Search Results (176)

After the completion of open-pit coal mining, land reclamation is implemented to restore the disturbed eco–hydrological system, for which accurate soil moisture characterization is essential. We evaluated the feasibility and performance of an Auto-Regressive Moving Average (ARMA)-based ground-penetrating radar (GPR) inversion scheme for estimating soil moisture in a reclaimed mine area. GPR data were acquired over a reconstructed three-layer soil profile in a reclaimed open-pit coal mine, and soil moisture content was independently determined using the oven-drying method on core samples. An ARMA model was used to describe the relationship between the GPR reflections and soil electromagnetic properties and to invert the vertical distribution of soil moisture. The ARMA-derived GPR estimates reproduced the measured moisture profile well within the depth interval of 1.4–3.0 m and revealed the clear vertical zonation of soil moisture associated with the engineered layering. Correlation coefficients between the ARMA-inverted GPR estimates and oven-drying measurements ranged from 0.64–0.78 for 0–1.4 m, 0.84–0.93 for 1.4–2.2 m, and 0.98–0.99 for 2.2–3.0 m, indicating that inversion accuracy improves systematically with depth. These results demonstrate that ARMA-based GPR inversion provides a reliable and non-destructive approach for quantifying soil moisture in reclaimed mine soils and offers practical support for monitoring and assessing the effectiveness of reclamation in open-pit coal mining areas. 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

Open-pit coal mining is characterized by multiple pollution sources, diverse types, and extensive affected areas, leading to complex air pollution with wide diffusion. Traditional fixed monitoring methods cannot address these limitations. Taking a coal mine in Xinjiang as a case study, this study developed a drone-mounted mobile atmospheric monitoring system, focusing on nitrogen dioxide (NO₂) and suspended particulate matter (PM_2.5 and PM₁₀) to explore their distribution, diffusion patterns, and influencing factors. The results show distinct seasonal pollutant characteristics: NO₂ and ozone (O₃) dominate in summer, while particulate matter prevails in winter. The temporal distribution exhibits a bimodal pattern, with high levels in the early morning and evening hours. Spatially, higher pollutant concentrations accumulate vertically below ground level, while lower levels are observed above it. Horizontally, elevated concentrations are found along northern transport corridors; however, these levels become more uniform at greater heights. A spatiotemporal prediction model integrating convolutional neural network (CNN) and long short-term memory (LSTM) network was successfully applied to real-time pollutant prediction in open-pit coal mining areas. This study provides a reliable mobile monitoring solution for open-pit coal mine air pollution and offers valuable insights for targeted pollution control in similar mining areas. Full article

With the development of mineral resources, the inevitable creation of numerous abandoned mines has impacted environmental resources. Numerous studies have been conducted on the restoration and management of individual abandoned mines. However, there has been no systematic study on the overall ecological restoration planning of abandoned mine clusters. Hence, there is an urgent need to research restoration planning strategies, focusing on the characteristics of abandoned mines and their environmental impacts. In this study, abandoned mines in Toli County, Xinjiang, were selected as the case. The K-means clustering analysis method was employed to study the spatial distribution of abandoned mines, selecting longitude, latitude, and road access as analytical factors. Based on spatial location attributes, three groups of abandoned mines were identified. The Analytic Hierarchy Process (AHP) was used to study the ecological importance evaluation model in Toli County, selecting eight evaluation factors including vegetation, precipitation, and population density, and dividing the ecological importance levels of various sectors to establish a three-stage restoration project. The Principal Component Analysis (PCA) method was used to assess the hazards of abandoned mines, selecting distance, land type, area, and ecological impact as influencing factors and determining the management sequence of abandoned mines within each project. The results show that (1) longitude, latitude, and road indices help to mitigate geographical obstacles such as mountains and rivers, ensuring a high degree of continuity in abandoned mine areas; (2) the AHP reveals that the combined weight of population density, gross domestic product, and vegetation index exceeds 80%, which are key factors affecting the priority of ecological restoration; and (3) the application of PCA provides a scientific basis for the hazard assessment and management of abandoned mines, prioritizing those close to densely populated areas and with larger areas. The significance of this study lies in providing a systematic method for ecological restoration planning of abandoned mines, as well as offering important references for future research and practice in related fields. Full article

