Mining

The automation of mining mobile equipment is a topic of considerable interest, as it has the potential to significantly reduce the number of accidents and implement the so-called zero-entry mining concept, which would eliminate the need for any human presence on the mine site. Nevertheless, the current state of robotics and automation technology does not yet meet the requirements for the implementation of fully autonomous operations in mines. Autonomous mining equipment continues to operate under the supervision of humans, and a considerable number of mining equipment has not yet been automated. This indicates the necessity of identifying novel strategies to increase the safety of mining operations through the utilization of robotics and automation technologies. One potential solution to address this challenge is to increase the involvement of humans in autonomous mining operations. This could entail integrating human decision-makers into the decision-making loops of autonomous mining equipment. To this end, we propose the paradigm of autonomous collaborative mining, wherein humans and autonomous machines work together in a collaborative manner to increase the safety and efficiency of mining operations. We analyze the enabling factors required to implement this paradigm and present the case of autonomous loading using LHDs based on the autonomous collaborative mining paradigm. Full article

Predicting and analyzing the stability of underground stopes is critical for ensuring worker safety, reducing dilution, and maintaining operational efficiency in mining. Traditional stability graphs are widely used but often criticized for oversimplifying the stability phenomenon and relying on subjective classifications. Additionally, the imbalanced nature of stope stability datasets poses challenges for traditional machine learning and statistical models, which often bias predictions toward the majority class. This study proposes a novel methodology for developing site-specific stability graphs using probabilistic modeling and machine learning techniques, addressing the limitations of traditional graphs and the challenges of imbalanced datasets. The approach includes rebalancing of the dataset using the Synthetic Minority Over-Sampling Technique (SMOTE) and feature selection using permutation importance to identify key features that impact instability, using those to construct a bi-dimensional stability graph that provides both improved performance and interpretability. The results indicate that the proposed graph outperforms traditional stability graphs, particularly in identifying unstable stopes, even under highly imbalanced data conditions, highlighting the importance of operational and geometric variables in stope stability, providing actionable insights for mine planners. Conclusively, this study demonstrates the potential for integrating modern probabilistic techniques into mining geotechnics, paving the way for more accurate and adaptive stability assessment tools. Future work includes extending the methodology to multi-mine datasets and exploring dynamic stability graph frameworks. Full article

This study presents a constitutive model for simulating the behavior of weak rock masses under various stress conditions, including the effects of pore pressure and temperature. Addressing the limitations of existing models in accurately representing the complex anisotropic response of these materials, the model utilizes Monte Carlo simulations to integrate stress anisotropy, pore pressure effects, and deviatoric stress states. This approach aims to capture the impact of geological factors such as foliation and jointing on the mechanical behavior of weak rock masses, which are often characterized by low strength and high deformability. Five rock types (claystone, mudstone, sandstone, shale, and siltstone) were simulated, generating 1000 cases per type with variability modeled using Weibull distributions. Statistical validation, employing the Kolmogorov–Smirnov test and Q–Q plots, demonstrated a strong agreement between simulated and experimental data. The results suggest that the proposed model can effectively predict deformation patterns in weak rock masses, offering potential applications in mining, geothermal energy extraction, and other engineering projects involving these challenging geological formations. Full article

Rock fracturing by blasting is the most common and efficient method of rock fragmentation in mining operations. The fragmentation size affects the productivity and costs of downstream operations and is influenced by the rock mass and blast design encountered. The encountered rock mass is the unmodifiable parameter in blasting. Therefore, blasting improvements can be achieved through blast design, which includes explosive selection, geometrical design, and initiation sequencing and delays. Stress wave interactions between blastholes can improve or diminish fracturing. The analysis conducted in this study through numerical modelling indicates an improvement in blast outcomes with appropriate delay and sequencing in some cases. The optimum delay ensures the formation of fractures on the succeeding blasthole and constructive interactions with the stress wave from the preceding blasthole, increasing the stress pulse and fracturing. While it is insignificant in intact rock blasting, the firing sequence is vital when blasting through the contacts of soft and hard rocks or joints, depending on the infill material. Sequential initiation and the firing direction do not improve fracturing in all cases; for example, when blasting through an empty joint, the joint acts as a free face with minimum to no interaction of the stress wave from adjacent charges. In such cases, simultaneous initiation can be used with caution based on the intensity of induced vibrations. Full article

