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A safety risk assessment method for TBM tunnel construction based on attribute interval identification theory
Bo Wang1,2,3, Qikai Li4, Zefan Xu1
1School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Scientific Reports
|March 5, 2025
Summary
This study introduces a dynamic safety risk evaluation system for Tunnel Boring Machine (TBM) construction, incorporating variable weights and attribute interval theory to manage uncertainties and improve risk assessment accuracy.
Area of Science:
- Civil Engineering
- Risk Management
- Tunneling Technology
Background:
- Tunnel Boring Machine (TBM) construction presents complex safety challenges.
- Existing safety risk evaluations often fail to capture the dynamic nature of these risks.
Purpose of the Study:
- To develop a comprehensive, dynamic safety risk evaluation index system for TBM tunnel construction.
- To address uncertainties inherent in TBM construction risk assessment.
Main Methods:
- Identification and analysis of safety risks specific to TBM tunneling.
- Application of variable weight theory to account for time-varying indicator importance.
- Development of a safety risk evaluation model based on attribute interval recognition theory.
Main Results:
- A TBM tunnel construction safety risk dynamic evaluation index system was established.
- The attribute interval recognition theory-based model effectively handles risk evaluation uncertainties.
- The model determines evaluation levels and attribute intervals for individual and composite attributes.
Conclusions:
- The proposed model provides a robust framework for dynamic safety risk evaluation in TBM construction.
- A case study validated the model's practical applicability and effectiveness in real-world scenarios.
