Title of article :
Stochastic Stability Analysis of Tunnels Considering Randomness of Rock Mass Properties
Author/Authors :
Mazraehli, Masoud aculty of Mining - Petroleum and Geophysics Engineering - Shahrood University of Technology, Shahrood, Iran , Zare, Shokroallah aculty of Mining - Petroleum and Geophysics Engineering - Shahrood University of Technology, Shahrood, Iran , Idris, Musa Adebayo Division of Mining and Geotechnical Engineering - Luleå University of Technology, Luleå, Sweden
Pages :
19
From page :
1123
To page :
1141
Abstract :
The purpose of this work is to present an approach for the probabilistic stability analysis of tunnels considering the heterogeneity of geo-mechanical properties. A stochastic procedure is followed to account for the variability in the rock mass property characterization. The finite difference method is coupled with the Monte Carlo simulation technique to incorporate the randomness of rock mass properties. Moreover, a particular performance function is defined to investigate the excavation serviceability based on the permissible deformations. In order to validate the analysis, the probabilistic and the deterministic results are compared with the in-situ measurements. It can be observed that in both the probabilistic and deterministic analyses the largest displacements occur in the invert. In contrast, the smallest displacements are recorded in the sidewalls. Utilizing the performance function, the probability of failure for the invert, crown, left, and right wall is estimated as 100%, 68.8%, 16.2%, and 20.9%, respectively. Comparing the measured and calculated convergences, it is conjectured that the deterministic analysis underestimates the displacements, while the measured values are very close to the mean values predicted by the probabilistic analysis. The results obtained indicate that the presented approach could be a reliable technique compared to the conventional deterministic method.
Keywords :
Underground excavations , Probabilistic stability analysis , Rock mass property variability , Finite difference method , Monte Carlo simulation
Journal title :
Journal of Mining and Environment
Serial Year :
2021
Record number :
2704110
Link To Document :
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