Mining

In situ uniaxial compressive strength mapping across dykes of different thicknesses within a coal mass and its influence zones at two mines in the Jharia coalfield has been carried out in this study. It provides insight into the manner in which the dyke intrusion altered the adjacent coal mass, leading to the formation of jhama and pulverized zones with modified strength properties. A Digital Schmidt Hammer with an impact energy of 2.207 Nm was used to estimate the in situ uniaxial compressive strength of the coal around the seam–dyke interface in different mines selected for the study. At the first mine, the dyke had a thickness of approximately 15 m, with its influence on the surrounding coal mass extending up to 13.5 m on both sides. Unlike the first mine, the dyke in the second mine was merely 1 m thick, with its effect limited to a zone of around 2.1 m. The average uniaxial compressive strength of unaltered (intact) coal at the studied mines ranged from 31.7 to 38.5 MPa. The zones influenced by the dyke at both mines comprised jhama, which exhibited a 15–18% higher uniaxial compressive strength compared to the surrounding intact coal, and pulverized coal zones, which showed a 46–56% reduction in strength relative to the intact coal. Full article

This study presents the design and validation of an automated skip loading system for vertical shaft hoisting operations, aimed at addressing inefficiencies in current manual systems that contribute to consistent underperformance in meeting daily production targets. Initial assessments revealed a task completion rate of 91.6%, largely due to delays and inaccuracies in manual ore loading and accounting. To resolve these challenges, an automated system was developed using a bin and conveyor mechanism integrated with a suite of industrial automation components, including a programmable logic controller (PLC), stepper motors, hydraulic cylinders, ultrasonic sensors, and limit switches. The system is designed to transport ore from the draw point, halt when one ton is detected, and activate the hoisting process automatically. Digital simulations demonstrated that the automated system reduced loading time by 12% and increased utilization by 16.6%, particularly by taking advantage of the 2 h post-blast idle period. Financial evaluation of the system revealed a positive Net Present Value (NPV) of $1,019,701, a return on investment (ROI) of 69.7% over four years, and a payback period of 2 years and 11 months. The study concludes that the proposed solution significantly improves operational efficiency and recommends further enhancements to the hoisting infrastructure to fully optimize performance. Full article

Organisations are increasingly adopting the Chain of Custody (CoC) standards in the mining industry to enhance the traceability of minerals. It ensures that the minerals they have received are from credible sources and accompanied by verifiable information. However, unlikeother industries such as timber, where the effectiveness and benefits of CoC standards are mainly explored, this study subtly shifts the focus towards identifying strategic opportunities and innovation areas within the CoC standards that could extend beyond traceability. Four CoC standards were selected, and their provisions examined. It was found that implementing these requirements could not only enhance transparency but also support broader sustainability goals across the entire value chain. The study also identifies several challenges that could act as barriers to the CoC system, and these are seen as opportunities for innovative approaches to enhance the effectiveness of the standards. These are labelled as transformative innovation areas, and while they do include blockchains and analytical proof of origin technologies, this study also seeks to advocate for solutions that are more pragmatic and scalable. By identifying opportunities and areas of innovation, the findings will help improve the practical implementation of the standards and suggest areas for future evaluations of effectiveness that could consider aspects beyond traceability, such as sustainability and transparency. Full article

The implementation and application of a safety factor (SF)-based numerical framework in FLAC3D-IMASS (Itasca Model for Advanced Strain Softening) is presented for the evaluation of the short-term stability of unsupported underground excavations in sedimentary rock masses during pillar recovery in bord-and-pillar mining. The stability of underground openings during the initial hours post-excavation must be ensured, as they are not accessed thereafter; therefore, short-term stability assessment is essential. The framework was specifically calibrated to field observations and applied to a case study from an Australian bord-and-pillar mine, focusing on plunge and bellout configurations commonly used during the pillar extraction stage to enhance ore recovery. The modelling approach was integrated with rock mass degradation behavior under static loading conditions and was used to calculate three-dimensional distributions of SF to identify potential failure zones. The results demonstrate that the coal (CO) roof scenario generally maintains structural stability, while the impure coal (Cox) roof scenario is observed to exhibit significant instability, particularly at greater excavation advancement. Among the tested bellout geometries, 8.0 m spans were observed to provide improved performance due to shorter tunnel lengths that enhance confinement and reduce the volume of disturbed rock. Overall, the proposed SF framework effectively captures localized failure mechanisms and is demonstrated as a practical design tool for assessing the short-term stability of unsupported structures during critical stages of underground mining operations. Full article

