Abstract
Coal and gas outbursts are among the most serious disasters affecting the safety of coal mines, with 39 deaths reported during 2019 in China. The cause of outbursts is fairly complicated and involves many influencing factors. Thus, methods of accurate prediction and prevention are quite immature. For this study, two groups of coal and gas experiments under different conditions are carried out to explore more effective prediction and prevention measures. The results show that a two-phase flow of coal and gas is ejected from an outburst mouth at high speed, crushing large particles into smaller ones. The crushing effect increases with a higher stress concentration factor and gas pressure, as does the relative intensity of outburst (RIO) nonlinearly. By analyzing the ejected coal, an outburst fragmentation index is developed based on a new surface theory, which can be linearly fitted with the RIO. The fitting parameters reflect the outburst risk from two dimensions. Next, the η prediction method is proposed, offering many advantages compared with current prediction methods. Furthermore, its relationship with the f prediction method is analyzed. Five grades of outburst risk (i.e., negligible-risk zone, low-risk zone, medium-risk zone, high-risk zone, and very-high-risk zone) are classified according to the ranges of fitting parameters. Finally, based on the η prediction method, a new method for coal and gas outburst prevention is specified, and its applications and prospects are discussed. The results have guiding significance for better preventing outbursts and ensuring safe coal-mine operations.
Published Version
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