Reduction of a Numerical Grid Dependency in High-pressure Diesel Injection Simulation Using the Lagrangian-Eulerian CFD Method

In the standard CFD code, Lagrangian-Eulerian method is very popular to simulate the liquid spray penetrating into gaseous phase. Though this method can give a simple solution and low computational cost, it have been reported that the Lagrangian spray models have numerical grid dependency, resulting in serious numerical errors. Many researches have shown the grid dependency arise from two sources. The first is due to unaccurate prediction of the droplet-gas relative velocity, and the second is that the probability of binary droplet collision is dependent on the grid resolution. In order to solve the grid dependency problem, the improved spray models are implemented in the KIVA-3V code in this study. For reducing the errors in predicting the relative velocity, the momentum gain from the gaseous phase to liquid particles were resolved according to the gas-jet theory. In addition, the advanced algorithm of the droplet collision modeling which surmounts the grid dependency problem was applied. Then, in order to validate the improved spray model, the computation is compared to the experimental results. By simultaneously regarding the momentum coupling and the droplet collision modeling, successful reduction of the numerical grid dependency could be accomplished in the simulation of the high-pressure injection diesel spray