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Leadership is a necessary element for ensuring workplace safety. Rather little is known about the role of leadership safety behaviours (LSBs) in the mining industry. Using regression analysis and structural equation modelling analysis, this study examined the cause-and-effect relationships between leadership safety behaviours and safety performance. Data were collected by questionnaires from 305 miners in China. Data were analysed using exploratory factor analysis and confirmatory factor analysis, which identified five main dimensions of LSBs: safety management commitment, safety communication with feedback, safety policy, safety incentives, and safety training; the analysis also identified three main dimensions of safety performance: employee’s safety compliance, safety participation, and safety accidents. The results showed the overall effects of each LSB variable on safety compliance in descending order as: safety training (0.504), safety incentives (0.480), safety communication with feedback (0.377), safety management commitment (0.281), and safety policy (0.110). The overall effects of each LSB variable on safety participation in descending order were: safety training (0.706), safety incentives (0.496), safety management commitment (0.365), and safety policy (0.247). Furthermore, we found that safety management commitment and safety incentives increased employees’ safety behaviours, but this influence was mediated by safety training, safety policy, and safety communication with feedback.

Coal is an important basic energy source, widely distributed throughout the world, but resource abundance is uneven. Despite the need to develop and form new energy sources, coal energy maintains its dominant position. However, due to the uneven distribution and non-renewable nature of coal resources, the relationship between the supply and demand of coal resources is tight. The rational exploitation of coal and reducing resource mining wastes are particularly important at the present stage. The original mining method of the Zhangjiamao coal mine resulted in a large waste of coal resources. After replacing the “110 construction method”, the original advanced end-support was canceled, which saved a lot of process time and engineering costs and greatly improved the mine production efficiency. With an average mining depth of +300 m, the working face is in a safe and stable state, and the 110-mining process has little impact on surface subsidence. Its successful application provides a reference experience for other mines to promote resource-saving and efficient mining.

A 3D numerical model was presented to investigate the blast-induced damage characteristics of highly stressed rock mass. The RHT (Riedel, Hiermaier, and Thoma) model in LS-DYNA was used to simulate the blast-induced damage and its parameters were calibrated by a physical model test. Based on the calibrated numerical model, the influences of confining pressure and free surface span on the blast-induced damage characteristics were investigated. The results show that under uniaxial loading, the crater volume increases with confining pressure increases. The uniaxial static load can change the optimal burden and the critical embedding depth of charge. In stressed rock, the variation law of the crater shape affected by radial tensile fractures is opposite to that affected by reflected tensile fractures. Under the biaxial static load, the crater volume of the borehole placed on the side of the max static load is greater than the other side. The explosion crater can be improved by increasing the free surface span on the same side. Finally, it is suggested that the blasting efficiency can be improved by preferentially detonating the charge on the side of the max static load, and then the charge on the other side can be detonated with a wider free surface span.

A simple and accurate evaluation method of broken rock zone thickness (BRZT), which is usually used to describe the broken rock zone (BRZ), is meaningful, due to its ability to provide a reference for the roadway stability evaluation and support design. To create a relationship between various geological variables and the broken rock zone thickness (BRZT), the multiple linear regression (MLR), artificial neural network (ANN), Gaussian process (GP) and particle swarm optimization algorithm (PSO)-GP method were utilized, and the corresponding intelligence models were developed based on the database collected from various mines in China. Four variables including embedding depth (ED), drift span (DS), surrounding rock mass strength (RMS) and joint index (JI) were selected to train the intelligence model, while broken rock zone thickness (BRZT) is chosen as the output variable, and the k-fold cross-validation method was applied in the training process. After training, there validation metrics including variance account for (VAF), determination coefficient (R2) and root mean squared error (RMSE) were applied to describe the predictive performance of these developed models. After comparing performance based on a ranking method, the obtained results show that the PSO-GP model provides the best predictive performance in estimating broken rock zone thickness (BRZT). In addition, the sensitive effect of collected variables on broken rock zone thickness (BRZT) can be listed as JI, ED, DS and RMS, and JI was found to be the most sensitive factor.

Large amounts of leaching residue are released into tailings dams from mines, and their acid content can cause environmental pollution. The aim of this study was to research the feasibility and value of a leaching residue backfill recycling method. The combination of property detection, laboratory tests (the neutralization method, strength test and diffusivity test) and numerical simulation methods (3D computational fluid dynamics (CFD) simulations of pipeline transportation properties) were used to assess the performance of the leaching residue backfill. The results show that backfill body with the cement:sand mass ratio of 1:3, the leaching residue:classified tailings ratio of 1:6, and slurry mass concentration of 71 wt % can meet the strength and pipeline self-flowing transportation requirements of mine backfill. The leaching residue is a good backfill aggregate, and its recovery ratio can reach 19.5 wt %. In addition, the recycling of leaching residue effectively alleviates the problem of mine waste emissions and protects the ecological environment surrounding the mining area. This study serves as a guide for the recycling of fine tailings and the environmental governance of the mining area.