This paper aims to develop a robust empirical–analytical model using the statistics of mine water level rebound in abandoned mines and the basic physical principles of underground hydraulics. The data collected and treated included the time series of the mine water level for 35 closed and flooded mines from four European countries. Within the developed model, mine water level evolution is governed by an ordinary differential equation with one fitting parameter that depends on the floodable cavity volume in a mine and water inflow before flooding begins. The model assumes that rock properties and residual void distribution are homogeneous, and the mines being flooded are almost isolated hydraulically from the neighboring ones. The exponential formula, as the governing equation solution, was found to be the most suitable for fitting the measurements. The calculated exponential curves allow for excellent or very good fitting of the measured water levels for 17 of 35 mines, and acceptable fitting for 11 mines in terms of minimizing mean-square-root deviation. The proposed approach can be applied to preliminary assessments of mine water level rebound in developing and calibrating sophisticated numerical flow models. Full article

As the global shift toward renewable energy accelerates, large-scale energy storage is essential to balance intermittent supply and growing demand. While conventional Pumped Hydro Storage remains dominant, Underground Pumped Hydro Storage (UPHS) offers a promising alternative, particularly in flat regions with ample subsurface space. Southern Ontario, Canada, underlain by thick salt formations and a history of salt mining, presents favorable conditions for UPHS development, yet relative studies remain limited. This work presents the first UPHS-specific geomechanical feasibility assessment in the Canadian Salina Group, introducing a paired-cavern layout tied to Units B and A2 and explicitly capturing both elasto-plastic and creep behavior. Using COMSOL Multiphysics 6.3, a three-dimensional numerical model was developed featuring two vertically separated cylindrical caverns located in Unit B and the lower part of Unit A2. A 24 h operating cycle was simulated over a 10-year period, incorporating elasto-plastic deformation and salt creep. Minimum working pressures were varied to evaluate long-term cavern stability. The results show that a minimum pressure of 0.3 σ_v balances structural integrity and operational efficiency, with creep strain and volumetric convergence remaining within engineering limits. Beyond previous salt-cavern studies focused on hydrogen or CAES, this study provides the first coupled elasto-plastic and creep simulation tailored to UPHS operations in bedded salt, establishing a safe operating-pressure guideline and offering site-relevant design insights for modular underground energy storage systems in sedimentary basins. 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

A barrier pillar between the surface and underground mining sections provides a critical buffer zone in the transition from the boxcut highwall to underground sections by isolating stress fields from underground sections and preventing them from affecting the boxcut highwall slope. In this study, an empirical scaled span method and Rocscience RS2 software were used to conduct parametric studies on key parameters for designing barrier pillars and analyzing the room and pillar design for a planned underground mine on the Great Dyke, Zimbabwe. The approach included analyzing the effect of barrier pillar width, assuming a 10° dipping angle of the orebody, with room and pillar dimensions of 7 m and 6 m, respectively. The impact on boxcut slope stability and the roof of the first stope was monitored. The stability of the barrier pillar was analyzed for varying widths (6 m, 10 m, 20 m, 30 m, and 40 m) and orebody dipping angles (0°, 10°, 20°, 30°, and 40°). The effect of deteriorated rock mass conditions, represented by Geological Strength Index (GSI) values from 30 to 50, was assessed. The optimum room and pillar design was evaluated against the planned 6 m pillar sizes. This comprehensive study aims to support the integrity and longevity of the critical structures of the mining operation. Full article

