Mining

The thermal regime of underground mines, shaped by air temperature, velocity, and relative humidity, is a crucial factor for production and the health and safety of miners. While many aspects of this thermal regime have been thoroughly studied in the literature, local heat sources from mechanized equipment, such as load–haul–dump machines, conveyors, and auxiliary fans, have received comparatively little attention despite their significant impact on the thermal environment in mining development areas and stopes. This paper presents findings from a comprehensive study of the microclimatic air parameters in several nickel–copper and potash mines. We focus specifically on variations in air temperature in areas where mining equipment is operational. The heat output from different types of equipment, including load–haul–dump units, cutter–loaders, drilling rigs, conveyors, and auxiliary fans, has been quantified. We established empirical relationships for heat emissions from these machines and conducted a comparative analysis of their heat outputs. The main advantage of these relationships is their simplicity and the minimal number of input parameters required, making them practical for use in the field. Full article

Decreasing the rockburst potential in longwall mining of burst-prone coal seams has been a longstanding challenge for geotechnical engineering worldwide. One of the effective approaches is drilling of relief boreholes in front of the coal seam face from the airways. This work presents a novel approach based on the integral rockburst factor ($K_{Irb}$) taking account of the length of the dynamic abutment stress influence zone and the ratio of the vertical stress to the remote field virgin stress. The geotechnical conditions of seam 3 of the Alardinskaya mine (Kuznetsky basin, Russia) are taken as a study site. An approach of the finite-difference continuum damage mechanics is employed to describe the processes of deformation and fracture of coal and host rocks using an in-house software. The results indicate that the abutment stress maximum shifts deep into the seam after drilling and that the stress distribution along the coal seam horizon is a superposition of the solutions similar to those of the elastoplastic Kirsch problem. The results also indicate that the curves of $K_{Irb}$ dependence on spacing between the boreholes and their diameter are nonlinear and non-monotonic functions, which allows for optimizing of the drilling technology. Full article

Hyperspectral imaging technology holds great potential for various stages of the mining life cycle, both in active and abandoned mines, from exploration to reclamation. The technology, however, has yet to achieve large-scale industrial implementation and acceptance. While hyperspectral satellite imagery yields high spectral resolution, a high signal-to-noise ratio (SNR), and global availability with breakthrough systems like EnMAP, EMIT, GaoFen-5, PRISMA, and Tanager-1, limited spatial and temporal resolution poses challenges for the mining sectors, which require decimetre-to-centimetre-scale spatial resolution for applications such as reconciliation and environmental monitoring and daily temporal revisit times, such as for ore/waste estimates and geotechnical assessments. Hyperspectral imaging from drones (Uncrewed Aerial Systems; UASs) offers high-spatial-resolution data relevant to the pit/mine scale, with the capability for frequent, user-defined re-visit times for areas of limited extent. Areas of interest can be defined by the user and targeted explicitly. Collecting data in the visible to near and shortwave infrared (VNIR-SWIR) wavelength regions offers the detection of different minerals and surface alteration patterns, potentially revealing crucial information for exploration, extraction, re-mining, waste remediation, and rehabilitation. This is related to but not exclusive to detecting deleterious minerals for different processes (e.g., clays, iron oxides, talc), secondary iron oxides indicating the leakage of acid mine drainage for rehabilitation efforts, swelling clays potentially affecting rock integrity and stability, and alteration minerals used to vector toward economic mineralisation (e.g., dickite, jarosite, alunite). In this paper, we review applicable instrumentation, software components, and relevant studies deploying hyperspectral imaging datasets in or appropriate to the mining sector, with a particular focus on hyperspectral VNIR-SWIR UASs. Complementarily, we draw on previous insights from airborne, satellite, and ground-based imaging systems. We also discuss common practises for UAS survey planning and ground sampling considerations to aid in data interpretation. Full article

