time. The parallel performance using AMR varied depending on the geometry and simulation conditions. In general, the computations without valve motion or using a fine mesh could obtain better parallel performance than those with valve motion or using a coarse mesh