The Super-long Gravity Heat Pipe (SLGHP) is an efficient geothermal energy utilization technology that can transmit thermal energy by fully utilizing natural temperature differences without external energy input. This study focuses on the high-altitude geothermal environment of Mount Meager, Canada, and employs numerical simulations and dynamic thermal analysis to systematically investigate the thermal transport performance of the SLGHP system under both steady-state and dynamic operating conditions. The study also examines the impact of various structural parameters on the system’s performance. Three-dimensional CFD simulations were conducted to analyze the effects of pipe diameter, length, filling ratio, working fluid selection, and pipe material on the heat transfer efficiency and heat flux distribution of the SLGHP. The results indicate that working fluids such as CO₂ and NH₃ significantly enhance the heat flux density, while increasing pipe diameter may reduce the amount of liquid retained in the condenser section, thereby affecting condensate return and thermal stability. Furthermore, dynamic thermal analysis using a three-node RC network model simulated the effects of diurnal temperature fluctuations and variations in the convective heat transfer coefficient in the condenser section on system thermal stability. The results show that the condenser heat flux can reach a peak of 5246 W/m² during the day, while maintaining a range of 2200–2600 W/m² at night, with the system exhibiting good thermal responsiveness and no significant lag or flow interruption. In addition, based on the thermal output of the SLGHP system and the integration with the Organic Rankine Cycle (ORC) system, the power generation potential analysis indicates that the system, with 100 heat pipes, can provide stable power generation of 50–60 kW. In contrast to previous SLGHP studies focused on generalized modeling, this work introduces a site-specific CFD–RC framework, quantifies structural sensitivity via heat flux indices, and bridges numerical performance with economic feasibility, offering actionable insights for high-altitude deployment. This system has promising practical applications, particularly for providing stable renewable power in remote and cold regions. Future research will focus on field experiments and system optimization to further improve system efficiency and economic viability. Full article

Underground mining operations face increasing challenges due to their complex and hazardous environments. One key difficulty is ensuring real-time safety monitoring and disaster prevention. Traditional monitoring systems often suffer from delayed data acquisition and rely heavily on cloud-based processing. These factors limit their responsiveness during emergencies. To address these limitations, this study presents an underground Internet of Things (IoT) monitoring system based on edge computing. The system architecture is composed of three layers: a perception layer for real-time sensing, an edge gateway layer for local data processing and decision-making, and a cloud service layer for storage and analytics. By shifting computation closer to the data source, the system significantly reduces latency and enhances response efficiency. The system is tailored to actual mine-site conditions. It integrates pressure monitoring for artificial expandable pillars and roof subsidence detection in stopes. It has been successfully deployed in a field environment, and the data collected during commissioning demonstrate the system’s feasibility and reliability. Results indicate that the proposed system meets real-world demands for underground safety monitoring. It enables timely warnings and improves the overall automation level. This approach offers a practical and scalable solution for enhancing mine safety and provides a valuable reference for future smart mining systems. Full article

This study evaluates the capabilities of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Hyperion remote sensing sensors for mapping ophiolitic sequences and identifying manganese mineralization in the Bela Ophiolite region, located along the axial fold–thrust belt northwest of Karachi, Pakistan. The study area comprises tholeiitic basalts, gabbros, mafic and ultramafic rocks, and sedimentary formations where manganese occurrences are associated with jasperitic chert and shale. To delineate lithological units and Mn mineralization, advanced image processing techniques were applied, including band ratio (BR), Principal Component Analysis (PCA), and Spectral Angle Mapper (SAM) on visible and near-infrared (VNIR) and shortwave infrared (SWIR) bands of ASTER. Using these methods, gabbros, basalts, and mafic-ultramafic rocks were effectively mapped, and previously unrecognized basaltic outcrops and gabbroic outcrops were also discovered. The ENVI Spectral Hourglass Wizard was used to analyze the hyperspectral data, integrating the Minimum Noise Fraction (MNF), Pixel Purity Index (PPI), and N-Dimensional Visualizer to extract the spectra of end-members associated with Mn-bearing host rocks. In addition, the Hyperspectral Material Identification (HMI) tool was tested to recognize Mn minerals. The remote sensing results were validated by petrographic analysis and ground-truth data, confirming the effectiveness of these techniques in ophiolite mapping and mineral exploration. This study shows that ASTER band combinations (3-6-7, 3-7-9) and band ratios (1/4, 4/9, 9/1 and 3/4, 4/9, 9/1) provide optimal results for lithological discrimination. The results show that remote sensing-based image processing is a powerful tool for mapping ophiolites on a regional scale and can help geologists identify potential mineralization zones in ophiolitic sequences. Full article

