Search Results (2,622)

To study the creep compression characteristics and evolution mechanism of pressure-bearing graded crushed rock under constant load. Creep compression tests of crushed rock were conducted using the self-developed confined compression test system under different Talbot indexes and axial stresses. The axial displacement, void ratio, mass distribution, fractal dimension, and fragmentation of crushed rock during creep compression were analyzed. And the void ratio-fractal dimension model of crushed rock under pressure was established. The results reveal three-stage characteristics in axial displacement and void change, which correspond to rapid, attenuation, and stable change processes. The axial displacement and fragmentation amount are positively correlated with the axial stress and Talbot index, while the porosity is negatively correlated with them. The fractal dimension shows a positive correlation with axial stress and a negative correlation with the Talbot index. Additionally, a theoretical model was established to characterize the dynamic correlation between void ratio and fractal dimension during compression process, and its accuracy was verified, with a maximum error of only 0.0819. The research findings can provide insights for stability prediction and deformation control of crushed rock in engineering applications such as building foundation pits, ground treatment, and coal mine goafs. Full article

The Carboniferous coal seams in Northeast Kazakhstan remain insufficiently investigated, with a lack of comprehensive mineralogical and geochemical assessments necessary to understand the geological processes controlling coal quality. This study examines 15 coal samples from the Karagandy Coal Formation (KCF) at the Saradyr and Bogatyr mines using proximate and ultimate analyses, FTIR, XRD, SEM–EDS, ED-XRF, and ICP-OES, providing the first detailed comparison of mineralogical and geochemical characteristics—including depositional signals and inorganic constituent distribution—between these mines within the KCF. The coals exhibit an average ash yield of 24.1% on a dry basis, volatile matter of 21.6% on a dry and ash-free basis, and low moisture content of 1.1% (air-dry), with low sulfur levels of 0.7% in whole coal across both mines. Mineralogical composition is dominated by quartz and clay minerals, with minor pyrite, apatite, chalcopyrite, and rutile. Major oxides in the coal ash average 68.2% SiO₂ and 19.5% Al₂O₃, followed by Fe₂O₃, K₂O, and TiO₂ (3–12.1%). Among the 24 identified trace elements, Sm is the most abundant at 6.3 ppm with slight enrichment (CC = 2.8), Lu remains at normal levels (CC < 1), and most other elements are depleted (CC < 0.5). The Al₂O₃/TiO₂ ratios (3.8–10.8) indicate contributions from intermediate to mafic parent materials. The detrital mineralogy, parting compositions, and elevated ash content indicate significant accommodation space development during or shortly after peat accumulation, likely within a vegetated alluvial plain depression. These findings provide new insights into the depositional environment and coal-forming processes of the KCF and contribute to regional assessments of coal quality and resource potential. Full article

Occupational exposure to respirable coal mine dust remains a significant health risk, especially for underground workers. Rapid dust monitoring methods are sought to support timely identification of hazards and corrective actions. Recent research has investigated how optical light microscopy (OLM) with automated image processing might meet this need. In laboratory studies, this approach has been demonstrated to classify particles into three primary classes—coal, silicates and carbonates. If the same is achievable in the field, results could support both hazard monitoring and dust source apportionment. The objective of the current study is to evaluate the performance of OLM with image processing to classify real coal mine dust particles, employing scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX) as a reference method. The results highlight two possible challenges for field implementation. First, particle agglomeration can effectively yield mixed particles that are difficult to classify, so integration of a dispersion method into the dust collection or sample preparation should be considered. Second, optical differences can exist between dust particles used for classification model development (i.e., typically generated in the lab from high-purity materials) versus real mine dust, so our results demonstrate the necessity of site-specific model calibration. Full article

Rare earth elements (REE) are vital for renewable energy, electronics, and advanced technologies; however, the process-related evolution of REE research has not been systematically quantified. This study conducts the first large-scale bibliometric analysis of 76,768 REE-related publications (1975–2024) from Web of Science, using the Cross-Disciplinary Publication Index (CDPI) and Technology–Economic Linkage Model (TELM). Results reveal three development phases: publication growth from <300 (1975–1990) to >5000 after 2008, driven by China’s export restrictions and the global clean energy transition; China leads with 24.1% of publications, followed by the U.S. (11.7%) and Germany (6.4%). Interdisciplinary mapping identifies materials science as the central field (CDPI = 0.81) linked to nanotechnology (0.75) and environmental science (0.66). Four thematic clusters dominate: (i) deposit geology, (ii) material applications, (iii) green extraction technologies, and (iv) circular economy strategies. Recent emphasis on sustainable practices and unconventional sources—such as phosphorites, bauxite, coal fly ash, and urban mining—reflects a shift toward green innovation. The findings guide policies to diversify REE supply through unconventional deposits (~50 Mt coal-hosted REE), eco-friendly extraction, and recycling. Future priorities include AI-driven exploration, lifecycle assessment of secondary sources, and stronger global collaboration to secure resilient, sustainable REE supply chains. Full article

