Mahdizadeh Mahdi, Hosseini Navid, Afzal Peyman, Kaveh-Ahangaran Dariush, Yasrebi Amir-Bijan
22nd UK Conference of the Association for Computational Mechanics in Engineering, University of Exeter, Exeter, UK
Publication year: 2014

It is very important to have a comprehensive recognition of rocks on the way in designing underground spaces because this highly affects the determination of support system. Rock rating system is known as one of the ways of rocks analysis such as Q and RMR. However, RMR rating system is more common in mining studies. In this system, different parameters are applied and then each part of a rock mass is scored and finally the intended support system needed for the tunnel is suggested. The parameters entering to RMR are classified into two groups of quantitative and qualitative ones and are placed in one specific classification accordingly. Since quantitative parameters are not fixed yet, it is hard to determine an exact threshold between the classifications and devote a specific amount to one certain group. To solve this problem, membership functions can be defined for each one of the quantative parameters and the output point of every parameter can be figured out by fuzzy sets. Fuzzy inference system calculated the points related to the quantitative parameters and other parameters are classified based on quality and they are scored in the normal way. Ultimately, the amount of RMR is obtained from adding the points of every one of the parameters. The current essay evaluates the final results of the semi-fuzzy method due to the support system in every part of the mine which is sampled. These studies demonstrate that the semi-fuzzy method is well able to determine the support system required for mining tunnels.