The growing demand for green and, therefore, sustainable technologies present new challenges for our society. The European Union (EU) identified the critical raw materials (CRMs) and strategic raw materials (SRMs) necessary for these technologies and introduced policies to reduce reliance on external suppliers, which includes investigating the recovery of CRMs from extractive waste. This study assesses the recovery potential of mine waste collected in the Traversella mine district (Piedmont, Italy), known for its polymetallic Fe-Cu-W deposit. The characterization of waste rock samples involved chemical and mineralogical analyses, revealing metallic-bearing minerals such as magnetite and scheelite. Laboratory-scale magnetic and gravity separation tests were carried out and compared. Magnetic separation resulted in a recovery of 75.4% of Fe, 72.3% of Cu, and 83.7% of W, with a weak concentration. Instead, gravity separation produced high-grade Fe (67.6%) and W (1289 ppm) concentrate with lower recovery rates. Full article

This study presents an application of Boruta-SHapley Additive ExPlanations (Boruta-SHAP) for geotechnical characterization using Measure-While-Drilling (MWD) data, enabling a more interpretable and statistically rigorous assessment of feature importance. Measure-While-Drilling data collected at the scale of an open-pit mine was used to characterize geotechnical properties using regression-based machine learning models. In contrast to previous studies using MWD data to recognize rock type using Principal Component Analysis (PCA), which only identifies the directions of maximum variance, the Boruta-SHAP method quantifies the individual contribution of each Measure-While-Drilling variable. This method ensures interpretable and reliable geotechnical characterization as well as robust feature selection by comparing predictors against randomized ‘shadow’ features. The Boruta-SHAP analysis revealed that bit air pressure and torque-to-penetration ratio were the most significant predictors of rock strength, contradicting previous assumptions that rate of penetration was the dominant factor. Moreover, feature importance was conducted for fracture frequency and Geological Strength Index (GSI), a rock mass classification system. A comparative analysis of prediction performance was also performed using a range of different machine learning algorithms that resulted in strong coefficient of determinations of actual field or laboratory results versus predicted values. The results are plausible, confirming that MWD data could provide a high-resolution description of geotechnical conditions prior to mining, leading to a more confident prediction of subsurface geotechnical properties. Therefore, the fragmentation from blasting as well as downstream operational phases, such as digging, hauling, and crushing, could be improved effectively. Full article

The lithium market has been expanding due to the high demand for lithium-ion batteries, which are essential for electric and hybrid vehicles as well as portable devices. This has driven the search for new lithium ore deposits and the development of more efficient extraction and processing technologies. The main methods used for lithium extraction from hard rock ores include the acid process, the alkaline process, and chlorination roasting. This study investigated a chlorination process applied to α-spodumene extracted in Brazil for lithium chloride (LiCl) production. The ore underwent thermal treatment in the presence of calcium chloride (CaCl₂) and magnesium chloride (MgCl₂), followed by water leaching at 90 °C. The thermodynamics of the α-Li₂O·Al₂O₃·SiO₂ system, combined with calcium and magnesium chlorides, was analyzed using HSC 5.1 software. The main objective of this study was to produce lithium chloride from alpha spodumene and avoid decrepitation of the ore to the beta phase before mixing with the reagents, making the process faster and less expensive compared to traditional extraction methods. Pyrometallurgical tests were conducted in a muffle furnace, varying the molar ratio between chlorides (MgCl₂:CaCl₂) at 1:0, 0:1, 1:1, 2:1, and 1:2 and the mass ratio of spodumene to chlorides at 1:4, 1:6, and 1:8. The best lithium extraction result was approximately 95%, the conditions for obtaining the result were a spodumene:chloride ratio of 1:6 and a molar ratio between chlorides of 2:1. The results provide a better understanding of the chlorination roasting process and demonstrate the potential of the chlorination technique as a viable alternative to conventional lithium extraction methods. Full article

This study examines the conversion of an overflow ball mill into a new discharge system via Discrete Element Method (DEM) and Smoothed Particle Hydrodynamics (SPH) simulations, demonstrating significant performance improvements. The methodology integrates SPH to assess the effects of the slurry on energy dissipation, power loss, breakage rates, and material transport. The findings highlight significant operational inefficiencies in the overflow setup, extensive dead zones, and excessive charge volume that hinder milling efficiency by limiting grinding media interaction with the ore and reducing energy for comminution. Additionally, slurry pooling shifts the center of gravity, causing torque losses and direct material bypass to the discharge zone. Our simulations replicate these challenges and benchmark them against industrial-scale operations, identifying critical charge excesses that constrain throughput and elevate power consumption. The new proposed discharge system decouples the filling charge from the evacuation mechanism, releasing the effective volume in the mill, in addition to tackling common issues in the traditional grate discharge setups like backflow and carry-over. This arrangement substantially improved grinding efficiency, as demonstrated by enhanced breakage rates and diminished specific energy consumption. The results provide a robust framework for mill design and operational optimization, underscoring the value of integrated slurry behavior analysis in mill performance enhancement. Full article