Drilling methods have been increasingly employed for shaft excavation in coal mines in western China. However, the rock fragmentation performance of milled-tooth roller cutters remains inadequate under Jurassic strata conditions. To address this issue, a numerical orthogonal simulation study based on the Finite-Discrete Element Method (FDEM) was conducted. Cutter tooth edge geometry, cutter diameter, cone angle, and penetration depth were considered as four factors at three levels. The effects of these factors on average force, specific energy, damage factor, and proportion of shear cracks were investigated. The efficiency coefficient method was then applied to identify the optimal cutter, and the 8^# roller cutter was determined to be the most effective. The results indicated that cutter tooth edge geometry had the most significant influence on average force and specific energy, whereas penetration depth primarily affected the damage factor and proportion of shear cracks. Compared with the prototype cutter, the 8^# cutter, characterized by a 370 mm large cone-end diameter, a 3° cone angle, and V-edged teeth, exhibited superior rock fragmentation efficiency, achieving a maximum improvement of 31%. These results provide a theoretical basis for the structural optimization of cutters used in shaft drilling in coal mines in western China. Full article

Women in mining face unique health and safety challenges due to anatomical and physiological differences, making the assessment and management of ergonomic risks in underground coal mines critical. This study examines the ergonomic experiences of female mineworkers through six focus-group discussions, each comprising eight participants, using a qualitative research design involving women actively engaged in core mining activities at three South African mines. Findings reveal that mining equipment and work environments often fail to accommodate the physiological needs of female workers, exposing them to a range of ergonomic hazards. Beyond physical risks, the study highlights organizational and systemic shortcomings, including inadequate implementation of existing policies and regulations. Poor hygiene in toilet facilities was also reported, with three out of eight participants taking medication for urinary tract infections, underscoring gaps in occupational health provision. The findings emphasize the urgent need for mine-specific ergonomic programs developed through participatory approaches, as part of a broader strategy to prevent musculoskeletal injuries and improve working conditions for female mineworkers. The establishment of the Women in Mining Forum further indicates that the industry is not yet fully prepared to support women in underground mining, highlighting the need for targeted interventions to create a safer, more inclusive work environment. Full article

Prediction of coal and rock dynamic disasters is essential for ensuring the safety, efficiency, and long-term sustainability of deep mining operations. To improve the accuracy of acoustic methods for forecasting coal instability, acoustic emission (AE) source localization experiments are conducted on coal samples under uniaxial compression, and the multidimensional correlations among AE events together with the evolution characteristics of the corresponding complex network are investigated. The results show that the temporal correlations of AE events exhibit nonlinear decay with increasing time intervals, the spatial correlations display fractal clustering that transcends Euclidean geometry, and the energetic correlations reveal hierarchical transitions controlled by intrinsic material properties. To capture these interactions, a multidimensional correlation calculation method is developed to quantitatively characterize these multidimensional coupled relationships of AE events, and a complex network of AE events is constructed. The network evolution from sparse to highly interconnected is quantified using three parameters: average degree, clustering coefficient, and modularity. A rapid rise in the first two metrics, accompanied by a sharp decline in the latter, indicates the rapid strengthening of AE event correlations, the aggregation of local microcrack clusters, and their transition into a global fracture network, thereby providing a clear early warning of impending compressive failure of the coal sample. The study establishes a mechanistic link between microcrack evolution and macroscopic failure, offering a robust real-time monitoring tool that supports sustainable mining by reducing disaster risk, improving resource extraction stability, and minimizing socio-economic and environmental losses associated with dynamic failures in deep underground coal operations. Full article

Vertical shafts are the lifelines of coal mines, serving as critical conduits for resources and personnel. However, the long-term exposure of shaft walls to groundwater erosion significantly reduces their service life and increases the risk of structural failures. This issue is particularly pressing in Inner Mongolia and Henan Provinces, two of China’s major coal-producing regions, where the challenge of sulfate attack on shafts in deep stratigraphic environments has become a growing concern. This study focused on the corrosion damage observed in these two typical auxiliary shafts: the net diameters and depths of the auxiliary shafts in Shunhe Coal Mine and Mataihao Coal Mine are 6 m and 768.5 m and 9.2 m and 457 m, respectively. The rock section shaft walls in the study range from 5 to 10 m in thickness and are constructed using C40 to C60 grade concrete. To assess the extent of this damage, we conducted a comprehensive analysis of shaft wall samples using water analysis, XRD (X-ray diffraction) analysis, FT-IR (Fourier transform infrared) spectroscopy, and XRF (X-ray fluorescence) analysis. The findings reveal that the identified secondary sulfate reaction products within the shaft wall concrete include calcium sulfate, gypsum, ettringite, and thaumasite. The CaO loss rates in the auxiliary shaft walls of Shunhe Coal Mine and Mataihao Coal Mine are as high as 66% and 47%, respectively. Additionally, the concentrations of SO₃ and MgO in both mines exceed normal levels by up to 5 and 11 times, and 13 and 3 times, respectively. Despite this, severe corrosion is primarily confined to the inner surface of the auxiliary shaft walls, without significant penetration into the deeper shaft structure. The corrosion damage is predominantly concentrated in the shaft sections where the geological environment is characterized by bedrock. This study provides field evidence and laboratory analyses to inform the mitigation of sulfate attack in auxiliary shafts. Full article