The study evaluates the socioeconomic dynamics and their impact on life expectancy in coal mining communities in Colombia, aligning with the Sustainable Development Goals (SDGs), assessing the relationship between production, occupation, accident rates, mortality and royalties. Univariate, bivariate, path analysis and ARIMA models were used to identify patterns and projections. The results show a positive constraint between coal production and royalties, which is negative with the occupation, accident, and mortality rates. Despite the revenues generated, no improvements in the quality of life of mining communities are observed; the poor use of royalties reflects a lack of effective strategies to convert mining revenues into sustainable enhancements for local communities. It highlights the rush for more effective public policies to ensure that economic benefits are aligned with improvements in communities’ health, safety and quality of life. In the future, greater alignment with the SDGs, particularly SDG 3 (Health and Well-being) and SDG 8 (Decent Work and Economic Growth), will depend on a sustainable approach that prioritises investment in social infrastructure and the equitable distribution of resources derived from mining, thereby addressing current disparities. Full article

Amazon rainforests have many hidden treasures; thus, a balance between mine activities and the environment must be maintained. In the northern region of Brazil, there is a large diversity of metal ore deposits, the exploitation of which requires innovative and sustainable mining operations. Historically, mining operations have caused various environmental issues, such as landscape deterioration, damage to natural structures due to detonations, and soil and water pollution, and have also contributed to CO₂ emissions from diesel trucks. Here, to estimate and minimize the operating expenses of a large-scale open-pit iron mine, a mine-to-crusher model was developed. The calibration of the mine-to-crusher model was based on rock fragmentation from the blasting phase through the primary crushing phase from an analysis of pictures of the fragmented pile. A reduction in cost was determined for an optimum 90% passing size (P90). The calibration was performed with technical and economic parameters from 2 years before. For the studied iron ore mine site, an optimum P90 value between 0.29 and 0.31 m was determined. Full article

Mineral processing is a crucial stage in the mining process, involving comminution and concentration stages. Comminution is modeled using various ore variables and operational parameters, representing a complex system. An alternative to simplifying the complexity of these stages is adopting machine learning (ML) techniques; however, ML often requires a substantial amount of data for effective training and validation. The conjoint analysis methodology was used to develop a procedure for discretizing input variables and reducing the data needed for training neural networks, requiring only 77 different scenarios. Using the results from a comminution plant simulator built in Matlab Simulink, neural networks were trained to predict the key output parameters, such as the water consumption, energy consumption, operational parameters, and particle size generated by the plant. The predictive capability of the neural networks was excellent, achieving R² > 0.99 in all cases. The networks were tested with a new set of scenarios to assess their response to values not categorized in the discretization process, achieving R² > 0.98. However, the prediction capability was lost for out-of-range input variables. This approach is attractive for developing easy-to-implement ML tools capable of representing complex systems without needing large amounts of input data, thereby simplifying the modeling process in mineral processing. Full article

The South African gold mining industry requires complex water reticulation systems to deliver chilled water to underground production areas. However, chilled- and service-water wastage, including leaks and misuse, contribute to approximately 50% of the total chilled-water demand. The current inefficiency detection methods rely on broad, infrequent, and labour-intensive work, focusing only on identifying and quantifying wastages without comprehensive mitigation strategies. This study aimed to develop a novel accountability framework employing dynamic zero-waste baselines to identify and address inefficiencies closer to active working areas. The proposed method incorporates four key components—define, assess, execute, and communicate—into an accountability system to monitor performance and ensure sustainable improvements. The integration of dynamic zero-waste baselines within this accountability framework will ensure faster and more accurate inefficiency detection and, more importantly, the mitigation thereof, significantly reducing water wastage. This study successfully reduced the daily water wastage, with an annual energy cost benefit of approximately USD 1.6 million (ZAR 28.7 million). The successful implementation of this method met all the research objectives, confirming its effectiveness. Full article

To ensure the safe repurposing of post-mining landscapes, understanding and managing geotechnical risks, particularly ground movements such as settlements on opencast mining dump surfaces, is critical. Satellite-based radar interferometry (InSAR) technology offers highly detailed data on vertical ground movements with a high spatial and temporal resolution. By combining a data-driven approach, using InSAR-generated high-resolution datasets, with model-driven methods such as inverse modeling and classic time–settlement models, the efficient monitoring and prediction of opencast mine dump settlements can be achieved. This dual approach—leveraging advanced data analysis tools and precise modeling—yields valuable insights into spatial settlement behavior. In particular, classic time–settlement models are applied to the InSAR data through least square regression and Taylor approximation. The integration of both approaches enables the more robust, data-validated forecasts of key geotechnical indicators, such as the time to settlement stabilization and the expected maximum settlement over large areas. An application at a mine in central Germany illustrates the method by generating spatial predictions of the settlement behavior over more than 200 ha. In general, the results provide a comprehensive dataset for investigating other factors influencing the settlement behavior of opencast mine dumps. Full article

