Research on the surface subsidence characteristics and prediction models caused by coal mining under the reverse fault

Predicting and understanding the phenomenon of surface subsidence caused by coal mining in working faces with faults are important issues for safe coal mining and efficient production. In numerical simulation experiments, it was found that the phenomenon of surface subsidence manifests when faults e...

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Vydáno v:Scientific reports Ročník 14; číslo 1; s. 25316 - 16
Hlavní autoři: Luo, Jin, Li, Yingming, Guo, Qingbiao, Meng, Xiangrui, Wang, Liang
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Nature Publishing Group UK 25.10.2024
Nature Publishing Group
Nature Portfolio
Témata:
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704/4111
Asymmetric sinking
Coal
Coal mining
Expected model
Fault
Fault lines
Geology
Humanities and Social Sciences
Mathematical models
Mining engineering
multidisciplinary
Prediction models
Remote sensing
Science
Science (multidisciplinary)
Simulation
Subsidence
Surface subsidence
Unmanned aerial vehicles
Expected model
Fault
Asymmetric sinking
Surface subsidence
ISSN:2045-2322, 2045-2322
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Shrnutí:Predicting and understanding the phenomenon of surface subsidence caused by coal mining in working faces with faults are important issues for safe coal mining and efficient production. In numerical simulation experiments, it was found that the phenomenon of surface subsidence manifests when faults exist, and the degree of influence of faults with different dip angles on surface subsidence varies. This phenomenon is attributed to fault activation. According to the experimental results, the impact of faults with different dip angles on surface subsidence falls into three levels: level I for 35° faults, level II for 45° and 55° faults, and level III for 65° and 75° faults. Similarly, the relationship between the difficulty of fault activation and the dip angle of faults can be categorized as 35° faults prone to activation, 45° and 55° faults difficult to activate, and 65° and 75° faults not prone to activation. The probability integral correction model for fault mining, which integrates the surface subsidence values caused by fault-induced attenuation and the subsidence arising from separation spaces, was introduced, thereby constructing a surface subsidence prediction model. This proposed prediction model can accurately predict surface subsidence, with a root mean square error of 10.74 mm between the predicted and measured values, as validated using DInSAR results from the III 6301 working face in the Jincheng mining area.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-75182-x