Stochastic Modeling of the Particle Residence Time Distribution in an Opposed Multi-Burner Gasifier

The gasification technology of impinging streams has been extensively applied to chemical production and power generation. Particle residence time distribution (RTD) is an important parameter required for modeling, designing and optimization of an impinging stream gasifier. A stochastic mathematical model based on the Markov chains model is developed for the opposed multi‐burner gasifier (OMBG), which closely describes the behavior of the flow pattern and particle RTD in the gasification system. The model simulates the motion of single particle moving in the gasifier using the Markov chains. The predicted results give a reasonable fit to the experimental data. This shows that the flow process of particles in the gasifier has recirculation eddies, which have a downward flow direction near the downflow core and an upward flow direction near the wall, but no short‐circuit. Finally, the effect of particle flux rate on the RTD is predicted, and the contrast between gas and particles RTDs at a laboratory scale and in an industrial gasifier are presented. A good knowledge of the residence time distribution (RTD) of the various phases is essential for modeling, designing and optimization of multiphase reactors. A stochastic mathematical model based on the Markov chains model is developed for the opposed multi‐burner gasifier (OMBG), which closely describes the behavior of the flow pattern and particle RTD in a gasification system.