Industry 4.0 represents a crucial technological revolution for the modernization and competitiveness of companies, offering tools that enhance the efficiency, productivity, and sustainability of industrial processes. Adopting these technologies is essential, especially in crucial sectors such as mining, where their implementation can radically transform operations. This study investigates the adoption of Industry 4.0 technologies among mining and non-mining companies in Chile, using data from the Survey of Access and Use of Information and Communication Technology in Companies. A Principal Component Analysis (PCA) identified the main variables influencing technological adoption. The results indicate that mining companies are significantly more advanced in integrating technologies such as ERP, SCM, and Big Data, which optimize their operational processes and strengthen their competitiveness. In contrast, non-mining companies show a more dispersed adoption, which could limit their capacity for innovation. These findings underscore the importance of developing differentiated public policies that promote technological adoption in SMEs and less advanced sectors, also encouraging the development of internal capacities and collaboration between businesses and government to accelerate digital transformation. Full article

The mining industry is undergoing a transformation driven by the adoption of Industry 4.0 technologies, implementing autonomous trucks, drones, positions systems, and similar technologies. This article, drawing on experiences and observations from several studies conducted in the mining industry, explores the impact of these technologies on mining work. It identifies eight key potential changes in working conditions. Firstly, routine and dangerous tasks are increasingly automated, reducing physical strain but potentially leading to job displacement and increased maintenance demands. Secondly, operators and managers are shifting toward handling disturbances and training algorithms, as AI takes over decision-making processes. Thirdly, managers are responsible for more capital with fewer people, potentially altering managerial roles and spans of control. Fourthly, the global connectivity of operations makes the world both larger and smaller, with a universal language blurring boundaries. Fifthly, work becomes location-independent, allowing for remote operation and management. Sixthly, the distinction between work and private life blurs, with increased availability expected from operators and managers. Seventhly, technology expands human senses, providing real-time data and situational awareness. Eighthly and lastly, the pervasive collection and retention of data create a scenario where one’s history is inescapable, raising concerns about data ownership and privacy. These changes necessitate a strategic response from the mining industry to ensure socially sustainable technology development and to attract a future workforce. Full article

Mineral extraction is an important operation for the economy of different countries and generates millions of tons of mining waste. In this context, and in association with the high demand for paving aggregates and the lack of raw materials for this purpose, the feasibility of using iron ore processing waste has emerged as a promising alternative. This study evaluates the physical and mechanical behavior of asphalt mixtures incorporating waste from the company Samarco S.A., collected in Mariana-MG, to replace the fine aggregate in asphalt concrete mixtures, with a view to applications in the bearing layer of local traffic roads. Two mixtures, M2 and M3, containing 20% and 17% waste, respectively, were formulated and analyzed, compared to a reference mixture, M1. Evaluations were carried out using the Marshall method parameters, mechanical tests of resilience modulus, and fatigue life under controlled tension, as well as mechanistic analysis. Brazilian mechanistic–empirical design software (MeDiNa—v 1.5.0) contributed to this analysis. This analysis revealed that, for a traffic level of N = 5 × ${10}^6$ (average traffic) on a local road, pavements containing the M1 and M3 mixtures had the same layer thicknesses (6.9 cm), as well as the same fatigue class, equal to 1. The pavement with the M2 mixture had the thickest asphalt layer (8.2 cm) and a lower fatigue class equal to 0. But if compared in terms of the percentage of cracked area over 10 years, it still offers ideal performance conditions compared to the M1 and M3 mixes. Thus, it can be considered feasible to replace fine aggregate with iron ore waste in asphalt concrete for use on local roads in the region without altering the bearing capacity of the pavement. Full article

