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多源方法研究地下采矿引发山体地表沉降的预测与机理

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论文题目

Multi-source approach research on prediction and mechanis m of mountain surface subsidence caused by underground mining

Xiang Yang1Jiabo Geng, Xiang Lan2* , Shibin Tang2Qinglin Chen2

1 School of Economics and Management, Jiangxi University of Science and Technology, Ganzhou, China
School of Emergency Management and Safety Engineering, Jiangxi University of Science and Technology, Ganzhou, China

 

研究内容

Abstract: Mining activities may trigger hazards such as mountain subsidence. To predict the extent of mountain subsidence and an alyze the evolutionary characteristics of mountain subsidence, the optical images and S mall Baseline Subset InSAR (SBAS-InSAR) method were used, and the mountain subsidence was circled and interpreted. The cumulative subsidence in the area from 2024 to 2026 was predicted by combining the long short-term memory (LSTM) method, and the mountain surface subsidence slip was derived using MatDEM. The results of the study show that mountain surface subsidence begins with the formation of a primary subsidence zone, which slowly leads to the formation of primary and secondary subsidence zones. Under the influence of the penetrating channel, the primary and secondary subsidence areas merge to form a larger subsidence area. The subsidence area gradually disintegrates into several s mall areas during the sliding process, and the s mall areas underneath contribute to the main force of the subsidence movement,withasubstantial slip displacement. Based on this study, it is concluded that the accuracy of the results obtained from the LSTM methodishigherthanthatofthenumericalsimulationresults,andthemaximum cumulative subsidence is expected to reach 2,180 mm in 2026.

Keywords: Underground miningMountain surface subsidence; Remote sensing imageSBAS-InSARMatDEM 

Fig.2 Information map of the study area.(a)Location of the study area.(b)Location of the new and old collapsed areas;data are obtained fromGoogle Maps.(c)Front view of the new collapsed area.(d)Top view of the new collapsed area.(c,d)are obtained from Unmanned Aerial Vehicle.

Fig.3 Distribution of stratigraphic properties in the study area.

Fig.4 Schematic diagram of ore body hosting and mining. (a) Ore body location. (b) Ore body mining plan.

Fig.6 Elastic contact of particles
Fig.8 The mountain surface subsidence in the mining area at different times.(a–i)2015–2023.(j)3D live image.Satellite image data for GF-2 wereo btained from China Center for Resources Satellite Data and Application (https://data.cresda.cn).The images were processed using ENVI version 5.6 software  (http://www.exelisvis.com)
Fig.11  Variation in the mountain surface cumulative slip. (a–l) corresponding to 2015 to 2026
Fig.12  Trajectory of particle change in the Aregion.(a–l)corresponding to 2015 to 2026
Fig.14 (a) Cumulative subsidence in the ABC area. (b) Discrepancy between SBAS-InSAR and numerical simulation results

 

了解详情


 

Yang X, Jiabo G, Lan X, et al. Multi-source approach research on prediction and mechanis m of mountain surface subsidence caused by underground mining[J]. Frontiers in Earth Science, 2025, 13: 1642350.

来源:矩阵离散元MatDEM
ACTOpticalADSUM离散元
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首次发布时间:2025-11-12
最近编辑:1天前
MatDEM
中国自己的工程数值计算软件
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