Underground coal gasification (UCG) is a coal utilization technology that has attracted extensive attention over the years. In order to study the distribution and evolution law of the growth boundary of a coal gasification cavity under UCG, COMSOL numerical simulation software was used to conduct a multi-physical field-coupling numerical simulation of its growth process. In this study, we established a gasification reaction model of the cavity, and after simulation calculation, the growth boundary of the gasification cavity was obtained. Multiple data points were taken from the growth boundary of the gasification cavity for the fitting calculation, and the fitting function y=Fx of the gasification boundary growth was obtained. The core insight from this study is that a gasification boundary growth fitting function y=Fx was cross-fitted based on seven different gasification times t (5 d, 20 d, 40 d, 60 d, 80 d, 110 d, 150 d) and 10 different gasification agent inflow velocities v (0.1 m/s, 0.3 m/s, 0.5 m/s, 0.7 m/s, 1 m/s, 2 m/s, 4 m/s, 6 m/s, 8 m/s, 10 m/s) as orthogonal independent variables. An innovative multi-parameter fitting equation was constructed, y=Fx,t,v, with the gasification time t and the gasification agent inflow velocity v as independent variables. This fitting equation, y=Fx,t,v, can dynamically depict the gasification cavity boundary during the UCG process when different gasification times t and gasification agent inflow velocities v are inputted. The novelty of this study lies in the fact that it breaks through the limitations of traditional numerical simulation models that rely on a single variable, have limited adaptability, and focus on gasification cavities that lie mostly in the side-view direction. Moreover, through a multi-physics field-coupling numerical simulation in the top-view direction of the gasification cavity, we have improved the construction of the UCG numerical simulation model and cross-fitted the gasification boundary with respect to the gasification time t and gasification agent inflow velocity v to construct a fitting equation, achieving the quantitative representation of the nonlinear relationship between variables.
Ma et al. (Fri,) studied this question.