Mining doi: 10.3390/mining6030081

Authors: Mohammed Al-Aqydy Ahmad M. Al-Saleh Talal Ghazi Alharbi

Feldspar and quartz are essential ceramic raw materials, with feldspar acting as a flux and quartz as a structural filler. Feldspathic sand derived from granitic masses of the eastern Arabian Shield represents a promising local source. This study evaluates upgraded granitic detritus, commercially termed silspar, from the Khurs granite of the Dawadimi terrane. Twenty-five samples were chemically and technologically characterized; one compositionally anomalous sample (S2) was retained in the analytical tables for transparency but excluded before resource-level statistical preprocessing. Pearson correlation, principal component analysis and Ward hierarchical clustering were applied to 24 representative samples using eight chemical variables, while shrinkage, loss on ignition (LOI), whiteness (L*) and water absorption were used for external technological validation. Four chemistry-defined groups were identified: S1 and S3 form a dark impurity-rich pair; S4–S9 form the cleanest ceramic-grade group; S10–S13, S15–S17 and S24 define a transitional Ca-Fe-influenced group; and S14, S18–S23 and S25 form a more coherent potassic group. The firing variables differ significantly among the chemistry-defined groups under the standardized laboratory procedure. The results support controlled ceramic use of the representative Khurs-derived silspar, subject to stockpile homogenization and impurity control. Because phase proportions are normative estimates rather than direct XRD determinations, the work is presented as an integrated preliminary industrial-mineral screening assessment rather than a complete quantitative mineral-phase characterization.

Mining doi: 10.3390/mining6030080

Authors: Jakub Pietras Damian Kurdek Ryszard Hejmanowski Agnieszka A. Malinowska

Rock-salt mines deform through chamber closure and vertical translation of the surrounding rock mass, yet these responses are commonly evaluated separately. This study integrates underground levelling, convergence monitoring, and mine geometry to identify the depth at which vertical motion changes from subsidence to uplift in the Kłodawa Salt Mine, Poland. The database comprises levelling campaigns conducted between 1962 and 2021 and 337 convergence series containing 7671 observations. Annual vertical velocities were calculated between actual survey epochs. The zero-vertical-velocity zone (ZVVZ) was estimated between adjacent measured levels with opposite median velocities; bootstrap resampling and mutual-nearest benchmark pairing quantified sampling uncertainty and local consistency. No transition was bracketed within the monitored 450–630 m interval in 1987–1992. In 1992–1994, shallow levels continued to subside while deeper levels uplifted, yielding crossing depths of 570.4 m in Field 1, 514.4 m in Field 2, and 476.8 m in Field 3. Field 1 retained the reversal in the 1994–2021 average, with a crossing near 585.3 m, although that long interval cannot resolve intermediate changes. Independent, mostly later convergence records show a marked increase in closure below 690 m and increasing horizontal dominance with depth. The ZVVZ is therefore a spatially variable kinematic boundary within a mining-modified deformation field, not a strain-free horizon: roof descent and floor uplift may generate rapid closure while mean vertical translation remains near zero. The method provides a reproducible monitoring state for deep salt mines. Future work should re-adjust the historical levelling networks, acquire synchronous levelling and convergence data at 690–780 m, and test excavation, geology, and backfilling controls using a calibrated three-dimensional viscoplastic model.

Mining doi: 10.3390/mining6030079

Authors: Teodora Gavrilescu Vlad Păunescu

Historical underground workings in the Maleia–Livezeni sector of the Petroșani Coal Basin were reconstructed from four archival mining plans and a coordinate-referenced Drawing Exchange Format (DXF) dataset. Twelve extraction-sector polygons, principal galleries, exploitation limits, dated mining stages, and 567 internally checked mining-elevation annotations associated with Coal Seam No. 3 were integrated in a geographic information system (GIS) using the Romanian Stereo 70 coordinate reference system (EPSG:3844). Net elevation differences between 2007 and 2026 at seventeen surface benchmarks were used as response variables. Nearest-feature relationships and mining-exposure indicators for 50, 100, and 150 m neighbourhoods were evaluated using exploratory Spearman rank correlations. Among the originally selected 50, 100, and 150 m neighbourhoods, cumulative gallery length within 50 m showed the strongest planimetric association with |ΔZ| (ρ = 0.734, p = 0.0008, q = 0.010), while extraction-sector coverage and gallery length remained positively associated at broader scales. R19 showed the greatest immediate extraction-sector exposure, whereas R14, which recorded the largest elevation loss, was characterised by a broader concentration of surrounding workings. R09 recorded the smallest elevation change and was approximately 470 m from the nearest reconstructed extraction sector. Cumulative mining configuration was more informative than nearest-sector distance alone for interpreting spatially variable net surface-elevation change in this legacy mining setting and highlighted the limitations of archival GIS reconstruction.

Mining doi: 10.3390/mining6030078

Authors: Md Shehab Islam Iman Masoumi Zach Agioutantis Steven J. Schafrik Pedram Roghanchi Ali Moradi

The transition from open pit to underground mining is becoming increasingly important as near-surface ore is depleted and mines seek to extend operating life. Yet its environmental and operational effects are often discussed separately. This systematic review examines the risks reported during the transition stage and develops an integrated framework for mine planning. Following a PRISMA-guided approach, peer-reviewed literature published between 2010 and 2026 was screened, and 69 records were included in the final review, comprising 66 primary studies and three directly relevant review articles. The evidence shows that the transition redistributes rather than simply reduces environmental pressure. Water management, ground stability, underground air quality, ventilation, and energy demand may become more important as underground development advances, while some surface impacts may decline as open pit activity decreases. The review therefore treats the active overlap period as a distinct planning stage and brings the main environmental and operational risks into one transition-planning framework.

Mining doi: 10.3390/mining6030077

Authors: Pengtao Wang Jiajian Li Weidong Song Bolin Tang Zaihai Wu Hanwen Jia Xiaofei Li

In the subsequent backfilling mining method, the composite structure formed by the ore pillar and the backfill is the key element in ensuring the stability of the working face. Its mechanical behaviour directly affects mining safety and ore recovery rates. In order to elucidate the mechanical response and failure mechanisms of rock-like backfill composite structures (RLBCS) under biaxial loading, specimens with different water-to-cement (W/C) ratios (0.5, 0.6, 0.7 and 0.8) for the rock-like backfill were prepared in this study. Biaxial loading tests were conducted, with digital image correlation (DIC) technology employed simultaneously to monitor the evolution of strain and displacement on the specimen surface. The results indicate that the biaxial strength of RLBCS decreases exponentially as the W/C increases. When the W/C exceeds 0.7, the strength reaches a plateau. The strength contribution of the backfill increases relatively. The axial stress–strain curve exhibits four distinct phases. A pronounced bimodal distribution is observed when the W/C exceeds 0.5. The evolution of lateral strain exhibits a transition point where compression is followed by expansion. The threshold for lateral expansion stress exhibits a non-monotonic variation. The modulus of elasticity decreases as the W/C increases. The apparent structural strain ratio exhibits a non-monotonic variation. The failure pattern exhibits marked asymmetry. The rock-like side shows tensile failure. Where the interface is present, this manifests as localised crushing at the top of the rock-like layer, cracking along the interface, and bulging of the backfill. The W/C ratio of the rock-like material governs the failure mechanism of RLBCS. The strain localisation modes in backfill materials are classified into two types: post-peak abrupt and pre-peak gradual. The evolution of interface strain exhibits four distinct stages: an initial abrupt change, cooperative deformation, crack initiation, and post-peak instability. The spatiotemporal evolution of interfacial delamination and the deformation of the backfill was quantified through displacement field analysis. The research findings provide a theoretical basis for the design of underground mining operations.