Under the context of non-dyadic human–machine interaction in intelligent coal mines, this study investigates the impact of different dyadic collaboration modes on Team Situation Awareness (TSA). Based on a simulated coal mine monitoring task, the experiment compares four working modes—Individual Operation, Supervised Operation, Cooperative Operation, and Divided-task Operation—across tasks of varying complexity. TSA was assessed using both objective (SAGAT) and subjective (SART) measures, alongside parallel evaluations of task performance and workload (NASA-TLX). The results demonstrate that, compared to Individual or Supervised Operation, both Cooperative and Divided-task Operation significantly enhance TSA and task performance. Cooperative Operation improves information integration and comprehension, while Divided-task Operation enhances response efficiency by enabling focused attention on role-specific demands. Moreover, dyadic collaboration reduces cognitive workload, with the task-sharing mode showing the lowest cognitive and temporal demands. The findings indicate that clear task structuring and real-time information exchange can alleviate cognitive bottlenecks and promote accurate environmental perception. Theoretically, this study extends the application of non-dyadic interaction theory to intelligent coal mine scenarios and empirically validates a “Collaboration Mode–TSA–Performance” model. Practically, it provides design implications for adaptive collaboration frameworks in high-risk, high-complexity industrial systems, highlighting the value of dynamic role allocation in optimizing cognitive resource utilization and enhancing operational safety. Full article

Coal gangue, a solid waste from coal mining, has long been underutilized while posing environmental and safety risks. This study reviews the current research progress and future prospects of coal gangue as a resource in asphalt pavement. The physical and chemical properties of coal gangue were summarized, and the environmental issues caused by its accumulation were highlighted. The effects of using coal gangue as aggregates or fillers in asphalt mixture were reviewed, along with its activation methods. The research progress on using coal gangue as an aggregate or a cementitious material in mixtures stabilized with inorganic binders was also examined, emphasizing the effects of binder content and coal gangue properties on mechanical and durability performance. The findings indicate that despite its inferior physical properties, coal gangue demonstrates practical feasibility as a pavement material when appropriately incorporated and activated. Proper content enabled coal gangue to meet asphalt mixture or base material requirements, while excessive content reduced low-temperature resistance and caused structural defects. Activated or modified methods can effectively enhance interfacial interaction, high-temperature stability, or structural densification of coal gangue. Recent studies have expressed enthusiasm for innovative activation or modification methods and AI-based performance optimization, while key challenges remain regarding high activation-energy demand, limited aggregate-related research, and an incomplete understanding of interfacial mechanisms. Full article

Bolter miners have been widely used in coal mining or excavation industries. Its efficiency is closely related to the performance of its cutting reducer, which is literally determined by the thermal behavior of the planetary gear set. Thus, this study conducts experimental investigation on the thermal behavior of a cutting reducer (produced by Zhengzhou Machinery Research Institute Transmission Technology Co., Ltd., rated input power 170 kW, transmission ratio 3.06), where the results show the high temperature rise around the intermediate shaft for unloaded condition and significant influence of the torque for loaded conditions. Then, the Finite Element Method (FEM) is used to analyze the temperature field and thermal–structural coupling of the planetary gear set. The thermal stress and deformation increase by 11.5% and 38.4%, respectively, indicating high risk of gear damage. Moreover, the load spectrum imitating the actual industrial condition is added to the KISSsoft to evaluate the reliability and contact of the planetary gear set. The findings including low safety factors of the sun gear tooth surface and planetary gear root, slipping during the sun gear and planetary gear meshing, and uneven contact fluctuations can benefit planetary gear set optimization. Full article