The closure of coal and lignite mines has the potential to result in long-term environmental risks and socio-economic issues. To solve these, this research aims to improve the hazard assessment and risk management of former mining regions in a European project funded by the Research Fund for Coal and Steel. A multidisciplinary approach integrated historic, geological, topographical, environmental, and socio-economic data to create a methodology to support stakeholders at different decision-making levels in risk assessment and possible mitigation. For this purpose, a spatial decision support system was developed using a multi-hazard, multi-risk methodology. The individual hazards (post-mining, natural, and technical) are weighted using expert knowledge, their interaction analyzed, and then combined into a spatial multi-hazard index. Together with the other risk factors of social vulnerability and exposure, a comprehensive spatial risk map can be created automatically for individual regions using open-source components. In addition, GIS and statistical tools enable further analysis and visualization for decision-making by the relevant stakeholders. The methodology was validated through the examination of a first case study conducted in the post-mining region of the southern Ruhr area in Germany. The methodology and tool created significant results in two test scenarios, and will be tested and improved using other European mining sites during the next stages of the project. Full article

Iron ore extraction can lead to significant environmental degradation, particularly due to the generation of tailings during the beneficiation process. This issue was highlighted by the B1 dam collapse in Brumadinho, Brazil, in 2019. Therefore, the study and monitoring of affected areas is essential to assess soil quality throughout the rehabilitation process, whether through natural recovery or active rehabilitation practices. Microbial indicators can serve as valuable tools to track the recovery of these areas, given their high sensitivity and rapid response to environmental changes. The aim of this study was to evaluate soil microbial indicators, such as enzyme activity, microbial biomass carbon, microbial basal respiration and microbial diversity, and to select microbial approaches for monitoring the area affected by mining tailings in Brumadinho. The results indicated that the reference area initially outperformed the affected area on all evaluated bioindicators, highlighting environmental stress in the affected zone. Over the course of the study, the two areas began to show greater similarity, suggesting a natural recovery of the soil together with the return of natural vegetation. Indicators such as microbial carbon biomass went from values close to 50 mg of C Kg of soil⁻¹ in the affected area, to around 200, statistically equal to the reference. qCO₂ also varied in the affected area to values statistically equal to those of the reference over time, variated in the first collection to 0.25 mg of C-CO₂ mg of C⁻¹ h⁻¹ in the affected area against 0.1 in the reference area; in the last collection, both areas presented values close to 0.2. Enzymatic activity had superior values in the reference area about the affected area, being urease, and arylsulfatase more sensitive to show differences between areas over time. The metataxonomic data again revealed indicator species for each environment, including genera such as Bacillus, Mycobacterium, Acidibacter, and Burkholderia representative of the reference, and the genera Ramlibacter, Sinomonas, Psedarthrobacter, and Knoellia indicators of the affected area. By the end of this study, the applicability of microbial indicators for monitoring soil microbiota and its ecosystem services was successfully demonstrated. In addition, specific microbial indicators were proposed for monitoring areas affected by iron mining tailings. Full article

When volumes of mining excavations change, rock mass is displaced. Convergence in a salt mine may lead to substantial deformations. The displacement may, in turn, cause an inrush of water from the rock mass into the mine, which is a catastrophic event. Hence, salt excavation convergence is regularly monitored. Traditionally, convergence is measured at monitoring stations. The measurements were first performed with rigid instruments (such as a wire extensometer), then with manual laser rangefinders, and now attempts are made to employ terrestrial laser scanning (TLS). This article presents the evolution of TLS surveys in the mine. The method is demonstrated with multiple scans of a heritage chamber at the Wieliczka salt mine. The analyses indicate that TLS streamlines measurements and offers copious results. The main aim of this study was to identify the most effective and reliable determination of geometric changes in the excavation using TLS data from several years. The differences represented by the models adjusted to a common coordinate system with an error of 5 mm can be considered correct and reflecting the actual changes in the excavation. This gives significant opportunities for the use of TLS data in monitoring the behavior of mine workings in the future. However, considering the insufficient accuracy, the technology must not be the sole source of insight into mining excavation convergence. Full article

