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  • 标题:Influence of Underground Mining Direction Based on Particle Flow on Deformation and Failure of Loess Gully Area
  • 本地全文:下载
  • 作者:Yanjun Zhang ; Jiayuan Kong ; Yuanhao Zhu
  • 期刊名称:Computational Intelligence and Neuroscience
  • 印刷版ISSN:1687-5265
  • 电子版ISSN:1687-5273
  • 出版年度:2022
  • 卷号:2022
  • DOI:10.1155/2022/1698220
  • 语种:English
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Due to unique landform and lithological features of the loess gully area, the geological disasters caused by coal mining have become more complex. Moreover, the advancing direction of the working face has an important influence on the deformation of the slope on both sides of the gully. In this paper, combined with the specific conditions of a coal mine working face in western China, we use the method of particle flow numerical simulation and theoretical analysis to examine and observe the deformation, as well as characteristics of failures in the loess gully area under different mining directions of the working face. The deformation process of the gully area can be obtained by combining the numerical simulation results. According to different mining directions of the working face, the failure mode of mining in the loess gully area was divided into the back slope and along slope advancing failure modes. Through empirical evaluation, our investigation demonstrates that the bottom of the gully was damaged seriously by both along slope mining and back slope mining. Albeit the influence of coal seam excavation on the slope surface was relatively small; however, it is greater on the flat ground of the upper slope. Under the same mining conditions, the advancing direction of the working face affected the horizontal movement of the loess gully area but had less effect on the subsidence. Furthermore, we observed that the failure mode of the mining slope is highly correlated with the mining direction and relative position of the working face. The results obtained from this research can provide useful information for deformation and failure prediction, working face mining method, and geological disaster assessment in the loess gully area.
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