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Updating the models and uncertainty of mechanical parameters for rock tunnels using Bayesian inference

Geoscience Frontiers 2021年第5期12卷 224-236页

作者： Hongbo Zhao Bingrui Chen Shaojun Li Zhen Li Changxing Zhu School of Civil and Architectural engineering Shandong University of TechnologyZibo 255000ShandongChina State Key Laboratory of Geomechanics and Geotechnical engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan 430071HubeiChina School of Civil engineering Henan Polytechnic UniversityJiaozuo 454003China

rock mechanical parameters and their uncertainties are critical to rock stability analysis,engineering design,and safe construction in rock mechanics and *** back analysis is widely adopted in rock engineering to determine the mechanical parameters of the surrounding rock mass,but this does not consider the *** problem is addressed here by the proposed approach by developing a system of Bayesian inferences for updating mechanical parameters and their statistical properties using monitored field data,then integrating the monitored data,prior knowledge of geotechnical parameters,and a mechanical model of a rock tunnel using Markov chain Monte Carlo(MCMC)*** proposed approach is illustrated by a circular tunnel with an analytical solution,which was then applied to an experimental tunnel in Goupitan Hydropower Station,*** mechanical properties and strength parameters of the surrounding rock mass were modeled as random *** displacement was predicted with the aid of the parameters updated by Bayesian inferences and agreed closely with monitored *** indicates that Bayesian inferences combined the monitored data into the tunnel model to update its parameters *** study indicated that the performance of Bayesian inferences is improved greatly by regularly supplementing field monitoring *** inference is a significant and new approach for determining the mechanical parameters of the surrounding rock mass in a tunnel model and contributes to safe construction in rock engineering.

关键词： rock tunnel engineering Back analysis Bayesian inference Uncertainty analysis Markov chain Monte Carlo simulation

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