Development of a New Hybrid Stochastic/Trajectory Droplet Collision Model for Spray Simulations in Internal Combustion Engines

Abstract

Focusing on the spray simulation in engines using the Lagrangian-Drop Eulerian-Fluid (LDEF) approach, a new hybrid stochastic/trajectory (HST) droplet collision model with the improved collision frequency, the redivided collision cell, and an updated method for selection of the candidate collision pairs was developed in this study. The stochastic method used in the HST model was based on the theoretical framework of the time-counter (TC) direct simulation Monte Carlo (DSMC) method. Besides the stochastic method, the trajectory method was also introduced for the cases with sparse spray conditions in order to improve the reliability of the model predictions. The factor of “every parcel represents a certain number of droplets” was well considered in the calculations of the droplet collision frequency in the present model, which has not been attracted enough attention in previous models. Moreover, an adaptive collision cell technique was used for reducing the dependence of the calculation results on the computational mesh. The formula for selecting the collision pairs was updated in order to accurately reproduce the spatial distribution of the spray droplets after collision. To assess the performance of the droplet collision model, the experimental data with the direct spray-to-spray impingement under wide operating conditions were used for model validations. In addition, the numerical results by the droplet collision models including O'Rourke model, Nordin model, and no-time-counter (NTC) model were presented for comparison. The results indicate that the HST model is capable of satisfactorily reproducing the spray morphology, collision frequency, and Sauter mean diameter (SMD) of the droplets during the spray process. Meanwhile, good independence on the computational grid size, time step, and parcel number can be achieved by the HST model.