## 3 Applying the Methodology to the Example of Dabar Power Tunnel
### Quantitative Analysis
#### 3.3.2 Statistical Analysis  
A total of 1601 pieces of data on the analysed length of the tunnel were processed, so that the corresponding dependencies between all relevant parameters could be assessed. Figure 9(a) shows the variation in RMR along the analysed section of the tunnel. It can be seen that the largest proportion of RMR scores falls in the range of 60 to 80. The general trend of RMR values, indicated by a straight line showing the average values (red line in Figure 9(a)), is a slight decrease, but they are always between 60 and 70. Figure 9(b) shows the overbreaks in square meters (per meter of tunnel length) along the analysed tunnel sections. It can be seen that the majority of overbreaks are within the range of 0-5.0 m\({}^{2}\), with an average size of 2.5 m\({}^{2}\). Figure 11a shows the dependence of overbreak excavation on RMR values for all analysed data. It can be seen from the figure that with increased RMR value, the overbreak area decreases, which is the expected general trend. Figure 11b shows the dependence of overbreak excavation on RMR values for data in which geological overbreaks undoubtedly occurred and were duly mapped and geodetically surveyed in detail. The decrease in overbreaks with increased RMR shown in Figure 11 can be represented by a logarithmic function (evaluated using the linear least squares regression tool in MS Excel). The logarithmic function has an advantage over other functions (e.g., linear or exponential) due to the highest obtained value of determination coefficient (R\({}^{2}\)). Even though the indicative correlation between the two variables can be considered relatively low (R\({}^{2}\) = 0.301 for overbreaks overall and R\({}^{2}\) = 0.53 for geological overbreaks), it is assumed to be in fair agreement considering the similarity in shape of both lines, the complexities related to the geological nature of the problem, and the necessary simplifications introduced during the engineering-geological data collection. A similar trend line, seen in Figure 11a,b, indicates that the majority of overbreaks must have had a geological cause, which is reflected in the direct interconnectedness with RMR values on the two diagrams. Figure 10: **(a)** RMR values along tunnel section; **(b)** overbreaks along tunnel, per meter length. Figure 12 shows histograms of the frequency of overbreaks in the analysed section of the tunnel comprising the following intervals: 0-2.5, 2.5-5.0, 5.0-7.5, 7.5-10.0, 10.0-12.5, 12.5-15.0, 15.0-17.5, 17.5-20.0, 20.0-22.5, and 22.5-25.0 m\({}^{2}\). It can be seen from Figure 12a that the highest frequency of occurrence of overbreaks is within the interval of 0-2.5 m\({}^{2}\) (910 out of 1601 pieces of analysed data), followed by the frequency of occurrence of overbreaks within the range of 2.5-5.0 m\({}^{2}\) (518 out of 1601 pieces of data). Figure 12b shows a histogram (for the same interval ranges as in Figure 12a) for 72 recorded geological overbreaks. Here, the largest number of overbreaks is in the interval of 2.5-5.0 m\({}^{2}\), followed by 0-2.5 m\({}^{2}\). Figure 11: Measured overbreaks (m\({}^{2}\)) depending on RMR value for (**a**) all analysed data (1601 pieces of data) and (**b**) data for which geological overbreaks were confirmed by mapping (72 pieces of data). The main findings and the interpretation of the statistical analysis can be summarised as follows:  
1. Generally, from Figure 10a, it can be concluded that the geology is predominantly uniform, without significant deviations in the quality of the rock mass. Along the analysed tunnel section, the RMR value is in the range of 60 to 80, with an average of 65. 2. The largest proportion of overbreaks per meter length falls in the range of 0-5.0 m\({}^{2}\) (Figure 11a). 3. Undoubtedly, the geological overbreaks that were geodetically surveyed in detail have the same general decreasing trend with increasing RMR value as the overbreaks in general (Figure 11a,b).