Mining doi: 10.3390/mining6020032

Authors: Nafiu Olanrewaju Ogunsola Hendrik Grobler

Blasting-induced ground vibrations, typically quantified by peak particle velocity (PPV), pose one of the most critical environmental challenges in surface mining and can damage nearby structures and disrupt surrounding ecosystems. Consequently, the development of reliable and accurate predictive models is essential for designing safe, environmentally responsible, and sustainable blasting operations. This study develops a robust predictive framework using a harmonized database of 506 blasting events, from which 386 high-quality records were retained after preprocessing to model PPV as a function of charge per delay (Q), monitoring distance (R), and rock mass rating (RMR). Several machine learning (ML) algorithms, including artificial neural networks trained using the Levenberg–Marquardt algorithm (ANN-LM), adaptive neuro-fuzzy inference systems (ANFIS), Gaussian process regression (GPR), and decision trees (DT), were evaluated alongside conventional empirical models such as the USBM, Ambraseys–Hendron, Langefors–Kihlstrom, and BIS. To further enhance predictive capability, two optimization strategies, Bayesian optimization (BO) and differential evolution (DE), were applied to the GPR model, producing optimized BO-GPR and DE-GPR variants. Model performance was assessed using the correlation coefficient (r), variance accounted for (VAF), mean absolute error (MAE), and relative root mean square error (RRMSE). Results indicate that the BO-GPR model achieved the best predictive performance during testing for both the two-input (Q, R) and three-input (Q, R, RMR) configurations, with r values of 0.97426 and 0.98381, respectively, and VAF values exceeding 94%. SHAP analysis revealed monitoring distance as the dominant attenuating factor controlling PPV. The optimized framework provides an accurate, interpretable tool for vibration prediction and precision blast design, supporting environmentally responsible, sustainable mining operations.

Mining doi: 10.3390/mining6020031

Authors: Kemalcan Aydogdu Sebnem Duzgun

This paper presents a comprehensive methodology for assessing supply chain transparency and resiliency using a data-driven approach. Leveraging global trade data and Harmonized System (HS) codes, the methodology maps each stage of the supply chain to enhance regulatory compliance and mitigate operational risks. Transparency is evaluated using a novel classification system that categorizes branches as fully transparent, highly transparent, moderately transparent, or non-transparent. This enables raw material traceability, Scope 3 greenhouse gas (GHG) emission estimation, and identification of high-emission nodes for targeted reductions. Resiliency is assessed through graph analytics and stress testing, incorporating metrics such as the Giant Connected Component (GCC) and probabilistic simulations to analyze vulnerabilities and develop recovery strategies. A case study on the Cr-13 Steel Drill Pipe supply chain highlights the benefits of incorporating scrap materials for sustainability, alongside challenges related to traceability due to regulatory gaps and non-transparent networks. Monte Carlo simulations identify critical nodes whose disruption significantly affects network connectivity; therefore, resiliency, and transparency. This methodology delivers actionable insights to improve supply chain resiliency, sustainability, and operational efficiency. It is scalable across industries, enabling stakeholders to optimize management strategies, align with global climate initiatives, and build resilient and transparent networks.

Mining doi: 10.3390/mining6020030

Authors: Pierre Sawadogo Samuel Nakolendoussé Tikou Belem

Quantifying time-dependent rock mass degradation is critical for assessing long-term slope stability during open-pit mine closure. This study evaluates the geotechnical evolution of Paleoproterozoic arenites and argillites in the semi-arid Essakane Main Zone (Burkina Faso) over a 0–9-year atmospheric exposure period. Field characterization across 32 sampling stations included density measurements, point load testing (Is(50)), determination of the Geological Strength Index (GSI), and petrographic analysis. The results demonstrate a time-dependent reduction in physico-mechanical properties, modeled with a high correlation (R2 = 0.80–0.99). While density exhibited minor reductions, structural degradation was pronounced; the GSI decreased by 10 points for both lithologies, and Is50 dropped significantly, particularly in argillites (4.1 to 2.3 MPa) relative to arenites (4.0 to 3.6 MPa). Petrographic evidence indicates negligible chemical weathering and mineral neoformation. Consequently, the degradation was attributed primarily to physical processes, specifically microcracking and discontinuity deterioration driven by thermal cycling and phyllosilicate sensitivity in argillites. These empirical relationships provide essential quantitative input for numerical slope stability modeling in semi-arid mine closure scenarios.

Mining doi: 10.3390/mining6020029

Authors: Guihe Li Jun He Jia Yao

Uranium is a resource with exceptionally high energy density, releasing substantially more energy per unit mass than conventional fossil fuels. In uranium mining, in situ leaching offers significant advantages over open-pit and underground mining, including reduced environmental impact, lower operational costs, enhanced safety, and improved controllability. Within the in situ leaching framework, acid leaching faces limitations in high-carbonate ore bodies, while alkaline leaching is unsuitable for deposits rich in pyrite and other sulfide minerals due to side reactions and precipitate formation that hinder leaching efficiency. In contrast, CO2-O2 leaching, as a neutral leaching approach, exhibits broader applicability across diverse ore types and geological settings. Incorporating CO2 into the leaching process also enables carbon utilization, offering a potential pathway to cleaner uranium extraction aligned with carbon reduction and sustainable energy goals. This review systematically examines the geochemical principles, as well as hydrological and transport phenomena governing CO2-O2 in situ leaching. Recent technological advances are summarized, including progress in reaction kinetics and leaching efficiency, leaching solution design and control, and reservoir modification. Furthermore, the techno-economic implications of CO2-O2 in situ leaching are critically assessed, with particular emphasis on operational cost structures and the evolution of techno-economic analysis methodologies. On this basis, key challenges and future directions are identified. This work aims to support the future large-scale and economically efficient deployment of CO2-O2 in situ leaching for uranium resource development.

Mining doi: 10.3390/mining6020028

Authors: Melita Srpak Darko Pavlović Sanja Kovač Karolina Novak Mavar Ivan Zelenika

In the original publication [...]

Mining doi: 10.3390/mining6020027

Authors: Emily Sarver Çigdem Keleş Setareh Ghaychi Afrouz Eleftheria Agioutanti

Mining practices and operating conditions are continually evolving, and the respirable fraction of coal mine dust is accordingly expected to change in composition and particle characteristics over time. Between the early 2000s and late 2010s, several regulatory and operational changes occurred in U.S. underground coal mining that could plausibly influence respirable coal mine dust (RCMD), including expanded rock-dusting practices, increased emphasis on respirable crystalline silica, and reductions in diesel emissions. This study evaluated temporal differences in RCMD by comparing samples collected in 2003–2005 and 2018–2020 using particle-level scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM–EDX). The most consistent temporal change observed was an increase in carbonate particles, consistent with expanded rock-dusting practices. Shifts in coal- and rock-strata-derived dust were observed but were not consistent across regions, and no consistent trend toward finer particle sizes was identified. These results demonstrate the value of particle-level analysis for evaluating changes in RCMD characteristics over time.

Mining doi: 10.3390/mining6020026

Authors: Ricardo Nunes Nathalie Risso Moe Momayez

Strategic Mine Planning (SMP) creates the long-term economic baseline for mining operations, yet economic variability necessitates Dynamic Mine Planning (DMP) to rapidly stress-test those financial assumptions. Currently, this capability is hindered by fragmented software ecosystems that require manual data handoffs, slowing iteration and breaking the audit trail between market data and valuation models. While Generative AI affords an opportunity to automate these workflows, its adoption in the mining industry is stalled by concerns over data quality and the risk of uncritical acceptance of automated outputs. Addressing these challenges, this paper describes the Mine Intelligence and Decision Support (MINDS) framework. We present MINDS as a modular reference architecture that uses Large Language Model (LLM) agents to orchestrate the economic evaluation process while maintaining strict engineering oversight. The system integrates a conversational interface with a multi-agent assessment layer that acts as an adversarial review, assessing price assumptions against market intelligence before generating economic valuation scenarios. A proof-of-concept using the Marvin copper benchmark evaluates the framework, demonstrating automated request-to-report orchestration, execution stability with an average debate latency of 10.69 s and a transparent decision audit trail. These findings show that MINDS can systematize economic scenario analysis without sacrificing the governance and verification required for definitive feasibility studies.

Mining doi: 10.3390/mining6010025

Authors: Arthur Cesa Venturella Eduardo Kercher de Oliveira Jéssica Weiler Eduardo Miranda Ethur Ivo André Homrich Schneider

This study assessed the feasibility of cultivating Lavandula dentata in Technosols produced from fine and coarse coal mining waste, focusing on plant development, substrate functionality, essential oil production, and post-mining ecosystem restoration. The Technosols were formulated using coal waste from the Moatize Coal Mine, Mozambique, combined or not in different configurations with agricultural soil and amended with sewage sludge (3% organic matter) and chemical fertilizer to ensure adequate nutrient availability. The experiments were conducted in 30 L containers, performed in triplicate for each experimental group. All settings allowed good plant growth, although the treatment that used only fine waste presented the closest performance to agricultural soil in terms of the production of aerial biomass. In this case, the dried biomass production of the shoots reached an average of 165 g per pot over 8 months (with a standard deviation of 20.3). The study showed a positive correlation between plant development and the available water capacity of the substrates. The plant tissue of L. dentata, in all the Technosols configurations studied, presented a similar composition to the control, with a biomass composition within the standard range established by the literature. The essential oil production ranged from 0.3 to 0.7% (m/m), averaging 0.5% (m/m), with chemical characteristics also alike the control trial. Technosols composed of coal waste from Moatize appear to be an alternative, both to provide a suitable destination for mining waste and to provide conditions for the revegetation and recovery of degraded areas by coal mining. This avoids the commissioning of nearby areas to supply soil for the restoration process. L. dentata, in addition to its various medical, ornamental, and aromatic uses, has potential as an “ecological trigger” in the restoration process with environmental and socioeconomic benefits.

Mining doi: 10.3390/mining6010024

Authors: Evgeniya Ushakova Elena Kalinina Pavel Belkin Elena Menshikova Sergey Blinov Roman Perevoshchikov Vladimir Pugach

The organization of safe industrial waste management is an integral part of the global sustainable development strategy. This study provides a preliminary assessment of the processing and recycling potential of strongly alkaline (pH 11–12) sediments accumulated in an abandoned sludge pond (Berezniki, Perm Krai, Russia), based on the initial characterization of their material composition. Sediment samples from the sludge pond were collected, layer-by-layer, over the entire depths of four sediment cores. The collected samples have the following characteristics: sediment particles are composed of up to 80% fine particles < 0.05 mm, with up to 20% fine particles < 0.002 mm. XRD data showed that the sediment consisted of calcite (67.7 wt.%), halite (11.5 wt.%), and other hydrogenic and terrigenous minerals. XRF data also found that the primary constituents in the sediment are CaO (up to 40%), Cl (up to 13%), and LOI (up to 35%). The results of the material composition study indicate a high degree of similarity between the accumulated sediments and solid waste from soda ash production, known as ammonia–soda residue (ASR). Based on experience with calcium-containing waste, this study recommends options for the secondary use of sludge, identifying two main possibilities: environmental protection and construction. We have developed an algorithm for the recycling and reuse of sludge that identifies risks, limitations, and recommended next steps. However, significant knowledge gaps regarding the environmental, toxicological, and the physical–mechanical properties of sludge prevent us from recommending a specific disposal option. The results of this review will serve as guidelines to help develop a roadmap for the disposal process. They will also inform decision-makers about sustainability issues related to industrial waste disposal.

Mining doi: 10.3390/mining6010023

Authors: Tobias Rudolph Marcin Piotr Pawlik Chia-Hsiang Yang Roman Przyrowski Andreas Müterthies Sebastian Teuwsen Michael Hegemann

Underground gas storage (UGS) in salt caverns is increasingly important for a flexible and secure energy supply and for stabilizing the gas market. However, cavern operations can induce surface ground movements that must be monitored to safeguard infrastructure integrity and environmental compatibility. This research analyzes horizontal (W–E) and vertical ground movements above the cavern field Gronau-Epe in northwestern Germany, using radar interferometry (InSAR), specifically the SBAS (Small Baseline Subset) approach, combined with clustering and multi-criteria analysis. The study was conducted in cooperation between Uniper Energy Storage GmbH, the Research Center for Post Mining at THGA Bochum, and the company EFTAS. Freely available Copernicus Sentinel 1 data were integrated with public soil maps and operational storage information. A multistage workflow quantified deformation patterns, classified coherent deformation zones via clustering, and evaluated geological and technical drivers using multi-criteria analysis to better distinguish operational (primary) from overburden (secondary) influences. Results reveal long term deformation trends closely linked in time and space to injection/withdrawal cycles. Locally confined vertical and horizontal movements near caverns are attributed to salt convergence triggered by cyclic pressure changes, but they are linked to (hydro)geological and pedological factors. The developed approach shows strong monitoring potential in addition to classic mine surveying.

