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

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 s...

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Published in:PloS one Vol. 20; no. 5; p. e0321382
Main Authors: Liu, Ping, Jin, Xueqiang, Shang, Yongtao, Zhu, Jiaolan
Format: Journal Article
Language:English
Published: United States Public Library of Science 07.05.2025
Subjects:
Accidents
Analysis
Bayes Theorem
Bayesian analysis
Bayesian statistical decision theory
Biology and Life Sciences
Casualties
China
Collapse
Construction accidents & safety
Construction industry
Decision making
Design and construction
Earth Sciences
Engineering
Engineering and Technology
Failure
Fatalities
Forecasts and trends
Fuzzy Logic
Fuzzy sets
Geology
Health risks
Humans
Light rail transit
Medicine and Health Sciences
Methods
Nodes
Physical Sciences
Probability
Property damage
Railroads
Risk
Risk Assessment
Safety and security measures
Safety management
Sensitivity analysis
Social Sciences
Statistical analysis
Structural failures
Structure Collapse
Supervision
China
ISSN:1932-6203, 1932-6203
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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.
AbstractList 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.
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.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.
Audience Academic
Author Zhu, Jiaolan
Shang, Yongtao
Liu, Ping
Jin, Xueqiang
AuthorAffiliation 1 School of Civil Engineering, Lanzhou University of Technology, Lanzhou, China
Southwest Petroleum University, CHINA
2 School of Management Science & Real Estate, Chongqing University, Chongqing, China
AuthorAffiliation_xml – name: 1 School of Civil Engineering, Lanzhou University of Technology, Lanzhou, China
– name: Southwest Petroleum University, CHINA
– name: 2 School of Management Science & Real Estate, Chongqing University, Chongqing, China
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  fullname: Zhu, Jiaolan
BackLink https://www.ncbi.nlm.nih.gov/pubmed/40334209$$D View this record in MEDLINE/PubMed
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2025 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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Snippet The collapse accidents under cut and cover method in metro station construction occurred frequently, leading to severe casualties and property damage. With...
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StartPage e0321382
SubjectTerms Accidents
Analysis
Bayes Theorem
Bayesian analysis
Bayesian statistical decision theory
Biology and Life Sciences
Casualties
China
Collapse
Construction accidents & safety
Construction industry
Decision making
Design and construction
Earth Sciences
Engineering
Engineering and Technology
Failure
Fatalities
Forecasts and trends
Fuzzy Logic
Fuzzy sets
Geology
Health risks
Humans
Light rail transit
Medicine and Health Sciences
Methods
Nodes
Physical Sciences
Probability
Property damage
Railroads
Risk
Risk Assessment
Safety and security measures
Safety management
Sensitivity analysis
Social Sciences
Statistical analysis
Structural failures
Structure Collapse
Supervision
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Title Analysis of collapse risks under cut and cover method based on multi-state fuzzy Bayesian network
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