Search Results (594)

Slope failures in open-pit mining pose significant operational and safety issues, underscoring the importance of implementing effective stability monitoring frameworks for early hazard detection to allow for timely intervention and risk mitigation. This systematic review presents a comprehensive synthesis of existing and emerging methods and technologies used for slope stability monitoring in open-pit mining, including both remote sensing and in situ methods, as well as advanced technologies, such as Artificial Intelligence (AI), the Internet of Things (IoT), and Wireless Sensor Networks (WSNs). Using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines, a total of 49 studies were selected from a collection of four engineering databases, and a comparative analysis was conducted to determine the underlying differences between the various methods for open-pit slope stability monitoring in terms of their performance across key attributes, such as monitoring accuracy, spatial and temporal coverage, operational complexity, and economic viability. Their juxtaposition highlighted the notion that no universally optimal slope stability monitoring system exists, due to a series of compromises that arise as a result of inherent technological limitations and site-specific constraints. Notably, remote sensing methods offer large-scale, non-intrusive monitoring, but are often limited by environmental factors and data acquisition infrequency, whereas in situ methods provide high precision, but suffer from limited spatial coverage and scalability. This review further highlights the capacity of emerging methods and technologies to address these limitations, providing suggestions for future research directions involving the integration of multiple sensing technologies for the enhancement of monitoring capabilities. This study provides a consolidated knowledge base on open-pit slope stability monitoring methods, technologies, and techniques, to guide the development of integrated, cost-effective, and scalable slope monitoring solutions that enhance mine safety and efficiency. Full article

Land reclamation is crucial for restoring ecosystems in mining areas, improving land use efficiency, and promoting sustainable regional development. Traditional single-indicator assessments fail to capture the full complexity of reclamation, highlighting the need for a more comprehensive evaluation approach. This study combines field-measured and remote sensing data to develop multiple evaluation indices, creating a comprehensive framework to assess reclamation effectiveness. A soil quality index based on the Minimum Data Set (SQI_MDS) was developed to analyze spatial variations in soil quality, efficiently capturing key soil attributes. Remote sensing data were used to calculate the Dump Reclamation Disturbance Index (DRDI) and the Enhanced Coal Dust Index (E_CDI) to evaluate vegetation recovery and ecological improvements. The Comprehensive Evaluation Quality Index (CEQI) was introduced, synthesizing soil, vegetation, and ecological conditions for a holistic assessment. Key findings include significant soil quality improvement over time, with MDS effectively capturing variations; vegetation recovery increased with reclamation duration, though regional disparities were observed; ecological conditions steadily improved, as evidenced by a decline in ECDI values and reduced contamination; and the CEQI reflected overall improvements in reclamation effectiveness. This study offers a practical framework for coal mining land reclamation, providing scientific support for decision-making and guiding effective reclamation strategies for ecological restoration and sustainable land management. Full article

With the increasing mining depth, the stability of open-pit mine slopes has become an increasingly important concern. This study focuses on an open-pit mine in Southwest China and utilizes unmanned aerial vehicle (UAV) technology to gather data from these high and steep slopes. First, high-precision digital surface models and digital orthophoto data are collected using UAV terrain-following flight technology. However, two major challenges arise when applying geographic information systems (GISs) to this issue. The first challenge is that the extreme steepness of the slopes causes overlapping lithological layers at the same location, which GISs cannot resolve. The second challenge is that GISs cannot assess the influence of faults on landslides by calculating three-dimensional spatial distances. To overcome these issues, this study proposes the construction of a detailed 3D geological model for the entire mining area. This model allows for a more precise analysis of the lithology and fault spatial distances. A GIS is then applied to analyze the slope, curvature, and slope direction. Multi-source data fusion is employed to link spatial coordinates and create a dataset for further analysis. Five machine learning models for landslide prediction are compared using this dataset. Based on these comparisons, a high-precision random forest and slope boosting coupled method is developed to enhance the landslide prediction accuracy. Finally, a numerical simulation of a regional focus area is conducted, simulating the excavation process of an open-pit mine and analyzing the timing, location, and state of potential landslides. The results indicate that combining machine learning and multi-source data fusion provides a highly accurate, efficient, and straightforward method for landslide prediction in the high and steep slopes of open-pit mines. Full article