Mining doi: 10.3390/mining6010022

Authors: Muhammad Azeem Raza Samuel Frimpong Saima Ghazal

Underground mining environments are complex and hazardous operations where emergencies continue to happen. Underground mine emergencies require rapid, high-stakes decision-making under conditions of uncertainty, stress, and limited visibility. Conventional mine emergency training largely relies on instruction-based approaches which provide insufficient exposure to the cognitive and behavioral demands of real underground emergency situations. There has been an identified need to train miners for knowledge, skills, abilities, and other characteristics (KSAOs). This study proposes an Adaptive Immersive Training Framework (AITF), a cognitively grounded architecture that integrates cognitive task analysis (CTA), KSAOs, and situational awareness assessment for miner self-escape training and readiness. The AITF aligns NIOSH-identified self-escape competencies with immersive training scenarios designed to assess and develop cognitive readiness and decision-making. CTA of historical mine accidents is introduced as a foundational design method for translating accident investigation findings into simulation scenarios and performance metrics. A CTA of 2006 Darby Mine No. 1 explosion is presented as a proof of concept. The proposed framework supports individualized assessment, iterative scenario refinement, and data-driven feedback. The AITF advances miner training toward cognitive preparedness during mine emergencies and provides a foundation for future training systems that leverage digital tools, digital twins, and artificial intelligence for the mines of the future.

Mining doi: 10.3390/mining6010021

Authors: Ravil Mussin Vassiliy Portnov Andrey Golik Nail Zamaliyev Denis Akhmatnurov Nikita Ganyukov Krzysztof Skrzypkowski Krzysztof Zagórski Svetlana Efremova

The principal difficulty in studying the physico-mechanical and filtration-capacity properties of coals and host rocks under laboratory conditions using core samples lies in reproducing natural thermodynamic conditions characteristic of in situ depths. To address this issue, specialized equipment and methodologies for transferring measurement results are employed, including the Hoek–Brown failure criterion, the structural weakening coefficient, and the development of thermodynamic models. The reliability and accuracy of such measurements are determined by the degree of conformity between the adopted laboratory conditions and natural in situ conditions, the number of samples representing different lithological varieties, and the adequacy of sampling procedures ensuring representativeness. Particular challenges arise when sampling cleated and fractured coals formed under natural stress–strain conditions and contain methane, which significantly influences their physical properties. These difficulties are especially pronounced in prepared-for-mining high-gas-content coal seams of the Karaganda Basin at depths of approximately 700 m, where obtaining representative samples is technically complicated. Reliable values of the physico-mechanical properties of the coal–rock mass are essential for geomechanical calculations aimed at ensuring safe mining of high-gas-content seams through risk assessment of geodynamic phenomena, particularly in zones of geological disturbances, floor heave, and roof collapse. In this context, the use of a comprehensive suite of geophysical logging data from exploration boreholes makes it possible to obtain continuous, high-precision information on physico-mechanical and filtration-capacity properties. These methods are particularly important for characterizing the coal–rock mass in operating mines, since the natural state of host rocks and prepared coal seams is altered due to stress relief caused by mine workings, preliminary degasification measures, and hydraulic fracturing. The problem addressed is the need for reliable assessment of rock and coal seam parameters under natural thermodynamic stress–strain conditions, taking into account lithological composition, structural heterogeneity, fracture development, stratigraphic differentiation, and gas saturation. The aim of this study is to ensure efficient and safe coal extraction based on geomechanical calculations utilizing physico-mechanical and filtration-capacity properties of host rocks and gas-bearing coal seams, whether prepared for mining or not yet extracted. The research methods are based on an integrated complex of geophysical logging of exploration wells, specialized software tools, and statistical processing techniques to identify patterns in physico-mechanical and filtration-capacity properties of host rocks and coal seams under natural stress–strain conditions, as well as to determine the nature of changes in these properties within coal seams and roof and floor rocks in prepared mining areas. The physico-mechanical and filtration-capacity properties of host rocks and coals from the Lenin and Kazakhstanskaya mines were determined. Regularities governing the application of these parameters to coals of different formations and depths were established; fracture orientations and characteristics were evaluated; and relationships between changes in coal seam parameters and gas content were identified. A comprehensive methodological framework for studying the physical and capacity properties of the coal–rock mass under natural thermodynamic conditions has been developed. Its primary application is the investigation of coal seams prepared for mining to support geomechanical calculations for efficient and safe coal extraction, the implementation of degasification measures for high-gas-content seams, and the assessment of gas-dynamic risks based on the character of variations in physical parameters.

Mining doi: 10.3390/mining6010020

Authors: Angela Maria Andreica Mădălin Andreica Mădălina Dănilă

Background: Bucket-wheel excavators are critical assets in surface mining operations, where structural modifications to increase productivity must be validated through rigorous stress analysis to ensure operational safety. Following modification of an ERc 1400-30/7 excavator’s bucket wheel from 18 to 20 buckets, increased operational loads necessitated experimental verification of structural integrity. Methods: A custom 10-channel strain-gauge data acquisition system with 0–10 kHz bandwidth measured stresses in cable anchoring lugs and H-type diagonal members under operational conditions at the Jilț lignite mine, Romania. Measurements were performed during both left and right bucket-wheel rotation. Finite element analysis validated experimental results. Results: Maximum equivalent stresses of 210.0 MPa and 167.1 MPa were measured in the left and right anchoring lugs, respectively, during left bucket-wheel rotation, representing 59% and 47% of material yield strength with safety factors of 1.69 and 2.12. Significant load asymmetry was observed, with left rotation inducing 220–284% higher stresses than right rotation. FEA validation showed <15% agreement with measurements. Dynamic stress amplification of 15–32% above quasi-static values was attributed to bucket–soil interaction and structural vibration. Conclusions: Despite increased operational loads, measured stresses remain below yield strength, confirming structural adequacy. Both anchoring lugs require prioritized monitoring due to elevated stress levels and load asymmetry. The validated methodology provides a framework for post-modification verification of large mining equipment.

Mining doi: 10.3390/mining6010019

Authors: Jesse Addy Ishmael Anafo Erik Westman

Measure-While-Drilling (MWD) data provide real-time insight into subsurface conditions and drilling performance, yet their complexity and operational noise often hinder reliable modeling. This study demonstrates the role of Exploratory Data Analysis (EDA) in developing robust machine learning (ML) models for lithology classification and penetration rate (PR) prediction in mining operations. A structured EDA workflow—comprising data integrity assessment, feature distribution analysis, correlation mapping, and depth-wise parameter profiling—was implemented to identify redundant attributes, isolate non-productive intervals, and enhance dataset consistency. Through EDA-informed normalization and feature selection, data consistency and model performance were significantly improved. Machine learning algorithms, including Decision Tree, Random Forest, and Multi-Layer Perceptron, were trained on the refined dataset. The Random Forest Classifier achieved 98.45% accuracy in lithology prediction, while the Random Forest Regressor produced the most accurate PR estimation (R2 = 0.83, RMSE = 0.52). These results highlight EDA as a critical foundation for constructing physics-informed, data-driven models that enhance predictive reliability and operational efficiency in mining environments.

Mining doi: 10.3390/mining6010018

Authors: Andrey O. Kalashnikov Diana V. Manukovskaya Dmitry G. Stepenshchikov

Geometallurgical modeling is pivotal for optimizing mining projects, yet the selection of an appropriate modeling strategy often relies on empirical experience rather than a systematic methodology. This paper introduces a novel systems-theoretic framework that formalizes geometallurgical modeling as an information acquisition problem under cost and uncertainty constraints. We propose a taxonomy of four fundamental strategies (S0–S3) defined by their use of direct measurement, interpolation, and regression to populate the key target variable geometallurgical ore type in a spatial block model. A generalized decision algorithm is developed to select the optimal strategy by evaluating economic feasibility and predictive accuracy against system characteristics such as deposit complexity, cost structure, and internal variable correlations. The framework demonstrates that the proxy-based strategy (S2) generally offers the most robust balance between cost and accuracy for complex deposits. This work provides a scalable and generalizable approach applicable not only to geometallurgy but also to other domains involving spatial resource characterization under uncertainty, such as environmental monitoring and petroleum engineering.

Mining doi: 10.3390/mining6010017

Authors: Abraham Armah Mehrdad Razavi Richard Otoo Benjamin Abankwa Sandra Donkor

The mining industry still faces major environmental and socioeconomic problems as a result of tailings dam failures, which highlights the urgent need for improved monitoring and early-warning systems. This research offers practical recommendations for improved monitoring and safer design practices, in addition to investigating the use of digital image processing (DIP) as a non-invasive technique for tracking slope deformation in tailings dam models subjected to incremental pore water pressure increases. To replicate real-world conditions as closely as possible, a scaled laboratory embankment was built using coarse and fine tailings. During controlled pore-pressure loading, more than 500 high-resolution photos were taken, recording the entire deformation sequence from initial displacement to slope failure. The images were processed using Mathematica to generate pixel-by-pixel displacement fields and vector plots, providing a detailed visualization of deformation mechanisms. The findings demonstrated that DIP accurately detects and measures surface displacement, revealing the mechanisms, direction, and intensity of deformation. This study illustrates the extensive potential of DIP for real-time monitoring by directly connecting slope instability triggered by incremental pore water pressure with visual indications of slope deformation. While the results confirm the strong potential of DIP for deformation monitoring with a minimum detectable displacement of approximately 1.0 mm under controlled laboratory conditions, its field application may be affected by scale effects, variable lighting, and environmental occlusion. The mining industry benefits greatly from the insights gained through in-depth image analysis, which promotes safer tailings dam design and management. Overall, DIP can provide a reliable, scalable foundation for real-time deformation monitoring in operational tailings dams, where continuous image-based measurements can help identify early signs of instability and support proactive risk management.

Mining doi: 10.3390/mining6010016

Authors: Sara Innocenzi Dario Lippiello

The marble extractive industry heavily depends on diesel-powered equipment, particularly wheel loaders and excavators used for block handling, resulting in high energy consumption and operating costs. In this study, the potential for fuel reduction through managerial and technological transitions was evaluated using the example of the marble quarry located in the Carrara basin. The energy demand of excavators, wheel loaders, and dumpers was characterized using telemetry data gathered through an Industry 4.0 methodology. A standard elementary cycle was modeled via the program evaluation and review technique (PERT) to map productive tasks and idling periods. To ensure comparability, a specific consumption coefficient (SCC) was defined. Subsequently, a novel fuel handling index (FHI) is proposed to prioritize investments by accounting for the uncertainties and production variables typical of quarry projects. Results demonstrate that while idle management offers a 4% fuel reduction, transitioning to hybrid wheel loaders represents a more significant strategy, achieving a 12% saving among the scenarios analyzed. The full-hybrid scenario leads to a cumulative 17% reduction. This framework supports decision-making for energy efficiency in high-yield extraction sectors, mitigating the economic risk associated with technological transitions.

Mining doi: 10.3390/mining6010015

Authors: Nikolas Dmitrovic Shunde Yin

Hydraulic fracturing is a widely used technique in the oil and gas industry and, specifically, it is used in mining for fragmentation enhancement and rockburst risk mitigation. The technique is actively being applied to cave mining environments to induce caving and improve seismic response in deep high-strength rock masses. The method has great potential in Long Hole Open Stoping mines for large-scale stress management in high-risk environments. The use of hydraulic fracturing in deep mining was explored through the development of a conceptual design for the destressing of a mining pillar. Numerical modeling was conducted to understand the effects hydraulic fracture has on stress reduction, and how fractured geometries affect these results. The results of this analysis showed that there is a strong dependence on the geometry of hydraulic fractures on the stress reduction potential of the method. The developed conceptual design showed that hydraulic fracturing can be directly integrated into mine planning as a tool to strategically manage the hazards associated with highly stress pillars. The activities associated with treatment design directly identifies when treatment should occur in the mining sequence and provides a general assessment of risk reduction that can be used directly for operational decision-making.

