The deformation and failure of a coal–rock system in a deep environment is affected by its own mechanical properties, natural endowments, and geological structures; it is very important to study the energy evolution law of coal–rock systems. For this purpose, a Particle Flow Code in 2 Dimensions (PFC2D) simulation was conducted to assess the coal–rock structure and roadway surrounding rock. The hard roof would produce a rebound “energy supply” phenomenon when the coal was destroyed, and the influence of rock strength on the energy evolution of the coal–rock combination was analyzed. In addition, the energy evolution law of roadway surrounding rock with different roof strength is studied; the energy evolution process of roof and coal seam and deep and shallow coal mass are compared, according to the energy storage characteristics of roadway surrounding rock in different areas; the partition energy storage model of roadway surrounding rock is established preliminarily and the concepts of energy storage area and energy supply area of roadway surrounding rock are proposed; the prevention and control methods of near-field rock burst in deep roadways are discussed, and the research conclusions can provide theoretical reference for the research on the mechanism of rock burst in deep coal mines.

Understanding the excavation-induced deformation and failure behaviors of the URL (underground research laboratory) for the geological disposal of HLW (high-level radioactive waste) before its construction is essential due to its high safety requirements. To reveal the interaction between structures, the effect of supporting and the characteristics of the overloading-induced damage and safety factor, we carried out a physical model test on the deep underground chamber groups consisting of one main roadway and two parking lots (one is supported, the other is not supported), and the engineering background is the URL of HLW for the geological disposal in Beishan. This type of geomechanical model test is still the first to be carried out so far. The test results confirm that the chamber group is generally stable during the excavation process. After the excavation, the displacement of the intersection is 7–33% larger than that of the non-intersection. The displacement of the supported chamber is reduced by 14–22% compared with that without support. The tension of the bolt at the vault top is greater than that at the waist of the cave. Without support, the safety coefficient of crack initiation is 1.7; the safety coefficient of local destruction is 2.1; and the safety coefficient of general demolition is 2.3. In contrast, the safety coefficient of crack initiation is 1.9; the safety coefficient of local destruction is 2.2; and the safety coefficient of general demolition is 2.4 when the rock mass is supported. The research results provide an important basis for optimizing design schemes and evaluating the safety of the construction process for URL.

The impact risk evaluation for the strip filling of working faces has always been a research hotspot and a difficulty in the field of rock bursts. In this paper, the concept of the critical filling rate is first proposed, and the criterion for identifying the impact risk of the strip filling of a working face is established. Then, the membership function of coal body stress and the coal seam elastic energy index to impact risk was established, and the classification index of the impact risk grade was formed. On this basis, the overall and local evaluation method of the rock burst hazard for the strip filling of working faces was proposed. Finally, the C8301 working face of the Yunhe coal mine was taken as the engineering background, and the impact risk evaluation was carried out. It was found that the overall risk of the C8301 working face was determined as a strong impact risk, and there were six local risk areas, which included two weak impact risk areas, two medium impact risk areas, and two strong impact risk areas. This study can provide guidance and a reference for the impact risk evaluation of strip-filling mining under the same or similar conditions.

Microseismic monitoring technology serves as a vital tool for assessing the stability of coal and rock masses. The precision of energy calculations and the ability to integrate data across different systems have a direct impact on the effectiveness of early warning systems for hazards such as rockburst. This study utilized the 6306 working face of Shandong Energy Group’s Dongtan Coal Mine as its experimental site to address data inconsistencies caused by variations in sensor responses, localization algorithms, and energy calculation methods among microseismic monitoring systems. Two microseismic monitoring platforms, designated as System A and System B, were deployed to conduct a comparative and integrative study of cross-system energy calculations. The optimization of sensor layout facilitated a comprehensive analysis of the differences between the two systems in terms of P-wave arrival times, amplitude–frequency characteristics, and localization accuracy. Results indicated that System A achieved significantly lower localization errors, with an average of 49 m, compared to System B’s average of 70 m. Substantial differences were also found in waveform amplitude and dominant frequency, with a correlation coefficient of only 0.59 between the two systems. To bridge these disparities, an energy calculation method based on the displacement gauge function was developed. By fitting a localized gauge function R(Δ) and incorporating empirical coefficients, the energy calculation outputs of both systems were harmonized. Validation experiments demonstrated that the linear correlation coefficient of energy calculations between Systems A and B increased to 0.977 under the new method, confirming its effectiveness for data unification. This research provides critical theoretical and technical guidance for integrating microseismic data across systems and establishing unified early warning standards, thus advancing the monitoring and prediction of dynamic hazards in mining environments.