Advances in Computational Design

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Collapse risk evaluation method on Bayesian network prediction model and engineering application

  • WANG, Jing (Research Center of Geotechnical and Structural Engineering, Shandong University) ;
  • LI, Shucai (Research Center of Geotechnical and Structural Engineering, Shandong University) ;
  • LI, Liping (Research Center of Geotechnical and Structural Engineering, Shandong University) ;
  • SHI, Shaoshuai (Research Center of Geotechnical and Structural Engineering, Shandong University) ;
  • XU, Zhenhao (Research Center of Geotechnical and Structural Engineering, Shandong University) ;
  • LIN, Peng (Research Center of Geotechnical and Structural Engineering, Shandong University)
  • Received : 2016.10.12
  • Accepted : 2017.01.10
  • Published : 2017.04.25
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Abstract

Collapse was one of the typical common geological hazards during the construction of tunnels. The risk assessment of collapse was an effective way to ensure the safety of tunnels. We established a prediction model of collapse based on Bayesian Network. 76 large or medium collapses in China were analyzed. The variable set and range of the model were determined according to the statistics. A collapse prediction software was developed and its veracity was also evaluated. At last the software was used to predict tunnel collapses. It effectively evaded the disaster. Establishing the platform can be subsequent perfect. The platform can also be applied to the risk assessment of other tunnel engineering.

Keywords

References

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