Mining doi: 10.3390/mining6010014

Authors: Yun Liu Hui Li

Close-distance multi-seam mining frequently induces secondary surface deformation and subsidence. Extracting a lower coal seam beneath an existing goaf repeatedly disturbs the overburden, often leading to roof collapse and the expansion of vertical water-conducting fractures that connect the working face to aquifers. Furthermore, the overlying goaf increases the risk of water inrush into active lower workings. This study investigates the mechanisms of strata reactivation and fracturing within an overlying goaf during lower seam extraction at a mine in Northwest China. Using theoretical analysis, numerical simulation, and microseismic monitoring, the research examines the secondary fracture mechanisms of the goaf roof and the resulting water-inrush potential. Research Findings: Strata Instability: Analysis of the key sandstone strata indicates that subsidence (W) of the key rock blocks satisfies 3.17 < W1 = 4.61 m < 18 m for the lower seam and 3.17 m < W2 = 5.31 m < 69.6 m for the 3-1# seam. These values confirm that key rock blocks in the basic roof undergo “reactivated” instability following fracture during lower seam mining. Pressure Relief and Fluid Dynamics: Mining-induced fracture initiation and propagation trigger strata reactivation. As the distance to the center of the goaf decreases, the subsidence of the overburden increases, ultimately resulting in a “trapezoidal” bending deformation pattern. Due to secondary activation, the roof subsidence 30 m above the 221 coal seam increased from 1.89 m to 5.475 m. The layers of high-strength, medium-grained sandstone and siltstone overlying the 317 coal seam and beneath the 221 goaf serve as high-strength material for the overlying rock formations. This suppresses the development of the caving zone and fracture zone, leading to subsidence failing to reach the sum of the heights of the two coal seams (6.8 m) and only reaching a value of 5.475 m. During extraction, the stress field undergoes a distinct evolution: it transitions from an initial “regular triangular” pressure-relief zone into a tripartite “weak–strong–strong” distribution. Furthermore, fluid discharge in the overlapping zone between the 317 working face and the 221 goaf increased sequentially, displaying an “alternating” pattern of peak vector variations as the face advanced. Microseismic Activity: Monitoring within the 300–500 m range identified frequent low-energy events and high-magnitude events (104 J, 105 J). These findings demonstrate that secondary excavation directly impacts the aquifer, creating a significant water-inrush hazard for the active working face.

Mining doi: 10.3390/mining6010013

Authors: Roman Vladimirovich Klyuev

The study presents the development of a backfill composite based on technogenic waste with controlled volumetric stability, ensuring complete filling of underground voids while maintaining high strength performance. The formulation incorporates beneficiation and metallurgical wastes, as well as activators, foaming agents, and reinforcing fibers. A comprehensive analysis of strength, pore structure, and fracturing was performed using CT-scanning, 3D reconstruction, and fractal analysis. It was established that fibers of different nature exert multidirectional effects on porosity and strength, with basalt fiber contributing to the formation of a hierarchically stable structure. The results obtained confirm the feasibility of producing an environmentally efficient backfill material for safe mineral resource extraction.

Mining doi: 10.3390/mining6010012

Authors: Raphael Vicq Ferreira Costa Marianna Lopes Soares Felipe de Souza Cologna Nathalia Froiman Carmona Ludmilla Lage Fabianna Resende Vieira Gabriela Maria Arantes Rodrigues Vitor Brognaro Pimenta Maurício José da Silva Soares Teresa Valente

The rupture of the B-I dam at the Córrego do Feijão mine in Brumadinho, Minas Gerais, Brazil, on 25 January 2019, prompted the implementation of environmental remediation actions. Among these actions is the need for groundwater quality monitoring in the Feijão Pit (“Cava de Feijão”) area due to the disposal of tailings from dams B-I, B-IV, and B-IVA at this site. In order to assess potential impacts on groundwater, the determination of baseline values for elements of interest was proposed for ten monitoring wells installed in and around the pit, with monitoring results from 2019 to 2024, totaling 854 samples. Due to the lack of hydrochemistry data and local hydrogeological complexity of the existing aquifers within the context of the Iron Quadrangle (IQ), it was necessary to evaluate and determine individual baseline values for each monitoring well, assessing data variability and population distribution. For this purpose, the 95–95 Upper Tolerance Limit (UTL) method was applied to establish baseline values providing a robust statistical approach that encompasses 95% of observations with a 95% confidence interval as it is a widely used standard in statistics due to its practical balance between confidence and precision. This methodology proved effective and has potential for application in groundwater monitoring in areas that may present high compositional variability due to the chemical heterogeneity of the groundwater. The baseline values obtained for the main elements of interest, which are iron (Fe) and manganese (Mn), were consistent with findings from previous studies conducted in the hydrogeological units of the study area, also demonstrating that the adopted methodology was effective in identifying representative concentrations for the region.

Mining doi: 10.3390/mining6010011

Authors: Roohollah Shirani Faradonbeh Phillip Stothard Robert Solomon

Mining is undergoing a transformation driven by digitalisation and automation, promising improvements in efficiency, sustainability, and safety [...]

Mining doi: 10.3390/mining6010010

Authors: Egor Odintsov Zidong Zhao Vladimir Gusev Kai Wang Wenwei Wang

Mining operations conducted beneath water-bearing strata pose significant risks associated with the development of water-conducting fracture zones in the overburden. The height criterion for this parameter is critical to ensuring the stability of underground mine workings and preventing the risk of water inrush incidents. The research is based on physical and numerical simulations and aims to forecast the development of the water-conducting fracture zone. The methodology is based on in situ hydrogeology data, geotechnical boreholes, physical 2D modeling of rock strata, discrete element modeling using UDEC, and finite–discrete element modeling using Prorock software. A physical model of layered rock mass is constructed to simulate unfilled excavation areas induced deformation under real polymetallic ore field conditions. Based on the results, relationships between vertical subsidence, layer curvature, inclination, and the height of the water-conducting fracture zone were obtained. Particular attention is given to the effects of tectonic discontinuities, chamber geometry, and backfilling on fracture development. A stepwise excavation sequence is simulated to reproduce field conditions and assess the evolution of stress and deformation fields in the overburden. The study reveals that the propagation of the fracture zone around a mine excavation adheres to a polynomial law, characterized by an increase in height concurrent with the expansion of the excavation. This approach enables the design of safe extraction strategies beneath aquifers or surface water bodies. The proposed framework is expected to enhance prediction accuracy and reduce uncertainties.

Mining doi: 10.3390/mining6010009

Authors: Coraquetzali Magdaleno López Saúl Ortiz Landeros Héctor Herrera Hernández Eugenia Aldeco Pérez Carlos Estrada Arteaga Antonia Sandoval González Jorge Morales Hernández

The effects of key variables on weak-acid-dissociable (WAD) and free cyanide oxidation by ozone injection in gold mine pulp were studied at laboratory scale to find an alternative cyanide treatment. A fractional factorial analysis of five process variables (O3/O2 flow, reaction time, NH4HSO3 concentration, temperature, and pH) informed a 60-run experimental matrix, in a 1 L cylindrical reactor, with the process variables controlled during the ozone injection. The findings may inform future strategies for safer cyanide management in gold mining processes. Free cyanide is the most toxic form of cyanide. Its oxidation increases with higher O3/O2 concentrations, longer exposure time, and higher pH. Maintaining a pH above 7 is crucial. Lower pH values favor the dissociation of cyanide into its toxic, free form. WAD cyanide oxidation depends mainly on the O3/O2 concentration, exposure time, and NH4HSO3 concentration. Increasing O3/O2 and time enhanced both WAD and free cyanide oxidation, while NH4HSO3 concentration affected oxidation rates differently. The results show that free cyanide was significantly more oxidized (84.1413%) than WAD cyanide (67.2423%). Controlling the WAD cyanide process yields excellent free cyanide oxidation. This represents ongoing improvement at an industrial scale. This approach quantifies the extent to which process variables affect the WAD and free cyanide oxidation under controlled conditions, thereby greatly reducing environmental impact.

Mining doi: 10.3390/mining6010008

Authors: Fangwei Xie Jianfei Wang Sergey Alexandrovich Gordin Aleksandr Nikolaevich Ermakov Kirill Aleksandrovich Varnavskiy

Mining conveyor belts are critical components in bulk material transportation, but their operational safety is frequently threatened by diverse damages such as blocks, cracks, foreign objects, and holes. Existing detection methods, including traditional computer vision and conventional neural networks, struggle to balance accuracy and efficiency in harsh mining environments—marked by high levels of dust, uneven lighting, and extreme scale variability (5–300 pixels). Our study proposes WTConv-YOLO, an improved model based on YOLOv11, integrating two core modules: (1) wavelet transform convolution (WTConv), which achieves a logarithmically expanding receptive field with linearly growing parameters, allowing for the concurrent capture of high-frequency local details and low-frequency global context; (2) Scale-based Dynamic Loss (SD Loss), which dynamically adjusts bounding box similarity and localization loss weights according to target scale, mitigating IoU fluctuation interference and enhancing small-target detection stability. Experiments on the Mining Industrial Conveyor Belt Dataset show that WTConv-YOLOv11 achieves a mean Average Precision (mAP@0.5) of 73.8%—a 3.5% improvement over the baseline YOLOv11. A Python-based software system is developed for end-to-end detection. This work provides a practical solution for reliable conveyor belt damage detection in mining scenarios.

Mining doi: 10.3390/mining6010007

Authors: Ahmet Kurt Muhammet Mustafa Kahraman

In the mining industry, where equipment breakdowns cause expensive unplanned downtime, operational continuity is paramount. Internet of Things (IoT) technologies have the potential to make predictions; however, most solutions lack a holistic view and mapping of complex system interdependencies. This study presents a comprehensive predictive maintenance (PdM) framework specifically designed for continuous-operation mining environments, with a primary focus on Semi-Autogenous Grinding (SAG) mills. By combining exploratory data analysis, advanced feature engineering, classical machine learning (Gradient Boosting Classifier), and deep learning (LSTM with multiple time-window configurations), the system achieves real-time anomaly detection, root-cause explanation, and failure forecasting up to 48 h in advance (average lead time: 17 h). A four-layer digital twin architecture integrated with Streamlit enables actionable alerts classified as emergency, planned, or preventive interventions. Applied to a one-year dataset comprising 99,854 hourly records from an industrial SAG mill, the hybrid model prevented an estimated 219.5 h of unplanned downtime, yielding substantial economic benefits. The proposed solution is deliberately designed for high adaptability across multiple equipment types and industrial sectors beyond mining.

Mining doi: 10.3390/mining6010006

Authors: Waldo T. Gerber Corne S. L. Schutte Andries G. S. Gous Jean H. van Laar

Water wastage management (WWM) in deep-level mines remains a critical challenge, as wastage increases operational costs and threatens sustainability. This study presents a systematic state-of-the-art review of WWM in deep-level mines. Relevant literature was critically assessed to establish current practices, identify limitations, and explore emerging solutions. Five principal approaches were identified: leak detection and repair, pressure control with fixed schedules, network optimisation, accountability measures, and smart management. While each provides benefits, significant challenges persist. Particularly, current pressure control techniques, essential for limiting leakage, rely on static demand profiles that cannot accommodate the stochastic nature of service water demand, often resulting in over- or under-supply. Smart management systems, which have proven effective for managing stochastic utilities in other industries, present a promising alternative. Enabling technologies such as sensors, automated valves, and tracking systems are already widely deployed in mining, underscoring the technical feasibility of such systems. However, no studies have yet examined their development for WWM in deep-level mines. This study recommends a framework for smart water management tailored to mining conditions and highlights three opportunities: developing real-time demand approximation methods, leveraging occupancy data for demand estimation, and integrating these models with mine water supply control infrastructure for implementation and evaluation.

Mining doi: 10.3390/mining6010005

Authors: Xiaodong Wang Congcong Zhao

To address the severe geological hazards (e.g., high ground stress and rock burst) that threaten safety and efficiency in ultra-deep mining, this study develops a comprehensive microseismic monitoring system tailored for the Sishanling Iron Mine—a typical ultra-large-scale, ultra-deep mine with an extraction depth exceeding 1500 m. The system integrates high-sensitivity sensors, real-time data transmission, and intelligent processing algorithms. A scientifically designed sensor deployment plan achieves full-coverage of key mining areas, while a multi-level data processing framework encompassing signal acquisition, event detection, location inversion, and magnitude calculation enhances result accuracy. Applied in actual operations, the system effectively captures microseismic events with magnitudes from −2.14 to −1.96, achieving optimal planar and spatial positioning errors of 6.75 m and 9.66 m, respectively. It provides real-time early warning for hazards like rock burst, thereby mitigating risks and ensuring operational continuity. This work offers a practical reference for constructing microseismic systems in similar “double super” mines and enriches the theoretical and technical framework for safety monitoring in deep mining.

