Estimation of Hoek-Brown Strength Parameters from Time-Dependent Geotechnical Classification as Coal Roof Index (CRI) using Critical Plastic Strain Technique

Abstract

The roof fall or side fall is the most common type of rock failure observed particularly in underground coal mines. The numerical Method is one of the most advanced tools for the prediction of roof rock behaviour. The appropriate failure criteria play an important role in Numerical modelling. In this study, author has adopted Hoek-brown failure criteria for coal galleries using in numerical modelling. Numerical approaches take into account data from various 35 stable and failed cases of Indian coal mines. The Coal Roof Index (CRI) classification is a prime input parameter. The author first derived the range of ‘s’ parameter from the short-term stable cases (stand-up time < 90 days) and then the range of ‘m’ parameter value was refined by long term stable cases (stand-up time > 365 days). The final function of the strength parameter has been précised by consideration of all 35 cases. It has taken each of four different functions from the range of ‘m’, ‘s’, and ‘a’ parameter. Sixty-four function combinations of strength parameters have been simulated and the plastic strain value was obtained. These sixty-four combinations have been carried out based on the feedback mechanism after every combination to optimize the result and change the condition. The best-fitted curve has been established through the back analysis. It has been proposing an exponential relationship with CRI classification to estimate the Hoek-Brown strength parameters m, s, and a. The rock load height (RLH) was also observed through numerical modelling and a relationship was proposed between CRI and rock load height. The correlation coefficient for RLH vs CRI is quite impressive with R2 value of 0.84. The rock load is measured by multiplication of roof rock density and RLH. Thus, an appropriate support resistance can be calculated. The validation has been done by considering 5 Indian coal mine cases among which 2 are stable cases and 3 are unstable cases.