JOURNAL OF YANGTZE RIVER SCIENTIFIC RESEARCH INSTI ›› 2020, Vol. 37 ›› Issue (3): 162-169.DOI: 10.11988/ckyyb.20191131


Stability Analysis of Anhydrite Cavern Group Based on Hoek-Brown Failure Criterion

LIU Shuo1,WANG Han-xun1,ZHANG Bin1,XU Neng-xiong1,HU Zhen-fa2   

  1. 1.School of Engineering & Technology, China University of Geoscience, Beijing 100083, China;
    2.Hanshan Hengtai Non-metallic Materials Branch,Wanbei Coal-Electricity Group Co.,Ltd.,Ma’anshan 238171, China
  • Received:2019-08-29 Online:2020-03-01 Published:2020-05-09

Abstract: Estimating the stability of anhydrite cavern group or goaf areas exactly is of great significance for guaranteeing the production safety of anhydrite mine and the treatment of goaf area. With an anhydrite mine located in Feicheng, Shandong Province as an engineering example, the stability of anhydrite rock was estimated based on generalized Hoek-Brown criterion. First of all, the physical and mechanical parameters of anhydrite was obtained through laboratory test. In association with field investigation and lab tests, the strength of anhydrite rock mass was calculated based on the generalized Hoek-Brown failure criterion and geological strength index (GSI). Subsequently, the global stability of anhydrite cavern group was assessed by the numerical model built in FLAC3D5.0, while the local stability of anhydrite cavern group was estimated as well using element safety factor method (ESFM). Results indicated that the plastic zone of rock mass connected largely, and the pillars between caverns mainly broke. The element safety factor of pillars was between 0.9 and 1.1, implying poor stability status or even instability status. The global and local stability of the studied anhydrite cavern group were extremely inferior. Hence, the mining method should be optimized,or necessary supporting measures should be adopted to guarantee the production safety.

Key words: anhydrite rock mass, mining group, Hoek-Brown failure criterion, surrounding rock stability, element safety factor method (ESFM)

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