# Development of Rockburst Research: A Comprehensive Review
## 7 Discussions  
As a worldwide scientific problem, rockburst has always been a key research object of scholars and engineers. The developing trend of rockburst research can be divided into two stages. The research work in the first stage mainly focused on the failure and fracture characteristics of rocks and the mechanism of rockburst. At this stage, the study of the rockburst mechanism mostly stayed at the level of qualitative interpretation. The research work in the latter stage is more comprehensive, due to the gradual enrichment of research means. At this stage, new theories and research means make the research on the mechanism of rockburst more in-depth. Whilst classification, prediction and prevention methods of rockburst have gradually become a research hotspot and a large number of research results have been obtained, the following deficiencies are worth discussing:  
* Regarding numerical simulations, most numerical simulation studies of rockburst adopt a continuous media mechanics model, which has the deficiency of being unable to simulate the large deformation mechanical behavior of discontinuous media in rockburst development. DEM can make up for this deficiency, but the shortcoming of DEM is also obvious. The three elements, namely, motion, force and deformation, need artificial assumptions, resulting in more input parameters and calibration. Complex data structure, grid retrieval, determination of adjacent blocks and detection of generation or cancellation for block contact will consume a large computational cost. Figure 14: Typical energy-absorbing bolts [60; 191; 200; 201; 202; 203; 204; 205; 206]. Figure 15: Load-displacement behavior of different types of rockbolts [198]. * Regarding the physical model tests, due to loading conditions and the similarity relationship that needs to be met, the strength of similar materials is usually lower than that of the original rock with rockburst, so it is difficult to accumulate high energy. Coupled with an unclear brittle similarity relationship, whether the structure surface of similar materials can truly reflect the influence of the structure surface on rockburst is worthy of further discussion. On the other hand, owing to the complexity of the simulated excavation operation and the lack of dynamic similarity theory, it is also debatable whether it can truly reflect the influence of excavation dynamic disturbance on rockburst. * Regarding the empirical criteria, although some influencing factors of rockburst have been considered in the comprehensive criteria, there are many influencing factors in practical engineering, not only the static stress of surrounding rock but also other unpredictable dynamic disturbance. Moreover, the occurrence of rockburst is sudden and random, and the existing criteria are still difficult to accurately evaluate and predict rockburst. In addition, some empirical criteria are not unified, which causes trouble for researchers. * Regarding the mathematical model approaches for rockburst classification and prediction, whether using uncertainty algorithm models or machine learning, the crux for the accuracy of classification and prediction results is the amount and availability of data for rockburst. In actuality, the amount of existing rockburst data makes it difficult to ensure the high accuracy of model. The imbalance of training samples (such as \"rockburst occurrence\" records being far fewer in number than \"no rockburst\" records), leads to poor generalization capability of the model. On the other hand, there are few selected index factors in uncertainty algorithm models and input indices (rockburst influencing factors) in machine learning. Whether it can represent the most important influencing factors of rockburst is still worth discussing. * Regarding microseismic monitoring, due to the unpredictable distribution of underground strata, anisotropy of medium and the sudden change of wave velocity between two various rock formations, it is difficult to ensure the accuracy of microseismic source location results.