Detecting surface mineral indicators with high spatial precision remains a significant challenge in mineral exploration, particularly in remote or geologically complex regions such as Eastern Kazakhstan. This study addresses this challenge by integrating high-resolution multispectral imagery from Unmanned Aerial Vehicles (UAVs) to map iron oxide distributions, key indicators of ore mineralization such as copper porphyry at the Kyzylkiya mining site in Eastern Kazakhstan. The novelty of this study is the development of a statistical fuzzy logic model that integrates UAV-derived spectral indices, including the Normalized Difference Vegetation Index (NDVI) and targeted band ratios, to generate probabilistic maps of iron oxide presence at a fine spatial resolution of 5.29 cm. This approach enhances prediction accuracy by incorporating uncertainty and variability in spectral responses. The model’s output was validated through a multi-stage process involving independent multispectral datasets and ground-truth sampling, achieving an overall accuracy of 80%. The results reveal concentrated iron oxide anomalies in the northeast and northwest of the study area, underscoring the method’s effectiveness. This integrated UAV-fuzzy logic framework demonstrates a scalable and cost-effective solution for early-stage mineral exploration and can be adapted to similar geological settings globally. Full article

Mining (1) operations in remote areas (2) face significant challenges related to energy supply, high fuel costs, and limited infrastructure. This study investigates the potential for achieving energy independence (3) and resilience (4) in such environments through the integration of renewable energy sources (5) and battery–electric mining equipment. Using the “Studena Vrila” underground bauxite mine as a case study, a comprehensive techno-economic and environmental analysis was conducted across three development models. These models explore incremental scenarios of solar and wind energy adoption combined with electrification of mobile machinery. The methodology includes calculating levelized cost of energy (LCOE), return on investment (ROI), and greenhouse gas (GHG) reductions under each scenario. Results demonstrate that a full transition to RES and electric machinery can reduce diesel consumption by 100%, achieve annual savings of EUR 149,814, and cut GHG emissions by over 1.7 million kg CO₂-eq. While initial capital costs are high, all models yield a positive Net Present Value (NPV), confirming long-term economic viability. This research provides a replicable framework for decarbonizing mining operations in off-grid and infrastructure-limited regions. Full article

Occupational heat stress represents an increasing challenge to safety and operational performance in underground mining, where elevated temperatures, humidity, and limited ventilation are common. This study proposes an integrated framework to analyze the systemic impact of heat stress on human reliability in mining operations. We conducted a systematic literature review to identify empirical studies addressing thermal exposure, extracting key operational functions for modeling. These functions were structured using the Functional Resonance Analysis Method (FRAM) to reveal interdependencies and performance variability. Human reliability was evaluated using Fuzzy CREAM, which quantified the degree of contextual control associated with each function. Finally, we applied the Gaussian Analytic Hierarchy Process (AHP) to prioritize functions based on thermal impact, contextual reliability, and systemic connectivity. The results showed that functions involving subjective or complex judgment, such as assessing thermal stress or identifying psychophysiological indicators, exhibited lower reliability and higher vulnerability. In contrast, monitoring and control functions based on standardized procedures were more stable and resilient. This combined approach identified critical points of systemic fragility and offers a robust decision-support tool for prioritizing thermal risk mitigation. The findings contribute to advancing the scientific understanding of heat stress impacts in mining and support the development of targeted interventions to enhance human performance and safety in extreme environments. Full article

The purpose of this work was to obtain specialized enrichment cultures from an original extreme acidophilic consortium of extremely acidophilic microorganisms and to study their microbial community composition and biotechnological potential. At temperatures of 25, 35, 40 and 50 °C, distinct enrichments of extremely acidophilic microorganisms used in the processes of bioleaching sulfide ores were obtained using nutrient media containing ferrous sulfate, elemental sulfur and a copper sulfide concentrate as nutrient inorganic substrates, with and without the addition of 0.02% yeast extract. The microbial community composition was studied using the sequencing of the V3–V4 hypervariable region of the 16S rRNA genes. The different growth conditions led to changes in the microbial composition and relative abundance of mesophilic and moderately thermophilic, strict autotrophic and mixotrophic microorganisms in members of the genera Acidithiobacillus, Sulfobacillus, Leptospirillum, Acidibacillus, Ferroplasma and Cuniculiplasma. The dynamics of the oxidation of ferrous iron, sulfur, and sulfide minerals (pyrite and chalcopyrite) by the enrichments was also studied in the temperature range of 25 to 50 °C. The study of enrichment cultures using the molecular biological method using the metabarcoding method of variable V3–24 V4 fragments of 16S rRNA genes showed that enrichment cultures obtained under different conditions differed in composition, which can be explained by differences in the physiological properties of the identified microorganisms. Regarding the dynamics of the oxidation of ferrous ions, sulfur, and sulfide minerals (pyrite and chalcopyrite), each enrichment culture was studied at a temperature range of 25 to 50 °C and indicated that all obtained enrichments were capable of oxidizing ferrous iron, sulfur and minerals at different rates. The obtained enrichment cultures may be used in further work to increase bioleaching by using the suitable inoculum for the temperature and process conditions. Full article