Mining doi: 10.3390/mining6030076

Authors: Prince Owusu-Ansah Alex Justice Frimpong Ebenezer Tawiah Arhin Saviour Kwame Woangbah Ebenezer Adusei Ernest Adarkwah-Sarpong

The mining industry in Ghana, despite its economic significance, continues to grapple with occupational health and safety (OHS) issues, which include but are not limited to high accident rates and a largely reactive approach to safety. In this study, current practices in OHS management are assessed and a model is developed that reflects the interdependencies and associations between workplace hazards, accidents, health effects and preventative actions in a probabilistic fashion. A quantitative analytical design was employed and a sample of 298 workers, safety officers and supervisors from mines were surveyed. The data were analysed using Principal Component Analysis (PCA) to derive latent OHS factors, K-modes clustering and Hierarchical Clustering to classify worker safety profiles, and a Bayesian Network model was employed to investigate probabilistic dependencies. Three major OHS dimensions emerged from PCA: perceived adequacy of safety measures, formal training exposure, and safety resources. Three distinct worker profiles were identified, suggesting that the provision of physical safety equipment does not necessarily reflect perceived operational safety. Moreover, the Bayesian Network model indicated a conditional dependency between workers’ reported health issues and formal accident reporting, and that high hazard environments more than double the probability of an accident occurring (from 0.216 to 0.453). The results indicate that the industry is now operating in an incident-based manner. In order to mitigate the likelihood of accidents, management needs to move towards anticipatory safety management systems, which involve proactive health monitoring, equipment maintenance, and implementation of safety policies in practice.

Mining doi: 10.3390/mining6030075

Authors: Usha Yadav Siddhartha Agarwal Dariusz Obracaj Anindya Sinha Kunal Ranjit Andrei Andras Pedram Masoudi

The mining industry is facing increasing pressure to improve operational safety, environmental performance, and resource efficiency while adapting to rapid technological change. In this context, the concept of Mining Industry 5.0 is emerging as an extension of Industry 4.0, promoting the integration of human-centric approaches with advanced digital technologies in mining systems. This paper proposes a 6S framework—Safety, Security, Sustainability, Sensitivity, Service, and Smartness—conceptualized as a Cyber-Physical-Social Systems (CPSS)-based model that co-optimizes these six dimensions and supports adaptive and human-centric mining operations across the entire value chain. The study is based on a structured literature review and a comparative analysis of digital transformation practices in related sectors, including manufacturing, logistics, and energy, to identify solutions applicable to mining environments. The key enabling technologies, including artificial intelligence, digital twins, cyber-physical systems, and intelligent automation, are evaluated as particularly relevant to mining operations for improving workplace safety, process efficiency, and environmental management. The paper addresses challenges, including high investment costs, limited digital competencies, data interoperability issues, and cybersecurity concerns in mining practice. The results support the development of a roadmap for Mining Industry 5.0 by integrating the proposed 6S framework with technical and organizational operations in the mining sector.

Mining doi: 10.3390/mining6030074

Authors: Min Jia Dong Wang Yanhui Tang

Scientific evaluation of open-pit slope stability under the disturbance of underground goaf is critical to the safe production of open-pit coal mines. Taking an open-pit coal mine in Inner Mongolia as the engineering background, this study investigates the influence mechanism of underground goaf on slope stability. With discrete element numerical simulation, the movement law of overlying strata above the goaf is revealed, and the heights of the “three zones” and boundary movement angles are determined. Furthermore, limit-equilibrium theory is adopted to analyze slope stability affected by goafs from three perspectives: goaf span, occurrence position and inter-goaf spacing. The results indicate that under partial extraction conditions, goaf span is positively correlated with the height of the caving zone and negatively correlated with the boundary movement angle. As the goaf width increases, the mining-induced deformation field expands progressively, and a distinct bending-subsidence zone develops in the 50 m wide single-goaf case, resulting in a complete caving–fractured–bending-subsidence zonation. For adjacent goafs, smaller inter-goaf spacing promotes overlap of the mining-induced deformation fields and generally enhances overburden disturbance. As the spacing increases, the interaction between adjacent goafs tends to weaken, although the degree of reduction depends on goaf width and the deformation parameter considered. Therefore, the spacing of approximately 50 m observed in the present simulations is interpreted as a site-specific transition range rather than a universal critical threshold. Two landslide modes are identified in the Baozhixil open-pit mine: circular arc sliding and composite sliding controlled by the weak interlayer of No. 1 coal seam. Slope stability is negatively correlated with goaf span and positively correlated with the horizontal distance between the goaf and the slope face. For the analysis of inter-goaf spacing, slope stability shows a positive correlation with the proportion of non-collapse deformation area within the sliding mass.

Mining doi: 10.3390/mining6030073

Authors: Juan M. Menéndez-Aguado Oscar Jaime Restrepo Baena Juan C. Lucena

The strategic landscape governing extractive industries has undergone a profound transformation in the brief interval since the inaugural edition of this Special Issue in 2024 [...]

Mining doi: 10.3390/mining6030072

Authors: Zheng Chen Thuong Thi Nguyen Yuki Semoto Takaya Hamai Satoshi Soda

Mine drainage containing manganese (Mn) and zinc (Zn) poses a major environmental challenge. In Japan, Mn-rich mine drainage frequently exceeds the discharge standards of 10 mg/L for Mn and 2 mg/L for Zn. This study evaluated laboratory-scale continuous-flow constructed wetlands (CWs) for the treatment of both synthetic and actual mine drainage without addition of external organic carbon. The actual mine drainage was collected from an anonymous former Cu–Pb–Zn mine in Japan. Two limestone-filled CWs (2 L), one planted with Phragmites australis and the other unplanted, were operated at hydraulic retention times of 1–2 d. The influent mine drainage contained approximately 66 mg/L Mn and 10–15 mg/L Zn together with Fe, Cu, Cd, and Pb. During 170 days of continuous operation, the planted CW consistently achieved lower effluent Mn and Zn concentrations than the unplanted CW under both synthetic and actual mine drainage conditions. Effluent Mn concentrations in the planted CW ranged from 5.5 to 20.0 mg/L, compared with 46.1–54.2 mg/L in the unplanted CW. Likewise, effluent Zn concentrations ranged from 0.21 to 3.0 mg/L in the planted CW and from 2.4 to 10.1 mg/L in the unplanted CW. The superior performance of the planted CW was associated with enhanced limestone dissolution, elevated pH, and favorable rhizosphere conditions that likely promoted biologically mediated Mn(II) oxidation and the formation of Mn oxides, while Mn carbonate precipitation may also have contributed to Mn removal. These findings demonstrate that limestone-based planted CWs can effectively treat Mn-rich mine drainage without addition of external organic carbon and highlight their potential as sustainable, low-energy passive treatment systems for the long-term management of abandoned mine drainage.

