A New Method of Searching Underground Caverns' Safety Factor

Jiang, Quan; Xiang, Tianbing; Su, Guoshao

doi:10.1109/cso.2009.248

Cited by 1 publication

(1 citation statement)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When the strength reduction method is introduced into the numerical methods for stability analysis of tunnels, the resulting safety factor depends significantly on the failure criteria. Currently, three commonly used failure criteria for tunnels are the abrupt displacement criterion [24], the penetration of plastic yield zone criterion [25], and the numerical non-convergence criterion [20], which are the same for slope. In this paper, the abrupt displacement criterion was chosen for the stability analysis of the surrounding rock because of its high accuracy and clear physical significance [24].…”

Section: Strength Reduction Methods and The Failure Criterionmentioning

confidence: 99%

Prediction of the Tunnel Collapse Probability Using SVR-Based Monte Carlo Simulation: A Case Study

Meng

et al. 2023

Sustainability

View full text Add to dashboard Cite

Collapse is one of the most significant geological hazards in mountain tunnel construction, and it is crucial to accurately predict the collapse probability. By introducing the reliability theory, this paper proposes a calculation method for the collapse probability in mountain tunnel construction based on numerical simulation, support vector regression (SVR), and the Monte Carlo (MC) method. Taking the Jinzhupa Tunnel Project in Fujian Province as a case study, three-dimensional models were constructed, and the safety factors of the surrounding rock were determined using the strength reduction method. By defining the shear strength parameters of the surrounding rock as random variables, the problem was formulated as a reliability model, and the safety factor was chosen as the reliability index. To increase computational efficiency, the SVR model was trained to replace numerical simulations, and the MC method was adopted to calculate the probability of collapse. The results showed that the cause of the collapse was the change in the excavation method and the very late installation of supports. The feasibility and reliability of the proposed method have been verified, indicating that the method can be used to predict the probability of collapse in a practical risk assessment of mountain tunnel construction.

show abstract

Section: Strength Reduction Methods and The Failure Criterionmentioning

confidence: 99%

Prediction of the Tunnel Collapse Probability Using SVR-Based Monte Carlo Simulation: A Case Study

Meng

et al. 2023

Sustainability

View full text Add to dashboard Cite

show abstract

A New Method of Searching Underground Caverns' Safety Factor

Cited by 1 publication

References 6 publications

Prediction of the Tunnel Collapse Probability Using SVR-Based Monte Carlo Simulation: A Case Study

Prediction of the Tunnel Collapse Probability Using SVR-Based Monte Carlo Simulation: A Case Study

Contact Info

Product

Resources

About