This article presents a comparative analysis of rock mass fracturing at the Karasu gold deposit, located approximately 400 km northwest of Karaganda, Kazakhstan. The analysis is based on core drilling data and measurements from underground workings, including an old mine that was explored and investigated to gather missing information. The spatial characteristics of fractures and their relationship with tectonic faults are identified. The feasibility of using the Rock Quality Designation (RQD) index for classifying fracture systems is assessed. Engineering and geological studies include the identification of major fracture systems and their characteristics using Leapfrog and Rocscience software, chosen for their ease of use and extensive functionality. The stability parameters of open-pit slopes are calculated, considering the physical and mechanical properties of rocks, the degree of fracturing, and the influence of groundwater. Key engineering and geological elements of the rock mass are identified, emphasizing the necessity of integrating fracture data from various sources to improve the accuracy of mine design and ensure the safe operation of open pits. These studies are part of the exploration phase to assess the geological situation and the physico-mechanical properties of these rocks for further quarry design. Full article

The transition from open pit to underground mining intensifies water-related hazards such as Acid Mine Drainage (AMD), groundwater contamination, and aquifer depletion, threatening ecological and socio-economic sustainability. This study develops an Inclusive Disaster Risk Reduction (IDRR) framework using a Multi-Dimensional Risk (MDR) approach to holistically assess water hazards in China’s mining regions, integrating environmental, social, governance, economic, technical, community-based, and technological dimensions. A Multi-Criteria Decision-Making (MCDM) model combining the Fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) evaluates risks, enhanced by a Z-number Fuzzy Delphi AHP (ZFDAHP) spatiotemporal model to dynamically weight hazards across temporal (short-, medium-, long-term) and spatial (local to global) scales. Applied to the Sijiaying Iron Mine, AMD (78% severity) and groundwater depletion (72% severity) emerge as dominant hazards exacerbated by climate change impacts (36.3% dynamic weight). Real-time IoT monitoring systems and AI-driven predictive models demonstrate efficacy in mitigating contamination, while gender-inclusive governance and community-led aquifer protection address socio-environmental gaps. The study underscores the misalignment between static regulations and dynamic spatiotemporal risks, advocating for Lifecycle Assessments (LCAs) and transboundary water agreements. Policy recommendations prioritize IoT adoption, carbon–water nexus incentives, and Indigenous knowledge integration to align mining transitions with Sustainable Development Goals (SDGs) 6 (Clean Water), 13 (Climate Action), and 14 (Life Below Water). This research advances a holistic strategy to harmonize mineral extraction with water security, offering scalable solutions for global mining regions facing similar ecological and governance challenges. Full article

With the gradual depletion of mineral resources in temperate regions, cold regions have become primary areas for mineral extraction. However, the freeze–thaw phenomena induced by temperature fluctuations pose significant threats to the stability of rock masses on open−pit mine slopes, further affecting normal mining operations. To investigate the strength degradation and stability evolution patterns of freeze–thaw slope rock masses, this study takes the Wushan Open−Pit Mine as its engineering context. We analyzed the relationship between rock temperature and burial depth, conducted freeze–thaw cyclic tests under realistic temperature ranges, and developed a mechanical parameter characterization model for freeze–thaw rock masses by integrating the generalized Hoek–Brown strength criterion. Slope safety factors and potential landslide mechanisms were determined through numerical simulations and the strength reduction method. Key findings include the following: (1) Shallow rock temperatures exhibit high synchronization with atmospheric temperature, characterized by large fluctuations and rapid variation rates, whereas deep rock demonstrates opposite trends. (2) As freeze–thaw cycles increase and burial depth decreases, the internal friction angle and cohesion of slope rock masses follow negative exponential decay functions. After 20 freeze–thaw cycles, the internal friction angle and cohesion of rock at a 5.27 m depth decreased by 18.36% and 33.92%, respectively. In contrast, rock at a 0.10 m depth showed more severe reductions of 31.81% and 50.14%. (3) Increasing freeze–thaw cycles progressively lower the safety factors of slope benches, with potential slip surfaces displaying reduced average depths and curvature, alongside elevated dip angles. These findings provide critical insights for preventing freeze–thaw−induced landslide hazards in cold−region open−pit mine slopes. Full article

