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A dynamic Bayesian network based approach to safety decision support in tunnel construction

Author

Listed:
  • Wu, Xianguo
  • Liu, Huitao
  • Zhang, Limao
  • Skibniewski, Miroslaw J.
  • Deng, Qianli
  • Teng, Jiaying

Abstract

This paper presents a systemic decision approach with step-by-step procedures based on dynamic Bayesian network (DBN), aiming to provide guidelines for dynamic safety analysis of the tunnel-induced road surface damage over time. The proposed DBN-based approach can accurately illustrate the dynamic and updated feature of geological, design and mechanical variables as the construction progress evolves, in order to overcome deficiencies of traditional fault analysis methods. Adopting the predictive, sensitivity and diagnostic analysis techniques in the DBN inference, this approach is able to perform feed-forward, concurrent and back-forward control respectively on a quantitative basis, and provide real-time support before and after an accident. A case study in relating to dynamic safety analysis in the construction of Wuhan Yangtze Metro Tunnel in China is used to verify the feasibility of the proposed approach, as well as its application potential. The relationships between the DBN-based and BN-based approaches are further discussed according to analysis results. The proposed approach can be used as a decision tool to provide support for safety analysis in tunnel construction, and thus increase the likelihood of a successful project in a dynamic project environment.

Suggested Citation

  • Wu, Xianguo & Liu, Huitao & Zhang, Limao & Skibniewski, Miroslaw J. & Deng, Qianli & Teng, Jiaying, 2015. "A dynamic Bayesian network based approach to safety decision support in tunnel construction," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 157-168.
    • Handle: RePEc:eee:reensy:v:134:y:2015:i:c:p:157-168
    DOI: 10.1016/j.ress.2014.10.021
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    References listed on IDEAS

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    1. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2011. "Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 925-932.
    2. Montani, S. & Portinale, L. & Bobbio, A. & Codetta-Raiteri, D., 2008. "Radyban: A tool for reliability analysis of dynamic fault trees through conversion into dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 922-932.
    3. Langseth, Helge & Portinale, Luigi, 2007. "Bayesian networks in reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 92-108.
    4. Zhang, Limao & Wu, Xianguo & Skibniewski, Miroslaw J. & Zhong, Jingbing & Lu, Yujie, 2014. "Bayesian-network-based safety risk analysis in construction projects," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 29-39.
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