Land surface temperature (LST) is a key indicator reflecting the ecological environmental disturbance caused by open-pit coal mining activities and determining the ecological status in alpine permafrost regions. Thus, it is crucial to study the spatiotemporal variations and influencing mechanisms of LST throughout all stages of small-scale mining–large-scale land surface damage–ecological restoration. Landsat imagery over nine periods was extracted from the growing seasons between 1990 and 2024. This study retrieved LST while simultaneously calculating albedo, soil moisture, and normalized difference vegetation index (NDVI) for each time phase. By integrating land use/cover (LUCC) data, the spatiotemporal evolution patterns of LST in the mining area throughout all stages were revealed. Based on the Geodetector method, an identification approach for factors influencing LST spatial differentiation was established. This approach was applicable to the entire process characterized by significant land type transitions. The results indicate that the spatiotemporal variations in LST were significantly correlated with land surface damage and restoration caused by human activities in the mining area. With the implementation of ecological restoration, high and ultra-high temperatures decreased by about 25.98% compared to the period when the surface damage was the most severe. The main influencing factors of LST differentiation were identified for different land use types, i.e., natural and restored meadows (soil wetness, albedo, and NDVI), mine pits (albedo, aspect, and elevation), and mining waste dumps (aspect and albedo before restoration; aspect and NDVI after restoration). This study can provide a reference for monitoring the ecological environment changes and ecological restoration of global coalfields with the same climatic characteristics. Full article

Complex associations among production cost factors, multi-source cost information silos, and opaque transmission mechanisms of hidden costs in open-pit coal mining were addressed. The production process—including drilling, blasting, excavation, transportation, and dumping—was taken as the application context. A corpus of 103 open-pit coal mining standards and related research documents was constructed. Eleven entity types and twelve relationship types were defined. Dynamic word vectors were obtained through transformer (BERT) pre-training. The optimal entity tag sequence was labeled using a bidirectional long short-term memory–conditional random field (BiLSTM–CRF) 9 model. A total of 3995 entities and 6035 relationships were identified, forming a symmetry-aware knowledge graph for open-pit coal mining costs based on the BERT–BiLSTM–CRF model. The results showed that, among nine entity types, including Parameters, the F1-scores all exceeded 60%, indicating more accurate entity recognition compared to conventional methods. Knowledge embedding was performed using the TransH inference algorithm, which outperformed traditional models in all reasoning metrics, with a Hits@10 of 0.636. This verifies its strong capability in capturing complex causal paths among cost factors, making it suitable for practical cost optimization. On this basis, a symmetry-aware BERT–BiLSTM–CRF knowledge graph of open-pit coal mining costs was constructed. Knowledge embedding was then performed with the TransH inference algorithm, and latent relationships among cost factors were mined. Finally, a knowledge-graph-based cost factor identification system was developed. The system lists, for each cost item, the influencing factors and their importance ranking, analyzes variations in relevant factors, and provides decision support. Full article

The reclamation of exhausted open-pit coal mines is an energy-intensive and costly process. Traditional methods offer no economic return. This study explores the feasibility of using autonomous electric dump trucks (EDTs) to fill the pit, leveraging regenerative braking during descent to generate energy and reduce operational costs. A comprehensive energy balance model was developed based on the operational cycle of the Komatsu HD605-7 (E-Dumper) in the unique downhill-loaded logistics of the Pery quarry. The model incorporates vehicle dynamics equations, including rolling resistance, gradient, and aerodynamic forces, to calculate net energy consumption per cycle. Three energy storage system (ESS) configurations were compared: NMC/NCA batteries, LiFePO₄ (LFP) batteries, and a hybrid LFP + supercapacitor (SC) system. Simulation results demonstrate that the net energy per cycle decreases with increasing payload capacity, even becoming negative (net energy generation) for loads above 110 tons due to powerful regenerative braking on the 13% descent grade. The hybrid LFP + SC system proved most efficient, achieving the lowest specific energy consumption (kWh/ton) by effectively capturing high-power regenerative currents. While LFP batteries have a lower energy density, their superior cycle life, thermal stability, and safety make them the optimal choice for the harsh mining environment. The proposed operation strategy, utilizing EDTs in a downhill-loaded cycle, transforms mine reclamation from a cost center into a potentially energy-neutral or even energy-positive process. A hybrid ESS with LFP batteries and supercapacitors is recommended as the most reliable and efficient solution for this specific application. Full article

