Risk evaluation of metro tunnel shield construction based on game variable weight extension cloud theory

To address the issues of fuzziness and randomness in risk evaluation for subway shield construction, this study proposes a risk assessment model integrating variable weight theory and an extension cloud model to enable a more scientific and effective evaluation. Firstly, the WBS-RBS (Work Breakdown Structure-Risk Breakdown Structure) method was employed to establish a risk evaluation index system for metro tunnel construction, with risk levels classified into Grades I-V. Secondly, the ordinal relationship method (G1) and entropy weight method were applied to calculate the fixed weights of the evaluation indexes. The comprehensive fixed weights are determined based on the game theory, considering the dynamic changes of the evaluation indexes, and the optimal dynamic, comprehensive weights are calculated based on this combined with the variable weight theory. Finally, comprehensive affiliation degrees were obtained through the extension cloud model, and the comprehensive evaluation grade was determined according to the principle of maximum affiliation. The model was applied to the submarine tunnel section of Qingdao Metro Line 8. The results indicate that the risk level of the project is Grade III, which aligns with the actual construction conditions. This consistency validates the rationality and feasibility of the proposed method, offering a novel approach to guide safety management and risk decision-making in metro tunnel construction projects.

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Publication Details

Journal
Scientific Reports
Published
2025-05-30
DOI
https://doi.org/10.1038/s41598-025-03345-5
Citations
3
Primary Topic
Advanced Decision-Making Techniques
Type
article
Field-Weighted Citation Impact
9.74

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article

Risk evaluation of metro tunnel shield construction based on game variable weight extension cloud theory

Dun Wu, Lirong Wu, Xiuxia Sun
3 citations
Scientific Reports
Advanced Decision-Making Techniques
9.74
article

Risk evaluation of metro tunnel shield construction based on game variable weight extension cloud theory

Dun Wu, Lirong Wu, Xiuxia Sun
article en
3 citations

Abstract

To address the issues of fuzziness and randomness in risk evaluation for subway shield construction, this study proposes a risk assessment model integrating variable weight theory and an extension cloud model to enable a more scientific and effective evaluation. Firstly, the WBS-RBS (Work Breakdown Structure-Risk Breakdown Structure) method was employed to establish a risk evaluation index system for metro tunnel construction, with risk levels classified into Grades I-V. Secondly, the ordinal relationship method (G1) and entropy weight method were applied to calculate the fixed weights of the evaluation indexes. The comprehensive fixed weights are determined based on the game theory, considering the dynamic changes of the evaluation indexes, and the optimal dynamic, comprehensive weights are calculated based on this combined with the variable weight theory. Finally, comprehensive affiliation degrees were obtained through the extension cloud model, and the comprehensive evaluation grade was determined according to the principle of maximum affiliation. The model was applied to the submarine tunnel section of Qingdao Metro Line 8. The results indicate that the risk level of the project is Grade III, which aligns with the actual construction conditions. This consistency validates the rationality and feasibility of the proposed method, offering a novel approach to guide safety management and risk decision-making in metro tunnel construction projects.

Scientific ReportsVol. 15(1)
Anhui Jianzhu University (CN), Shandong University of Science and Technology (CN)
Shandong University, National Natural Science Foundation of China, Henan Polytechnic University, Shandong University of Science and Technology, State Key Laboratory of Coal Resources and Safe Mining, State Key Laboratory Cultivation Base for Gas Geology and Gas Control
Sustainable cities and communities
Openalex Percentile: Top 2%
Advanced Decision-Making Techniques
9.74
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