Located in northern Western Australia, the Pilbara is the highest productivity region for iron ore and other metal mining in Australia. As elsewhere, mine closure guidelines typically require post-closure landforms to be safe, stable, non-polluting and sustainable here in the long-term. I reviewed the primary literature, including international, national and state government guidelines and regional case studies for mine closure and related socio-environmental topics, to understand the key risks and management strategies needed to achieve these broad expectations for below water table (BWT) mining. Many BWT open cut mining projects will result in pit lakes in this region, many of which will be very large and will degrade in water quality with increasing salinisation over time. As an arid region, risks are dominated by alterations to hydrology and hydrogeology of largely unmodified natural waterways and freshwater aquifers. Although remote, social risks may also present, especially in terms of impacts to groundwater values. This remoteness also decreases the potential for realising practicable development of post-mining land uses for pit lakes. Explicitly considered risk-based decisions should determine closure outcomes for BWT voids, and when pit backfill to prevent pit lake formation will be warranted. However, maintaining an open pit lake or backfilling a void should also be considered against the balance of potential risks and opportunities. Full article

The reclamation of waste rock piles (WRPs) is complex, requiring adaptation of existing mine site reclamation techniques. An alternative approach has been developed for waste rock piles reclamation which involves installing finer materials on the top of waste rock piles. These finer layers (flow control layers—FCLs) redirect water flowing inside the pile toward its slope and limits water infiltration into reactive waste rocks. In the context of sustainable development, a mixture material made with sludge and slag can be used as an FCL in the reclamation of a waste rock pile. To assess the effectiveness of this material, a physical model was used and instrumented with sensors for monitoring volumetric water content and suction and equipped with the following components: (1) a rain simulator; and (2) drains that allow the recovery of water that infiltrates through the system. The physical model was tested with various cover layer thicknesses, inclinations, and precipitation rates. Investigation results showed that the water infiltration across the system was very low, leading to the conclusion that the sludge and slug mixture performed well as a flow control layer in the reclamation of waste rock piles. Full article

This paper presents an innovative numerical approach to simulating the progressive caving of rock mass in the overburden and floor during longwall mining. A modified caving algorithm is incorporated into FLAC3D 9.0, augmented with the IMASS constitutive model, to accurately replicate the fracturing response of various strata. This study aimed to analyze the longwall caving performance, overburden fracturing response, and shield support characteristics to optimize the mining process and enhance safety. The numerical analysis revealed a progressive stress release at the longwall face, attributed to damage in the form of spalling, which was accompanied by a high level of displacement. The fracture process zone above the shield canopy was not significant, indicating the effective performance of the shield in controlling the roof. However, the floor heave highlights the need for the implementation of effective risk and safety measures. Goaf is predicted to form with a longwall advance rate of 25.0–30.0 m, resulting from progressive macroscopic fracturing caused by the development of cracks initiated by bedding plane and rock mass failures. Above the caved zone, an active fracture zone is observed to evolve due to the continuous longwall mining and caving process. Full article

The aim of this study was to evaluate soil properties and Eragrostis tef (teff) growth on Technosols produced from coarse and fine coal wastes from Moatize Mine, Mozambique. The experiment was performed in triplicate in 30 L containers filled with different substrate conditions, composed of fine coal waste, coarse coal waste, agricultural soil, and sewage sludge as an organic matter source. The soil analyses included bulk density, available water capacity, permeability, and fertility. Plant growth was monitored for biomass production and plant tissue composition. All the substrates presented a good available water capacity and a proper drainage condition. Regarding soil fertility, there were shortages of potassium and boron in the substrates composed exclusively of coal wastes, which was reflected in the composition of the plant tissue. Even so, plant growth was statistically equivalent to the control in all conditions, except for the substrate produced exclusively with fine coal waste and sewage sludge, which presented a better performance. Technosols are an alternative for reducing the final mine waste volume, and Eragrostis tef is used as a means for land use after the mining process, with social gains, and as a tool in an ecological process for restoring coal mining sites. Full article

In the context of mining applications and the increasing demand for high load-bearing soils, utilizing weak soils poses a significant challenge. This study investigates the effectiveness of geosynthetics in stabilizing weak soils through numerical modeling using Abaqus software (R2016X)and validation via laboratory model testing. We examined the impact of various geosynthetic lengths and embedment depths across three soil types: clay loam (ML), sand (SM), and well-graded sand (SW). Our results reveal that ML and SM soil types exhibit local shear failure, while SW soil types demonstrate general shear failure. Notably, the bearing capacity of soils increases with coarser particle sizes due to higher Meyerhof parameters, leading to soil failure at lower settlements. Optimal geotextile embedment depths were determined as H/B = 0.125 for ML soil, H/B = 0.250 for SM soil, and H/B = 0.5 for SW soil. Additionally, the effect of geotextile length on bearing capacity is more pronounced in ML soil, suggesting greater effectiveness in fine-grained soils. The optimal geotextile lengths for installation are approximately 1.5 times the width for ML soil, 1.0 times for SM soil, and 1.0 times for SW soil. We also found that SW soil typically fails at lower settlements compared to ML and SM soils. Consequently, geotextile placement at shallower depths is recommended for SW soil, where the soil experiences higher tension and pressure. These findings contribute to enhance soil stabilization and load management in mining geotechnics. Full article

