With the in-depth advancement of the "Dual-Carbon" strategic goals and the development of new-quality productive forces, intelligent new-energy equipment has been increasingly widely applied in the mining industry, and the lithium-ion battery power supply has become an important power source for mine equipment. However, due to the complex working environment and limited space in mines, the risk of thermal runaway of lithium battery and its secondary disasters is significantly increased. To effectively prevent and control the disaster risk of lithium-ion battery power supply in mines, the disaster chain of "inducement - thermal runaway warning - secondary disaster" was reviewed. The results show that the lithium-ion battery power supply has formed a relatively systematic thermal runaway inducement analysis and monitoring and early warning system in the field of commercial and energy storage, but the research on the thermal runaway evolution mechanism in the complex environment of mines is still not deep enough. The early warning technology of mine thermal runaway should be further developed in the direction of multi-source information fusion and intelligence, and the coordination construction of active early warning and passive protection measures should be strengthened. The research results can provide support for the safe application of lithium-ion battery power supply in underground mines.

With the continuous increase in mining depth and the growing complexity of operating environments, the traditional safety governance model for non-coal mines is facing severe challenges. It is urgent to promote the transformation of this safety governance model toward pre-incident prevention. The evolution context of safety production policies for non-coal mines in China, which have shifted from "post-incident accountability" to "source control" and further to "systematic governance", was systematically sorted out, and a four-dimensional analytical framework of "access control-process supervision-transformation and upgrading-supervision and law enforcement" was constructed. The research shows that the current policy system has effectively promoted the optimization of industrial structure and has improved the safety situation. The number of accidents and fatalities in 2025 decreased by 49.0% and 38.3% respectively compared with 2018. However, in the face of new scenarios such as deep mine mining and intelligent construction, the policy system still has structural contradictions including lagging regulations and standards, implementation obstacles at the grassroots level, and insufficient technical support. Drawing on the experience of safety risk management in Australia, the United States and Canada, this paper proposes that China should establish a five-dimensional optimization path comprising improved legal frameworks, intelligent upgrading, collaborative governance, market-oriented incentives and accountability implementation to address the "last-kilometer" problem in policy implementation. In the future, in-depth research should be conducted on policy adaptation in cutting-edge fields, assessment of policy synergistic effects, and research on region-differentiated strategies, so as to provide institutional guarantees for the development of new-quality productive forces in the mining industry.

Lead-zinc ore is one of the important metallic mineral deposits in Hunan Province and has exerted significant environmental impacts on surface water and groundwater in the surrounding mining area. To investigate the influence of mining activities on surrounding water bodies, 16 groups of surface water samples and 12 groups of groundwater samples were collected. Piper trilinear diagram, Gibbs diagram, ion ratio analysis, chloro-alkaline index, factor analysis, correlation analysis, mineral saturation index, and geostatistical spatial analysis (Kriging interpolation, distance decay fitting, and directional variogram) were employed to analyze the hydrochemical characteristics and genesis of water quality in the study area. The results show that the water bodies in the study area are generally weakly alkaline, with Total Dissolved Solids (TDS) mass concentration ranging from 70 to 1 190 mg/L. The groundwater is dominated by SO₄-Ca and HCO₃-Ca·Mg hydrochemical types. The hydrochemical evolution is dominated by weathering dissolution of carbonate rocks, supplemented by forward cation exchange dominated by silicate rocks. The coupling of sulfide mineral oxidation and carbonate rock neutralization is the formation mechanism of the high , high TDS, and near-neutral pH characteristics of mine water. The influence of lead-zinc ore dissolution on different groundwater flow systems differs significantly, exhibiting strong spatial differentiation of hydrochemical characteristics. The water mineralization degree score (MDS) is centered on the mining core area and decays exponentially with distance, decreasing to 40% of the initial amplitude within 1 km and approaching the regional background level within 2-3 km. The influence width perpendicular to the groundwater flow direction is approximately 1.6 km. The impact of mining activities on surrounding water bodies shows a radial pattern, with stronger effects in water bodies closer to the mining area. The research results can provide a basis for water inrush risk warning, water pollution prevention and control, and rational utilization of mine water resources.

