COMPARATIVE ANALYSIS OF ROCK CLASSIFICATION SYSTEMS

Abstract

During the feasibility and preliminary design stages of a project, when very little detailed information is available on the rock mass and its stress and hydrologic characteristics, the use of a rock mass classification scheme can be of considerable benefit. At its simplest, this may involve using the classification scheme as a check-list to ensure that all relevant information has been considered. At the other end of the spectrum, one or more rock mass classification schemes can be used to build up a picture of the composition and characteristics of a rock mass to provide initial estimates of support requirements, and to provide estimates of the strength and deformation properties of the rock mass. This research comprises the comparison of three most commonly used rock mass classification system i.e. RMR (Rock Mass Rating), Q System (Rock Mass Quality) and GSI (Geological Strength Index) using geological data from Daimer Bhasha Dam & Gulpur Hydropower Project study. The main objective of rock mass classifications carried out in this study was to obtain adequate data to develop a correlation between all three systems that could be used in future excavation and support-design studies. In order to accomplish this task, literature survey was carried out, followed by a comprehensive collection of field data. Field studies involved detailed discontinuity surveys of the exposed rock mass at the surface and on the cores taken at various depths. Finally correlations were obtained between all three classification systems with the use of statistical analysis. The results indicate a strong relationship between RMR & Q, GSI & RMR and GSI & Q. It was observed that Q-system seems to be more adequate for describing deformation zones and fractured zones in weak rocks. Furthermore, existing correlations i.e. Bieniewski (1976), Tugrul (1998), Rutledge & Preston(1978), Cameron-Clark & Budavari (1981), Moreno (1981) Milne (1998) & Hoek (1995) 7 were compared to develop the best correlation that would be acceptable in these conditions. Tugrul (1998) correlation gives the best estimate of field values for RMR when Q ratings are available. While Milne (1998) correlation best estimates the field value for GSI when RMR ratings are available.