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Risk Assessment Model for Water and Mud Inrush in Deep and Long Tunnels Based on Normal Grey Cloud Clustering Method

  • Tunnel Engineering
  • Published:
KSCE Journal of Civil Engineering Aims and scope

Abstract

In terms of the frequent occurrence and much trouble in governance of the disaster caused by water and mud inrush in deep and long tunnels, the risk assessment model based on normal grey cloud clustering method was proposed. Taking the Jigongling Tunnel of Fanba Expressway as an example, firstly the evaluation target was divided into 8 clustering indices and 4 grey categories according to the grey clustering method. In order to avoid the defects that the traditional whitenization weight functions could not give a good description of system’s randomness and ambiguity, the cloud model was introduced to improve it. Then the whitenization weight values were discretized by using the one-dimensional forward cloud generator to simulate the uncertainties in engineering, and the normal grey cloud whitenization weight functions were established. Afterwards, combined with the engineering data of Jigongling Tunnel collected on site, the clustering weight of each clustering index was analyzed under specific engineering and the clustering coefficient of the target was determined. Lastly the risk of water and mud inrush in Jigongling Tunnel was evaluated using the model. The results, which showed that the risk of water and mud inrush in target D1, D2 and D3 was respectively medium, extremely high and high, were compared with the excavation data. The two coincided with each other well which indicated that the model had a certain engineering value and could provide reference for related engineering.

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Authors and Affiliations

  1. School of Civil Engineering, Central South University, Changsha, 410075, China

    Tian-zheng Li & Xiao-li Yang

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  1. Tian-zheng Li
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  2. Xiao-li Yang
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Correspondence to Tian-zheng Li.

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Li, Tz., Yang, Xl. Risk Assessment Model for Water and Mud Inrush in Deep and Long Tunnels Based on Normal Grey Cloud Clustering Method. KSCE J Civ Eng 22, 1991–2001 (2018). https://doi.org/10.1007/s12205-017-0553-6

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