DEM-based analysis of water inrush process of underground engineering face with intermittent joints in karst region
DOI:
https://doi.org/10.56748/ejse.23480Keywords:
Intermittent joint, Karst tunnel, Tunnel face, Water inrush process, Numerical simulationAbstract
Water inrush disaster of karst tunnel often lead to significant economic losses and serious casualties, which is an urgent engineering roadblock to be solved in the construction of tunnel in karst area. In this paper, three-dimensional discrete element method considering fluid-solid coupling effect and structural characteristics of water-mud resistant rock mass is adopted to systematically study the evolution law of displacement field and seepage field of intermittent joint type water-mud resistant rock mass of tunnel face and its water inrush critical characteristics during the process of sequential excavation of karst tunnel close to the frontal high-pressure water-rich karst cavity. The results show that: With the tunnel face gradually approaching the front-concealed high-pressure water-rich karst cavity, the stability of water-mud resistant rock mass is increasingly affected by high-pressure karst water, and karst water pressure gradually becomes the main control factor. The closer the tunnel face is to the front-concealed high-pressure water-rich karst cavity, the greater the extrusion displacement of karst tunnel face and its increase amplitude, the higher damage degree of water-mud resistant rock mass of face. With the advance of tunnel excavation, the intermittent cracks in the water-mud resistant rock mass of face gradually connect and form a stable hydraulic connection. The flow velocity and seepage pressure of karst water rise significantly at the moment of overall instability of face and the formation of water inrush channel, showing obvious precursor characteristics. The research achievements provide a reference for early warning and prevention and control of water inrush disaster of karst tunnel face.
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Copyright (c) 2023 Shuguo Zhang, Ling Dai, Xiaohu Yuan, Qirui Wang, Jingmao Xu
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