| Summary: | Rock mass classification (RMC) is of critical importance in support design and applications to mining, tunneling and other underground excavations. Although a number of techniques are available, there exists an uncertainty in application to complex underground works. In the present work, a generic rock mass rating (GRMR) system is developed. The proposed GRMR system refers to as most commonly used techniques, and two rock load equations are suggested in terms of GRMR, which are based on the fact that whether all the rock parameters considered by the system have an influence or only few of them are influencing. The GRMR method has been validated with the data obtained from three underground coal mines in India. Then, a semi-empirical model is developed for the GRMR method using artificial neural network (ANN), and it is validated by a comparative analysis of ANN model results with that by analytical GRMR method.
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