Characterization of energy-driven damage mechanism and gas seepage in coal under mining-induced stress conditions

Gas seepage and progressive failure of coal are common energy-driven mining phenomena. A comprehensive understanding of the energy-driving mechanism behind the catastrophic behavior of mining-induced coal is fundamental to innovating the technology of coal and gas co-mining. Thus, this study simulat...

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Veröffentlicht in:International journal of rock mechanics and mining sciences (Oxford, England : 1997) England : 1997), 2024-09, Vol.181, p.105834, Article 105834
Hauptverfasser: Hao, Qijun, Zhang, Ru, Gao, Mingzhong, Xie, Jing, Ren, Li, Zhang, Anlin, Wang, Mengni, Zhang, Zetian
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Sprache:eng
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Zusammenfassung:Gas seepage and progressive failure of coal are common energy-driven mining phenomena. A comprehensive understanding of the energy-driving mechanism behind the catastrophic behavior of mining-induced coal is fundamental to innovating the technology of coal and gas co-mining. Thus, this study simulated three typical mining stress evolution process in protective coal-seam mining (PCM), top-coal caving mining (TCM), and non-pillar mining (NM) to investigate the energy evolution and distribution patterns of coal. The results indicate a strong correlation between energy dissipation and gas seepage. By transitioning from PCM and TCM to NM, the peak elastic strain energy of gas-bearing coal increased by 155.92 %, and the ratio of peak dissipative energy decreased from 51 % to 41 %. Under the PCM stress path, gas seepage decreased the energy storage by 13.52 %, whereas the pre-mining pressure relief and enhanced permeability simulation increased in peak dissipation energy by 49.66 %. Using the cumulative dissipative energy as a damage variable reveals that the degree of coal damage evolution under PCM is higher than other mining methods. Based on the energy-driven damage mechanism, a new coal permeability model was established, and its comparison with classical permeability model demonstrated its excellent fitting effectiveness.
ISSN:1365-1609
DOI:10.1016/j.ijrmms.2024.105834