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Collapse Risk Analysis of Deep Foundation Pits in Metro Stations Using a Fuzzy Bayesian Network and a Fuzzy AHP

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  • Guohua Zhang
  • Chengtang Wang
  • Yuyong Jiao
  • Hao Wang
  • Weimin Qin
  • Wu Chen
  • Guoqiang Zhong

Abstract

Collapse risk analysis is of great significance for ensuring construction safety in foundation pits. This study proposes a comprehensive methodology for dynamic risk analysis of foundation pit collapse during construction based on a fuzzy Bayesian network (FBN) and a fuzzy analytical hierarchy process (FAHP). Firstly, the potential risk factors contributing to foundation pit collapse are identified based on the results of statistical analysis of foundation pit collapse cases, expert inquiry, and fault tree analysis. Then, a FAHP and improved expert elicitation considering a confidence index are adopted to elicit the probability parameters of the BN. On this basis, quantitative risk reasoning and sensitivity analysis of foundation pit collapse are achieved by means of fuzzy Bayesian inference. Finally, an actual deep foundation pit in a metro station was used to illustrate a specific application of this approach, and the results were in accordance with the field observations and numerical simulation results. The proposed approach can provide effective decision-making support for planners and engineers, which is vital to the prevention and control of the occurrence of the foundation pit collapse accidents.

Suggested Citation

  • Guohua Zhang & Chengtang Wang & Yuyong Jiao & Hao Wang & Weimin Qin & Wu Chen & Guoqiang Zhong, 2020. "Collapse Risk Analysis of Deep Foundation Pits in Metro Stations Using a Fuzzy Bayesian Network and a Fuzzy AHP," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-18, April.
    • Handle: RePEc:hin:jnlmpe:4214379
    DOI: 10.1155/2020/4214379
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    Cited by:

    1. Fu, Lipeng & Wang, Xueqing & Zhao, Heng & Li, Mengnan, 2022. "Interactions among safety risks in metro deep foundation pit projects: An association rule mining-based modeling framework," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    2. Changjian Chen & Wei Zou & Ping Geng & Wenqi Gu & Feiyun Yuan & Chuan He, 2023. "Study on Seismic Damage Risk Assessment of Mountain Tunnel Based on the Extension Theory," Sustainability, MDPI, vol. 15(6), pages 1-18, March.
    3. Cebi, Selcuk & Karakurt, Necip Fazıl & Kurtulus, Erkan & Tokgoz, Bunyamin, 2024. "Development of a decision support system for client acceptance in independent audit process," International Journal of Accounting Information Systems, Elsevier, vol. 53(C).

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