To reveal the failure mechanism and dynamic catastrophe evolution law of pillar group and solve the problem of large-area goaf collapse caused by pillar group instability in gently inclined orebody mining, the PFC2D numerical simulation method was adopted to conduct parallel uniaxial loading test simulations on three specimens with different strengths. The failure force chain and crack evolution characteristics of multiple pillars were analyzed, the chain instability mechanism of multiple pillars was revealed, and a key pillar theory based on trigger pillars, chain-breaking pillars, and critical pillars as well as a key pillar identification method were proposed. The method was verified by using the Fetr6 chromite mine case. The research shows that the instability of pillar group follows the law of chain failure, and pillars fail sequentially in the order of their strength from low to high. The trigger pillar is the weakest pillar that fails first during the chain failure process. The chain-breaking pillar can stop the propagation of chain failure in the pillar group. The critical pillar determines the critical state of overall instability of the pillar group system. The proposed key pillar identification method can accurately identify key pillars in the chain dynamic instability process. Verified by the Fetr6 chromite mine case, when the pillar bearing area loss rate reaches 0.523, the pillar group system can be judged as overall unstable. The research results provide a theoretical basis and technical support for the stability assessment and disaster prevention and control of pillar group in mines.

To address the local instability problem of the talc-bearing soft rock slope on the east side of the M Pit in an open-pit copper-cobalt mine, engineering geological investigation, three-dimensional numerical simulation (FLAC3D), and limit equilibrium analysis (Slide 2D/3D) were comprehensively employed to investigate and analyze the stability of the talc-bearing slope. The slope instability mechanism was revealed and a corresponding treatment scheme was proposed. The research results indicate that the east slope of the M Pit is in a stable state as a whole, but the slope section with talc exposure at +1 335 m to +1 380 m is in an unstable state. The talc layer has low strength and is prone to slaking upon contact with water, constituting a dominant weak interlayer. The shear strength of its interface with the surrounding rock decreases significantly, forming a potential sliding surface and leading to a deep shear-shallow tension failure mode of the talc-bearing slope. Accordingly, a comprehensive treatment scheme of "7% cement-treated soil replacement + steel-plastic geogrid + blind ditch drainage at the slope toe" was proposed and implemented. Nearly one year of on-site monitoring shows that the slope displacement curve is generally stable and the treatment effect is remarkable. The established treatment technology framework of "instability mechanism analysis-quantitative stability evaluation-treatment scheme design-treatment effect monitoring feedback" can provide a theoretical basis and engineering reference for the treatment of slopes containing weak interlayers such as talc.

The safety and stability of the tailings pond are crucial for ensuring underground collaborative mining. To investigate the influence of the tailings pond on mine engineering, a three-dimensional geological-structural model of a certain lithium-containing porcelain stone mine was established using the coupled GTS/NX and FLAC3D modeling method, and the optimization of the sealing length of the +225 m adit within the inundation line of the tailings pond and the analysis of the influence of the tailings pond on the stability of ore body mining were conducted. The results show that significant changes are observed in the stress, displacement, and plastic zone of the surrounding rock of the adit under different sealing lengths. The optimal sealing length is determined to be 105 m, at which the tensile stress at the adit opening is reduced to 0.20 MPa, the displacement deformation is 8 mm, and no plastic zone is generated in the sealing area, so that the water pressure of the tailings pond can be effectively controlled and the stability of the adit can be ensured. It is found from the comparison of the mechanical responses of ore body mining under conditions with and without the tailings pond that, when the tailings pond is present, the tensile stress of the roof of the mined-out area is reduced from 0.87 MPa (under the condition without the pond) to 0.84 MPa, the displacement is reduced from 15 mm to 14 mm, and the plastic zone of the mined-out area is not connected with the surface or the plastic zone of the tailings pond. Therefore, under the current engineering and geological conditions, the tailings pond is not the dominant factor for the stability of ore body mining. However, stress and deformation monitoring still needs to be strengthened during the subsequent mining process. The research results can provide method reference and data support for the collaborative safety design and assessment of tailings ponds and underground mining in similar mines.