Mining doi: 10.3390/mining6010004

Authors: Anatoliy Protosenya Alexey Ivanov

Assessing the stress–strain state around interacting mining excavations using the finite element method (FEM) is computationally expensive for parametric studies. This study evaluates tabular machine-learning surrogate models for the rapid prediction of full stress–strain fields in fractured rock masses treated as an equivalent continuum. A dataset of 1000 parametric FEM simulations using the elastoplastic generalized Hoek–Brown constitutive model was generated to train Random Forest, LightGBM, CatBoost, and Multilayer Perceptron (MLP) models based on geometric features. The results show that the best models achieve R2 scores of 0.96–0.97 for stress components and 0.99 for total displacements. LightGBM and CatBoost provide the optimal balance between accuracy and computational cost, offering speed-ups of 15 to 70 times compared to FEM. While Random Forest yields slightly higher accuracy, it is resource-intensive. Conversely, MLP is the fastest but less accurate. These findings demonstrate that data-driven surrogates can effectively replace repeated FEM simulations, enabling efficient parametric analysis and intelligent design optimization for mine workings.

Mining doi: 10.3390/mining6010003

Authors: Alireza Kamran Pishhesari Mahdi Shahsavar Amin Moniri-Morad Javad Sattarvand

While multi-view visualization systems are widely used for mining vehicle teleoperation, they often impose high cognitive load and restrict operator attention. To explore a more efficient alternative, this study evaluated a merged-view interface that integrates multiple camera perspectives into a single coherent display. In a controlled experiment, 35 participants navigated a teleoperated robot along a 50 m lab-scale path representative of an underground mine under both multi-view and merged-view conditions. Task performance and eye-tracking data—including completion time, path adherence, and speed-limit violations—were collected for comparison. The merged-view system enabled 6% faster completion times, 21% higher path adherence, and 28% fewer speed-limit violations. Eye-tracking metrics indicated more efficient and distributed attention: blink rate decreased by 29%, fixation duration shortened by 18%, saccade amplitude increased by 11%, and normalized gaze-transition entropy rose by 14%, reflecting broader and more adaptive scanning. NASA-TLX scores further showed a 27% reduction in perceived workload. Regression-based sensitivity analysis revealed that gaze entropy was the strongest predictor of efficiency in the multi-view condition, while fixation duration dominated under merged-view visualization. For path adherence, blink rate was most influential in the multi-view setup, whereas fixation duration became key in merged-view operation. Overall, the results indicated that merged-view visualization improved visual attention distribution and reduced cognitive tunneling indicators in a controlled laboratory teleoperation task, offering early-stage, interface-level insights motivated by mining-relevant teleoperation challenges.

Mining doi: 10.3390/mining6010002

Authors: Alejandro Díaz Heber Hernández Javier Gallo Luis Álvarez

Optimizing the blast energy distribution is crucial for enhancing rock fragmentation, minimizing overexcavation, and boosting profitability in mining operations. This study introduces a theoretical model to predict the blasting Energy Factor (Fe) in mining tunnels, based on the Cracking Energy (Eg) of the rock mass, derived from the deformation energy of brittle materials (Young’s modulus) and adjusted by the Rock Mass Rating (RMR). The model was validated using 42 blasting datasets from horizontal galleries at El Teniente mine, Chile. Data included geometric parameters (tunnel sections, drilling length, diameter, number of holes, meters drilled), explosive type and consumption, and geomechanical properties, particularly the RMR. Results show that as rock mass quality improves (higher RMR), both Fe and %Eg increase, more competent rock masses require higher input energy to initiate and propagate cracks, and a greater portion of that energy is effectively utilized for crack formation. For instance, rock masses with an RMR of 66 exhibited an average Fe of 7.62 MJ/m3 and %Eg of 4.8%, while those with an RMR of 75 showed higher values (Fe = 8.47 MJ/m3, %Eg = 6.4%). This confirms that less fractured rock masses require higher Fe and %Eg for effective fragmentation. Lithology also plays a significant role in energy consumption. Diorite displayed the highest Fe (8.34 MJ/m3) and higher efficiency (%Eg = 7.0%), whereas andesite showed lower Fe (7.61 MJ/m3) and lower crack propagation efficiency (%Eg = 3.7%). Unlike traditional Fe prediction methods, which rely solely on explosive data and excavation volume, this model integrates RMR, enabling more precise energy allocation and fostering sustainable mining practices. This approach enhances decision-making in blast design, offering a more robust framework for optimizing energy use in mining operations.

Mining doi: 10.3390/mining6010001

Authors: Jorge L. V. Mariz Giorgio de Tomi

The classification of mineral resources and reserves provides a structured framework for evaluating the geological, technical, and economic aspects of mineral deposits. To reduce subjectivity and enhance reliability, international reporting standards established the principles of transparency, materiality, and competence. Many operating mines are seeking alignment with these frameworks to strengthen governance and access global capital. Within this context, the Mineral Resources and Reserves Readiness Index (MR3 Index) is introduced as a tool to assess the degree of alignment of mining operations with international reporting requirements. For operating mines, a key variable in the MR3 Index is the demonstrated ability to consistently convert Inferred Mineral Resources into mine production, even without prior reclassification into Indicated or Measured categories. When supported by geological homogeneity and well-defined controls, this track record serves as a strong proxy for geological confidence and operational maturity. The methodology was applied to an underground lithium mine in Brazil, which achieved a readiness level of 95.5%. A sensitivity analysis demonstrated the robustness of the MR3 Index and showed that the final score is considerably more sensitive to the class scores than to the selection of class weights, reinforcing the importance of documentation quality and technical consistency in public reporting.

Mining doi: 10.3390/mining5040086

Authors: Abigail L. Paul Nicholas A. Beier

Reclamation of tailings facilities at oil sands mines in northern Alberta presents a significant challenge for industry, regulators, and researchers. Atterberg limits are an established method for quantifying clay behaviour in geotechnical engineering, which has been adopted for oil sands tailings due to their high clay mineral content. Correlations between remoulded undrained shear strength and liquidity index, originally developed for natural clays, have also been applied to oil sands tailings. This paper proposes a new material-specific correlation between remoulded undrained shear strength and liquidity index based on laboratory testing of oil sands tailings. Additionally, the results of Atterberg limits tests on oil sands tailings suggests that the inherent variability of the test itself has a greater effect on the measured value than the preparation method and test procedure. The results of this study support the idea that index properties such as Atterberg limits can provide a cost-effective method for field monitoring and early-stage reclamation design.

Mining doi: 10.3390/mining5040085

Authors: Gennadiy Korshunov Igor Iliashenko Stanislav Kovshov

This article delineates the outcomes of a comprehensive analysis of occupational conditions in coal mining, focusing on dust exposure. A multifaceted model is proposed for the holistic evaluation of occupational environments, integrating risk assessment methodologies and decision-making frameworks within a risk-based paradigm. Risk assessment involved pairwise comparison, T. Saaty’s Analytic Hierarchy Process, a pessimistic decision-making approach, and fuzzy set membership functions. Correlations were established between respiratory disease risk among open pit coal mine workers and dust generation sources at the project design phase. The risk values were then validated using source attributes and particle physicochemical parameter analysis, including disperse composition and morphology. The risk assessment identified haul roads as a predominant factor in occupational disease pathogenesis, demonstrating a calculated risk level of R = 0.512. The dispersed analysis indicated the prevalence of PM1.0 and submicron particles (≤1 µm) with about 77% of the particle count, the mass distribution showed the respirable fraction (1–5 µm) comprising up to 50% of the total dust mass. Considering in situ monitoring data and particulate morphology analysis haul roads (R = 0.281) and the overburden face (R = 0.213) were delineated as primary targets for the implementation of enhanced health and safety interventions. While most critical at the design stage amidst data scarcity and exposure uncertainty, the approach permits subsequent refinement of occupational risks during operations through the incorporation of empirical monitoring data.

Mining doi: 10.3390/mining5040084

Authors: Ibrahima Dia Bocar Sy Ousmane Diagne Sidy Mané Lamine Diouf

This paper presents a real-time quarry truck monitoring system that combines deep learning and license plate recognition (LPR) for operational monitoring and weighbridge reconciliation. Rather than estimating load volumes directly from imagery, the system ensures auditable matching between detected trucks and official weight records. Deployed at quarry checkpoints, fixed cameras stream to an edge stack that performs truck detection, line-crossing counts, and per-frame plate Optical Character Recognition (OCR); a temporal voting and format-constrained post-processing step consolidates plate strings for registry matching. The system exposes a dashboard with auditable session bundles (model/version hashes, Region of Interest (ROI)/line geometry, thresholds, logs) to ensure replay and traceability between offline evaluation and live operations. We evaluate detection (precision, recall, mAP@0.5, and mAP@0.5:0.95), tracking (ID metrics), and (LPR) usability, and we quantify operational validity by reconciling estimated shift-level tonnage T against weighbridge tonnage T* using Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), R2, and Bland–Altman analysis. Results show stable convergence of the detection models, reliable plate usability under varied optics (day, dusk, night, and dust), low-latency processing suitable for commodity hardware, and close agreement with weighbridge references at the shift level. The study demonstrates that vision-based counting coupled with plate linkage can provide regulator-ready KPIs and auditable evidence for production control in quarry operations.

Mining doi: 10.3390/mining5040083

Authors: Sergey Alexandrovich Gordin Alexander Nikolaevich Ermakov Alexander Yuryevich Zakharov Jianfei Wang

Suspended conveyor belts are widely used in mining, including in systems with non-contact support such as magnetically suspended conveyors, where the maximum admissible linear mass of the loaded belt determines the required supporting forces. This paper presents a method for estimating the upper limit of the linear mass of a suspended belt for a given belt width and bulk material. Several cross-sectional configurations are analysed, and analytical expressions for the bulk cross-sectional area under limiting fill are derived. A numerical search over the troughing radius is then performed to find the radius that maximises the cross-sectional area and to select the configuration that provides the largest area. For this configuration, the extremum condition leads to a transcendental equation; so, symbolic regression with the PySR package is used to obtain an explicit approximation for the radius that maximises the area as a function of belt width and angle of repose. Substituting this expression into the standard formula for linear mass yields a closed-form estimate of the maximum admissible linear mass. Numerical examples show good agreement with the optimisation results and indicate that the formula is suitable for preliminary design of suspended and magnetically suspended belt conveyors.

Mining doi: 10.3390/mining5040082

Authors: Yuriy Kozhubaev Roman Ershov Abbas Ali Yiming Yao Changwen Yin

The mining industry places high priority on occupational safety, process quality and operational efficiency. Roadheaders are widely deployed in coal mines to support fully automated excavation, reducing workers’ physical strain and improving overall safety. This article examines an automatic control system for a roadheader cutting head designed to increase mining efficiency, reduce energy consumption and maintain stable performance under varying coal and rock conditions. The system integrates advanced control algorithms with geological strength index (GSI) analysis and asynchronous motor control strategies. GSI-based adaptive speed control conserves energy and increases cutting efficiency compared to manual control. By reducing dynamic load fluctuations, transitions between different cutting zones become smoother, which decreases equipment wear. The proposed control system incorporates speed feedback loops that use a proportional–integral (PI) controller with field-oriented control (FOC), as well as super-twisted sliding mode control (STSMC) with FOC. FOC with STSMC improves roadheader productivity by applying advanced control strategies, adaptive speed regulation and precise geological strength analysis. It is also better able to handle disturbances and sudden loads thanks to STSMC’s nonlinear control robustness. The result is safer, more efficient, and more cost-effective mining that can be implemented across a wide range of underground mining scenarios.

Mining doi: 10.3390/mining5040081

Authors: Yuriy Kozhubaev Roman Ershov Yiming Yao Changwen Yin Yunfeng Kun

This article describes the current status and future development trends of mine hoist control systems. The growing market demand for hoists and the need for stable, uninterrupted operation ensure the practical application of this article. A permanent magnet synchronous motor (PMSM) is used as the primary power source for the mine hoist. A MATLAB model is developed, using PID controllers to control the PMSM’Scheme 10. tons of CO2 from electricity consumption, this equates to a reduction of 300 to 800 tons per year.

Mining doi: 10.3390/mining5040080

Authors: Leslie Vinet Héctor Valdés-González Mauricio Calderón

Despite technological advancements in mining, Chile lacks comprehensive risk management models for tailings storage facilities (TSFs), which hinders the prevention and mitigation of structural and environmental risks. This study aims to develop an integrated risk management model for TSFs in Chile, combining geological and mining engineering with an updated regulatory framework to enhance safety and reduce environmental impacts. The research adopts a mixed-methods approach. Qualitatively, it draws on 10 semi-structured interviews with engineers, geologists, academics, and professionals from the Chilean mining industry, selected through purposive sampling, to explore how and why the current risk management model should be improved. Quantitatively, it analyzes data from 303 surveys assessing the existing regulatory framework, a proposed new regulatory decree for Chile, and key variables to be considered in TSF risk management. The results present a new model that integrates geochemical and geotechnical characterization, process variables, in situ sensors, remote sensing, and artificial intelligence to generate dynamic risk indicators and early warning systems throughout the life cycle of the facility, including closure and liability valuation. Its multiscale design, adaptable to seismic and hydrogeological conditions and suitable for small- and medium-scale mining, overcomes existing static and fragmented approaches, enabling more effective decision-making with a focus on environmental and community safety. The study concludes that the model provides a robust and coherent tool for TSF risk management by integrating technical expertise, the current regulatory framework, and the management of key variables that enhance the ability to anticipate and mitigate structural and environmental risks.

