Irrational coal exploitation under mountainous areas commonly results in deep mining landslide disasters, which can cause unpredictable catastrophic destruction and massive casualties. In order to prevent deep mining landslides induced by underground coal mining, a mechanical model for mining overburden failure, a preliminary discrimination model of deep mining landslides, is established for the very first time based on some simplifying assumptions. A deep mining landslide occurs when one or more sets of strata interfaces or discontinuities near the slope surface are involved in the mining-induced overburden fracture zone. The discrimination model is verified using FLAC3D numerical simulation studies on the inclined multiple coal seam Guanwen coal mine, which is located in southern Sichuan province and possess a typical medium mountain landform. In the absence of adequate practical applications, further study is still necessary to be conducted to improve the discrimination model.
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First and foremost, this project is funded by the National Natural Science Foundation of China (No.51304156, No.51874230), Ph.D. Programs Foundation of Ministry of Education of China (No. 20106121110003), Natural Science Foundation of Shaanxi Province (No. 2011JY005), Key Laboratory Scientific Research Program of Shaanxi Province (No. 13JS066), Key Technology Innovation Team of Shaanxi Province (No. 2013KCT-16). Additionally, we would show our deepest gratitude to our team who participated this study with great cooperation, and to those who have helped develop the fundamental and essential academic competence. Last but not least, I would like to thank all my friends, especially my lovely roommate, for their encouragement and support.
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Xueyi, Y., Xuwei, M. A preliminary discrimination model of a deep mining landslide and its application in the Guanwen coal mine. Bull Eng Geol Environ 79, 485–493 (2020). https://doi.org/10.1007/s10064-019-01565-4
- Deep landslide
- Discrimination model
- Underground mining
- Overburden failure
- Slope stability