Tailings ponds are mostly located in mountainous areas with scarce hydrological data, and the rational formula method is widely adopted for their design flood derivation, in which the determination of the confluence parameter m value directly affects the engineering scale, safety and reliability, and economic benefits. However, in actual engineering design and safety evaluation, the determination of the m value has often not received enough attention, leading to deviations in calculation results and affecting the rationality and safety of the project. Confluence parameters not only depend on natural conditions such as the underlying surface of the basin, but also have a dynamic coupling relationship and nonlinear feedback effect with elements such as peak discharge and confluence duration. According to the Regulation for calculating design flood of water resources and hydropower projects and the Hydrological Manual of Qinghai Province, the m value ranges were determined respectively, and the response laws of confluence time, peak discharge, and average flow velocity to the variation of the m value were systematically investigated. The results shows that the confluence parameter has a significant regulatory effect on peak flood discharge, and this response mechanism has not received sufficient attention. Given that the catchment areas of tailings ponds are mostly small-scale watersheds, it is recommended to scientifically determine the m value based on systematic analysis of topographic and geomorphological characteristics, vegetation coverage characteristics, and field investigations, following the concept of "localized adaptation and multidimensional verification", so as to improve the scientificity and reliability for the design and construction of tailings ponds.

Intelligent upgrading of mining equipment is the core pathway to address the safety and efficiency bottlenecks in deep mining and to achieve high-quality development of the mining industry. The development process of Changsha Institute of Mining Research Co., Ltd from technology introduction to independent innovation was systematically reviewed, and the complete intelligent equipment system covering shaft construction, rock drilling and excavation, and underground auxiliary operations was introduced. Key technological breakthroughs in CKT series raise boring machines, CKY/CKQ series full-spectrum mining equipment, and intelligent auxiliary equipment integrating AI vision and robotics were highlighted. In response to the common industry shortcomings, such as insufficient adaptability of equipment and difficulties in multi-machine coordination under deep and complex working conditions, a cutting-edge technology layout covering intelligent sensing, digital twin, and cluster coordination was proposed, and the strategic path for transformation from a single equipment supplier to a full-scenario intelligent mining service provider was clarified. The research and development practices of Changsha Institute of Mining Research Co., Ltd have provided an important model for China to break away the dependence on imported high-end mining equipment and ensure the independent controllability of mining equipment.

To meet the requirements for improving the load capacity and operational efficiency of the auxiliary shaft hoisting system in mines, the extra-large cage for modern mine auxiliary shaft was designed and studied based on the finite element method. The mechanical performance of the overall cage and its key components under a fully loaded condition of 150 t was systematically evaluated by establishing a three-dimensional solid model and conducting static simulation analysis using the ANSYS Workbench platform. The results indicate that the maximum equivalent stress of the overall cage is 47.749 MPa, and the overall safety factor, calculated based on the yield strength of Q690 steel, is 14.45. The safety factors of the main beams, columns, and tail beam are 16.3, 19.9, and 20.4, respectively, all of which are above the design control value n_min=13 and are in compliance with the safety regulations. The structural stress distribution is reasonable, and the deformation is controllable. It is demonstrated by engineering application that the overall transportation capacity and operational safety of cage for large-scale equipment can be improved by the design, and that a systematic design method from design constraints, load transfer paths, global structural response, local strength verification to engineering validation is established, and a reference is provided for the structural design of extra-large hoisting cages in deep mines.

Blasting fragmentation is regarded as an important basis for evaluating blasting effects and optimizing blasting parameters, and the subsequent operations such as shoveling, transportation, and crushing and grinding are directly affected. With blasting fragmentation prediction and post-blast fragmentation recognition as the main line, the formation mechanism and main influencing factors of blasting fragments were introduced. Prediction methods, including empirical and semi-empirical models, mechanism analysis and numerical simulation, statistical learning and artificial intelligence, as well as recognition techniques, including traditional detection, 2D image recognition, 3D point cloud, and photogrammetry, were systematically reviewed. The characteristics of different methods in terms of prediction accuracy, mechanism interpretability, computational efficiency, field applicability, and implementation cost were compared. The analysis results show that existing methods have their own advantages and applicable boundaries, and that accurate prediction, stable recognition, and low-cost application are still difficult to achieve simultaneously under complex mine conditions. It is concluded through analysis that current research is mainly constrained by the lack of model interpretability and cross-scene generalization ability, the vulnerability of recognition results to field environments, and the underdevelopment of data standards and engineering application systems. The synergy among mechanistic models, data-driven methods, and multi-source recognition technologies should be strengthened in future research, with emphasis placed on real-time fragmentation prediction based on multi-source data fusion, precise recognition and control in complex environments, and coordinated optimization of intelligent blasting equipment and prediction models, so that support can be provided for establishing a closed-loop control system comprising pre-blast prediction, post-blast recognition, effect evaluation, and parameter feedback.