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Dynamic risk evaluation method for collapse disasters of drill-and-blast tunnels: a case study
Bo Wu1,2,3, Weixing Qiu1, Wei Huang1
1College of Civil Engineering and Architecture, Guangxi University, 100 University Road, Nanning, Guangxi 530004, China.
Mathematical Biosciences and Engineering : MBE
|December 14, 2021
Summary
A new dynamic risk assessment method combines Cloud model (CM) and Bayesian network (BN) to predict tunnel collapse probability. This approach provides real-time guidance for safer highway rock tunnel construction.
Area of Science:
- Geological Engineering
- Risk Management
- Civil Engineering
Background:
- Tunnel collapse is a frequent and hazardous geological event in highway rock tunnel construction.
- Accurate risk assessment is crucial for mitigating tunnel collapse and ensuring construction safety.
Purpose of the Study:
- To establish a novel dynamic risk assessment methodology for tunnel collapse.
- To provide real-time guidance for on-site highway rock tunnel construction.
Main Methods:
- A new dynamic risk assessment methodology was developed, integrating the Cloud model (CM) and Bayesian network (BN).
- Tunnel collapse risk factors were identified, and an index system was constructed.
- The methodology was applied to evaluate the probability of tunnel collapse risk during construction.
Main Results:
- The dynamic evaluation model was validated through a case study of the Yutangxi tunnel.
- The risk value of tunnel collapse within a construction cycle was successfully predicted.
- The method provided effective guidance for on-site construction, reducing the occurrence of tunnel collapse.
Conclusions:
- The proposed dynamic risk assessment method is feasible and demonstrates significant application potential.
- The integration of CM and BN offers a robust approach for real-time tunnel collapse risk management.
- This methodology can enhance safety and efficiency in highway rock tunnel construction.
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