Mining doi: 10.3390/mining6030071

Authors: Khalid Boujounoui Abdelmoughit Abidi Khalid El Amari Dong-Sheng He Imane Aarab Oussama Jabrane Pedro Martínez-Pagán

The selective separation of chalcopyrite from pyritic ores represents a major industrial challenge due to inadvertent copper activation. This study systematically investigates the batch flotation kinetics of a complex sulfide ore (Draa Sfar North, Morocco) using a first-order kinetic model (R2>0.916). The impacts of pulp pH, chemical depressants, and specialized collectors were evaluated to optimize the copper/iron selectivity index (SICu/Fe). The results reveal a high-alkalinity paradox: At pH 11.0, chalcopyrite kinetics experience a severe passivation bottleneck (Ki,Cu=0.1330 min−1). At pH 11.5, selectivity collapses (SI=2.64) due to persistent iron sulfide floatability (Ki,Fe=0.2066 min−1). Conversely, natural pH (≈6.0) provides a superior baseline (SI=3.32), where 40 g/t sodium cyanide (NaCN) yielded a peak index of SICu/Fe=10.25. As an eco-friendly substitute, sodium lignosulfonate (LSNa) achieved outstanding performance (SICu/Fe=5.30), reducing iron kinetics to their lowest level (Ki,Fe=0.0356 min−1) via ferric–anionic complexation. Furthermore, Danafloat 271 secured the highest collector-driven selectivity (SICu/Fe=5.03) by suppressing the iron matrix (Ki,Fe=0.0306 min−1) following Hard–Soft Acid–Base principles. This study clarifies specific aspects of selective copper–iron flotation, demonstrating that natural pH circuits with green depressants or selective collectors offer a sustainable alternative.

Mining doi: 10.3390/mining6030070

Authors: Yaşar Ağan Türker Hüdaverdi

Blast-induced flyrock is one of the most critical hazards in surface mining and quarrying, posing significant risks to occupational safety, nearby structures, and the environment. Accurate prediction of flyrock distance is therefore essential for safe blast design and effective risk management. In this study, Random Forest (RF), Extra Trees (ET), and Support Vector Regression (SVR) models were developed to predict flyrock distance, and their hyperparameters were optimized using the Secretary Bird Optimization Algorithm (SBOA) and the Spider-Tailed Horned Viper Optimizer (STHVO). Prior to optimization, six cross-validation strategies were compared using GridSearchCV to identify the most appropriate strategy for each model. The final models were evaluated on an independent test dataset using the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), variance accounted for (VAF), and Nash–Sutcliffe efficiency (NSE). Model interpretability was investigated using SHapley Additive exPlanations (SHAP). The results showed that appropriate cross-validation and metaheuristic hyperparameter optimization improved predictive performance, with the ET–STHVO model achieving the best overall results. SHAP analysis identified B/D, PF, H/B, RBS, and U/B as the most influential predictors. The proposed framework provides an accurate, robust, and interpretable decision-support tool for safer blasting operations.

Mining doi: 10.3390/mining6030069

Authors: Abdelhak Tabet Oussama Zerzour Haythem Dinar Khaled Kefi Ali Ahmed Benyoucef Toufik Batouche

The Ouenza open-pit mine is one of Algeria’s major iron ore producers, where efficient blasting and fragmentation control are essential to maintaining stable, productive mining operations. The primary objective of this study is to quantitatively assess the agreement between predicted and measured rock fragmentation at the Ouenza open-pit mine. The research methodology includes a comprehensive analysis of blasting parameters. Field experiments used four blasts, all executed with the same blasting plans on the same working face to ensure comparability. The rock fragmentation was precisely measured and analyzed using the advanced image-processing software Wip-Frag to determine the particle-size distribution. The Kuz–Ram model predicted the fragment size distribution using the same blasting design implemented in the field, and the predicted fragmentation was quantitatively evaluated against Wip-Frag measurements using the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The statistical evaluation yielded an R2 of 0.9095, an RMSE of 9.71%, and an MAE of 6.54%, indicating good overall agreement between the predicted and measured fragmentation, despite noticeable deviations in the coarse-fragment size range. The observed discrepancies were mainly associated with potential inaccuracies in the field implementation of the designed blast pattern, limited compliance with blasting procedures, and the natural heterogeneity of the rock mass. The results show that comparing Wip-Frag measurements with Kuz–Ram predictions is an effective way to identify discrepancies between predicted and actual fragmentation and to determine the field factors driving these differences. These findings provide practical insights into blast implementation and fragmentation control under actual mining conditions.

Mining doi: 10.3390/mining6030068

Authors: Al-zamely Saif Salim Ibraheem Batugin Andrian Sergeevich Thulfiqar S. Hussein

Current geological site assessment models focus on examining stable natural features and neglect measuring surrounding industrial and environmental hazards. This methodological deficiency is clearly evident in the management of technological heritage in existing or abandoned mining areas. This research presents the modified GAMGES geo-environmental assessment model to address this practical gap in the regional planning of industrial geoparks. The proposed model integrates the geo-environmental safety (GES) block as a mathematical discount factor that measures the risks of surface deformation, seismic activity, gas emissions, and pollution from mining waste. The research applies the developed criteria to the Kirov Mine database in the Kuzbass Basin, renowned for its combined technological and geodynamic characteristics. The numerical results demonstrate a lower overall site value compared to the conventional model due to the detection of active ground fissures and continuous methane migration across tectonic faults. The model provides planners with a quantitative decision support framework for dividing industrial heritage sites into multiple safety zones that ensure visitor protection and the security of sustainable tourism facilities.