The present study investigates the process of selective leaching of low-grade phosphate ore of the Karatau basin using organic acids such as formic and citric acids. Chemical and instrumental analyses of the investigated phosphate ore were carried out, including X-ray diffraction (XRD), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), and Fourier-transform infrared spectroscopy (FTIR). Based on experimental data, reaction rate constants were calculated, and the obtained activation energies for each of the reagents were used. The reaction rate constants indicate that formic acid led to a more gradual increase in P₂O₅ concentration over time, while citric acid demonstrates a more significant increase in phosphorus concentration at all temperatures, especially at 70 °C. The activation energy for formic acid is 14.69 kJ/mol, indicating a diffusion-controlled reaction mechanism, whereas the activation energy for citric acid is higher, i.e., 35.78 kJ/mol, suggesting a more complex mechanism involving both diffusion and chemical processes. The present study highlights the importance of selecting appropriate reaction conditions to achieve maximum efficiency for the leaching of phosphate ore, depending on both temperature and reagent used. Full article

Selecting the most appropriate mining method to recover mineral resources is a critical decision-making task in mining project development. This study introduces an artificial intelligence-based mining methods recommendation system (AI-MMRS) for the pre-selection of underground mining methods. The study integrates and evaluates the capability of two approaches for mining methods selection (MMS): the memory-based collaborative filtering (CF) approach aided by the UBC-MMS system to predict the top-3 relevant mining methods and supervised machine learning (ML) classification algorithms to enhance the effectiveness and novelty of the AI-MMRS, addressing the limitations of the CF approach. The results reveal that the memory-based CF approach achieves an accuracy ranging from 81.8% to 87.9%. Among the classification algorithms, artificial neural network (ANN) and k-nearest neighbors (KNN) classifiers perform the best, with accuracy levels of 66.7% and 63.6%, respectively. These findings demonstrate the effectiveness and viability of both approaches in MMS, acknowledging their limitations and the need for continuous training and optimization. The proposed AI-MMRS for the pre-selection stage supplemented by the direct involvement of mining professionals in later stages of MMS, has the potential to significantly aid in the MMS decision-making, providing data-driven and experience-based recommendations following the ongoing evolution of mining practices. Full article

This work aims to evaluate the use of a superabsorbent polymer (SAP) to provide improvements in the handling properties of iron ore tailings (IOT). The material studied came from the magnetic separation reprocessing of the material discarded at the Gelado Dam, located in Serra dos Carajás in the state of Pará, Brazil. While the concentrate presents reasonable handling conditions, the tailings, with 61.5% iron, 15% moisture, and 39% of the mass, have high cohesiveness and adhesiveness due to their fine nature and the climatic conditions of the Amazon rainforest. However, the tailings can still be considered a product as long as the handling and transportation logistics are feasible. Thus, studies with an SAP and IOT were carried out in a bench rotating drum to promote mixing between them, and the main variables studied were the SAP dosage and the required contact time. The improvement in the physical properties of the IOT were evaluated considering the Hausner ratio, Carr index, Jenike’s flow function index, Atterberg limits, and chute angle. The superabsorbent polymer promoted a significant improvement in the state of consistency of the material, and the best performance was obtained with a dosage of 1000 g t⁻¹. As long as a suitable contact condition was promoted, a contact time of 1 min was enough to achieve the expected benefits. After dosing with the superabsorbent polymer, the material’s handling classification changed from ‘cohesive’ to ‘easy flow’, and the chute angle was reduced from 90° to levels below 60°. It was concluded that the application of the superabsorbent polymer has the potential to improve the fluidity of the material discarded in the magnetic concentration operation, allowing it to be handled throughout the production and transportation chain. The SAP appears to be an important additive for the full use of the material present in the dam (100% recovery), with both economic and socio-environmental benefits. Full article