The duration of water immersion significantly affects the mechanical response of rock materials. This study investigated the weakly cemented sandstone from the Wulagen Open-pit Mine to examine how varying immersion times affected the mineral composition, micro-porous structure, and macro-mechanical properties of the sandstone. The current study aimed to explore the mechanisms underlying the degradation of the strength and deformability of sandstone due to prolonged water exposure. The analysis showed that immersion time notably influenced the pore structure as well as the mineralogical characteristics of weakly cemented sandstone. These changes were the primary factors leading to alterations in its mechanical properties and failure modes. Specifically, with increasing immersion time, clay minerals absorbed water and expanded, with the most significant expansion occurring between 30 and 60 days. This rapid internal crack growth led to an exponential decrease in compressive strength and elastic modulus, with the most significant decline occurring between 30 and 60 days. The failure mode of the sandstone transitioned from extensional fracture to shear failure. Acoustic emission analysis revealed that, in the dry state, tensile cracks were about three times more prevalent than shear cracks, while after 60 days of immersion, shear cracks accounted for over 80%. After 60 days of immersion, microscopic cracks were fully interconnected, and the mechanical properties of the sandstone showed minimal change, with shear failure becoming predominant. These experimental results provide theoretical guidance for preventing the collapse of slopes composed of weakly cemented rock under long-term immersion conditions. Full article

An important process in the mining industry is material handling, where trucks are responsible for transporting materials extracted by shovels to different locations within the mine. The decision about the destination of a truck is very important to ensure an efficient material handling operation. Currently, this decision-making process is managed by centralized systems that apply dispatching criteria. However, this approach has the disadvantage of not providing accurate dispatching solutions due to the lack of awareness of potentially changing external conditions and the reliance on a central node. To address this issue, we previously developed a multi-agent system for truck dispatching (MAS-TD), where intelligent agents representing real-world equipment collaborate to generate schedules. Recently, we extended the MAS-TD (now MAS-TDRL) by incorporating learning capabilities and compared its performance with the original MAS-TD, which lacks learning capabilities. This comparison was made using simulated scenarios based on actual data from a Chilean open-pit mine. The results show that the MAS-TDRL generates more efficient schedules. Full article

The implementation of fleet management software in mining operations poses challenges, including high initial costs and the need for skilled personnel. Additionally, integrating new software with existing systems can be complex, requiring significant time and resources. This study aims to mitigate these challenges by leveraging advanced technologies to reduce initial costs and minimize reliance on highly trained employees. Through the integration of computer vision and multi-objective optimization, it seeks to enhance operational efficiency and optimize fleet management in open-pit mining. The objective is to optimize truck-to-excavator assignments, thereby reducing excavator idle time and deviations from production targets. A YOLO v8 model, trained on six hours of mine video footage, identifies vehicles at excavators and dump sites for real-time monitoring. Extracted data—including truck assignments and excavator ready times—is incorporated into a multi-objective binary integer programming model that aims to minimize excavator waiting times and discrepancies in target truck assignments. The epsilon-constraint method generates a Pareto frontier, illustrating trade-offs between these objectives. Integrating real-time image analysis with optimization significantly improves operational efficiency, enabling adaptive truck-excavator allocation. This study highlights the potential of advanced computer vision and optimization techniques to enhance fleet management in mining, leading to more cost-effective and data-driven decision-making. Full article