Mining doi: 10.3390/mining5040079

Authors: Aleksandr Kulchitskiy Mikhail Nikolaev

Reliable detection of defects in steel wire ropes is pivotal to ensuring safety and maintaining operational reliability of hoisting and lifting systems in mining and other industries. This study proposes an automated monitoring method based on analyzing the cross-sectional size profile extracted from high-quality visual images. Each image undergoes preprocessing—adaptive binarization, noise suppression, and edge extraction—followed by formation of a one-dimensional thickness profile along the rope’s longitudinal axis. Aggregate statistical descriptors (mean, standard deviation, extrema, and shape descriptors) computed from this profile are supplied to a CatBoost gradient boosting classifier. The model achieves an F1-score exceeding 0.93 across diagnostic categories (intact, bend, kink, break), with particularly high accuracy for critical damage such as wire breaks. Compared with conventional image CNN classifiers, the proposed approach offers higher interpretability, lower computational complexity, and robustness to noise and visual artifacts. The results substantiate the method’s efficacy for real-time automated condition monitoring of mining equipment and its suitability for integration into industrial machine-vision systems. The results substantiate the method’s efficacy for real-time automated condition monitoring of mining equipment and its suitability for integration into industrial machine-vision systems.

Mining doi: 10.3390/mining5040078

Authors: Eshan K. Maitra Mohammed F. Al Dushaishi

Drillstring vibrations are detrimental to drill bits and downhole equipment, affecting drilling efficiency and operational cost in severe drillstring vibration cases. The complex behavior of drillstring vibration, including axial–torsional–lateral coupling and interactions among external forces, necessitated laboratory experiments to address challenges observed in the field. This review paper aims to provide practical insights into essential design considerations that support the effective development of laboratory-scale drillstring experiments. This study analyzes previous work on design methodologies, experimental configurations, measurement techniques, and downhole dynamic simulations. The comparative analysis, highlighting the key similarities and physical design novelties across different experiments, identifies that instrumentation limitations and incoherent downscaling approaches were among the primary setbacks from achieving realistic downscaled experimental models. Fewer studies have examined the interaction between flowing fluids and the drillstring to simulate realistic drilling operations. The study identifies unified experimental configurations across works that simulate similar drilling and vibration dynamics. A comprehensive summary of the foundational knowledge for research-objective-based design suggestions is presented to guide future laboratory-scale drilling vibration experimental design and innovation.

Mining doi: 10.3390/mining5040077

Authors: Aleksander Sokolov Vitalijs Kuzmovs Ulises Miranda Ordóñez Vladimir Gostilo

The determination of the elemental composition of minerals at mining enterprises is important at all stages of mineral processing. An evaluation of metrological characteristics achieved through the online analysis of lump, ore, charge feed, cake and slag materials on a conveyor belt is presented. Each implementation of the online XRF analysis at mining enterprises was preceded by laboratory studies, the development of measurement methods and the calibration of a specific XRF analyzer using standard reference samples for a specific concentration range of the monitored elements. In this work, typical application areas for monitoring the concentration of elements in rocks on conveyor belts are presented, as well as those solutions that made it possible to achieve the required measurement accuracy with an X-ray fluorescence analyzer in an online mode.

Mining doi: 10.3390/mining5040076

Authors: G. M. Wali Ullah Micah Nehring Mehmet Kizil Peter Knights

The mining industry faces the critical challenge of balancing economic profitability with environmental responsibility. Traditional mine planning models often prioritise financial gains, particularly Net Present Value (NPV), while placing less emphasis on environmental impacts, such as carbon emissions. This research presents a comprehensive multi-objective optimisation model for production scheduling in sublevel stoping operations. The model simultaneously aims to maximise NPV and minimise carbon emissions, providing a more sustainable framework for decision-making. The carbon emission objective comprehensively accounts for energy consumption across all key mining activities, including drilling, blasting, ventilation, transportation, crushing, and backfilling, using a “top-down” accounting method. The multi-objective problem is solved using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), which generates a set of Pareto-optimal solutions representing the trade-off between the two conflicting goals. The model is applied to a conceptual copper deposit with 200 stopes. The results demonstrate a clear trade-off: schedules with higher NPV inevitably lead to higher carbon emissions, and vice versa. For instance, one solution yields a high NPV of $312.94 million but with 23,602 tonnes of CO2 emissions. In contrast, another, more environmentally friendly solution reduces emissions by 26.5% to 18,647 tonnes, resulting in only a 1.21% reduction in NPV. This research concludes that integrating environmental objectives into mine planning is not only feasible but essential for promoting sustainable mining practices, offering a practical tool for operators to make informed, balanced decisions.

Mining doi: 10.3390/mining5040075

Authors: Cemalettin Okay Aksoy Guzin Gülsev Uyar Aksoy Yavuz Aydemir Hasan Berker Sarısan Erdem Kaya

Fires in underground mines pose significant risks to worker safety. In this study, a digital twin of an underground mine was created, and the heat, gas distribution, and airflow dynamics were investigated during and after the fire using computational fluid dynamics (CFDs) methods at three different locations. While traditional methods did not indicate any problems, the results from the CFDs analyses revealed some important findings. One of the key findings of the study was the change in airflow direction caused by the changing thermodynamic conditions caused by the fire. The digital twin allows us to demonstrate how a fire at any point within the mine can affect the entire mine under these changing thermodynamic conditions. The digital twin enables the real-time monitoring of underground events. Additionally, it facilitates strategic planning to anticipate potential incidents during a fire in an underground mine, allowing for necessary precautions to be implemented.

Mining doi: 10.3390/mining5040074

Authors: Jeff B. Langman Amanda Balogh D. Eric Aston Timothy E. Link Emile Milan Bridget Eckhardt

With the weathering of iron sulfide minerals, acid rock drainage (ARD) emanates from the 60-millon tonne Main Waste Stockpile (MWS) at the Red Dog Mine. Following completion of the stockpile, a collection trench was constructed in 2012–2013 to capture and treat a portion of the ARD, and a cover system was emplaced from 2021 to 2025 to cover 90% of the stockpile. Select wells in the collection trench are associated with the different cover phases. Analysis of the water chemistry of samples collected at the wells indicates increased pH and decreased dissolved solids with each phase of the cover along with significant changes in flow and solutes such as aluminum, iron, sulfate, and zinc. Although the cover should continue to decrease ARD volume, acidity, and solute concentrations, an evaluation of historical acid production and iron sulfide consumption in the stockpile indicates a likely majority of the iron sulfide content remains available for weathering and acid production. Continued MWS ARD monitoring is necessary to evaluate the multi-year effect of the cover because of the variability of the pre-cover ARD, identification of seasonal and multi-year precipitation influences on ARD generation, and a yet to be determined influence of the cover on the volume of infiltrating precipitation.

Mining doi: 10.3390/mining5040073

Authors: Denis Akhmatnurov Nail Zamaliyev Ravil Mussin Vladimir Demin Baurzhan Tolovkhan Nikita Ganyukov Krzysztof Skrzypkowski Waldemar Korzeniowski Jerzy Stasica Zbigniew Rak

The development of a geomechanical model is aimed at enhancing the safety of mining operations through the determination of optimal slope angles and the probabilistic assessment of pit wall stability. For the conditions of open-pit mining, three-dimensional geomechanical models were constructed based on the calculation of the slope stability factor using the Rocscience Slide2/Slide3 (v.9.027, 2023) software package. The stress–strain state of the rock mass at the final stage of extraction was evaluated using the finite element method. Strength reduction factors (SRF) were determined considering the physico-mechanical properties of the rocks forming the near-contour zone of the massif. The stability of the pit slopes was assessed along individual geological cross-sections in accordance with the design contours of the Northern Katpar open pit. Calculations performed using several methods confirmed the overall stability of the pit walls. The final design parameters of the projected open pit were determined. For the first time, it was established that in the southern and southwestern sectors of the Northern Katpar pit, within the elevation range of +700 to +400 m, a reduction in the SFR (from 1.18 to 1.41) occurs due to the predominance of siltstones and the presence of tectonic disturbances. The generalized results of numerical slope stability analyses for the design pit contour, together with the developed geological–structural model of the deposit, provide a basis for ensuring the safe conduct of mining operations at the site.

Mining doi: 10.3390/mining5040072

Authors: Chafika Eddine

This study examines Panama’s 2023 mining restrictions to illuminate persistent legitimacy crises in extractive governance. Employing a qualitative case study, it draws on 25 semi-structured interviews with government officials, industry representatives, Indigenous leaders, local communities, mining critics and other civil society actors, alongside policy and document analysis. Findings suggest that legitimacy reconstruction relies on four interdependent conditions: procedural justice, institutional trust, epistemic legitimacy, and relational governance. Stakeholders consistently emphasized transparency, capacity building, and inclusive engagement as essential for future mining activity, underscoring that technical standards alone are insufficient without credible institutions. Building on—but extending beyond—frameworks such as Social License to Operate (SLO) and Free, Prior and Informed Consent (FPIC), this paper offers Social Legitimacy for Mining (SLM) as a provisional, co-produced framework. Developed through literature synthesis and refined by diverse stakeholder perspectives, SLM is applied in Panama as an illustrative proof of concept that may inform further research and practice, while recognizing the need for additional adaptation across jurisdictions.

Mining doi: 10.3390/mining5040071

Authors: Jingyu Huang Yutong Chai Jennifer Williams Shunde Yin

Underground pumped hydro storage (UPHS) in solution-mined salt caverns offers a promising approach to address the intermittency of renewable energy in flat geological regions such as Southern Ontario, Canada. This work presents the first fully coupled thermo-hydro-mechanical (THM) numerical model of a two-cavern UPHS system in Southern Ontario, providing a foundational assessment of long-term cavern stability and brine leakage behavior under cyclic operation. The model captures the key interactions among deformation, leakage, and temperature effects governing cavern stability, evaluating cyclic brine injection–withdrawal at operating temperatures of 10 °C, 15 °C, and 20 °C over a five-year period. Results show that plastic deformation is constrained to localized zones at cavern–shale interfaces, with negligible risk of tensile failure. Creep deformation accelerates with temperature, yielding maximum strains of 2.6–3.2% and cumulative cavern closure of 1.8–2.6%, all within engineering safety thresholds. Leakage predominantly migrates through limestone interlayers, while shale contributes only local discharge pathways. Elevated temperature enhances leakage due to reduced brine viscosity, but cumulative volumes remain very low, confirming the sealing capacity of bedded salt. Overall, lower operating temperatures minimize both convergence and leakage, ensuring greater stability margins, indicating that UPHS operation should preferentially adopt lower brine temperatures to balance storage efficiency with long-term cavern stability. These findings highlight the feasibility of UPHS in Ontario’s salt formations and provide design guidance for balancing storage performance with geomechanical safety.

Mining doi: 10.3390/mining5040070

Authors: Tatiana Ponomarenko Konstantin Spivakov Natalia Romasheva

Aluminum’s unique properties have led to its widespread use across multiple industries, including transportation, aviation, power generation, construction, and food packaging. In recent years, global aluminum consumption has risen significantly, with China experiencing particularly sharp growth in both production and demand. In Russia, the aluminum industry is dominated by UC RUSAL, which consolidates all Russian aluminum and alumina production facilities, along with several international operations and mining assets. Despite its global presence, the company remains heavily reliant on imported raw materials (approximately 50%) for alumina production, resulting in reduced operational efficiency and declining output. This dependency has necessitated the exploration of strategies to diversify raw material sources across different stages of the aluminum production value chain. This study identifies and classifies key diversification options for global aluminum companies, focusing on secondary aluminum production, primary aluminum production, and alumina extraction from mined minerals, industrial waste, and by-products. The options were evaluated based on predefined criteria (feasibility, cost per Mg of alumina, logistics, alumina output, and economic security), and two options were selected. The research substantiates the feasibility of diversifying production through nepheline utilization. For the medium term, an economic efficiency assessment was conducted for a proposed 30% capacity expansion at the Pikalevo Alumina Refinery. Additionally, long-term opportunities for increasing aluminum output were identified, including leveraging foreign assets while accounting for associated risks.

