## 4 Discussion
The comparison of the joint condition parameters is summarized in Table 2. The additional parameter in the \(RMR_{b}\) (for \(RMR_{14}\)) calculation is the intact rock alterability parameter, which is related to shales and similar weak rocks [33]. For strong rocks, the rating for intact rock alterability is 10 as per \(RMR_{14}\) suggestions. Minimum values for \(F_{e}\) and \(F_{s}\) are 1 and maximum values are 1.32 and 1.3, respectively [7]. Taking into consideration the structure of the two versions of \(RMR\) (\(RMR_{89}\) and \(RMR_{14}\)) and characterization criteria leads to the conclusion that \(RMR_{14}>RMR_{89}\). The literature also supports the notion that \(RMR_{14}\) values are higher than \(RMR_{89}\)[7; 49]. A similar trend can be seen in Figure 8.  
Currently, in the two systems, rock bolt spacing and shotcrete thickness depend on the same principle. The back analysis approach for rock mass quality determination is introduced and explained through an example in this manuscript. This approach can be a valuable tool for the evaluation the parameters in these systems. The linear and truncated correlations between \(RMR\) and \(Q\) systems are assessed based on published data and data of Projects 1 and 2. For the use of an empirical classification system for tunnel support design, at least two systems should be used and they should be checked through correlation as suggested [2]. Because the \(RMR\) and \(Q\) systems have different structures and are based on different experiences, some of their parameters and rating procedures for each parameter are different, and there is no scientific basis to correlate them directly--a conclusion that has been evaluated through published data. The rock mass fabric index approach [19] is a truncated version of \(RMR_{89}\) and \(Q\) systems and shows comparatively better results for correlation. In this correlation approach, only the rock structure and joint condition parameters are taken into account. Moreover, the traditional method of correlation is replaced by introducing a rock mass fabric index chart, which is similar in structure to the geological strength index (GSI) chart [50]. The \(RMR\) and \(Q\) correlation results using preliminary support design is also unsatisfactory. The difference between the two rock mass qualities (calculated \(Q\) and back calculated \(Q\)) exists because of their having different parameters and ratings and the crude correlation between the rock mass quality index and rock bolt spacing [9], which was also highlighted by [PERSON] [40]. Another reason for this is that the two systems are based on different experiences and different methods of calculating the rock mass quality. Comparing the ratings for groundwater of the two systems, the suggested rating for groundwater (based on the general condition) in \(RMR_{89}\) is 15 for completely dry, 10 for damp, 7 for wet, 4 for dripping, and 0 for flowing conditions, whereas the \(Q\) system suggests \(J_{w}=1\) from the dry to minor flow conditions. Different scenarios yield different results. Furthermore, in the suggested shotcrete thickness for a given tunnel span, the contribution of the rock mass quality to shotcrete thickness is not the same in the support charts of the two system. This is explained in Example 2. Example 2:  
Tunnel span or D\({}_{\text{e}}\) (ESR = 1) = 20 m, Shotcrete thickness = 15 cm  
Contribution of rock mass quality for shotcrete thickness in \(Q\) system = 50%  
Contribution of rock mass quality for shotcrete thickness in \(RMR\) system = 64.4%