Mining doi: 10.3390/mining6030066

Authors: Shuo Yan Xiaodong Wang Yiming Wen Xiangdong Niu Yong Cheng

Deep metal mines commonly contain vertically stacked goafs whose geometry and rock mass properties are incompletely documented. This study evaluates a field-constrained screening framework for high-displacement material scenarios at the Lehong Pb-Zn mine. The framework combines a Latin hypercube sampling (LHS)-FLAC3D response library with static Bayesian inference. Evidence comprised 93 goaf records, 186 Mathews exposed-surface assessments, laboratory constraints, and 40 archived numerical scenarios, whose maximum downward displacement ranged from 4.48 to 31.75 cm. Friction angle φ showed the strongest marginal Pearson correlation with displacement (r = −0.81), followed by cohesion (r = −0.55) and elastic modulus (r = −0.22). At the response library Q75 threshold of 15.04 cm, the Laplace-smoothed probability increased from 0.262 (95% credible interval, 0.142–0.403) across all scenarios to 0.600 (0.352–0.824) under joint cohesion–friction angle degradation. However, the archived design was not an ideal 40-point LHS, and bootstrap resampling retained the scenario ordering in only 45.8–54.8% of replicates. All 93 inventory identifiers matched the Mathews stability table, enabling reproducible site-level triage when Bayesian network results are combined with treatment and stability evidence. The framework is an exploratory screening tool rather than an absolute failure probability model, collapse propagation model, or dynamic early warning system.

Mining doi: 10.3390/mining6030067

Authors: Chengjin Gu Matilde Costa e Silva Baogui Yang Qifan Ren Paula Falcão Neves

Cemented paste backfill (CPB) is widely used in mining, but its high brittleness, low toughness, and limited ductility can cause it to crack and spall, or even damage the overall structure, thereby limiting its application in deep underground mine excavations. To this end, this study investigates the damage and failure mechanisms of cemented gangue–rubber paste backfill (CGRPB) and analyses its energy evolution characteristics. The aims are to: (i) assess the CGRPB mechanical properties, i.e., toughness, ductility, and brittleness due to incorporating rubber; (ii) analyze the fracture propagation process of CGRPB from an energy evolution perspective. Therefore, monotonic and cyclic compression tests were conducted on CGRPB samples containing 0%, 5%, and 10% recycled rubber powder. This study focuses on analyzing compressive strength, failure modes, stress–strain responses, energy evolution and the damage evolution process. Key findings include: (1)the effect of rubber incorporation on strength is dosage- and curing-age-dependent; a moderate rubber content (5%) improves early-age strength, whereas excessive rubber addition reduces strength due to increased porosity and weakened load-bearing capacity; (2) samples with rubber significantly reduce the length, number, and width of cracks, achieving better structural integrity; (3) introducing rubber improves the pre-peak deformation capacity of the samples; (4) the strain growth magnitude is positively correlated with the rubber content, enhancing their toughness and ductility; (5) adding rubber effectively reduces the damage propagation rate within the sample; (6) under loading, rubber elastic deformation in samples dissipates energy, which describes the approximately linear energy storage and dissipation trend; (7) among the investigated rubber contents, 5% rubber incorporation achieved a favorable balance between mechanical strength, toughness, and ductility.

Mining doi: 10.3390/mining6030065

Authors: Hayden Bradbury Allan Trench Dirk G. Baur

Lithium, as a Li-ion battery constituent, is pivotal for the transition to clean energy. Western Australia (WA) has become a global leader in hard-rock lithium mining, realising 10-fold growth from 2010 to 2024 and with royalty receipts to the WA government surpassing $1 billion AUD. Given the sector’s economic significance, we analyse key performance metrics including resource/reserve build, production growth, cumulative capital deployed, capital intensity, and development timelines for the new-generation lithium mines. Several enabling factors supported the rapid build-out of capacity. These include an efficient mine permitting process to manage environmental impacts and competing land use issues, a stable royalty regime, energy and logistics infrastructure, availability of a skilled workforce, and mining services capability. Contrary to the standard industry narrative that new mineral projects are constrained by legislative delay, the new lithium projects achieved development timelines of 7 years or less from first resource to production. This has broader implications for critical mineral projects where success is likely to depend less on strategic classification and more on project quality, financing, and regional capability.

Mining doi: 10.3390/mining6030064

Authors: Michel Varelija Aleksandra Babaryka Krzysztof Fulawka Alexander Bondarchuk Philipp Hartlieb

Numerical modelling is a powerful tool used in geomechanics; however, its reliability depends on proper validation. This study demonstrates the use of intelligent rock bolt measurements to validate the numerical model of underground deformation, providing a practical and applicable approach even with all numerical modelling simplifications. A numerical model of a selected Case Study Location was developed using geomechanical data from laboratory tests (uniaxial compressive strength, triaxial test, and Brazilian test). The numerical model was validated using deformation data collected by intelligent rock bolts installed in the underground mine. Applying statistical data correction methods, the model data accuracy was further improved. Applying Kalman filtering improved the correlation between measured and modelled deformations from 0.90 to 0.98, demonstrating the effectiveness of statistical methods. The novelty of this work lies in the combined use of intelligent rock bolts, FEM simulations, and statistical data correction to achieve a practical and reproducible validation framework, even when simplified geological assumptions are used.

Mining doi: 10.3390/mining6030063

Authors: Lev Levin Mikhail Semin Stanislav Maltsev Ivan Panteleev Maria Bartolomei Sergey Bublik Ilya Lozhkin Oleg Plekhov

This study investigates the influence of unsteady heat and mass transfer processes on the formation of gas composition and thermal conditions in a large cross-section (132 m2) blind-end chamber of a gypsum mine during the operation of diesel-powered mining equipment, including a front-end loader representing the LHD class and a dump truck. The modeled system considers a chamber where the LHD operates continuously, while the dump truck enters periodically to perform haulage cycles. Ventilation is provided from an adjacent panel haulage drift using a booster fan. Numerical simulations were carried out using ANSYS Fluent within the RANS framework, employing the realizable k-ε turbulence model, with consideration of thermal and gas convection. A dynamic mesh approach was applied to explicitly represent the motion of the dump truck. Both steady-state scenarios, corresponding to extreme equipment positions, and a fully transient case involving dump truck entry into the chamber followed by idling were analyzed. The results demonstrate that the movement of the dump truck generates a pronounced piston effect, which alters the jet flow structure and temporarily increases the supply of fresh air to the working face. It is shown that steady-state assumptions based on prolonged equipment presence near the face overestimate the total NOx concentration within the large chamber and may not adequately reflect actual gas conditions over typical loading cycle durations. The analysis of unsteady processes using the dynamic mesh approach reveals significant inertia in contaminant accumulation within the chamber. This finding enables a more accurate estimation of the required airflow rate, reducing excessive safety margins compared to calculations based on the assumption of continuous equipment operation near the face.

