Geomechanics and Engineering

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An analytical model for assessing soft rock tunnel collapse risk and its engineering application

  • Xue, Yiguo (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • Li, Xin (Institute of Marine Science and Technology, Shandong University) ;
  • Li, Guangkun (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • Qiu, Daohong (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • Gong, Huimin (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • Kong, Fanmeng (Geotechnical and Structural Engineering Research Center, Shandong University)
  • Received : 2020.02.01
  • Accepted : 2020.11.22
  • Published : 2020.12.10
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Abstract

The tunnel collapse, large deformation of surrounding rock, water and mud inrush are the major geological disasters in soft rock tunnel construction. Among them, tunnel collapse has the most serious impact on tunnel construction. Current research backed theories have certain limitations in identifying the collapse risk of soft rock tunnels. Examining the Zhengwan high-speed railway tunnel, eight soft rock tunnel collapse influencing factors were selected, and the combination of indicator weights based on the analytic hierarchy process and entropy weighting methods was obtained. The results show that the groundwater condition and the integrity of the rock mass are the main influencing factors leading to a soft rock tunnel collapse. A comprehensive fuzzy evaluation model for the collapse risk of soft rock tunnels is being proposed, and the real-time collapse risk assessment of the Zhengwan tunnel is being carried out. The results obtained via the fuzzy evaluation model agree well with the actual situation. A tunnel section evaluated to have an extremely high collapse risk and experienced a local collapse during excavation, verifying the feasibility of the collapse risk evaluation model. The collapse risk evaluation model proposed in this paper has been demonstrated to be a promising and innovative method for the evaluation of the collapse risk of soft rock tunnels, leading to safer construction.

Keywords

Acknowledgement

Much of the work presented in this paper was supported by the National Natural Science Foundation of China (grant numbers 51379112, 51422904, 41877239 and 41772298), and the State Key Development Program for Basic Research of China (grant number 2013CB036002), and Fundamental Research Funds for the Central Universities (grant number 2018JC044), and Natural Science Foundation of Shandong Province (grant number JQ201513). The authors would like to express appreciation to the reviewers for their valuable comments and suggestions that helped improve the quality of our paper.

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