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<p>Based on the identification and analysis of safety risks in TBM tunnel construction, we construct a comprehensive safety risk dynamic evaluation index system tailored to this context. To account for the dynamic nature of safety risks during TBM tunnel construction, variable weight theory is incorporated, allowing for a more accurate reflection of the time-varying importance of risk indicators. Building on the theoretical framework of attribute interval recognition theory, we establish a TBM tunnel construction safety risk evaluation model grounded in attribute interval theory. This model effectively addresses the various uncertainties inherent in the risk evaluation process for TBM tunnel construction. It determines the evaluation level and attribute intervals for each individual indicator, and subsequently calculates the interval values for both the individual indicators and the composite attribute. Finally, a case study demonstrates the model’s effectiveness and practical applicability.</p>

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A safety risk assessment method for TBM tunnel construction based on attribute interval identification theory

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年3月5日

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  • Bo Wang,
  • Qikai Li,
  • Zefan Xu,
  • Shibin Niu,
  • Xiangtian Nie

摘要

Based on the identification and analysis of safety risks in TBM tunnel construction, we construct a comprehensive safety risk dynamic evaluation index system tailored to this context. To account for the dynamic nature of safety risks during TBM tunnel construction, variable weight theory is incorporated, allowing for a more accurate reflection of the time-varying importance of risk indicators. Building on the theoretical framework of attribute interval recognition theory, we establish a TBM tunnel construction safety risk evaluation model grounded in attribute interval theory. This model effectively addresses the various uncertainties inherent in the risk evaluation process for TBM tunnel construction. It determines the evaluation level and attribute intervals for each individual indicator, and subsequently calculates the interval values for both the individual indicators and the composite attribute. Finally, a case study demonstrates the model’s effectiveness and practical applicability.