The rational delineation of open-pit mining areas constitutes the core foundation for achieving safe, efficient, economical, and sustainable mining operations. The quality of this decision-making directly impacts the economic benefits experienced throughout the mine’s entire lifecycle and the efficiency of resource recovery. Traditional open-pit mining area delineation relies on an experience-driven manual process that is inefficient and incapable of real-time dynamic data optimization. Thus, there is an urgent need to establish an intelligent decision-making model integrating multi-source data and multi-objective optimization. To this end, this study proposes an intelligent mining area division algorithm. First, a geological complexity quantification model is constructed, incorporating innovative adaptive discretisation resolution technology to achieve precise quantification of coal seam distribution. Second, based on the quantified stripping-to-mining ratio within grids, a block-growing algorithm generates block grids, ensuring uniformity of the stripping-to-mining ratio within each block. Subsequently, a matrix of primary directional variations in the stripping-to-mining ratio is constructed to determine the principal orientation for merging blocks into mining areas. Finally, intelligent open-pit mining area delineation is achieved by comprehensively considering factors such as the principal direction of mining areas, geological conditions, boundary shapes, and economic scale. Practical validation was conducted using the Shitoumei No. 1 Open-Pit Coal Mine in Xinjiang as a case study in engineering. Engineering practice demonstrates that adopting this methodology transforms mining area delineation from an experience-driven to a data-driven approach, significantly enhancing delineation efficiency. Manual simulation of a single scheme previously required approximately 15 days. Applying the methodology proposed herein reduces this to just 0.5 days per scheme, representing a 96% increase in efficiency. Design costs were reduced by approximately CNY 190,000 per iteration. Crucially, the intelligently recommended scheme matched the original design, validating the algorithm’s reliability. This research provides crucial support for theoretical and technological innovation in intelligent open-pit coal mining design, offering technical underpinnings for the sustainable development of open-pit coal mines. Full article

Open-pit mining often induces geological hazards such as slope instability, surface subsidence, and ground fissures. To support sustainable mine operations and safety, high-resolution monitoring and mechanism-based interpretation are essential tools for early warning, risk management, and compliant reclamation. This study focuses on the Baorixile open-pit coal mine in Inner Mongolia, China, where 48 Sentinel-1 images acquired between 3 March 2017 and 23 April 2021 were processed using the Small-Baseline Subset and Distributed-Scatterer Interferometric Synthetic Aperture Radar (SBAS-DS-InSAR) technique to obtain dense and reliable time-series deformation. Furthermore, a Trend–Periodic–Residual Subspace-Constrained Regression (TPRSCR) method was developed to decompose the deformation signals into long-term trends, seasonal and annual components, and residual anomalies. By introducing Distributed-Scatterer (DS) phase optimization, the monitoring density in low-coherence regions increased from 1055 to 338,555 points (approximately 321-fold increase). Deformation measurements at common points showed high consistency ($R^2$ = 0.97, regression slope = 0.88; mean rate difference = −0.093 mm/yr, standard deviation = 3.28 mm/yr), confirming the reliability of the results. Two major deformation zones were identified: one linked to ground compaction caused by transportation activities, and the other associated with minor subsidence from pre-mining site preparation. In addition, the deformation field exhibits a superimposed pattern of persistent subsidence and pronounced seasonality. TPRSCR results indicate that long-term trend rates range from −14.03 to 14.22 mm/yr, with a maximum periodic amplitude of 40 mm. Compared with the Seasonal-Trend decomposition using LOESS (STL), TPRSCR effectively suppressed “periodic leakage into trend” and reduced RMSEs of total, trend, and periodic components by 48.96%, 93.33%, and 89.71%, respectively. Correlation analysis with meteorological data revealed that periodic deformation is strongly controlled by precipitation and temperature, with an approximately 34-day lag relative to the temperature cycle. The proposed “monitoring–decomposition–interpretation” framework turns InSAR-derived deformation into sustainability indicators that enhance deformation characterization and guide early warning, targeted upkeep, climate-aware drainage, and reclamation. These metrics reduce downtime and resource-intensive repairs and inform integrated risk management in open-pit mining. Full article

