Upscaling coal self-heating reaction models from the laboratory to field applications

Abstract

During the coal mining process, real-time monitoring and analysis of gases are crucial for preventing and controlling coal spontaneous combustion (sponcom). Laboratory-based gas evolution tests and reaction models on coal for sponcom prevention are often difficult to be scaled up in field goaf conditions. Computational fluid dynamics modelling addresses these challenges but faces issues with temperature impacts on coal properties and upscaling to goaf environments. Addressing these issues, this study has developed a novel coal oxidation model that accounts for variation in coal properties with temperature and introduces oxidation products of C₂H₄ and C₂H₆ as key gas indicators. This model uses gas composition and concentration changes to assess the progression of sponcom in longwall goaf. Compared to previous models, this approach significantly improves accuracy by incorporating key gas indicators and better capturing the temperature-dependent behaviours of coal. Simulation results indicate a clear localisation trend of coal sponcom in the goaf: as the reaction intensifies, the highest-temperature points initially move deeper into the goaf and then migrate towards face areas with higher oxygen concentrations. The decrease in O₂ concentration, changes in the Graham's ratio, and the generation of C₂H₄ and C₂H₆ can all indicate different stages of coal self-heating. This phenomenon reveals the complex interactions between temperature, oxygen concentration, and coal properties. The findings highlight the critical role of temperature and gas components in sponcom, providing a basis for optimising monitoring locations in goaf areas to improve early detection and real-time risk assessment, ultimately enhancing sponcom early-warning accuracy and coal mine safety.