Probabilistic analysis of tunnel displacements based on correlative recognition of rock mass parameters

doi:10.1016/j.gsf.2020.12.015

	Probabilistic analysis of tunnel displacements based on correlative recognition of rock mass parameters
	Zheng, Minzong 1,2; Li, Shaojun 1; Zhao, Hongbo 3; Huang, Xiang 1,2; Qiu, Shili 1
刊名	GEOSCIENCE FRONTIERS
	2021-07-01
卷号	12 期号:4 页码:15
关键词	Uncertainties Correlation Displacement Multivariate distributions Relevance vector machine
ISSN号	1674-9871
DOI	10.1016/j.gsf.2020.12.015
英文摘要	Displacement is vital in the evaluations of tunnel excavation processes, as well as in determining the post-excavation stability of surrounding rock masses. The prediction of tunnel displacement is a complex problem because of the uncertainties of rock mass properties. Meanwhile, the variation and the correlation relationship of geotechnical material properties have been gradually recognized by researchers in recent years. In this paper, a novel probabilistic method is proposed to estimate the uncertainties of rock mass properties and tunnel displacement, which integrated multivariate distribution function and a relevance vectormachine (RVM). The multivariate distribution function is used to establish the probability model of related random variables. RVM is coupled with the numerical simulation methods to construct the nonlinear relationship between tunnel displacements and rock mass parameters, which avoided a large number of numerical simulations. Also, the residual rock mass parameters are taken into account to reflect the brittleness of deeply buried rock mass. Then, based on the proposed method, the uncertainty of displacement in a deep tunnel of CJPL-II laboratory are analyzed and compared with the in-situ measurements. It is found that the predicted tunnel displacements by the RVM model closely match with the measured ones. The correlations of parameters have significant impacts on the uncertainty results. The uncertainty of tunnel displacement decreases while the reliability of the tunnel increases with the increases of the negative correlations among rock mass parameters. When compared to the deterministic method, the proposed approach is more rational and scientific, and also conformed to rock engineering practices. (C) 2021 China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V.
资助项目	National Natural Science Foundation of China[U1765206] ; National Natural Science Foundation of China[51621006] ; National Natural Science Foundation of China[41877256] ; Innovation Research Group Project of Natural Science Foundation of Hubei Province[ZRQT2020000114]
WOS研究方向	Geology
语种	英语
出版者	CHINA UNIV GEOSCIENCES, BEIJING
WOS记录号	WOS:000654356800008
内容类型	期刊论文
源URL	[http://119.78.100.198/handle/2S6PX9GI/27465]
专题	中科院武汉岩土力学所
作者单位	1.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Hubei, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Shandong Univ Technol, Sch Civil & Architectural Engn, Zibo 255000, Shandong, Peoples R China
推荐引用方式 GB/T 7714	Zheng, Minzong,Li, Shaojun,Zhao, Hongbo,et al. Probabilistic analysis of tunnel displacements based on correlative recognition of rock mass parameters[J]. GEOSCIENCE FRONTIERS,2021,12(4):15.
APA	Zheng, Minzong,Li, Shaojun,Zhao, Hongbo,Huang, Xiang,&Qiu, Shili.(2021).Probabilistic analysis of tunnel displacements based on correlative recognition of rock mass parameters.GEOSCIENCE FRONTIERS,12(4),15.
MLA	Zheng, Minzong,et al."Probabilistic analysis of tunnel displacements based on correlative recognition of rock mass parameters".GEOSCIENCE FRONTIERS 12.4(2021):15.