Mining doi: 10.3390/mining5040069

Authors: Arthur Paim Cescon Giovani Jordi Bruschi Eduardo Pavan Korf

The concept of urban mining refers to the recovery and valorization of valuable resources from urban and industrial waste, contributing to circular economy principles. Within this framework, the present study provides a critical review of alkali-activated binders incorporating bivalve mollusk shells as alternative calcium sources. Shells from oysters, scallops, mussels, clams, cockles, and periwinkles were examined, either in their natural or calcined forms, for use as calcium sources, alkaline activators, or fillers in low-carbon binders. The review evaluates key processing parameters, including precursor composition, type and concentration of alkaline activators, curing conditions, and calcination temperatures, and compares the resulting mechanical, chemical, and microstructural properties. In addition, several studies report applications of these binders in soil stabilization and heavy metal immobilization, demonstrating performances comparable to Portland cement. The findings confirm the technical potential of mollusk shell residues and their contribution to the circular economy by diverting aquaculture waste from landfills and marine environments. Nonetheless, significant knowledge gaps persist, including the limited investigation of non-oyster species, the absence of field-scale studies, and the lack of resource mapping, life cycle, or economic assessments. This synthesis highlights preliminary insights, such as optimal calcination temperatures between 700 and 900 °C and effective combinations with silica and alumina-rich residues. Overall, it outlines a pathway toward transforming an underutilized waste stream into sustainable and technically viable construction materials.

Mining doi: 10.3390/mining5040068

Authors: Eustina Gurumani Tawanda Zvarivadza Lawrence Ndhlovu Rejoice Moyo Richard Masethe Mbalenhle Mpanza Moshood Onifade

Study develops and field-validates a SCADA-based real-time monitoring system to reduce unplanned dilution and hanging-wall over-break in underground long-hole stoping at a Zimbabwean gold mine. The objectives were to detect and constrain drilling deviation in real time, quantify the impact on stope stability and dilution, and evaluate operational and economic effects. The system integrates IMU inclinometers (hole angle), rotary encoders (depth), and LiDAR (collar spacing) with a Siemens S7 PLC (RS Americas, Fort Worth, TX, USA) and AVEVA™ InTouch HMI 2023 R2. Field trials across three production stopes (12L, 14L, 15L) compared baseline manual monitoring to SCADA control. Mean angular deviation fell from 0.8–1.6° to 0.2–0.3°, length deviation from 0.8–1.1 m to 0.05–0.08 m, and positional error from 0.25–0.32 m to 0.04–0.06 m; major collapses were eliminated, and ELOS dropped (e.g., 0.20 m to 0.05 m). Dilution decreased from 25% (typical 21–26%) to 16–18%, with mill feed grade rising from 1.90 to 2.25 g/t; production rates were maintained, with brief auto-stops in 5% of holes and rapid operator correction. Real-time drilling control materially reduces unplanned dilution and improves wall stability without productivity penalties, yielding compelling economics.

Mining doi: 10.3390/mining5040067

Authors: Melita Srpak Darko Pavlović Sanja Kovač Karolina Novak Mavar Ivan Zelenika

Varaždin County is rich in mineral resources, attracting considerable investor interest in opening new exploration areas and expanding existing exploitation fields. Since the economic value of mineral resources changes with market conditions, continuous professional assessment is required. Although the proposed methodological framework is broadly applicable to mineral resource management, this case study focuses on the exploitation of construction sand and gravel deposits in Varaždin County. In this way, it addresses the sustainability challenges characteristic of quarry operations rather than large-scale mining projects. The objective of this study was to develop and test a new method for quantifying sustainability indicators in the mineral resource management (spatial, resource-related, environmental, economic, and social sustainability—IPREGS) and for calculating an aggregated composite index (AKI) using a pilot project for construction sand and gravel. The research establishes a cause–effect relationship between quantified indicators (IPREGS) and the newly established aggregated composite index (AKI). Methodologically, the study applied multivariate analysis to questionnaire data, enabling the selection, weighting, and aggregation of indicators and the design of a conceptual framework for AKI calculation. The resulting methodology provides an instrument for monitoring and improving sustainable mineral resource management, supporting the objectives of the circular economy. The findings highlight the potential of the AKI to reduce systemic inefficiencies, guide policy development, and offer a transparent mechanism for assessing both implementation and effectiveness. This significantly improves the current state and strengthens the basis for evidence-based economic policy-making. The case study in Varaždin County further demonstrated that the AKI not only reproduces administrative decisions with high consistency but also clarifies how applicants should proceed in cases of partial acceptance and how policymakers can interpret conflicting outcomes across different index variants.

Mining doi: 10.3390/mining5040066

Authors: Roohollah Shirani Faradonbeh Mohammad Imtiaz Shah Moein Bahadori Hyoongdoo Jang

The relentless pace of industrialisation and globalisation has precipitated the rapid depletion of surface mineral deposits, presenting a formidable challenge to conventional mining operations and exerting a detrimental impact on their profitability. This depletion, coupled with the escalating demand for minerals, has driven prices to unprecedented highs, thereby inflating operating costs across various industries. Traditional surface and underground mining methods, struggling to meet burgeoning demands, contribute significantly to environmental degradation and substantial energy consumption. In response to these challenges, this study advocates for a paradigm shift from conventional mining methods and mineral resources toward untapped alternatives that hold the potential for enhanced economic viability and sustainability. Utilising environmentally friendly techniques and adopting more economical approaches becomes paramount in addressing the pressing demands of the current era and securing resources for future generations. This short review examines potential alternative mineral resources and the associated mining methods, including fluidised mining, deep-sea mining, brine mining, urban mining, in-situ and heap leaching, and space mining. A meticulous evaluation of the state-of-the-art technologies developed for these unconventional methods is conducted, including an assessment of their respective advantages and disadvantages. Finally, the study deliberates on the prospects of each approach, elucidating their potential contributions to alleviating the global metal crisis. This research provides insights that can inform sustainable mining practices and guide the industry toward a more environmentally responsible and economically viable future. The urgency of such a transition is underscored by the need to address the challenges posed by conventional mining and ensure the availability of mineral resources for generations to come.

Mining doi: 10.3390/mining5040065

Authors: Andrey Sidorenko Aleksey Kriukov Anatoliy Meshkov Sergey Sidorenko

This article presents a concept for modernizing the transport system of high-performance coal mines through the transition from traditional monorail to rubber-tyred transport (RTT). The study was conducted based on materials from the V.D. Yalevsky Mine of JSC “SUEK-Kuzbass” with daily longwall output up to 60,000 tons and production capacity up to 10 million tons per year. Analysis of the existing transport system efficiency revealed low equipment utilization rates (52–70%) and significant time losses during shift changeovers (up to 4.3 h/day in development workings). Technical solutions for phased RTT implementation were developed, including six roadway surface scenarios and a fleet composition of 60 specialized equipment units. The research methodology is based on time study observations using the automated “Granch” system, analysis of equipment utilization coefficients, and economic–mathematical modeling using NPV, MIRR, and payback period. The transition to rubber-tyred transport provides a five-fold increase in travel speed (from 4.5 to 25 km/h), reduction in shift changeover time to zero, increase in operating time by 20% in development and 4.5% in extraction, and a reduction in longwall move duration from 173–209 to 88 days. Additional coal production amounts to 6.5 million tons. Economic justification shows NPV of USD 64.2 million with MIRR of 2.4% and a payback period of 4.5 years.

Mining doi: 10.3390/mining5040064

Authors: Emiliano Mendonça Silva Maria do Carmo S. Barreto Marcello M. Veiga Giorgio De Tomi

Artisanal and Small-Scale Gold Mining (ASGM) is a primary source of global mercury pollution, creating an urgent need for sustainable, low-cost alternatives to amalgamation. This study investigates the use of cassava wastewater (manipueira), a cyanogenic agricultural byproduct, as a lixiviant for a gold concentrate (14.30–15.87 ppm Au) from an artisanal mine. Two approaches were evaluated: direct leaching with manipueira in natura (250 ppm CN−) in single and double 8 h and 12 h cycles, and leaching with a cyanide solution concentrated from dilute manipueira (100 ppm CN−) via a simplified air-stripping system. Results were benchmarked against the mine’s amalgamation (44.7% recovery) and 30-day heap leach (75.8% recovery) processes. The most effective method observed was a two-cycle, 8 h leach with manipueira in natura, which achieved a mean gold recovery of 76.75±4.71%. This result is comparable to the efficiency of the site’s lengthy heap leach process and suggests a promising, faster, route to eliminating mercury use. Longer (12 h) leaching cycles yielded lower recoveries, suggesting process limitations such as preg-robbing. The cyanide concentration method proved inefficient, recovering a maximum of 12.40% of the available cyanide and resulting in a weaker lixiviant. The findings demonstrate that while direct leaching is a viable alternative to mercury, the inherent instability of manipueira necessitates a focus on developing efficient, controlled systems to extract and concentrate its cyanide content, thereby creating a standardized “green” reagent from a large-volume agricultural waste stream.

Mining doi: 10.3390/mining5040063

Authors: Sahendra Ram Ashok Kumar Krzysztof Skrzypkowski Jerzy Stasica Zbigniew Rak Maciej Madziarz

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.

Mining doi: 10.3390/mining5040062

Authors: Keane Baulen Size Rejoice Moyo Richard Masethe Tawanda Zvarivadza Moshood Onifade

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.

Mining doi: 10.3390/mining5040061

Authors: Thania Nowaz Samuel Olmos Betin Lukas Förster Paulina Fernandez Oscar Jaime Restrepo Baena

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.

Mining doi: 10.3390/mining5040060

Authors: Mahdi Saadat Mattin Khishvand Andrew Seccombe

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.

Mining doi: 10.3390/mining5040059

Authors: Dmytro Rudakov Somayeh Sharifi Sebastian Westermann

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.

Mining doi: 10.3390/mining5030058

Authors: Jingyu Huang Yutong Chai Jennifer Williams Shunde Yin

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 σv 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.

Mining doi: 10.3390/mining5030057

Authors: Marat M. Khayrutdinov Alexander V. Aleksakhin Tatiana N. Kibuk Lyudmila N. Korshunova Maria A. Lozinskaya Olga Yu. Legoshina Oleg O. Skryabin Galina V. Kruzhkova

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.

Mining doi: 10.3390/mining5030056

Authors: Benedict Ncube Hideki Shimada Takashi Sasaoka Akihiro Hamanaka Koki Kawano Joan Atieno Onyango

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.

Mining doi: 10.3390/mining5030055

Authors: Yutong Chai Wenwen Cui Ao Ren Soheil Asgarpour Shunde Yin

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.

Mining doi: 10.3390/mining5030054

Authors: Panting He Yunsen Wang Guiping Zheng Hong Zhou

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.

Mining doi: 10.3390/mining5030053

Authors: Saima Khurram Zahid Khalil Rao Amin Beiranvand Pour Khurram Riaz Arshia Fatima Amna Ahmed

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.

Mining doi: 10.3390/mining5030052

Authors: Elmira Orynbassarova Hemayatullah Ahmadi Bakhberde Adebiyet Amin Beiranvand Pour Alma Bekbotayeva Nurmakhambet Sydyk

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.

Mining doi: 10.3390/mining5030051

Authors: Josip Kronja Ivo Galić

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.

Mining doi: 10.3390/mining5030049

Authors: Khussain Valiyev Aliya Yskak Elena Latyuk Alena Artykova Rakhimbayev Berik Vadim Chashkov Aleksandr Bulaev

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.

Mining doi: 10.3390/mining5030050

Authors: Ana Russo

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.

Mining doi: 10.3390/mining5030048

Authors: Mohammad Afrazi Chia Yu Huat Moshood Onifade Manoj Khandelwal Deji Olatunji Shonuga Hadi Fattahi Danial Jahed Armaghani

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.

Mining doi: 10.3390/mining5030047

Authors: Ali Tahaei Ehsan Fadaei Farzin Ghadami Argelia Fabiola Miranda Perez

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.

Mining doi: 10.3390/mining5030046

Authors: Oscar Jaime Restrepo-Baena Sara Pérez-Zapata María Margarita Gamarra Jorge Iván Tobón Gustavo Viana

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.

Mining doi: 10.3390/mining5030045

Authors: Marisa Nascimento Paulo Fernando Almeida Braga Paulo Sergio Moreira Soares

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 CO2eq per ton of LCE, of which 262 kg originated from foreground processes. In the background processes, the largest contribution was 456 kg of CO2eq 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.