This study was conducted at a fixed monitoring site in the southern dump of the large-scale Antaibao open-pit coal mine of China Coal Pingshuo, using long-term monitoring methods. Based on data from 2019 and 2024 in the reclaimed area of the Pingshuo open-pit coal mine, all seedlings and saplings within the Robinia pseudoacacia L. + Ulmus pumila L. + Ailanthus altissima (Mill.) Swingle mixed forests were studied to analyze changes in their abundance and the driving factors influencing their survival rates from 2019 to 2024. The main conclusions are as follows: (1) The species composition of seedlings and saplings remained unchanged but the number of seedlings increased significantly. The majority of newly recruited seedlings were U. pumila., accounting for 92.22% of the total new seedlings, whereas R. pseudoacacia had the highest mortality rate among seedlings. The distribution patterns of seedling-to-sapling transition, sapling-to-tree transition, and seedling–sapling mortality were generally consistent with the overall distribution of seedlings and saplings at the community level. (2) At both the community and species levels, the optimal models for seedling and sapling survival were the height model and the biological factor model. Overall, survival rates of both seedlings and saplings showed a significant positive correlation with height. (3) The biological factors affecting the survival of U. pumila saplings were the basal area (BA) at breast height and the number of conspecific adult trees. The former was significantly negatively correlated with U. pumila seedling survival, while the latter was positively correlated. For R. pseudoacacia seedlings, the key biological factors were the number of heterospecific adult trees and the number of heterospecific seedlings. The former was significantly negatively correlated with survival, whereas the latter was significantly positively correlated. The primary factor influencing sapling survival was sapling height, which showed a significant positive correlation. Full article

This study systematically analyzes the influence of the charge length-to-diameter ratio and stemming length on the radius and volume of blasting craters in coal and rock blasting crater tests to effectively address the challenge of achieving coal–rock separation in mixed blasting construction. In addition, it examines the energy distribution mechanism of blasting fragmentation and establishes characteristic equations for coal and rock blasting craters. Numerical simulations and blasting tests are conducted to investigate the casting effect of rock benches and the fragmentation characteristics of coal and rock benches under different charge structures. The results indicate that when the ratio of charge length to stemming length exceeds 0.91 and 0.74 for the coal and rock benches, respectively, the utilization rate of explosive energy for rock fragmentation gradually surpasses that for rock throwing. The charging structure is identified as a key factor in achieving coal–rock mixed blasting and separation mining. The explosive energy is effectively utilized with a bottom interval length of 2 m for rock benches and a stemming length ranging from 2.5 to 3 m for coal seams. This configuration raises the connectivity of rock damage cracks, improves the distribution of tensile cracks at the top of the coal seam, and prevents bulging or coal–rock interactions (blasting mixing) at the coal–rock interface. The findings demonstrate that the optimized charging structure effectively achieves separate mining in coal–rock mixed blasting, fulfilling the requirement of avoiding coal–rock mixing during blasting. The research provides valuable mining strategies and technical experience for achieving separate mining in coal–rock mixed blasting in open-pit coal mines and improving the recovery of thin coal seams. Full article

As the world’s largest open-pit coal producer, China faces severe dust pollution in mining operations. Cabins of mining equipment (electric shovels, haul trucks, drills) exhibit unique micro-environmental contamination due to dual-source pollution (external infiltration and internal secondary dust generation), posing severe health risks to miners. This study focused on electric shovel cabins at the Heidaigou open-pit coal mine to address cabin dust pollution. Through analysis of dust physicochemical properties, a pollution characteristic database was established. Field measurements and statistical methods revealed temporal–spatial variation patterns of dust concentrations, quantifying occupational exposure risks and providing theoretical foundations for dust control. A novel gradient-pressurized air purification system was developed for harsh mining conditions. Key findings include the following. (1) Both coal-shovel and rock-shovel operators were exposed to Level I (mild hazard level), with rock-shovel operators approaching Level II (moderate hazard level). (2) The system reduced respirable dust concentrations from 0.313 mg/m³ to 0.208 mg/m³ (≥33.34% improvement) in coal-shovel cabins and from 0.625 mg/m³ to 0.421 mg/m³ (≥32.64% improvement) in rock-shovel cabins. These findings offer vital guidance for optimizing cabin design, improving dust control, and developing scientific management strategies, thereby effectively protecting miners’ health and ensuring operational safety. Full article

