## 3 Results
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Parameter**} & \multicolumn{2}{c}{**Rating**} \\ \cline{2-3}  & **Project 1** & **Project 2** \\ \hline Joint frequency (joints/m) & 10.66–32.56 & 6.51–30.33 \\ UCS (MPa) & 4.042–6.95 & 4.245–8.73 \\ Ground Water & 0–15 & 0–15 \\ \(F_{0}\) & \(-12\) to \(-2\) & \(-12\) to 0 \\ \(F_{e}\) & 1 & 1 \\ \(F_{s}\) & 1.186–1.296 & 1.22–1.3 \\ Persistence (m) & 2 & 2 \\ Roughness & 3 & 2 \\ Infilling (mm) & 5 & 2 and 5 \\ Weathering & 4 & 3, 4 and 5 \\ Alterability (\%) & 10 & 10 \\ \(RMR_{\text{Basic}}\) & 55.49–78.51 & 32.88–72.55 \\ \(RMR_{\text{Adjusted}}\) & 56.33–88.5 & 41.37–84.63 \\ \(\text{Min.}-\text{Max}\) (st. dev) & \(\frac{56.33-88.5}{79.188}\) (7.52) & \(\frac{42.74-84.63}{67.086}\) (9.387) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: \(RMR_{14}\) rating for Projects 1–2. Figure 6: Details of (**a**) joint frequency rating; (**b**) \(RMR_{14}\). Section 2.5 discussed the assessment of the characterization and classification of the tunneling quality index system. The characterization criteria have remained the same since its development, except for the inclusion of the intact rock strength in the form of a normalized factor in the structure of the \(Q\) system equation and the revised rating for \(SRF\) in a high stress--strength ratio environment. The basic suggestion of the creators of the system to use an interval of 5 in \(RQD\) rating is activated because this suggestion in calculating the value of \(Q\) is generally ignored in literature. Furthermore, for tunnel support design, both \(RMR\) and \(Q\) systems have been refined and revised, either in the form of characterization, support, or both. Currently, the rock bolt spacing is regarded as a function of the rock mass quality, and the shotcrete thickness, along with rock mass quality, is a function of the tunnel span. A back calculation approach for rock mass quality determination is proposed, as shown in Figure 1 and explained in Example 1. Figure 8: Linear correlation between \(RMR_{89}\) and \(RMR_{14}\). Figure 7: Difference in \(RMR_{14}\) and \(RMR\)* in term of percentage frequency. Also, the results of correlations between \(RMR\) and \(Q\) systems are shown in Figures 9-11. A linear correlation in Figure 9 shows that the data are considerably scattered and predictions from the correlation may lead to erroneous results. Logically, therefore, a good correlation can only emerge if the joint orientation and intact rock strength are ignored in the \(RMR\) system or included to the \(Q\) system, and the stress condition is ignored in the \(Q\) system. After applying this approach on the data of Projects 1-2, results shown in Figure 10 are also scattered and have a low correlation coefficient. The rock mass fabric index approach is also used. The predicted \(RMR_{89}\) was correlated with the calculated \(RMR_{89}\), as shown in Figure 11. The calculated \(RMR_{89}\) is based on suggested equations of the continuous rating. The results show that the predicted \(RMR_{89}\) is higher than that calculated, which is because of the high value of the predicted \(F_{RMR}\) from \(F_{Q}\). However, the rock mass fabric index approach yields comparatively better results than former approaches do and have a high correlation coefficient. Figure 10: Linear correlation between \(N\) and \(RMR_{\mathrm{mod}}\) based on the data of Project 1–2. Figure 9: Linear correlation between \(Q\) and \(RMR_{89}\) based on the published data of Table 3.  
Because the rock bolt spacing and shotcrete thickness are based on the same principal in both systems, a correlating bridge between them has been developed, based on the summarized published data in Table 3. However, this did not yield any satisfactory results, as listed in Table 7, because the development of the two systems are based on different approaches. Moreover, support charts of \(RMR\) and \(Q\) system indicate that rock mass quality and tunnel span are contributing different contribution for supports.