Coal burst has become a worldwide problem that needs to be solved urgently for the sake of coal mine safety production due to its complicated triggering mechanisms and numerous influencing factors. The risk assessment of coal burst disasters is particularly critical. In this work, 15 factors affecting coal burst occurrence are selected from the perspectives of geodynamic environment and geological and mining conditions, and the influence mechanism of each factor on coal bursts is analyzed. An evaluation index system of coal burst risk is put forward. A hierarchical model of coal burst prediction is established, and the weight of each influencing factor to coal burst risk is calculated. Based on the fuzzy comprehensive evaluation method, a coal burst prediction model is established, which can scientifically decompose and simplify the complicated problem and make coal burst prediction and prevention more pertinent and effective. The model is applied to assess the coal burst risk level of a coal mine in Shanxi Province, and the evaluation result is consistent with practical situations. This method considers the influencing factors comprehensively and determines the weight of each factor scientifically compared with other forecasting methods.

The hard roof of coal mines has the characteristics of high hardness, good integrity, and large layer thickness, which leads to many ground control problems. To reveal the influence of a hard roof structure on the stress performance and coal pillar stability during mining operations, the 8,104 and 8,105 working faces in the Tongxin coal mine were considered as the research object to analyze the stress behavior during the working face advance. Numerical simulation software FLAC^3D was used to establish the numerical model of the longwall face under hard roof conditions. The stress distribution laws and coal pillar stability under different roof strengths were analyzed so as to explain the impacts of the hard roof on the stress distribution at the working face. The results show that during the second face proceeding, the influence zone of the front abutment pressure under hard roof conditions is 6 m wider than that under soft roof conditions, and the bearing stress at the working face is 10.4 MPa higher. At the mining position, the plastic zone of the pillar under hard roof conditions is 11 m wider than that under soft roof conditions, and the peak vertical stress is 5.13 MPa higher than that under soft roof conditions. At 25 m ahead of the working face, the plastic zone of the pillar under hard roof conditions is 6 m wider than that under soft roof conditions, and the peak vertical stress is 24.84 MPa higher than that under soft roof conditions. Additional overburden pressure produced by the uncaved hard roof increased pillar stress and plastic zones. Therefore, the hard roof is the main cause of strong ground pressure behavior in the Tongxin coal mine. Aiming at the strong mine pressure behavior, it is suggested to adopt the pre-splitting technology to reduce the influence of the hard roof on mine pressure.

The research aims to improve prediction accuracy for heights of fractured water-conducting zones (FWCZs) and effectively prevent and control roof water disasters, to ensure safe coal mining. For this purpose, the method that integrates the improved cuckoo search (ICS) algorithm and extreme learning machine (ELM) is used to predict heights of FWCZs. Based on an analysis of factors influencing FWCZs, the ICS algorithm is employed to optimize two key parameters of the ELM model, the input weight ѡ and the bias b of hidden elements, thus establishing the ICS–ELM model for predicting the height of the FWCZ. The ICS–ELM model is trained using 42 measured samples, and the trained model is employed to predict the remaining six sample data points. The obtained prediction results show a relative error of only 3.97% and are more consistent with the actual situation. To verify the effectiveness of the model, the prediction results are compared with those of the adaptive particle swarm optimization based least squares support vector machine (APSO–LSSVM) and particle swarm optimization (PSO) based backpropagation (PSO–BP) models. The average relative errors of the two models are 8.21 and 9.75%, respectively, which further proves that the ICS–ELM model improves the accuracy of prediction results for heights of FWCZs. The heights of FWCZs predicted using the model are accurate and reliable, and the accuracy meets the requirements of engineering practice.

The fully mechanized top-coal caving mining method was used to mine the 15 m thick No. 3–5 seam at a depth of 450 m in Tongxin mine, located in the Datong area, China. The seam was overlain with strong strata that are hard to cave and four partially mined coal seams. Excessive mine roadway closure and severe ground conditions at the longwall face and the tailgate were induced by periodic weighting and remnant coal pillars left in the four mined coal seams above. These ground conditions were studied using physical modelling and microseismic monitoring. The results indicated that hard rock strata above the coal seam did not cave readily, causing minor and major face loading events. The ground conditions deteriorated when mining was undertaken below the remnant pillars left in the four upper Jurassic seams. In addition, the physical model showed overlying longwall goaf collapse reaching the upper goafs and causing global movement in the strata. The data from the physical model and the underground microseismic survey presented here agreed closely with the visual observations and reported events that occurred at the underground longwall face in Tongxin coal mine. Overall, this study demonstrated the mechanisms of the overburden strata movement, longwall weighting occurrences and deteriorating ground conditions along the longwall face and the tailgate roadway when mining was undertaken under the overlapped Jurassic remnant coal pillars. Methods to minimize these bad ground conditions were suggested, using stress relief hydraulic fracturing methods and blasting, such as pre-splitting and softening of coal pillars and roof strata in key places. A design of small coal pillars <3–5 m in size were recommended for overlying seams to minimize stress concentrations in seams below.

Fissured coal mass under triaxial unloading condition exhibits higher burst potential than the triaxial loading condition, which poses challenge to safety and productivity of resources extraction and underground space utilization. To comprehensively understand the mechanism of unloading-induced burst during excavation process, this study investigated the fracture and energy evolution of samples with different fissure types such as single, two parallel, and two coplanar-parallel using PFC^2D modelling. Triaxial loading tests were conducted to determine the compressive strengths and other parameters. With increase of fissure inclination angle, the triaxial compressive strength decreases for β = 0°–30°, and then increase for β = 30°–90°. The strength of samples with two coplanar-parallel fissures is the highest. Fissure can significantly change the distribution of fracture and elastic energy. Secondary cracks were generated starting from both ends of the fissure. For β = 0°–60°, low elastic strain energy area was produced around the fissure along the loading direction. The elastic strain energy is transferred to the outside of fissures. For β = 75°–90°, only a small amount of high elastic strain energy was generated on both sides of the fissure. The fracture expansion under unloading conditions occurred due to tensile stress T caused by unloading differential rebound deformation and the shear stress on the fissure surface.

The longwall mining method with gob-side entry retaining via roof cutting is a new underground coal mining method which has the characteristics of a high resource recovery ratio and environmental friendliness. Due to the complexity of this method, the research method of case-based dynamic on-site monitoring, analysis, adjustment, and optimization is usually adopted. Based on a roadway retaining via roof cutting project, in addition to the traditional indirect monitoring method of hydraulic support pressure, this study innovatively establishes a direct monitoring method for roof caving by monitoring the gangue pressure in the goaf, which provides data for the roof cutting effect and offers a new method for studying the overlying strata movement. In the project, a comprehensive monitoring and analysis system was established, including gangue pressure, cable bolt stress, bracket pressure, roadway deformation, and roof separation, which was used to dynamically analyze the effect of roof cutting and optimize the support design. The results show that the pressure of the hydraulic support close to the roof cutting is low, indicating that roof cutting is favorable in the roadway retaining mining method. The roadway deformation in the advanced abutment pressure area of the working face is small. The mining-induced stress caused by the collapse and compaction of the overlying strata in the goaf is the dominant factor affecting the effect of roadway retaining, especially in the 50–100 m range behind the working face, where the dynamic load causes high bearing capacity of the support elements, large roadway convergence, and roof separation. Temporary support and supplementary reinforcement should be added when necessary. The monitoring system presented in this study is highly comprehensive, simple, reliable, and low in cost, providing a reference for roof cutting roadway retaining projects and roof caving-related studies.