Abstract
Rock mass classifications aim to provide a qualitative evaluation of the rock mass for the preliminary design of structures in rocks. The support system based on the rock mass classification has been applied to a variety of applications such as tunnels, powerhouses, and crude oil storage in Pakistan, and around the world. Bieniawski’s Rock Mass Rating (RMR), Barton’s Q System and Hoek and Brown Geological Strength Index (GSI) are the most widely known rock mass classification system and efforts have been made by various researchers around the world to develop correlations between them, the lesser-known systems Rock Condition Rating (RCR) and Rock Mass Number (QN) were also checked for its use in the construction industry since these systems omit some parameters used during field investigation. This research is an attempt to develop a correlation between RMR, GSI, and Q System of Rock mass classifications on a statistical approach using 240 data points recorded through a geological logs of exploratory drifts and tunnel logs during excavation for the Gulpur Hydropower Project, Pakistan. The correlations presented in this research were developed using various statistical approaches (i.e., linear, logarithmic, power, exponential, and polynomial) to develop correlation which not only allows us to compare the results of various statistical approaches but also tells us which approach gives the best results for correlation between two rock mass classification systems.