Development of correlations between various engineering rockmass classification systems using railway tunnel data in Garhwal Himalaya, India

Abstract

Abstract Rockmass classifications are an integral part of engineering design and excavation procedures of tunnels and other underground structures. These classifications are directly linked to ground reaction and support requirements, and various classification systems are widely used across the globe. However, as different classifications serve different purposes, it is imperative to establish inter-correlatability between them. Despite the availability of numerous rock mass classifications, there are still gaps in understanding the behavior of rock masses, particularly in complex rockmass conditions. The aim of this study is to bridge this gap by establishing an engineering classification for metamorphic rocks in the Himalayan region. Data from 34 locations along a 618-meter-long railway tunnel in the Garhwal Himalaya of India were collected to evaluate rockmass classes in an adit. Using this data, existing classification systems were reviewed, and new correlations were developed between different rock classifications. The study primarily focuses on local rockmass conditions and examines Rock Mass Rating (RMR), Q-system (Q), Rock Mass Number (Qn), Rock Condition Rating (RCR), Rock Mass Index (RMi), Rock Structure Rating (RSR), and Geological Strength Index (GSI). Our analysis indicates that certain correlations, such as RMR-Q, RMR-RMi, RMi-Q, and RSR-Q, are comparable to those previously established, while others, such as RSR-RMR, RCR-Qn, and GSI-RMR, show weak correlations. These deviations in published correlations may be due to individual parameters of estimation or measurement errors. Furthermore, we found that incompatible classification systems exhibit low correlations. Our study highlights the need to revisit existing correlations, particularly for rockmass conditions that are extremely complex, and the predictability of existing correlations exhibit high variations. In conclusion, our study contributes to a better understanding of rockmass classifications and provides a more comprehensive engineering classification of metamorphic rocks in the Himalayan region. By establishing new correlations between existing classification systems, this study can serve as a guide for future rock engineering projects and aid in developing appropriate excavation techniques.