Mining doi: 10.3390/mining6030062

Authors: Soroush Khazaei Roberto Noriega Hooman Askari-Nasab Yashar Pourrahimian

Stockpiles and run-of-mine (ROM) pads are critical control points between mine production and processing plant feed. The grade, quality mix, and variability of material delivered to the crusher and mill are largely determined by how these structures are designed, built, and reclaimed. Despite the operational significance of stockpile management, the field remains fragmented across five distinct research streams—physical blending theory, stockpile state modelling, reclaim sequencing and equipment scheduling, plant-feed and stockpile blending optimization, and sensor-driven reconciliation and closed-loop control—with limited integration between them. This paper presents a systematic review of 27 sources published between 1976 and 2025, including peer-reviewed journal articles, conference papers, a preprint, a book, and one industry publication. The literature search was conducted in May 2025 using Scopus, Web of Science, and Google Scholar, with records screened by title/abstract and full text for direct relevance to stockpile reclamation or grade blending in mining operations. A structured coverage matrix identifies that studies combining high spatial fidelity with strong optimization rigor are consistently absent from the literature, and that uncertainty handling and sensor-driven or real-time capability remain substantially underdeveloped. Six research gaps are identified and prioritized by practical significance, implementation readiness, and literature maturity. The four most operationally critical gaps concern: spatially explicit reclaim scheduling under live ROM-pad constraints; tractable multi-attribute blending formulations for polymetallic operations; uncertainty propagation to plant-feed predictions; and field-scale closed-loop validation. The review provides a structured development roadmap for ROM-pad optimization frameworks and identifies the specific integration challenges that must be addressed to move the field from static stockpile monitoring toward adaptive, sensor-updated decision support.

Mining doi: 10.3390/mining6030061

Authors: Samuel Frimpong Mabel Obosu

The mining industry continues to face significant safety challenges, particularly with powered haulage equipment (PHE). PHE incidents account for a substantial percentage of mining-related fatalities, often resulting from vehicle collisions, equipment rollovers, operator errors, and blind-spot hazards. Despite the industry’s efforts to improve safety protocols, fatal accidents involving haulage trucks remain persistent. The mining industry has increasingly adopted automation to enhance operational efficiency and improve safety, particularly in surface mines where haulage truck accidents remain a critical concern. Automation has significantly reduced human exposure to hazardous tasks by removing operators from dangerous environments, thereby mitigating risks associated with human error and fatigue-related accidents. However, achieving zero fatalities in mining operations remains an ongoing challenge, necessitating a deeper evaluation of current technologies and safety interventions. This paper explores the review and integration of advanced safety technologies, such as real-time monitoring, machine learning-based predictive models, and enhanced automation frameworks to improve hazard detection and response time. A structured methodology is employed to review automated systems, accident data analysis, and an assessment of automation technologies in active mining operations. Specific findings highlight the impact of automation on reducing accident rates, the effectiveness of various intervention strategies, and challenges in full-scale implementation. The novelty of this paper lies in its roadmap to achieving zero fatalities through a review of structured integration of automation and predictive safety interventions. It outlines the broader benefits of Automated Haulage Systems, including productivity gains and operational cost reductions, contributing to the ongoing discourse on mining safety by providing a data-driven framework for the successful implementation of automated haulage trucks, ensuring a safer and more efficient mining environment.

Mining doi: 10.3390/mining6030060

Authors: Yu Liang Yutong Chai Xingyu Wang Samantha Espley Shunde Yin

Lined rock caverns offer a promising option for underground hydrogen, helping to mitigate renewable intermittency and enhance system stability. Considering the geological characteristics of hard rock formations in Southern Ontario, Canada, this study establishes a thermo–gas–mechanical coupled framework that incorporates hydrogen mass and energy evolution in the cavern, gas–wall convective heat exchange, dynamic cavern-volume feedback, and the deformation behaviour of the sealing layer, concrete lining, and surrounding rock. The influences of cavern geometry, sealing material, and in situ stress on the short–term thermodynamic and mechanical responses are further examined. The results show that hydrogen temperature and pressure exhibit clear stage–dependent evolution during the charging–storage–discharging cycle. The comparison between the first and 20th operating cycles indicates that repeated operation mainly causes a moderate adjustment of the cyclic thermal state and temperature–pressure baseline, without changing the overall stage–dependent response pattern. During charging, temperature and pressure increase simultaneously; during storage, both gradually decrease as thermal energy is transferred to the cavern wall; and during discharging, expansion causes pronounced cooling and depressurization, followed by gradual recovery driven by heat transfer from the surrounding rock. Cavern geometry significantly affects stress redistribution around the cavern. The circular cavern shows a relatively uniform stress distribution, whereas the arched cavern is more prone to local stress concentration near the sidewall–floor transition zone. The sealing material mainly influences gas temperature fluctuations through its thermal conductivity. The fibre–reinforced plastic (FRP) sealing layer amplifies thermal fluctuations during cyclic operation, whereas the steel sealing layer promotes heat dissipation through the lining and surrounding rock, thereby moderating cavern–gas temperature variations. In situ stress difference further controls the directional distribution of stresses around the cavern. As the minimum horizontal principal stress increases, compressive stress concentration at the crown and invert becomes stronger, while relative stress release occurs near the sidewalls. These findings provide a thermo–mechanical basis for preliminary cavern–geometry design, comparison of sealing–layer thermal performance, and assessment of in situ stress adaptability for lined rock cavern hydrogen storage in Southern Ontario.

Mining doi: 10.3390/mining6030059

Authors: Congcong Zhao Zepeng Han Hongnan Qin Zhentao Li

To examine the deformation behavior and failure mechanisms of large-scale mine chutes under complex service conditions, we performed multiple C-ALS three-dimensional laser scanning surveys on the 1#, 2# and 3# chutes at an iron mine in Anhui Province. The results showed that all three chutes had severe non-uniform expansion, with maximum diameters of 12.2 m, 14.8 m and 16.9 m, respectively. The maximum annual wear rates during the detection period were 2.4 m, 6.0 m and 2.5 m, respectively. The failure of the chutes was mainly caused by local block collapse drops, influenced by the joints and fissures of the surrounding rock, and the wear showed significant discontinuous and non-uniform characteristics. Based on the detection data, a three-peak Gaussian model is established to describe the nonlinear distribution of the expansion along depth, with peak centers located at −462 m, −497 m and −520 m. By comparing linear and exponential models, it is determined that the expansion exhibits a linear evolution trend with time. Based on the maximum diameter and annual wear rate, we estimate the remaining safe service life of each chute, and provide the confidence interval for the expansion value at a 90% confidence level (such as [1.31 m, 4.83 m] at −520 m). Research shows that high-precision 3D laser scanning can effectively reveal the deformation and evolution laws inside the chute. It is recommended to immediately take reinforcement measures for chute 2 and establish a dynamic monitoring system for the common weak zone between −480 m and −520 m. Research on the evolution of surrounding rock fractures should be carried out to provide a scientific basis for chute life assessment and risk control.