Accurate prediction of the coal abrasive index (AI) is critical for optimizing coal processing efficiency and minimizing equipment wear in industrial applications. This study explores tree-based machine learning models; Random Forest (RF), Gradient Boosting Trees (GBT), and Extreme Gradient Boosting (XGBoost) to predict AI using selected coal properties. A database of 112 coal samples from the KwaZulu-Natal Coalfield in South Africa was used. Initial predictions using all eight input properties revealed suboptimal testing performance (R²: 0.63–0.72), attributed to outliers and noisy data. Feature importance analysis identified calorific value, quartz, ash, and Pyrite as dominant predictors, aligning with their physicochemical roles in abrasiveness. After data cleaning and feature selection, XGBoost achieved superior accuracy (R² = 0.92), outperforming RF (R² = 0.85) and GBT (R² = 0.81). The results highlight XGBoost’s robustness in modeling non-linear relationships between coal properties and AI. This approach offers a cost-effective alternative to traditional laboratory methods, enabling industries to optimize coal selection, reduce maintenance costs, and enhance operational sustainability through data-driven decision-making. Additionally, quartz and Ash content were identified as the most influential parameters on AI using the Cosine Amplitude technique, while calorific value had the least impact among the selected features. Full article

The use of high-pressure grinding rolls (HPGRs) is increasing in the ore industries as advanced technology is available for this type of comminuting. There are important parameters in these devices, which have many effects on productivity. One of the main reasons for damage on the rolls and, therefore, decreases in the machine’s productivity and efficiency is surface wear. This phenomenon must be carefully understood so that it can be controlled as much as possible through the readjustment and optimization of the effective parameters. In this research, the wear mechanism of HPGRs in a production line for iron ore concentrate was investigated. The results showed that there was greater wear at the center of the rolls and that changes to the chemical and physical properties of the incoming iron compared to the design condition reduced the rolls’ lives. The results showed a failure to perform appropriate mechanical adjustment and improper repair and maintenance. Full article

This study presents a methodology developed in collaboration with the Colombian National Mining Agency, aimed at enhancing the economic and productive activity of small-scale miners in Colombia through the promotion of associativity. Despite persistent challenges in the formalization and sustainable development of the artisanal mining sector, fostering associative models offers a pathway towards a more sustainable mining industry, aligned with current national policies. The proposed roadmap, designed to achieve this objective, is divided into three sequential phases. The first, the Baseline Survey, focuses on comprehensively understanding the initial socio-economic and operational conditions of mining communities. This is followed by Participatory Strategic Planning, which involves projecting the long-term role and development of mining associative figures. Finally, the Annual Operational Planning and Execution phase concentrates on the concrete implementation of activities designed to achieve sustainable organizational goals. During the design and initial implementation of this roadmap, we found that continuous support and tailored training programs are essential for mining communities. These programs are critical for fostering the development of collective skills and strengthening community ties within mining organizations. The findings highlight that by strengthening collective capabilities and community ties, mining organizations can enhance their self-management capacities and significantly contribute to the economic development of their regions. This approach addresses key challenges in the sector by promoting a more organized and resilient operational framework. The implementation of a participatory methodology, coupled with specific organizational strengthening programs, coordinated execution, and continuous monitoring, provides a viable route towards a more sustainable and formalized small-scale mining sector in Colombia. This roadmap offers a practical framework for fostering self-managed and economically contributing mining organizations. Full article

The present study aimed to estimate the contribution of the mining and mineral processing steps of lithium concentrate production in Brazil to the Global Warming Potential (GWP100) using an LCA perspective. No previous national study was identified that quantified national GHG emissions in mining and beneficiation operations for lithium ores. This study is considered original and aims to contribute to filling this gap. The functional unit was 1 ton of lithium carbonate equivalent (LCE) in the mineral concentrate. The contribution to GWP100 was estimated at 1220 kg of CO_2eq per ton of LCE, of which 262 kg originated from foreground processes. In the background processes, the largest contribution was 456 kg of CO_2eq from emissions in the production of ammonium nitrate, used in the manufacture of mining explosives. An analysis of substituting electricity sources in the product system showed a reduction of 22.7% and 14.7% in the estimated global warming impact when using wind or solar power, respectively. Full article