Quantitative assessments of the correlations between rock mass rating (RMR) and geological strength index (GSI)

• Published in: Tunnelling and underground space technology 2019-01, Vol.83, p.73-81
• Main Authors: Zhang, Qi, Huang, Xianbin, Zhu, Hehua, Li, Jianchun
• Format: Article
• Language: English
• Subjects: Assessments; Basic classified indices; Classification; Compressive strength; Computer simulation; Construction; Correlation analysis; Geological strength index; Geology; Monte Carlo simulation; Monte Carlo simulation method; Quantitative correlation; Rock mass rating; Rock properties; Rocks; Statistical analysis; Statistical methods; Tunnel construction; Tunnels
• ISSN: 0886-7798; 1878-4364
• DOI: 10.1016/j.tust.2018.09.015

Among various engineering classification systems, RMR and GSI are two of the most widely used rock mass classification systems. Correlation between RMR and GSI can provide an alternative approach to determine one from the other. Based on the latest improved RMR, known as RMR14, the quantitative assessments of the correlations between RMR and GSI is conducted systematically based on the studies on the correlations of basic classified indices, which are mainly related to the structural conditions of rock mass. 260 groups of field investigating results obtained directly from the tunnel excavation faces of six new construction tunnels are collected to assess the quantitative correlations of the basic classified indices for the rock mass integrity condition and the surface condition of discontinuities, respectively. Monte Carlo simulation method is employed to generate sufficient samples based on the statistical characteristics of the collected 260 group results, and a simplified quantitative correlation between RMR and GSI is proposed statistically. Then, an expression merely related to the uniaxial compressive strength of rock is derived to reflect the basic classified indices for the strength and alterability of intact rock. A comprehensive quantitative correlation combined with the intact rock properties is suggested. Finally, the two proposed quantitative correlations between RMR and GSI are applied to evaluate 36 sites of the surrounding rock mass of Suocaopo Tunnel in Guizhou Province, China. The validated results show that the proposed simplified quantitative correlation shows a rather good performance to reflect the correlation of RMR and GSI. Moreover, the comprehensive quantitative correlation is more accurate because that the intact rock properties are considered merely with the uniaxial compressive strength.