probabilistic analysis of tunnel face stability below river using bayesian framework

probabilistic analysis of tunnel face stability below river using bayesian framework

;Weiping Liu;Xiaoyan Luo;Jinsong Huang;Lina Hu;Mingfu Fu
journal of power sources 2018 Vol. 2018 pp. -
52
liu2018mathematicalprobabilistic

Abstract

A key issue in assessment on tunnel face stability is a reliable evaluation of required support pressure on the tunnel face and its variations during tunnel excavation. In this paper, a Bayesian framework involving Markov Chain Monte Carlo (MCMC) simulation is implemented to estimate the uncertainties of limit support pressure. The probabilistic analysis for the three-dimensional face stability of tunnel below river is presented. The friction angle and cohesion are considered as random variables. The uncertainties of friction angle and cohesion and their effects on tunnel face stability prediction are evaluated using the Bayesian method. The three-dimensional model of tunnel face stability below river is based on the limit equilibrium theory and is adopted for the probabilistic analysis. The results show that the posterior uncertainty bounds of friction angle and cohesion are much narrower than the prior ones, implying that the reduction of uncertainty in cohesion and friction significantly reduces the uncertainty of limit support pressure. The uncertainty encompassed in strength parameters are greatly reduced by the MCMC simulation. By conducting uncertainty analysis, MCMC simulation exhibits powerful capability for improving the reliability and accuracy of computational time and calculations.

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ID: 195569
Ref Key: liu2018mathematicalprobabilistic
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0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
195569
Unique Identifier:
10.1155/2018/1450683
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Scimatic Chain (ID: 481)
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