Mining doi: 10.3390/mining6030058

Authors: Mouad Benssaou Atmane Madi Abdelilah Benhammou Mohamed Abioui Nourissaid Içame Mehdi Ousbih Ahmed Elmouden Abderrahmane Wanaim Hassan El-Baghdady Moha Ikenne

In the Western Anti-Atlas, the stratiform copper mineralisations of the Tabia Member are distinctly hosted within sedimentary rocks, forming deposits comparable to the sediment-hosted stratabound copper (SSC) type. In Tizert, Ouarmdaz, and Talat n’Ouamane, the sandstones and clays host primary sulphides as disseminations and copper carbonates occurring as small continuous or lenticular beds, small geodes, and coatings on clay laminations. In Tiferki, the conglomerates are more mineralised; sulphides are represented by chalcopyrite and bornite, locally altered into chalcocite. Copper carbonates appear as malachite and azurite coating pebbles and deeply impregnate the granular matrix. From a sedimentological and sequence-stratigraphic perspective, the conglomeratic level at Tiferki represents a low-sea-level prism (LST) formed during a stage of maximum platform exposure allowing erosion products to accumulate at the base of the slope. By contrast, the silty–sandy complex known as the “Talat n’ Ouamane level” corresponds to a prograding sedimentary sequence (Highstand Systems Tract, HST) that developed after a relative regression where the platform was only partially exposed. In both cases, relative sea-level fall promoted the emergence of the hinterland and active erosion, supplying the depositional environment with coarse detrital during the maximum drops in sea level and sandy-to-micro-conglomeratic deposits during less pronounced regressions. This detrital supply probably brought copper in the form of grains and especially dissolved copper, which is largely deposited at the bottom of slopes and in marine environments where microbial communities contribute to the precipitation of copper. The selective distribution of sulphides within the Tabia Member shows that only the low-sea-level and high-sea-level prisms are enriched in stratiform copper, while the transgressive and maximum flooding systems tracts lack significant mineralisation. This suggests that sea-level variations played a controlling role in copper deposition. The regressive trend of the high sea-level suite continued until emergence, reflected by the invasion of the environment by red or ochre siltstones from the alluvial plain. The emergence at the transition from sandstones to dolomites, and the “Red Beds”-type mineralisation embedded in these subaerial facies, support the syngenetic origin of the sulphides in the Tabia Member. After this main emplacement of stratiform copper, the sulphides would have undergone remobilisation and alteration during a significant episode of vertical water escape that deformed the host facies and enhanced mineral concentration within permeable sandstones. Even the clays were delaminated and coated with a thin films of copper carbonates on their surfaces. In the Tamjout dolomites, carbonates are percolated by acidic solutions, contributing to the brecciation and silicification of the stromatolitic layers. Copper mineralisation accompanies this silicification and fills the karstification pockets.

Mining doi: 10.3390/mining6030057

Authors: Teodora Gavrilescu Cornel Păunescu

Mining-induced subsidence represents one of the most significant long-term geomechanical hazards associated with underground coal exploitation, often continuing for decades after mining activities have ceased. Understanding the persistence and spatial distribution of post-mining ground deformation is essential for evaluating residual geological hazards and improving long-term monitoring strategies in former mining regions. This study investigates the long-term evolution of mining-induced subsidence in the Maleia sector of the Jiu Valley Coal Basin (Romania), an area historically affected by intensive underground coal extraction. A geodetic monitoring network consisting of seventeen permanent benchmarks, initially established in 2006, was reoccupied and remeasured using Global Navigation Satellite System (GNSS) technology in 2026. The comparative analysis was performed against historical measurements acquired during the 2007 monitoring campaign, providing a nineteen-year temporal framework for deformation assessment. Analysis of vertical displacements revealed persistent subsidence at all monitored benchmarks, confirming the continued post-mining adjustment of the geological structure. Measured cumulative vertical displacements ranged from −0.082 m to −3.853 m, with the highest deformation recorded at benchmark R14. The calculated average annual subsidence rates reached values of up to −0.203 m/year and are reported as normalized indicators of cumulative deformation over the nineteen-year observation interval. The results demonstrate that mining-induced geomechanical instability may persist for decades after underground mining has ceased, emphasizing the necessity of long-term monitoring strategies in former coal mining regions affected by residual geological hazards. This study provides one of the few long-term GNSS field datasets documenting delayed mining-induced subsidence over a nineteen-year observation period in an underground coal basin, contributing rare field evidence of persistent post-mining geomechanical evolution in Eastern Europe.

Mining doi: 10.3390/mining6030056

Authors: Mehrshad Samadi Seyed Amir Konjkav-Sabzevari Zohreh Sheikh Khozani

Blast-induced ground vibration is a critical environmental hazard in open-pit mining operations, capable of causing severe damage to adjacent structures and infrastructure. Accurately predicting vibration intensity is universally quantified by the peak particle velocity (PPV) index. Among the various factors affecting blast-induced ground vibrations, the distance from the blast face to the monitoring point (D) and the charge weight per delay (W) are the most influential and controllable parameters in a specific mine site. Therefore, these variables were selected as inputs for PPV estimation. The present study develops advanced white-box machine learning (ML) models, including Multi-Expression Programming (MEP), Gene Expression Programming (GEP), Multivariate Adaptive Regression Splines (MARS), and Stronger Variable Creator Machines (SVCMs), for predicting PPV. The general explicit equation was derived from the developed ML models implemented in a spreadsheet program, which can be easily used to estimate PPV. The MEP model achieves the highest accuracy, with a correlation coefficient (CC) of 0.993177 and a root mean square error (RMSE) of 0.836337, followed by the MARS, GEP, and SVCM models. The results of the present study, supported by k-fold cross-validation and parametric analysis, confirmed the potential of the proposed models for PPV estimation.

Mining doi: 10.3390/mining6030055

Authors: Mustapha Amrani Yassine Taha Omar Inabi Mostafa Benzaazoua Rachid Hakkou

Conventional pavement design methods are generally intended for highways and are not suited to the extreme loading conditions experienced by mining haul roads. This study presents an innovative pavement design for a heavily trafficked phosphate mine haul road (≈22.35 kT·day−1) constructed entirely from phosphate mine waste rock (PMWR), offering a sustainable alternative to conventional aggregates. The proposed structure comprises a 0.35 m sub-base (0–100 mm), a 0.25 m base (0–63 mm), and a 0.07 m semi-granular asphalt concrete (BBSG 0–20 mm) wearing course designed to combine high mechanical performance with effective dust control. The design was validated through an integrated experimental program that included repeated load triaxial testing (RLTT), asphalt stiffness, fatigue and rutting tests, thermogravimetric analysis (TGA), and full-scale field trials involving EV2 plate-load testing, dust monitoring, and emergency braking tests using a Komatsu 730E haul truck. The results demonstrate that the proposed pavement provides excellent structural performance. The asphalt mixture achieved a stiffness modulus of 9160 MPa, a fatigue resistance of 139.6 µε, and a proportional rut depth (PRD) of only 2.2%. In the field, the compacted sub-base and base reached average EV2 values of 153 MPa and 181 MPa, respectively, confirming their high load-bearing capacity. The paved haul road reduced airborne dust emissions by approximately 91%, surpassing the mine’s target of 80%, while also enabling haul-truck operating speeds to double, with associated reductions in tire wear and maintenance. Despite these performance gains, the proposed solution remains economically attractive, with a construction cost of approximately 23.97 €/m2. Overall, the study demonstrates that phosphate mine waste rock can be successfully transformed into a durable, cost-effective, and environmentally sustainable pavement solution for heavy-haul mining roads, providing a practical example of circular economy principles in mining infrastructure.