Mining doi: 10.3390/mining5030044

Authors: Bugunei Bat-Erdene Koki Kawano Takashi Sasaoka Akihiro Hamanaka Hideki Shimada

A case study of designing a waste dump was conducted for the iron mine located in the Bulacan area, Philippines. Iron ore mines generate a relatively high amount of waste, and at the study mine, the constrained waste dumping area of 3 hectares necessitated a higher dump design, leading to potential stability issues. Additionally, the waste dump is projected to be situated on an inclined surface; subsequently, there is a concern about dump stability. Therefore, this study aims to find the optimum waste dump design by assessing its stability, and a geometrical configuration was conducted to optimize the bench parameters. Numerical modeling of the finite difference method (FDM) was used to estimate the distribution of the Factor of Safety by simulating several models. Models with steeper base inclinations (>12°) demonstrate progressive instability, as demonstrated by pre-assessment. The statistical analysis results show that the total model simulations with a 45-degree slope angle have a significantly high probability of failure of 38.2%. Whereas models with 35-degree and 40-degree slope angles have probabilities of failure calculated as 0.3% and 6.5%, respectively. Therefore, results suggest that the general slope angle should be kept at 40 degrees or less. Moreover, the results show that an average of 0.02 points drops in FoS for each 2.5 m of increment in dump height. Regarding geometrical setup, four benches with 7.5 m of berm would be preferable for the waste dump design of the case study. Overall, the effect of an inclined surface as a base was discussed, the effect of a gradual increase in dump height was outlined, and the significance of the dump slope angle on dump design was highlighted.

Mining doi: 10.3390/mining5030043

Authors: Fisseha Gebreegziabher Assefa Lu Xiang Zhongao Yang Angesom Gebretsadik Abdoul Wahab Yewuhalashet Fissha N. Rao Cheepurupalli Mohammed Sazid

Dust emissions from unpaved haul roads in open-pit coal mining pose a significant risk to air quality, health, and operational efficiency of mining operations. This study integrated real-time field monitoring with numerical simulations using ANSYS Fluent 2023 R1 to investigate the generation, dispersion, and migration of particulate matter (PM) at the Ha’erwusu open-pit coal mine under varying meteorological conditions. Real-time measurements of PM2.5, PM10, and TSP, along with meteorological variables (wind speed, wind direction, humidity, temperature, and air pressure), were collected and analyzed using Pearson’s correlation and multivariate linear regression analyses. Wind speed and air pressure emerged as dominant factors in winter, whereas wind and temperature were more influential in summer (R2 = 0.391 for temperature vs. PM2.5). External airflow simulations revealed that truck-induced turbulence and high wind speeds generated wake vortices with turbulent kinetic energy (TKE) peaking at 5.02 m2/s2, thereby accelerating particle dispersion. The dust migration rates reached 3.33 m/s within 6 s after emission and gradually decreased with distance. The particle settling velocities ranged from 0.218 m/s for coarse dust to 0.035 m/s for PM2.5, with dispersion extending up to 37 m downwind. The highest simulated dust concentration reached 4.34 × 10−2 g/m3 near a single truck and increased to 2.51 × 10−1 g/m3 under multiple-truck operations. Based on spatial attenuation trends, a minimum safety buffer of 55 m downwind and 45 m crosswind is recommended to minimize occupational exposure. These findings contribute to data-driven, weather-responsive dust suppression planning in open-pit mining operations and establish a validated modeling framework for future mitigation strategies in this field.

Mining doi: 10.3390/mining5030042

Authors: Jose Rodriguez George Barakos Phillip Stothard Alejandro Marcelo Acosta Quelopana

Technological advances are prompting mining companies to explore new options to enhance the efficiency of activities such as drilling, blasting, ventilation, and the loading and hauling of ore and waste. The emergence of digital environments, such as the Metaverse, allows companies in mining and other industrial sectors to simulate or predict scenarios in real time, generate ideas, and propose solutions before implementing them in the real world. There are various risks associated with the Metaverse and virtual worlds; however, there is insufficient information about the potential threats that could impact the Mining Metaverse. This investigation aims to establish a preliminary model for the efficient integration of the Metaverse into the mining industry. It highlights its potential by referencing previously adopted technologies such as virtual reality (VR), augmented reality (AR), and the Internet of Things (IoT) in mining and other sectors. It also seeks to identify and explain the risks associated with using a Mining Metaverse, considering constraints that will be valuable not only to the Australian mining industry but also on a global scale.

Mining doi: 10.3390/mining5030041

Authors: Jordan J. Silva Anna L. M. Batista Augusto Y. C. Santos Leonardo J. F. Campos Pedro H. A. Campos Pedro B. Casagrande Douglas B. Mazzinghy

Geometallurgy is an approach that utilizes predictive models that can support business decisions, mitigate risks, and enhance production efficiency. To develop an accurate geometallurgical model, it is essential to understand the behavior of each lithology within the ore body through geometallurgical testing. In this context, the present study aims to evaluate the performance of bench-scale tests conducted on the main mining fronts of a zinc mine operation located in Brazil. The mineral processing plant was designed to process lead and zinc sulfide ores without material stockpiling, where all ores extracted from the underground mine are immediately processed. The geometallurgical characterization was conducted through the following steps: sampling, crushing, grinding, and flotation. The recovery, concentrate, and tailing contents during the flotation stages of galena and sphalerite were analyzed. A mineralogical characterization using a Mineral Liberation Analyzer (MLA) was performed to assess the degree of particle liberation and mineral associations within the studied mining fronts. The results indicate that a higher degree of pyrite liberation leads to greater metallurgical recovery of mineralized bodies A (breccia-hosted orebody), B (sphalerite-rich doloarenite orebody), and C (upper replaced stratiform orebody). Among these, mineralized body C presents the highest recovery in the zinc and lead stages, with 99.5% and 86.2%, respectively.

Mining doi: 10.3390/mining5030040

Authors: Onalethata Saubi Rodrigo S. Jamisola Kesalopa Gaopale Raymond S. Suglo Oduetse Matsebe

In this study, we model a solution surface, with each point having nine components using artificial intelligence (AI), to optimise the effects of ground vibration during blasting operations in an open-pit diamond mine. This model has eight input parameters that can be adjusted by blasting engineers to arrive at a desired output value of ground vibration. It is built using the best performing artificial neural network architecture that best fits the blasting data from 100 blasting events provided by the Debswana diamond mine. Other AI algorithms used to compare the model’s performance were the k-nearest neighbour, support vector machine, and random forest—together with more traditional statistical approaches, i.e., multivariate and regression analyses. The input parameters were burden, spacing, stemming length, hole depth, hole diameter, distance from the blast face to the monitoring point, maximum charge per delay, and powder factor. The optimised model allows for variations in the input values, given the constraints, such that the output ground vibration will be within the minimum acceptable value. Through unconstrained optimisation, the minimum value of ground vibration is around 0.1 mm/s, which is within the vibration range caused by a passing vehicle.

Mining doi: 10.3390/mining5030039

Authors: Alexey Cherepovitsyn Irina Mekerova Alexander Nevolin

In a dynamic global market, platinum-group metals (PGMs), particularly palladium, are in high demand across various industries due to their unique properties. Palladium plays a crucial role in environmentally friendly technologies, such as catalytic converters, which mitigate harmful automotive emissions. Additionally, it is essential for clean energy production, particularly in hydrogen generation, which makes palladium a critical resource for building a sustainable and secure supply chain. This study evaluates the prospects of the palladium market through strategic analysis, focusing on the Russian mining and metals company PJSC MMC Norilsk Nickel. The research employs strategic and industry analysis methods to examine palladium production, market dynamics, and technological advancements, as well as emerging applications in the context of a green economy. The article analyzes the economics of palladium production, including price volatility driven by stringent environmental regulations and the rising adoption of electric vehicles. The palladium market faces challenges such as a constrained resource base, supply disruptions due to sanctions, price instability, and growing demand from key sectors, particularly the automotive industry. Nevertheless, innovation-driven trends offer promising opportunities for market growth, aligning with sustainable development principles and the transition toward a green, low-carbon economy in both established and emerging markets. As a key scientific contribution, this study proposes a modified methodological approach to industry analysis, enabling the assessment of a mining and metals company’s competitive sustainability in the palladium market over the medium and long term. Furthermore, the research models the life cycle of palladium as a commodity, considering evolving market trends and the rapid development of new industries within the green economy.

Mining doi: 10.3390/mining5030038

Authors: Keyumars Anvari Jörg Benndorf

Real-time mining (RTM) has become increasingly significant in response to the growing need for sustainable mineral resource extraction, driven by global population growth and technological progress. This innovative approach addresses critical challenges, such as declining ore grades, deeper and less accessible deposits, and rising energy costs, by integrating advanced online grade monitoring, data analysis, and process optimization. By employing real-time grade control, dynamic mine planning, and production optimization, it enhances the efficiency of resource extraction while minimizing environmental and social impacts. Originally proposed about a decade ago, RTM has gained attention for its potential to revolutionize the industry. This review examines recent advancements in closed-loop concepts, emphasizing the integration of advanced sensors and data analytics to enable continuous monitoring and adaptive decision making across the mining value chain. It highlights the role of online sensor technologies in providing high-resolution data for process optimization and evaluates various mining optimization techniques. The paper also explores data assimilation methods, such as Kalman filters and artificial intelligence (AI), showcasing their ability to continuously update models and reduce operational uncertainties. Ultimately, it proposes a comprehensive framework for adaptive, data-driven mining operations that promote sustainable development, enhance profitability, and improve decision-making capabilities.

Mining doi: 10.3390/mining5030037

Authors: Madeleine Guillen Guillermo Iriarte Hector Montes Gerardo San Martín Nicole Fantini

This study was conducted on a copper porphyry deposit located in Espinar, Cusco (Peru), with the objective of developing and comparing predictive models for processing capacity in SAG grinding circuits. A total of 174 samples were used for the JK Drop Weight Test (JKDWT) and 1172 for the Bond Work Index (BWi), along with 36 months of operational plant data. Three modeling methodologies were evaluated: DWi-BWi, SGI-BWi, and SMC-BWi (Mia, Mib), all integrated into a geometallurgical block model. Validation was performed through reconciliation with actual plant data, considering operational constraints such as transfer size (T80) and maximum throughput (TPH). The model based on SMC parameters and BWi showed the best predictive performance, with a root mean square error (RMSE) of 143 t/h and a mean relative deviation of 1.5%. This approach enables more accurate throughput forecasting, improving mine planning and operational efficiency. The results highlight the importance of integrating geometallurgical and operational data to build robust models that are adaptable to ore variability and applicable to both short- and long-term planning scenarios.

Mining doi: 10.3390/mining5020036

Authors: Fernanda Espínola Emilio Castillo Luis Felipe Orellana

The progress toward energy transition has made it essential to secure large quantities of critical metals to meet both short- and long-term demand, driving the exploration of new approaches, such as deep-sea mining (DSM). This study conducts a bibliometric analysis to examine the current scientific landscape of DSM, identifying trends, critical factors, and research gaps through a combined PESTEL and bibliographic analysis covering co-authorship, co-citation, co-occurrence, and bibliographic coupling. This comprehensive approach not only highlights emerging areas but also helps guide research efforts toward priority topics that support the advancement of DSM toward more sustainable exploitation. The results provide a general overview of recurrent themes and underexplored areas, serving as a basis for future research. While significant progress has been made in the environmental, technological, political, and legal dimensions, there remains a major gap in studies addressing the economic and social aspects of DSM, which account for less than 14% of the literature analyzed. This imbalance limits the integration of a truly sustainable framework, underscoring the need to promote interdisciplinary approaches and foster synergies among organizations and countries to build a more balanced and holistic understanding.

Mining doi: 10.3390/mining5020035

Authors: Isabelle Contrucci Jannes L. Kinscher Kévin Delage Emmanuelle Klein

The former Provence coal basin, closed since 2003, has been monitored by a microseismic network since 2008. The objective is to detect the precursor signs of a brittle subsidence that would be caused by the collapse of the old underground mining works. Since the start of monitoring, no subsidence has affected the risk areas, and nearly 4000 events with a local magnitude between −3 < ML < 3 have been recorded. One sector in particular, called the Fuveau swarm, located outside the risk zones and therefore outside the brittle subsidence hazard zones, has attracted attention since 2012 because it was the subject of several seismic episodes felt in 2010, 2012, 2014, late 2016–early 2017, and August 2017. Since 2017, it has been established that the observed seismicity cannot be explained only by instability phenomena in the old mining works. The most likely hypothesis is that of the remobilization of faults hydraulically connected to the mining works, with seismic activity that is closely linked to variations in the groundwater level, which are themselves influenced by pumping and effective rainfall. This paper shows, through multiplet analysis method of the seismic data recorded by the monitoring network stations, that part of the seismicity in the monitoring areas is also due to the reactivation of tectonic faults. This conclusion is based on the concordance between the location of the multiplets and the orientation of the main faults mapped in the studied areas, as well as on the fact that the strongest events belong to these multiplets. This finding underscores the need to integrate fault reactivation into seismic monitoring strategies, beyond the current focus on mining-induced instabilities. This conclusion leads us to recommend revising the list of post-mining hazards, as post-mining seismic risk is often overlooked in many European regulations.