Precise monitoring of damage evolution in coal-rock mass during mining emerges as a paramount requirement for developing accurate early warning systems for coal burst hazards. However, limited research has demonstrated the integrated damage characteristics of the coal-rock mass under static and dynamic loads during longwall mining. Therefore, in this paper, two novel seismic monitoring approaches, the Seismic Cluster Index (CI) and the Number of High Ground Motions (NHGMs), are developed to study the evolution of coal-rock mass damage during longwall mining under static and dynamic loads, respectively. Two months of monitored seismic data from a burst-prone longwall are used for analysis. The results show that CI can depict coal-rock damage conditions under static load, which identifies coalescence of fractures based on seismic source sizes and inter-event distances. Ground motion intensity has a positive correlation with seismic energy. The induced dynamic disturbance to roadways can further weaken the coal-rock mass, depending on the distance from the seismic sources. High-intensity dynamic disturbances, as indicated by elevated NHGMs and accelerated increments, strongly correlate with coal-burst damage. The proposed CI and NHGMs framework evaluate coal-rock mass damage and forecasts coal burst hazards, validated by the correlation between high CI/NHGMs values and actual burst locations. Full article

Roof water inrush is a major hazard threatening coal mine safety. This paper addresses the risk of roof water inrush during mining in the shallow-buried Jurassic coalfield of Northern Shaanxi, taking the Guojiawan Coal Mine as a case study. A systematic framework of “identification of main controlling factors–coupling of subjective and objective weighting–GIS-based spatial evaluation” is proposed. An integrated weighting system combining the Fuzzy Analytic Hierarchy Process (FAHP) and the Coefficient of Variation (CV) method is innovatively adopted. Four weight optimization models, including Linear Weighted Method, Multiplicative Synthesis Normalization Method, Minimum Information Entropy Method, and Game Theory Method, are introduced to evaluate 10 main controlling factors, including the fault strength index and sand–mud ratio. The results indicate that the GIS-based vulnerability evaluation model using the Multiplicative Synthesis Normalization Method achieves the highest accuracy, with a Spearman correlation coefficient of 0.9961. This model effectively enables five-level risk zoning and accurately identifies high-risk areas. The evaluation system and zoning results developed in this paper can provide a direct scientific basis for the design of water prevention engineering and precise countermeasures in the Guojiawan Coal Mine and other mining areas with similar geological conditions. Full article

This article delineates the outcomes of a comprehensive analysis of occupational conditions in coal mining, focusing on dust exposure. A multifaceted model is proposed for the holistic evaluation of occupational environments, integrating risk assessment methodologies and decision-making frameworks within a risk-based paradigm. Risk assessment involved pairwise comparison, T. Saaty’s Analytic Hierarchy Process, a pessimistic decision-making approach, and fuzzy set membership functions. Correlations were established between respiratory disease risk among open pit coal mine workers and dust generation sources at the project design phase. The risk values were then validated using source attributes and particle physicochemical parameter analysis, including disperse composition and morphology. The risk assessment identified haul roads as a predominant factor in occupational disease pathogenesis, demonstrating a calculated risk level of R = 0.512. The dispersed analysis indicated the prevalence of PM1.0 and submicron particles (≤1 µm) with about 77% of the particle count, the mass distribution showed the respirable fraction (1–5 µm) comprising up to 50% of the total dust mass. Considering in situ monitoring data and particulate morphology analysis haul roads (R = 0.281) and the overburden face (R = 0.213) were delineated as primary targets for the implementation of enhanced health and safety interventions. While most critical at the design stage amidst data scarcity and exposure uncertainty, the approach permits subsequent refinement of occupational risks during operations through the incorporation of empirical monitoring data. Full article

Fertilization is an effective measure to rapidly improve soil quality in reclaimed mining areas. However, the combined effects of fertilization regimes and reclamation age on phosphorus (P) fraction transformation and the pqqC-harboring microbial community in reclaimed soils remain unclear. In this study, we investigated the dynamics of inorganic P fractions and the pqqC-harboring bacterial community under different fertilization treatments (no fertilizer: CK; chemical fertilizer: CF; organic manure: M) and reclamation ages (1, 5, and 10 years) in a coal mining reclamation area of Shanxi Province, using long-term field experiments combined with high-throughput sequencing. Results showed that compared with the CF and CK treatments, the M treatment significantly increased soil organic matter (SOM), available P (AP), and total nitrogen (TN) content, and promoted the conversion of moderately labile P (NaOH-Pi) to labile P fractions (H₂O-Pi, NaHCO₃-Pi). Meanwhile, the pqqC gene abundance increased with reclamation age, with the M treatment maintaining the highest levels in all fertilization regimes. Co-occurrence network analysis of core species revealed that the number of connections gradually decreased and the network structure simplified with increasing reclamation age. Correspondingly, the microbial community transitioned from an initial stage characterized by rapid response and intense competition to a stable phase. Specifically, Pseudomonas spp. played a key role in P mobilization. Structural equation modeling (SEM) further demonstrated that reclamation age directly promoted the pqqC gene abundance and AP content, whereas fertilization indirectly influenced P transformation by regulating microbial diversity. Our findings reveal that reclamation age and fertilization synergistically shape the inorganic P profile and the associated bacterial community, providing insights for developing targeted P management strategies in reclaimed lands. Full article