Reliable stability analysis of surrounding rock for super section tunnel based on digital characteristics of joint information. Issue 1 (1st January 2020)

• Record Type: Journal Article
• Authors: He, Peng; Wang, Gang; Sun, Shangqu; Li, Weiteng; Jiang, Feng; Zheng, Chengcheng
• Is Part Of: Geomatics, natural hazards & risk. Volume 11:Issue 1(2020)
• Page Start: 1528
• Page End: 1541
• Publication Date: 2020-01-01
• Subjects: tunnel engineering -- surrounding rock stability -- discontinuous deformation analysis -- removable blocks -- digital characterization of joint information; Geomatics -- Periodicals; Geomatics; Periodicals; 526.905
• DOI: 10.1080/19475705.2020.1803996
• Languages: English
• ISSNs: 1947-5705

Abstract

Abstract: Since all available surrounding rock classification approaches don't consider the size effect of the tunnel excavation span and unfavourable geologic bodies, it's impossible to evaluate the systematic stability of the surrounding rock by rock mass classification alone. In addition, the evaluation results usually have poor robustness because of the uncertainty of structural information. In this paper, the actual distribution information and probability distribution model of the joints in tunnel face are obtained. Many random numbers that meet the probabilistic distribution models can be produced by Monte carlo simulation, and many random rating values of these evaluation indices are also obtained. The distribution probability affiliated with different rock mass levels can be attained by inductive statistics, and a robust evaluation of surrounding rock classification is carried out. The deformation and failure process of surrounding rock are simulated based on the discontinuous deformation analysis. A comparison analysis of removable blocks and their distribution characteristics is carried out by UJN. The most likely damaged parts and rockfall styles are indicated, and a comparison between calculation result and practical collapse of Laohushan tunnel is carried out, which are nearly the same. The research results offer practical guidance for field construction and supporting optimization.