4.7 Article

Analysis of excessive deformations in tunnels for safety evaluation

期刊

TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
卷 45, 期 -, 页码 190-202

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tust.2014.09.006

关键词

Tunnels; Excessive deformation; Material point method; Numerical methods; Deep coal mines

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Tunnel construction is increasing worldwide in mining and civil engineering. There have been several accidents that resulted in delays, cost overruns, some with more severe consequences. To help minimize these accidents, it is necessary to assess and manage the risks associated with tunnel construction and exploration. A particular type of accident, or undesirable event, which can occur during tunnel construction and operation, is associated with the occurrence of excessive deformations occurring inside the tunnel. This can happen due to deficient design, construction defects, and high in situ stresses or due to specific swelling and squeezing grounds. Deep coal mines where large deformations can occur during and after excavations due to the soft properties of the rock and the high in situ stresses, are particularly vulnerable to this type of event. The associated non-linear problems are related with geomechanical behavior of the rock mass, changes in the geometry of cavities and in some cases with developing surface contacts due to large strains. In this paper, the phenomena involved in large material deformations are analyzed in detail and the basic equations for the Chen's large deformation theory are presented. The application of an FEM based method to simulate large material deformations, the Material Point Method (MPM) to the simulation of large deformation that occurs in tunnels when failure occurs, is also described. An application of MPM to the Jiahe Coal Mine, in China is presented, and the numerical results obtained with MPM compared with solutions using Chen's large deformation theory. Safety considerations about the excessive deformation scenario in tunnels are drawn and a risk assessment methodology with special use of Bayesian networks is proposed. A simplified schematic example was presented,for two case scenarios. (C) 2014 Elsevier Ltd. All rights reserved.

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