Mining doi: 10.3390/mining6030054

Authors: Daniel Oguntayo Temitope Awolusi Samuel Gboyega Arowolo Paul Terkumbur Adeke

The increasing global demand for pavement infrastructure has intensified the consumption of non-renewable construction materials, particularly natural aggregates and soils, raising significant environmental and resource sustainability concerns. In response, there is a growing need to explore alternative materials that can reduce reliance on these finite resources. Mine tailings, generated in large volumes from mining operations, have emerged as a promising substitute due to their potential to enhance asphalt concrete performance while mitigating environmental impacts associated with their disposal. This study presents a comprehensive review of the application of selected mine tailings in asphalt mixtures. It critically examines their physicochemical properties and evaluates their influence on key performance characteristics of asphalt pavements. The review further highlights the various applications, benefits, and limitations associated with their use. Despite increasing research interest, the field remains relatively underdeveloped, with limited experimental validation for practical pavement applications. The findings of this study provide valuable insights into the sustainable utilisation of mine tailings and identify key research gaps, offering direction for future experimental and field-based investigations in pavement engineering. The study observed that the performance of asphalt mixtures incorporating mine tailings from aluminium, copper and iron by-products is largely dependent on the physicochemical and mineralogical characteristics of these materials. The particle size, specific area and presence of reactive oxides are essential ingredients for improved interaction with the bitumen content of the mixture.

Mining doi: 10.3390/mining6030053

Authors: Valeriy Peregudov Mels Shautenov Talgat Almenov Din-Mukhammed Shabaz Bakytbek Bektur

Coal ash-slag waste from coal-fired power plants is a high-volume technogenic material whose resource potential is controlled by particle-size heterogeneity, mineralogical composition, and the occurrence modes of valuable elements. This study investigated Au occurrence in ash-slag waste derived from Ekibastuz coal and evaluated gravity–magnetic preconcentration as a diagnostic first stage for separating Au- and Fe-bearing products. The material was characterized by particle-size analysis, X-ray diffraction, chemical analysis, optical and electron-probe microscopy, atomic absorption analysis (AAS), kinetic spectral analysis (KSA), gravity concentration, and magnetic separation. The feed was an aluminosilicate–ferruginous material dominated by mullite, magnetite, quartz, and hematite. In the coarse material, liberated native Au co-reported with heavy Fe-bearing phases: the vibratory spiral concentrate contained 0.99 g/t Au and 39.00% Fe, corresponding to 52.58% Au recovery and 66.49% Fe recovery. The combined spiral and centrifugal concentrates yielded 1.04 g/t Au at 63.22% recovery, representing an approximately eightfold upgrade relative to the 0.13 g/t feed. In contrast, gravity recovery from the finest fraction was approximately 1%, indicating ultrafine, poorly liberated, or matrix-associated Au. KSA gave higher Au values than AAS, reflecting matrix heterogeneity and method-dependent preparation and detection effects rather than analytical superiority. The results support a size-selective gravity–magnetic preconcentration route followed by targeted mineralogical verification and product-specific downstream extraction.

Mining doi: 10.3390/mining6030052

Authors: Noaman Bouhlali Abdellatif Elghali Yassine Taha Mostafa Benzaazoua

Phosphate rock is a finite resource whose extraction in sedimentary deposits generates substantial volumes of waste rock. This study develops a panel-scale 3D geological modeling workflow for operational material accounting in a multilayer sedimentary phosphate deposit. Phosphate layers were modeled using a hanging wall–footwall approach and evaluated against independent well data. Bone Phosphate of Lime (BPL) grades were estimated from borehole-layer composite assay values using nearest neighbor, inverse distance weighting, and ordinary kriging. Domain-wise external validation showed that ordinary kriging provided the most consistent agreement with withheld observations in most mineable layers. Each mineable layer was treated as an independent estimation domain, with one composite BPL value retained per drillhole and per mineable layer. The validated block models were regularized to the mine plan and aggregated into operational strips, enabling strip-scale material accounting and mineability filtering under operation-specific technical criteria. To limit disclosure of confidential operational quantities, panel-scale resource, recoverable resource, and residual ore results are presented in relative rather than absolute terms. The results show that most modeled phosphate-bearing material satisfies the applied criteria and is classified as recoverable, whereas residual phosphate-bearing material excluded by the operational criteria remains concentrated in a limited subset of layers. The terms ‘resource,’ ‘recoverable resource,’ and ‘residual ore’ are used throughout in an operational material-accounting sense only and are not intended in the sense of any international mineral reporting code. Strip-based stripping ratio maps further reveal spatial variability in waste-to-ore and waste-to-grade relationships. The resulting workflow provides a quantitative spatial basis for future scenario-based assessment of waste management and selective dumping alternatives in sedimentary phosphate mining.

Mining doi: 10.3390/mining6030051

Authors: Kursat Hasozdemir Mert Meral Muhammet Mustafa Kahraman

Accurate near-real-time granulometry is critical for optimizing energy efficiency in comminution circuits, yet standard optical monitoring systems fail under the harsh conditions of industrial mining. High conveyor velocities induce motion blur, while heavy dust loads occlude particle boundaries, leading to severe under-counting of fine fractions and an overestimation of product coarseness. This paper proposes a novel tracking framework to overcome these limitations. The method integrates a five-frame temporal rolling buffer with a multi-stream augmentation architecture that decouples motion and texture features. Experimental validation on the feed of a secondary conical crusher at an operational facility demonstrates that the proposed framework recovers significant particle data lost by baseline models, correcting the measured D80 and D50 values of the crushed material. This correction reveals a finer true load, enabling more precise closed-loop control of crusher settings and reducing unnecessary energy consumption.

Mining doi: 10.3390/mining6030050

Authors: Alexey Cherepovitsyn Irina Mekerova Alexander Nevolin

The palladium market represents a critical role in supporting key industrial sectors and facilitating the energy transition, as it is widely used in the automotive industry, electronics, chemical manufacturing, and hydrogen energy. These sectors influence a steady demand amid tightening environmental regulations and the development of green technologies. The aim of this study is to assess the structural transformation of the global palladium market through 2030 and to project Russian palladium production for 2026–2028 amid the energy transition by applying economic-mathematical methods, including linear regression, the Grey forecasting model, exponential smoothing, and Autoregressive Integrated Moving Average (ARIMA) time-series modeling. Particular attention is paid to the analysis of factors influencing the dynamics of the global palladium market, including the electrification of transportation, the substitution of palladium with alternative materials, and changes in global supply chains. The simulation results showed that the exponential smoothing model possesses the highest predictive accuracy, enabling it to estimate future palladium production volumes. The market is undergoing a structural transformation: declining demand from the traditional automotive sector is partially offset by the development of new applications in hydrogen energy, electronics, and advanced materials, suggesting that technological improvements can compensate for the loss of conventional demand segments. The key findings are (1) exponential smoothing (R2 = 0.9812) outperforms linear regression, Grey model, and ARIMA; (2) Russian palladium production is projected at 74–130 tonnes (2026), 63–141 tonnes (2027), and 54–150 tonnes (2028); and (3) the decline in automotive demand is partially offset by new applications. Our findings confirm the need for Russian producers to adapt their strategies to the structural transformation of global demand, deepen domestic processing, and develop new high-tech applications for palladium to maintain their competitive positions amid the energy transition.