The stability of internal dumps in open-pit coal mines is critical for the safe production and economic performance of the entire mine. To further enhance slope stability and ensure safe production, a new method for constructing trenches (referred to as an anti-sliding trench) on the sloped basal bed of the dump slope in open-pit mines was proposed to improve slope stability. The internal dump slope at the Luzigou anticline of the Anjialing Open-Pit Mine was studied. The slope failure modes of the dumping steps were studied experimentally and by numerical simulations at different widths of anti-slide trenches at the slope’s toe in a staged loading state. Without anti-slide trenches, shear-layer and along-layer failure modes occurred, while the failure modes with anti-slide trenches included shear-layer, along-layer, and squeeze-out failure. Based on the limit equilibrium theory and the determined failure modes, the preset anti-slide trenches at the toe of the dumping steps were theoretically analyzed. The relationships between the slope stability coefficient and the width and depth of anti-slide trenches, as well as the physical and mechanical parameters of the slope body, were derived. Given the physical and mechanical parameters of the slope body and targeted improvement in the slope stability coefficient, the size parameters of anti-slide trenches were designed and optimized through the derived relationships. At the Anjialing Coal Mine, presetting anti-slide trenches with a depth of 1.5 m and a width of 22.68 m at the toe of the dumping steps increased the slope stability coefficient from 1.3095 to 1.6. The proposed method provides a guiding reference for designing similar internal dump slopes in open-pit coal mines and for disaster prevention. Full article

Coal seams, as critical components of open-pit mine slopes, are subjected to both quasi-static and dynamic loading disturbances during mining operations, with their mechanical properties directly influencing the slope stability. Consequently, to clarify the mechanical properties and failure mechanisms of coal seams affected by the strain rate under the static–dynamic loading conditions, the mineral composition and meso-structural characteristics of lignite were analyzed in this study, and uniaxial compression tests with different quasi-static loading rates and dynamic compression tests with different impact velocities were conducted. The results indicate that there is an obvious horizontal bedding structure in lignite, which leads to differences in mechanical response and failure mechanism at different strain rates. Under the quasi-static loading, lignite exhibits significantly lower strain-rate sensitivity than compared to dynamic impact conditions. The Poisson’s ratio difference between the bedding matrix and the lignite will produce interfacial friction, which gradually decreases with the increase in the distance from the interface, thus promoting the transformation of lignite from multi-crack tensile shear mixed fracture to single-crack splitting failure. Under the dynamic impact conditions, low-impact velocities induce stress wave reflection at bedding interfaces due to wave impedance disparity between the matrix and lignite, generating tensile strains that result in bedding-plane delamination failure; at higher velocities, incomplete energy absorption by the rock specimen leads to fragmentation failure of lignite. These findings are of great significance for the stability analysis of open-pit slopes. Full article

In response to the insufficiency of shear strength and severe segregation of cemented backfilling material in coal mines, a shear strength test, static segregation index test, and homogeneity degree test were carried out, taking slurry concentration (SC) as the main control factor. The effect law of SC on shear strength, the static segregation index, and the homogeneity degree was discussed. The relationship between the static segregation index and homogeneity degree and shear strength was analyzed, and the action mechanism of SC on shear strength was revealed. The research results show that for cemented backfill in coal mines, with a suspending agent content of 0 and a curing age of 28 d, when SC increases from 77% to 80%, shear strength increases by 31.43%, the static segregation index of the backfilling slurry decreases by 40.29%, and the homogeneity degree of the backfill increases by 69.23%. The increase in SC can enhance shear strength, reduce the segregation degree of backfilling slurry, and improve the homogeneity of backfill. The reason for the increase in shear strength lies in the fact that SC reduces the segregation degree of the backfilling slurry. The research in this paper has certain guiding significance for the timely support of the surrounding rock in the working face and the effective control of surface settlement. Full article