The underground mining industry faces significant challenges in maintaining reliable communication due to multipath fading and physical obstructions, leading to weak signals and dead spots. This study addresses these issues by proposing a smart antenna system with circular polarization and beam steering capabilities. The system utilizes a four-element square patch array and a Butler matrix for beamforming, enabling directional signal transmission. The antenna was designed and optimized using CST simulations. The experimental results demonstrate the antenna’s ability to steer beams in four directions, significantly reducing signal interference and improving coverage. The antenna achieved a bandwidth of 400 MHz (5.52–5.99 GHz) and a gain of up to 9.69 dBi, effectively mitigating polarization mismatches. The novelty of this study lies in the integration of circular polarization and beam steering into a compact, cost-effective system, specifically designed to enhance communication in underground mining environments. This solution improves both safety and operational efficiency by providing reliable communication in harsh conditions. Full article

The numerous challenges facing the global mining industry and the adverse impacts on the natural and human environment call for urgent action. In the present industry 4.0, the signature influx of emerging technologies (ETs) has seen various sectors of the economy embracing their application. To improve the safety, operational efficiency, and sustainability of the mining value chain, there has been a significant increase in the adoption, incorporation and application of ETs such as digital twins, artificial intelligence, the internet of things, and blockchain. Through a bibliometric analysis of scholarly publication outputs on ETs in the mining industry, this study visualises and ascertains the development and trends of these technologies from 1986 until now. Bibliometric datasets made up of 135 articles drawn from the popular Scopus database were employed. Dataset analysis revealed influential scholarly outputs, authors, and research clusters. The study provides relevant stakeholders in the sector with firsthand insight into the state of ET integration and use in the mining sector. Further studies are recommended to explore innovative technological interventions in other industries that can be adapted to enhance and optimise the activities and processes of the mining sector. Full article

With the accelerating global transition to clean energy, underground hydrogen storage (UHS) has gained significant attention as a flexible and renewable energy storage technology. Ontario, Canada, as a pioneer in energy transition, offers substantial underground storage potential, with its geological conditions of salt, limestone, and sandstone providing diverse options for hydrogen storage. However, the hydrogen transport characteristics of different rock media significantly affect the feasibility and safety of energy storage projects, warranting in-depth research. This study simulates the hydrogen flow and transport characteristics in typical energy storage digital rock core models (salt rock, limestone, and sandstone) from Ontario using the improved quartet structure generation set (I-QSGS) and the lattice Boltzmann method (LBM). The study systematically investigates the distribution of flow velocity fields, directional characteristics, and permeability differences, covering the impact of hydraulic changes on storage capacity and the mesoscopic flow behavior of hydrogen in porous media. The results show that salt rock, due to its dense structure, has the lowest permeability and airtightness, with extremely low hydrogen transport velocity that is minimally affected by pressure differences. The microfracture structure of limestone provides uneven transport pathways, exhibiting moderate permeability and fracture-dominated transport characteristics. Sandstone, with its higher porosity and good connectivity, has a significantly higher transport rate compared to the other two media, showing local high-velocity preferential flow paths. Directional analysis reveals that salt rock and sandstone exhibit significant anisotropy, while limestone’s transport characteristics are more uniform. Based on these findings, salt rock, with its superior sealing ability, demonstrates the best hydrogen storage performance, while limestone and sandstone also exhibit potential for storage under specific conditions, though further optimization and validation are required. This study provides a theoretical basis for site selection and operational parameter optimization for underground hydrogen storage in Ontario and offers valuable insights for energy storage projects in similar geological settings globally. Full article

Geometallurgy is an approach that integrates geology, mining, processing, and environmental areas, aiming to increase knowledge of the deposit and reduce risks in mining projects and/or operations. Growing changes in economic and operational scenarios require the development of robust models for metallurgical responses. Typically, the population of geometallurgical variables is small, and there are restrictions on applying geostatistical techniques, such as Ordinary Kriging, since recoveries are considered non-additive variables. This study used multiple linear regression to develop a geometallurgical model for a bauxite mine. The developed models enabled reconciliation with real results, and this application for bauxite mining represents a novelty in the literature. The model estimated the mass recovery in the coarse fraction with an accuracy greater than 97%. Additionally, the geometallurgical model developed for Mineração Rio do Norte (MRN) allows predictability and mapping potential product quality deviations. Full article