In the Posušje region of the External Dinarides (Bosnia and Herzegovina), bauxite deposits are hosted along a Late Cretaceous–Paleogene forebulge unconformity that records an extended emersion phase of the Adriatic Carbonate Platform. Historically, open-pit mining has targeted surface and shallow subsurface bauxite bodies, but ongoing exploration must now focus on deeper structurally preserved deposits. To address this challenge, we integrate remote sensing, geological mapping, borehole data, and 3D structural modeling to assess the distribution and structural controls of bauxite deposits. Balanced and restored cross-sections reveal a complex interplay between inverted normal faults, fold structures, and foredeep burial, which collectively influenced bauxite accumulation and preservation. Statistical analyses of deposit size, shape, and orientation indicate that larger bauxite bodies are concentrated in the footwalls of inverted normal faults, where prolonged or repeated exposure enhanced karst development and bauxite accumulation. Additionally, the predominant NW–SE elongation of bauxite bodies suggests that pre-existing structural lineaments played a key role in paleokarst morphology, supporting the influence of syn-depositional extensional faulting on bauxite distribution. These findings demonstrate that bauxite exploration in fold–thrust belts requires an integrated structural approach, where 3D geological modeling can delineate prospective areas prior to costly geophysical surveys and drilling campaigns. Insights from the Posušje region can refine mineral exploration strategies in other orogenic settings, highlighting the importance of structural inheritance in karst bauxite accumulation and preservation. Full article

The motor drive system is pivotal for vehicles, particularly in new energy applications. However, conventional hybrid systems, which combine generator sets and single batteries in parallel configurations, fail to meet the operational demands of large pure electric mining dump trucks under fluctuating power requirements—such as high reserve power during acceleration and robust energy recovery during braking. Traditional single-motor configurations struggle to balance low-speed, high-torque operations and high-speed driving within cost-effective ranges, often necessitating oversized motors or multi-gear transmissions. To address these challenges, this paper proposes a dual-motor symmetric powertrain configuration with a seven-speed gearbox, tailored to the extreme operating conditions of mining environments. By integrating a high-speed, low-torque motor and a low-speed, high-torque motor through dynamic power coupling, the system optimizes energy utilization while ensuring sufficient driving force. The simulation results under extreme conditions (e.g., 33% gradient climbs and heavy-load downhill braking) demonstrate that the proposed configuration achieves a peak torque of 267 kNm (200% improvement over single-motor systems) and a system efficiency of 92.4% (vs. 41.7% for diesel counterparts). Additionally, energy recovery efficiency reaches 85%, reducing energy consumption to 4.75 kWh/km (83% lower than diesel trucks) and life cycle costs by 38% (USD 5.34/km). Field tests in open-pit mines validate the reliability of the design, with less than a 1.5% deviation in simulated versus actual performance. The modular architecture supports scalability for 60–400-ton mining trucks, offering a replicable solution for zero-emission mining operations in high-altitude regions, such as Tibet’s lithium mines, and advancing global efforts toward carbon neutrality. Full article

Artificial intelligence in the mining industry is key to improving safety, optimizing resources, and ensuring sustainable operations in complex environments. The main objective of this research is to develop an autonomous mobile station equipped with artificial vision and artificial intelligence to identify and track equipment, people, and animals in critical areas of mining operations, issuing real-time alerts to reduce occupational risks and improve operational control. The research is applied with an experimental approach, designed to validate the effectiveness of the proposed system in real open-pit mining environments. The proposed methodology consisted of five stages: (i) Selection of data collection equipment, (ii) Definition of the positioning scheme, (iii) Incorporation of the communication system, (iv) Data processing and transformation, and (v) Equipment identification and tracking. The results showed an average accuracy of 98% in the validation and 95% in the test, achieving perfect performance (100%) in key categories such as excavators and drills, highlighting the potential of this technology to transform mining towards safer and more efficient standards. Full article