The depletion of shallow coal reserves necessitates a shift from open-pit to underground mining, increasing the need for safe and efficient backfill systems. However, traditional backfill materials—especially cement—are costly and environmentally burdensome. To address this, our study explores a sustainable alternative using industrial waste, contributing to the principles of a circular economy. This research presents a novel backfill formulation that achieves full cement replacement through the use of fly ash, supplemented with nanocrystalline silica and glass fiber to enhance strength and setting dynamics. Eighteen sample sets were prepared for each composition, using consistent mixing, curing, and testing protocols. Mechanical strength was evaluated at multiple curing intervals alongside microstructural characterization using SEM and XRD. The results show that mixtures containing nanomodified silica and fiber exhibit significantly improved compressive, shear, and splitting strength—up to 40% higher than fly ash-only compositions. Microstructural analysis revealed accelerated C-S-H gel development, reduced porosity, and more uniform pore structures over time. These findings confirm the mechanical viability and economic potential of waste-based backfill systems. The proposed formulation enables safer underground operations, improved extraction efficiency, and reduced environmental impact—offering a scalable solution for modern coal mining. Full article

The stability of open-pit mines under low-temperature conditions is critical for safe and efficient coal extraction. However, the mechanisms of rock damage and fracture under combined temperature and stress effects remain unclear, particularly regarding the evolution of mechanical properties under repeated freeze–thaw cycles and varying peripheral pressures. This study investigates the damage and rupture behavior of coal-bearing sandstone in cold-region open-pit mines through experimental testing and theoretical modeling. The research was conducted in three stages: (1) freeze–thaw and peripheral pressure experiments to evaluate mechanical property evolution; (2) acoustic emission monitoring to analyze internal fracture initiation, propagation, and coalescence under temperature–stress coupling; (3) development of a local deterioration model to quantify post-damage strength decay considering low-temperature erosion and freeze–thaw effects. Results show that increasing freeze–thaw cycles leads to a transition from brittle to ductile behavior, while higher peripheral pressures significantly enhance ductility. Mechanical parameters are highly sensitive to peripheral pressure but largely independent of freeze–thaw cycle count. Acoustic emission signals respond strongly to temperature, and temperature–stress coupling governs the three-stage evolution of fracture germination, extension, and penetration. The local deterioration model effectively captures post-peak residual strength and damage evolution. These findings indicate that in regions with higher microcrack density, fault propagation is driven by rapid coalescence under stress concentration, whereas in lower-density regions, it is dominated by gradual fracture growth and temperature-induced expansion. The results provide theoretical guidance for stability assessment and support design in open-pit coal mines in cold environments. Full article

Slope instability in open-pit coal mines threatens safety and infrastructure. Displacement phenomena (cracks, deflection, heaving) signal potential failure. While counterweight backfilling stabilizes slopes, site-specific protocols for heterogeneous settings, such as Indonesia’s Barito Basin (Warukin Formation), lack standardization. This study addresses this gap at PT. Bhumi Rantau Energi’s Mahoni Pit by integrating high-resolution displacement monitoring (Leica Nova TM50), geotechnical analysis (RQD, RMR), and numerical modeling (SLIDE 7.0, RS2 v11). The objectives were to characterize the displacement mechanisms, quantify the counterweight effectiveness, and optimize the geometry. The results show “warning”-level velocities (>10 mm.h⁻¹) across points, with peak displacement (907 mm.day⁻¹ at IPD_MHN_26) driven by pore pressure in weak fill/mud layers (c′: 2–20 kPa; thickness: 71–100 m). Counterweights significantly increased the Factor of Safety (FoS) from critical levels (e.g., 0.960, PF = 74.4%) to stable values (e.g., 1.160, PF = 1.8%), representing 20–35% improvements. RS2 identified fill material as the primary displacement zone (max: 2.10 m). Optimized designs featured phased backfilling (200 k–10 M BCM) with a 50 m width and 11° inclination. Tailored counterweight deployment effectively mitigated the instability in slopes underlain by weak strata. The integrated approach provides a validated framework for optimizing designs in similar sedimentary basins, enhancing safety and reducing costs. Full article