A Whole Explosive Dispersion Process Prediction Model for Fuel Clouds
Xing Chen, Zhongqi Wang, Yun Liu
Abstract
Abstract The study of the liquids and granular materials dispersed by high explosions is of great significance in the fuel‐air‐explosion and petrochemical fields. However, there is minimal dynamic dispersal research at high speed. Therefore, the numerical calculation methods of explosive dispersion have become a priority. A model is proposed that can predict the characteristics of the explosive dispersal for fuel both in the near‐field and the far‐field. Then, the basic laws of the fuel cloud formed during explosive dispersal are derived. The model is constructed by six parts of different processes, with the characteristics obtained by tracking the fuel droplets or particles and calculating their velocity, displacement, mass, and particle size. This model is validated using two sets of experimental data consisting of dynamic fuel dispersion and static fuel dispersion that fit the model well.