Topic > Geomechanical classification (Rock Mass Rating-RMR)

The geomechanical classification (Rock Mass Rating - RMR) is the most used classification of rock masses provided by ZTBieniawski between 1972 and 1973. It is based on six parameters of which five they are universal and the sixth is used specifically for different applications. Predicting the RMR using fuzzy logic makes it easier to predict the rock rating to be roughly the same as that calculated from the experimental data. It becomes of great importance when we do not have the evaluation tables of the six parameters, so by using fuzzy membership functions, we can approximately predict the RMR of the rock. Introduction While working in the fields, it is impossible to predict the RMR simply by observing the experimental data provided, as this involves many preliminary experiments on rock samples. Therefore, using the membership functions, we can easily get an idea of ​​the quality of the rock which will give more or less the same value that we would have obtained from the experimental data. The Bieniawski geomechanical classification system provides a general rock mass rating (RMR) increasing with rock quality from 0 to 100. The five universal parameters are: rock strength, core quality, groundwater conditions, rock spacing joints and fractures and joint characteristics. The sixth parameter, joint orientation, is entered differently for specific applications in tunnels, mines and foundations. The rock mass rating increments corresponding to each parameter are summed to determine the RMR. Tables 1 to 5 show the experimental data of the universal parameters. Table 6: Geomechanical classification of rock masses Table 1: Ratio of rock mass...... center of paper...... (∑ Wi * Xi) / (∑ Wi) (1) With the formula given above , we can easily calculate the membership degree of the RMR. So, XRMR = (0.8 * 3 + 0.9 * 4 + 0.1 * 2 + 0.7 * 5 + 0.5 * 1) / (3+4+2+5+1) = 0, 68corresponding to 0.68 degree of membership in RMR figure 6, we approximately obtain that the value of RMR is between 65 and 70, which represents good rock quality. Result Fuzzy logic gives approximately the same result as you would get from the real experiment or experimental results. Conclusion Fuzzy logic is designed to solve problems the same way humans do: by considering all available information and making the best possible decision given the input. The Bieniawski rock mass classification incorporates geological, geometric and design/engineering parameters in arriving at a quantitative value of the quality of the rock mass.