Analysis of collapse risks under cut and cover method based on multi-state fuzzy Bayesian network

Ping Liu, Xueqiang Jin, Yongtao Shang and Jiaolan Zhu

PLOS ONE, 2025, vol. 20, issue 5, 1-23

Abstract: The collapse accidents under cut and cover method in metro station construction occurred frequently, leading to severe casualties and property damage. With increasing of metro station construction in China, more and more attention has been paid to collapse under cut and cover method. However, this subject is still not well studied and understood in China. To fill the research gap, this paper investigates collapse risk in the cut and cover method construction process using a multi-state fuzzy Bayesian network. Firstly, based on accident statistical analysis, 9 intermediate factors and 16 bottom factors of collapse were identified, and then a multi-state Fuzzy Bayesian network model was established based on these causative factors. Secondly, triangular fuzzy functions were utilized to fuzzily the data of nodes, and conditional probabilities were used to represent the uncertainty relationship between nodes. Additionally, an expert credibility-based survey method was employed to ensure the accuracy of node failure probability assessment. The method was applied to predict the risk of a case project using cut and cover method, and the results demonstrated that the probabilities of no-failure, moderate-failure, and severe-failure were 71%, 19%, and 10%, respectively. Sensitivity analyses of multi-states were performed to identify the key causal factors for moderate and severe collapse. The method can be used to predict the risk probability and key causal factors for collapse accidents. The result can provide decision support for cut and cover method construction, which could contribute to reducing the occurrence of collapse.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0321382

DOI: 10.1371/journal.pone.0321382

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