Geotechnical Engineering

Displacement back analysis of rock parameters of Hoek-Brown criterion using nonlinear regression method

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  • 1. College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao, Shandong 266590, China; 2. Shandong Provincial Key Laboratory of Civil Engineering Disaster Prevention and Mitigation, Shandong University of Science and Technology, Qingdao, Shandong 266590, China; 3.Qingdao Institute of Survey and Geomatics, Qingdao, Shandong 266555 China

Received date: 2017-04-21

  Online published: 2018-06-05

Supported by

This work was supported by the National Natural Science Foundation of China (41672291).

Abstract

In the Hoek-Brown criterion, many factors affecting rock failures are considered and the nonlinear failure characteristics can be described more accurately. It is known that the uncertainty of rock parameters seriously affects the application of the criterion. Using the sensitivity analysis and the displacement equation of surrounding rocks, the nonlinear regression method(NLRM) has been proposed for the analysis of the rock parameters of the Hoek-Brown criterion. In developing the above mentioned method, the uniform design and FLAC3D software are used. And we develop a reasonable back analysis method and procedures by leading into the differential evolution. The method is successfully used to analyze the stability of the tunnels in Qingdao metro. Results show that the NLRM can better reflect the relationship between the parameters geological strength index(GSI), agitating coefficient D, Poisson’s ratio and the displacements of tunnels. It can be concluded that the analytical results are very good agreement with the monitoring ones. The proposed method can be used for obtaining the parameters of the Hoek-Brown criterion accurately.

Cite this article

TIAN Mao-lin, XIAO Hong-tian, YAN Qiang-gang, . Displacement back analysis of rock parameters of Hoek-Brown criterion using nonlinear regression method[J]. Rock and Soil Mechanics, 2017 , 38(S1) : 343 -350 . DOI: 10.16285/j.rsm.2017.S1.042

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