Mining doi: 10.3390/mining5020034

Authors: Andrea Cronje Jean H. van Laar Johann F. van Rensburg Jan C. Vosloo

Despite the rapid improvement in the availability and resolution of real-time electricity data, budget development processes in mining have remained relatively unchanged. Currently, there is no standard for the evaluation of mine electricity cost budgets. This study aims to determine whether forecasting processes used by mines produce budgets of sufficient quality and resolution to be used as a tool for daily energy- and cost management. A literature review was conducted to determine a set of best practices for electricity budgeting on mines. These findings were used to develop a survey to evaluate the current state of budgeting processes on South African mines. Surveys were conducted at 41 mine business units. Survey results were processed and analyzed and found that there are significant shortcomings in complying with the identified best practices. The majority of mines produced forecasts in lower resolutions than actual available data, thereby reducing their usefulness as energy management tools. The methods currently employed by mining sites are not scalable and are vulnerable to human error. Only 7% of participating business units’ budgets passed the identified best practices. Adherence to best practices, identified in this paper, will assist mines in improving electricity cost forecasts for more proactive- and sustainable energy management. This will also assist the industry in aligning with the UN Sustainable Development Goals (SDGs) of Affordable and Clean Energy (SDG 7), Industry, Innovation, and Infrastructure (SDG 9), and Responsible Consumption and Production (SDG 12).

Mining doi: 10.3390/mining5020033

Authors: Abdurauf Abdukodirov Jörg Benndorf

The navigation of Unmanned Ground Vehicles (UGVs) in underground mining environments is critical for enhancing operational safety, efficiency, and automation in hazardous and constrained conditions. This paper presents a thorough review of path-planning algorithms employed for the navigation of UGVs in underground mines. It outlines the key components and requirements that are essential for an effective path planning framework, including sensors and the Robot Operating System (ROS). This review examines both global and local path-planning techniques, encompassing traditional graph-based methods, sampling-based approaches, nature-inspired algorithms, and reinforcement learning strategies. Through the analysis of the extant literature on the subject, this study highlights the strengths of the employed techniques, the application scenarios, the testing environments, and the optimization strategies. The most favorable and relevant algorithms, including A*, Rapidly-exploring Random Tree (RRT*), Dijkstra’s, Ant Colony Optimization (ACO), were identified. This paper acknowledges a significant limitation: the over-reliance on simulation testing for path-planning algorithms and the computational difficulties in implementing some of them in real mining conditions. It concludes by emphasizing the necessity for full-scale research on path planning in real mining conditions.

Mining doi: 10.3390/mining5020032

Authors: Rohan Le Roux Mohammadali Sepehri Siavash Khaksar Iain Murray

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.

Mining doi: 10.3390/mining5020031

Authors: Luis E. Martinez Mendoza Oscar J. Restrepo Baena Juan M. Menéndez-Aguado

This research aims to define an operational plan for the sustainability of small-scale artisanal gold mining (ASGM) in Northeast Antioquia, Colombia. A qualitative approach with a descriptive scope was used, for which a documentary or bibliographical review technique was made. Accordingly, articles, theses, books and institutional documents were reviewed as any contribution to the research topic. Likewise, this documentation contributed to defining aspects for elaborating the operational plan. Based on the reviewed sources, the need was found to propose an operational plan for this area to contribute to sustainability. Based on the sustainability analysis of ASGM in the zone, three common factors could be identified within the various positions proposed: the environmental, economic, and socio-cultural dimensions. With these, different needs were recognised in the area of study that still need action. An operational plan was devised to address these challenges and support the sector’s long-term sustainability.

Mining doi: 10.3390/mining5020030

Authors: Soumen Paul Nageswara R. Kolikipogu Hajime Ikeda Autar K. Raina Vinod A. Mendhe Somnath Chattopadhyaya V. M. S. R. Murthy

This research investigates the engineering properties of sandstone through tests performed prior to and following heat treatment. This study concentrated on evaluating the physical and mechanical properties, such as density, compressive strength, and wave velocities, in conjunction with the mineralogical, Cerchar hardness, and basic geochemical characteristics of the rock. Heat treatment was conducted at different temperatures (35 °C, 200 °C, 400 °C, 600 °C, and 800 °C), followed by analyses utilizing X-ray fluorescence (XRF), thin section analysis, and scanning electron microscopy (SEM) techniques. The results were analyzed to assess the influence of heat treatment on rock properties, utilizing Design Expert software for data evaluation. Numerical analysis with FLAC3D was conducted to validate the observed values at various temperature levels, further investigating the impact of the treatment on the engineering properties of sandstone. A significant finding was the reduction in strength, particularly correlated with a decrease in primary wave velocity, which is associated with an uneven distribution of strength within the rock. Increased temperature results in stress concentrations that facilitate crack formation, while variations in grain size significantly influence crack propagation. This study highlights the substantial influence of temperature on the compressive strength and general material properties of sandstone.

Mining doi: 10.3390/mining5020029

Authors: Xiujuan Feng Qianjin Niu

A low-grade uranium-gold polymetallic ore is associated with many rare elements, such as beryllium (Be), zirconium (Zr), thorium (Th), and cerium (Ce). It has potential development and utilization value. In order to improve the development and utilization rate of a low-grade uranium-gold polymetallic ore, beryllium (Be) in low-grade uranium-gold polymetallic ore was extracted by a combined method of (NH)2SO4 and Al2(SO4)3. The effects of different concentrations of (NH4)2SO4 solution on the leaching of beryllium (Be) in low-grade uranium-gold polymetallic ore with different particle sizes after sieving were studied; microstructure and physicochemical analyses were carried out. The leaching mechanism of beryllium (Be) was revealed. The experimental results showed that when the low-grade uranium-gold polymetallic ore in (NH)2SO4 solution is 6 g/L and Al2(SO4)3 is 3 g/L, the particle size of the ore sample is 0.01 mm, the concentration of beryllium (Be) in the leaching solution reaches 0.521 mg/L after 3 days of leaching, the concentration of beryllium (Be) in the leaching solution of the sample without Al2(SO4)3 solution is 0.007 mg/L, and the leaching rate of beryllium (Be) reaches 98.6%. SEM and XRD analyses showed that the silicate composition in the sample after leaching was obviously destroyed compared with the control group when the (NH)2SO4 solution was 6 g/L, which increased the contact area on the surface of the ore sample and promoted the leaching of beryllium (Be) in the uranium ore sample. The research results lay a theoretical foundation for the development and extraction of beryllium (Be) associated with low-grade uranium-gold polymetallic ore.

Mining doi: 10.3390/mining5020028

Authors: Geisianny Moreira Jefferson Brendon Almeida dos Reis Elisa Catão Caldeira Pires Cristine Chaves Barreto Helson Mario Martins do Vale

Mining significantly impacts terrestrial ecosystems despite its importance to the global economy. As part of soil ecosystems, fungi are highly responsive to environmental and human-induced drivers, shifting community composition and structure. Indeed, fungi play a key role in maintaining ecosystem resilience. Thus, we aim to address the question of whether soil fungal communities maintain similar ecological functions despite changes in community composition due to the impact of mining across ecosystems. To evaluate the ecological role of fungi across four ecosystems with varying iron mining impact levels, we used the FUNGuild database to assign functional guilds at the genus level. Co-occurrence network and ordination analyses were used to infer ecological relationships among fungal taxa and visualize the correlation between edaphic properties and fungal communities. A total of 22 functional guilds were identified, with dung saprotrophs, wood saprotrophs, fungal parasites, plant pathogens, ectomycorrhizal fungi, animal pathogens, and endophytes being the most abundant. Soil properties such as pH, organic matter, texture, and nutrients drive taxonomic and functional shifts. Our findings indicate that while mining activities shift fungal community compositions across ecosystems, the profiles of functional guilds show overlap between highly, moderately, and lowly impacted ecosystems, indicating functional redundancy. Network analysis reveals that highly connected hub taxa contribute to ecological redundancy across ecosystems and might act as a buffer against environmental disturbances. Our findings emphasize the important ecological role of soil fungi and indicate a potential for using fungal communities as bioindicators of ecological recovery in post-mining landscapes. From a mining and restoration perspective, this offers a low-cost, ecologically meaningful tool for monitoring soil recovery and guiding reclamation efforts.

Mining doi: 10.3390/mining5020027

Authors: Rodrigo Estay Claudia Pavez-Orrego

Induced seismicity resulting from mining activities is one of the major challenges faced by the mining industry. Although such events have been documented for over a century in countries with extensive mining traditions, such as Canada, Australia, and Chile, their impact has intensified over time. This increase is primarily attributed to the greater extraction depths, where elevated stress levels and environmental conditions heighten the likelihood of rockburst occurrences. Seismic events within mines lead to significant human casualties and substantial infrastructure damage, necessitating the implementation of various safety protocols. Among these, seismic indicators are employed to identify periods when high-magnitude seismic events are most likely to occur through the analysis of parameters such as magnitude, energy, time, and decay rate. In this context, the present study aims to utilize the accumulated frictional energy generated by microearthquakes within the Bobrek mine, Poland, as a seismic indicator (variation of frictional energy in time), establishing its correlation with the occurrence of high-magnitude seismic events exceeding the background activity. Thousands of combinations of seismic parameters were tested to maximize the performance of this frictional energy-based indicator, parameters such as moment magnitude, frictional energy, and rock properties. The optimal set of parameters was determined using the Piece Skill Score (PSS) and subsequently applied to the Accumulated Frictional Heat (AFH) methodology. According to the results, the seismic indicator forecasts 86.6% of events with magnitudes Mw ≥ 2.3, with an average forecasting time of 9.76 h, indicating that, on average, these events can be anticipated approximately 10 h before their occurrence.

Mining doi: 10.3390/mining5020026

Authors: Fabiane Paschoal da Veiga William Mateus Kubiaki Levandoski Giovani Jordi Bruschi Mariana Krogel Maria Alice Piovesan Deise Trevizan Pelissaro Pedro Domingos Marques Prietto Eduardo Pavan Korf

The increasing production of iron ore has led to the accumulation of iron ore tailings (IOTs), which pose significant environmental and safety risks when stored in tailings dams. This study investigates the potential of IOTs as a precursor in alkali-activated binder systems, aiming to provide a sustainable solution for mining waste management. Industrial calcium carbide lime and sodium silicate (Na2SiO3) were used as activators in varying concentrations (Na2SiO3: 10%, 15%, 20%, 25%, and 30%; carbide lime: 5%, 7.5%, and 10%), with curing conditions of 23 °C for 7 days. Techniques including unconfined compressive strength tests, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and metal leaching tests were employed to evaluate the mechanical performance and environmental safety of the alkali-activated binders. The results reveal that a mixture containing 20% Na2SiO3 and 10% carbide lime achieved the highest compressive strength of 0.33 MPa at 7 days. The binder also showed negligible metal leaching, meeting environmental safety standards. These findings confirm the viability of using IOTs in the development of durable, eco-friendly construction materials, offering a scalable and sustainable solution for the management of mining waste and promoting circular economy principles in the construction sector.

Mining doi: 10.3390/mining5020025

Authors: Javier Ruiz-del-Solar

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.

Mining doi: 10.3390/mining5020024

Authors: Lucas de Almeida Gama Paixao William Pratt Rogers Erisvaldo Bitencourt de Jesus

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.

Mining doi: 10.3390/mining5020023

Authors: Ava Azadi Moe Momayez

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.

Mining doi: 10.3390/mining5020022

Authors: Magreth Sungwa Dotto Yashar Pourrahimian

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.

Mining doi: 10.3390/mining5020021

Authors: Gabriele Baldassarre Camila Mori De Oliveira Adriano Fiorucci Rossana Bellopede Paola Marini

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.

Mining doi: 10.3390/mining5010020

Authors: Daniel Goldstein Chris Aldrich Quanxi Shao Louisa O’Connor

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.

Mining doi: 10.3390/mining5010019

Authors: Paulo F. A. Braga Caroline R. dos S. Brigido Camila P. Pinto Silvia C. A. França Gustavo D. Rosales

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.