## 3 Results
### Surrounding Rock Excavatability Classification Based on Rock-Breaking Data
#### 3.1.1 Selection of Surrounding Rock Excavatability Evaluation Indexes
Therefore, the concept of \(BQ\) SRE classification is to explore the intrinsic association between \(BQ\) values and penetration and determine the law between SRE and TBM parameters in order to establish a comprehensive system applicable to TBM tunnels. Using the rock mass classification in constructing KS Tunnel as a benchmark, 10,754 penetration datasets were collected in the stable phase during TBM tunneling, containing a variety of lithologies and five surrounding rock types (Classes II, IIIa, IIIb, IV, and V). In order to expand the data breadth, data were collected at a frequency of 60 Hz, as shown in Table 2. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Class** & **Data Size** & \
\begin{tabular}{c} **Penetration** \\ **Range/(mm/rev)** \\ \end{tabular} & **Mean/(mm/rev)** &
\begin{tabular}{c} **Standard** \\ **Deviation** \\ \end{tabular} \\ \hline II & 2297 & 1.01–8.74 & 3.76 & 1.41 \\ IIIa & 2170 & 2.21–10.89 & 6.65 & 1.44 \\ IIIb & 2085 & 4.01–14.87 & 9.8 & 1.9 \\ IV & 2175 & 6.08–19.49 & 12.58 & 1.84 \\ V & 2027 & 8.43–39.95 & 20.65 & 6.01 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Penetration statistics table of different rock mass classes. Figure 16: Correlation between \(K_{\varphi}\) and \(PR\). Table 2 shows that the distribution of penetration data under different surrounding rock classes was discrete, with significant overlaps between adjacent rock mass classes. In order to improve data representativeness, this paper automatically sorted and determined the final penetration range according to the principle of the highest frequency of the subinterval to which each class belongs. The specific division process is as follows: (1) sorting the data under each rock mass class by the frequency of subintervals using the Pareto chart; (2) determining the threshold at a cumulative frequency of 90% using the cumulative frequency curve; (3) determining the upper and lower limits of the intervals within the cumulative frequency of 90% as the final penetration range of each class. The Pareto chart and cumulative frequency curves of individual surrounding rock classes are shown in Figure 17.  
Figure 17: Penetration Pareto charts of different surrounding rock classifications: (**a**) Class II; (**b**) Class IIIa; (**c**) Class IIIb; (**d**) Class IV; (**e**) Class V.  
For example, Figure 17a shows that the penetration threshold for the cumulative frequency of 90% was (1.75, 2.12), and the upper and lower limits were 1.38 and 5.82, respectively. Therefore, the penetration range for Class II surrounding rock was determined as (1.38, 5.82). In addition, Figure 17 shows that the intervals were continuous after the combination of overlapping subintervals under different surrounding rock classes at a cumulative frequency of 90%. The final penetration ranges under individual classes are shown in Table 3. Table 3 indicates that the penetration ranges under individual classes can be effectively reduced using the above method in order to conform to the actual excavation to the maximum extent. However, Class V surrounding rock had a more discrete penetration distribution than the other four rock types due to fracturing, soft texture, and low integrity. The intrinsic correlation between \(BQ\) values and penetration was investigated to achieve \(BQ\)-based SRE classification. Statistical analyses of penetration and \(BQ\) values were performed using field data and Equation (3) (Figure 18). A fitted equation (R\({}^{2}\) = 0.8325) was derived (Equation (15)). Analysis of variance was used to verify the significance of the model. The calculated significance was 0.000 (\(p\) < 0.01), indicating significant correlations, and the fitted model was accurate  
Table 4 shows that as the SRE grade increases from 1 to 6; i.e., when the \(BQ\) value increases, the corresponding SRE decreases. As the fracturing degree of the surrounding rock decreases, rock hardness gradually increases; thus, the cutter wear is increasingly exacerbated.