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

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.

• Record URL:
  • https://doi.org/10.1007/s12205-017-0553-6
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/12267988
• Supplemental Notes:
  • © Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg 2018.
• Authors:
  • Li, Tian-zheng
  • Yang, Xiao-Li
• Publication Date: 2018-5

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References;
• Pagination: pp 1991-2001
• Serial:
  • KSCE Journal of Civil Engineering
  • Volume: 22
  • Issue Number: 5
  • Publisher: Korean Society of Civil Engineers
  • ISSN: 1226-7988
  • EISSN: 1976-3808
  • Serial URL: http://link.springer.com/journal/12205

Subject/Index Terms

• TRT Terms: Aggressive waters; Cluster analysis; Mud; Risk assessment; Tunneling; Tunnels
• Uncontrolled Terms: Cloud method; Grey relational analysis
• Geographic Terms: China
• Subject Areas: Bridges and other structures; Highways; Planning and Forecasting; Safety and Human Factors;

Filing Info

• Accession Number: 01679190
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 27 2018 2:05PM