The presence of free muscovite in tailings can negatively affect the mechanical strength and rheological properties of cemented paste backfill, as has been observed for several cementitious materials. The aim of this study is to evaluate the influence of free muscovite content in tailings on the consistency and rheology of cemented paste backfill. For this purpose, cemented paste backfill mixtures were prepared from two different tailings. The mixtures were prepared at solids contents between 70% and 74% and with the addition of 5% GU (general use Portland cement)/slag binder. In addition, the influence of muscovite was studied by varying the muscovite content of the tailings from about 14% to 25%. Abrams cone slump tests and rheological analyses were carried out for each recipe. The results show a decrease in slump height and an increase in yield stress, Herschel–Bulkley flow index, and infinite shear rate Cross viscosity with increasing muscovite content for a given solids content. Therefore, water should be added to maintain the required flowability of cemented paste backfill, which increases the water/binder ratio and may affect the mechanical strength. A method is presented for determining the amount of binder to be incorporated to maintain the water/binder ratio of the original cemented paste backfill recipe. Full article

With the issue of energy shortages becoming increasingly serious, the need to shift to sustainable and clean energy sources has become urgent. However, due to the intermittent nature of most renewable energy sources, developing underground hydrogen storage (UHS) systems as backup energy solutions offers a promising solution. The thick and regionally extensive salt deposits in Unit B of Southern Ontario, Canada, have demonstrated significant potential for supporting such storage systems. Based on the stratigraphy statistics of unit B, this study investigates the feasibility and stability of underground hydrogen storage (UHS) in salt caverns, focusing on the effects of cavern shape, geometric parameters, and operating pressures. Three cavern shapes—cylindrical, cone-shaped, and ellipsoid-shaped—were analyzed using numerical simulations. Results indicate that cylindrical caverns with a diameter-to-height ratio of 1.5 provide the best balance between storage capacity and structural stability, while ellipsoid-shaped caverns offer reduced stress concentration but have less storage space, posing practical challenges during leaching. The results also indicate that the optimal pressure range for maintaining stability and minimizing leakage lies between 0.4 and 0.7 times the vertical in situ stress. Higher pressures increase storage capacity but lead to greater stress, displacements, and potential leakage risks, while lower pressure leads to internal extrusion tendency for cavern walls. Additionally, hydrogen leakage rate drops with the maximum working pressure, yet total leakage mass keeps a growing trend. Full article

This paper focuses on the solvometallurgical properties of choline chloride-based deep eutectic solvents for copper extraction from chalcopyrite concentrate. The study, conducted with scientific rigor, utilized the response surface methodology to optimize the extraction process and investigate the effects of the temperature and contact time on the copper recovery efficiency. The results showed that the ChCl-EG-Ox solvent at 80 °C and 48 h produced the highest copper recovery rate, exceeding 76%. This underscores the potential of deep eutectic solvents for sustainable metal extraction. Kinetic studies revealed the influence of temperature on dissolution kinetics, with higher temperatures leading to faster reaction rates. The mineralogical analysis demonstrated the changes in the chalcopyrite concentrate after dissolution, while spectroscopy and mass spectrometry highlighted the esterification reactions in the solvent. The study also examined the effects of adding water and heating on the solvent’s behavior, providing insights into the chemical interactions and structural changes. Ultimately, the research demonstrated that ChCl-based deep eutectic solvents present a promising avenue for environmentally friendly and efficient copper extraction processes in the metallurgical industry. Full article

Drilling and blasting is the conventional method used for rock fragmentation in open pit mining. Blast-induced damage can reduce the level of stability of benches and pit slopes. To develop an optimal blast design, an adequate knowledge of the rock properties and in situ fractures is needed. Fractures are generally the paths of least resistance for explosive energy and can affect the intensity of blast-induced damage. Discrete Fracture Networks (DFNs) are 3D representations of joint systems used for estimating the distribution of in situ fractures in a rock mass. The combined finite/discrete element method (FDEM) can be used to simulate the complex rock breakage process during a blast. The objective of this paper is to develop a methodology for assessing the influence of in situ joints on post-blast fracturing and the associated wall damage in 2D bench blast scenarios. First, a simple one-blasthole scenario is analyzed with the FDEM software Irazu 2D and calibrated based on a laboratory-scale blasting experiment available from previous literature. Secondly, more complex scenarios consisting of one-blasthole models at the bench scale were simulated. A bench blast without DFN (base case) and one with DFN were numerically simulated. The model with DFN demonstrated that the growth path and intensity of blast-induced fractures were governed by pre-existing fractures, which led to a smaller wall damage area. The damage intensity for the base case scenario is about 82% higher than for the blast model with DFN included, which highlights the significance of in situ fractures in the resulting blast damage intensity. The methodology for developing the DFN-included blasting simulation provides a more realistic modeling process for blast-induced wall damage assessment. This results in a better characterization of the blast damage zone and can lead to improved slope stability analyses. Full article