## 5 Analysis and Discussion of Numerical Simulation Results
### Analysis of Rockburst Risk Assessment for the Deep-Buried Roadway Crossing Stratigraphic Boundary  
Rockburst is a sudden geological disaster influenced by multiple factors and characterized by randomness and complexity. First, evaluating the risk of rockburst requires assessing the rockburst potential, i.e., the internal causes of rockburst occurrence. Rockburst potential is defined as the tendency and intensity of a rock to experience rockburst under specific geological and mechanical conditions [28]. To quantitatively evaluate rockburst potential, brittleness and energy indexes were introduced in the previous section to assess the intrinsic properties of rocks that tend to induce rockburst under certain conditions, based on an understanding of their mechanical behavior. However, rocks with high rockburst potential are still subject to external factors in the field, and predicting rockburst in engineering practice solely based on potential evaluation is inappropriate. With the long-term development of geo-stress measurement and numerical simulation technologies, many researchers have achieved qualitative and quantitative predictions of the location and intensity of rockburst by combining numerical simulation and field measurement [8]. Rockburst is mainly due to variations in geo-stress caused by deep rock excavation, so many researchers have proposed numerical evaluation indexes of rockburst risk through the relationship between the stress environment and rock strength, and the main forms are \(\sigma_{0}/\sigma_{c}\) ([PERSON] criterion), \(\sigma_{c}/\sigma_{1}\) ([PERSON] criterion), \((\sigma_{0}+\sigma_{1})/\sigma_{c}\) ([PERSON] criterion) and their similar expressions [9; 10]. These indexes reflect that a corresponding rockburst level is likely to occur when the applied stress approaches or exceeds the rock strength threshold. While some expressions are structurally similar, their threshold values for predicting different levels of rockburst may vary. This variation is primarily because the  
Figure 15: Radar map of surrounding rock displacement distribution at different monitoring sections (unit: mm). critical values of these indexes are often derived from empirical data in specific engineering contexts or industries [9]. Therefore, appropriate calibration is necessary for practical engineering applications, based on actual rockburst cases observed on site. [PERSON] et al. considered the effect of deviatoric stress and proposed the Brittle Shear Rate (BSR) index to evaluate the rockburst risk [26]; the expression of BSR is shown in (12). [PERSON] et al. [35] based their calculation on the BSR to evaluate the effect of large-scale destress blasting on the release effect of the mining area. \[BSR=\frac{\sigma_{1}-\sigma_{3}}{\sigma_{c}}= \begin{cases}>\!0.7&\text{Serious }\text{ Rockburst}\\ 0.6\!\sim\!\!0.7&\text{Moderate }\text{ Rockburst}\\ 0.45\!\sim\!\!0.6&\text{Light }\text{ Rockburst}\\ 0.35\!\sim\!\!0.45&\text{No }\text{ Rockburst}\end{cases}  \tag{12}\]  
Evaluate the applicability of rockburst risk indexes and their value ranges of values based on those proposed by many scholars through the stress-intensity relationship. In the rockburst risk assessment of the Huize lead-zinc mine, it was found that the Barton criterion significantly overestimates the likelihood of rockburst occurrence at the site. The Russenes criterion, which is expressed in terms of tangential and radial stresses in the surrounding rock, is difficult to implement in numerical simulations due to the requirement for coordinate transformation [36]. The BSR index, proposed by [PERSON], was found to more accurately describe the rockburst characteristics at this site. Based on the applicability analysis of the rockburst criteria, the BSR index is selected as the preferred indicator for rockburst risk assessment at this location. The FISH function in the 3 DEC software was used for secondary development to enable BSR visualization.