## 3 Parameter Design Method of TBM Tunnel ASRBs
### Identification of Potential Rockburst Source Areas in Deeply Buried Hard Rock TBM Tunnels  
When a TBM is tunneling in an area with an intense or extremely intense rockburst risk, the surrounding rock will accumulate a large amount of elastic strain energy [58]. If the accumulated elastic strain energy exceeds the minimum energy storage limit, the excess strain energy will be quickly released, resulting in serious dynamical rupture and even rapid ejection of the rock mass around the tunnel, which is a rockburst [23; 59]. Therefore, when TBM-tunneling into a tunnel section with an intense or extremely intense rockburst risk, it is essential to accurately identify the high-ground-stress and high-elastic-strain-energy-concentration areas and to arrange ASRBs accordingly. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Type**} & \multirow{2}{*}{**Citetion**} & \multirow{2}{*}{**References**} & \multirow{2}{*}{**Assessment Indexes**} & \multicolumn{4}{c}{**Rockburst Grade Assessment Results**} \\  & & & & **None** & **Slight** & **Moderate** & **Intense** \\ \hline \multirow{4}{*}{Single-factor criteria} & [PERSON] criterion [49] & \(\sigma_{c}/\sigma_{t}\) & [14.5,+\(\sigma_{\text{e}}\)) & [5.5,14.5) & [2.5,5.5) & [0.2,5) \\  & [PERSON] criterion [50] & \((\sigma_{t}/\sigma_{t})/\sigma_{t}\) & [0.0,3) & [0.3,0.5) & [0.5,0.8) & [0.8,+\(\infty\)) \\  & [PERSON] criterion [51] & \(\sigma_{t}/\sigma_{t}\) & [0.0,2) & [0.2,0.3) & [0.3,0.5) & [0.5,5,+\(\infty\)) \\  & Strain energy storage index [52] & \(\phi_{tt}/\sigma_{tt}\) & [0.2,0) & - & [2.0,5.0] & [5.0,+\(\infty\)) \\  & Brittleness coefficient [53] & \(\frac{\alpha_{tt}/\sigma_{t}}{\sigma_{tt}}\) & [0.3] & (0.5,0) & [5.0,+\(\infty\)) & - \\ \hline \multirow{2}{*}{Composite-factor criteria} & Rockburst vulnerability index & [54] & \(F_{1}F_{2}F_{3}F_{4}F_{5}\) & - & - & - & - \\  & Excavation vulnerability potential & [55] & \(F_{1}E_{2}E_{3}E_{4}\) & [0.50,0.85) & [50.105] & [105,+\(\infty\)) \\ \hline \multirow{4}{*}{Single-factor criteria} & \multicolumn{4}{c}{Note: \(\sigma_{t}\) is the uniaxial compressive strength of the rock, \(\sigma_{t}\) is the maximum principal stress, \(\sigma_{t}\) is the maximum tangential stress, \(\sigma_{t}\) is the maximum axial stress, \(\phi_{tt}\) is the elastic strain energy (density), \(\phi_{tt}\) is the dissipated energy (density), \(\sigma_{t}\) is the uniaxial tensile strength of the rock, \(\alpha\) is the adjustment parameter, \(\varepsilon_{f}\) and \(\varepsilon_{b}\) are the strain in the pre-peak and post-peak regions under uniaxial compression conditions, \(F_{i}\) is the stress control factor, \(F_{r}\) is the rock biophysical factor, \(F_{m}\) is the rockmass system stiffness, \(F_{g}\) is the geologic structure factor, \(E_{1}\) is the stress condition parameter, \(E_{2}\) is the ground support parameter, \(E_{3}\) is the excavation span parameter, and \(E_{4}\) is the geological structure parameter.} \\ \cline{1-1} \cline{2-5}  & & & & & \\ \end{tabular}
\end{table} 
Table 5: The common theoretical and empirical criteria for rockburst grade assessment [48]. Several suggested methods can be used to identify potential rockburst source areas in TBM tunnels, as shown in Figure 5. The first method is the microseismic (Figure 5a) and acoustic emission (Figure 5b) monitoring method, which collects information on the fracturing damage of the surrounding rock and uses areas of fracture concentration to identify potential rockburst seismic source areas. The second method is the disturbed stress monitoring method (Figure 5c), which infers the location of the potential rockburst seismic source areas by monitoring the change in stress increments at different depths of the surrounding rock.