Mining doi: 10.3390/mining6030049

Authors: Shakenov Aman Tulegenovich Utegenova Assem Yerzhankyzy Stolpovskikh Ivan Nikitovich Orumbassarova Ainura Berikbolovna Boris V. Malozyomov Nikita V. Martyushev

The performance of haul trucks in open-pit mining is strongly affected by haul-road geometry, surface condition, rolling resistance, and operational traffic regimes. However, existing studies often consider road-surface mapping, vehicle dynamic response, and onboard telemetry as separate information streams, which limits the reproducible assessment of how road-related factors are associated with VIMS-derived fuel-use proxy burden, mechanical dynamic response, and transport-cycle instability. This study proposes a field-based, segment-level multisensor framework that integrates unmanned aerial vehicle/light detection and ranging (UAV/LiDAR) road-surface reconstruction, global positioning system/inertial measurement unit (GPS/IMU) trajectory and vibration data, and Caterpillar Vial Information Management System (VIMS) telemetry into a unified spatiotemporal analytical dataset. The methodological contribution consists in the synchronization of heterogeneous data sources at the road-segment level, the calculation of interpretable road-condition and vehicle-response indicators, and the statistical assessment of road-related effects while explicitly accounting for confounding factors such as longitudinal grade, payload state, speed regime, truck class, and operational variability. Unlike studies that use LiDAR mapping, vibration monitoring, or onboard telemetry as separate diagnostic channels, the proposed approach introduces a segment-level analytical framework in which road morphology, truck response, and operational penalties are aligned within the same spatial unit, interpreted under confounder-aware conditions, and verified through repeat-pass reproducibility and robustness checks. The framework was tested on haul roads around the Ekibastuz open-pit coal mine. The field analysis identifies road segments where degraded surface morphology, increased waviness, unfavorable longitudinal profile, and higher rolling resistance coincide with increased mechanical dynamic response, VIMS-derived fuel-use proxy burden, braking instability, and travel-time variability. The results are interpreted as controlled field-supported associations rather than as isolated causal effects. The proposed maintenance ranking should therefore be regarded as a decision-support output, while the operational effectiveness of specific repair interventions requires future before–after validation.

Mining doi: 10.3390/mining6030048

Authors: Tinotenda Blessing Chimbwanda Tyler Bettencourt Nathalie Risso Tejo Vikash Bheemasetti Angelina Anani Moe Momayez

Autonomous haulage systems (AHSs) have become increasingly important as mining operations seek to improve productivity and remove workers from hazardous environments. The systematic integration of this technology requires not only operational change management but also a deeper understanding of mine planning implications. The existing literature describes AHSs and implementation guidelines with a focus on operational safety and autonomous system architecture, but it does not systematically address required planning-level adaptations. This study aims to identify how surface mine planning frameworks must evolve to accommodate autonomy in open-pit metal mining operations. A systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, with emphasis on identifying the principal aspects of AHSs that must be considered in mine planning strategies. Findings reveal major shifts in workforce dynamics, communication infrastructure, and haul-road geometry, and show that road-width and load-channelization questions remain site-specific research needs rather than settled design rules. This study highlights the need for (i) mine planning frameworks that treat AHSs as a constraint on pit geometry, haul-road structural and functional design, fleet selection, production scheduling, road-maintenance strategy, and economic and social evaluation; (ii) human–systems integration and improved human-autonomous collaboration; and (iii) empirical validation of workforce transition strategies for more effective and safe deployment.

Mining doi: 10.3390/mining6030047

Authors: Muhammet Mustafa Kahraman

This paper presents a large-scale behavioural-cloning benchmark of linear-programming (LP) truck dispatch in commercial open-pit mining, quantifying how much of the LP policy is recoverable from observable cycle records and which learning models recover it. Drawing on 983,025 LP dispatch decisions across four operational years at a large copper mine, four learned model families are compared under an identical, strictly causal feature set and a strict temporal hold-out (Year 5)—a 72,681-parameter multilayer perceptron (MLP), Random Forest, LightGBM, and XGBoost—against five non-parametric baselines. Gradient-boosted trees recover substantially more of the LP policy than the MLP: XGBoost attains 41.04% top-one and 79.50% top-three accuracy (95% CI [40.80, 41.30]), and LightGBM 39.70%/77.95%, both significantly exceeding the cycle-continuity heuristic (35.21%/67.32%) and the MLP (32.4%/68.8%) by McNemar tests (all p < 0.001). The dataset is highly imbalanced (normalized entropy 0.814; imbalance ratio 16,921:1), and front-end-loader classes with negligible support are not learnable. Permutation analysis shows the truck’s previous shovel dominates the MLP policy (+7.46 pp), yet XGBoost exceeds the previous-shovel-only Bayes-optimal accuracy of 32.40%, demonstrating that observable features beyond previous shovel carry exploitable signal the MLP fails to capture. A learning-curve ablation shows the gradient-boosting advantage is attributable to model architecture rather than training-data volume and is robust to hyperparameter choice, consistent with the established behaviour of tree ensembles on tabular data. The results indicate a learnability ceiling that sits well above the MLP and is partly model-limited rather than purely informational; they also show that imitation fidelity is distinct from dispatch quality, which is not assessed here. The study reframes behavioural cloning of commercial FMS dispatch as a diagnostic and benchmarking tool and motivates model choice, imbalance-aware learning, and richer state recovery as the levers for data-driven dispatch analysis.

Mining doi: 10.3390/mining6030046

Authors: Madeleine Guillen Guillermo Iriarte

Identifying sediment sources in mining-impacted watersheds is essential for understanding sediment dynamics and supporting environmental management. This study applies a geoenvironmental modeling approach based on geochemical sediment fingerprinting to quantify the relative contribution of three sediment sources in the Colca River micro-watershed (southern Peru): agricultural areas (ZAGR), non-mining areas (QSAM), and mining-influenced zones (ZAM). Water and sediment samples were collected during dry and wet seasons, and 31 elements were analyzed using inductively coupled plasma mass spectrometry (ICP-MS), supported by complementary analytical techniques. Source apportionment was performed using the FingerPro model in R 4.5.0, applying Conservation Index (CI), Consensus Ranking (CR), and Consistent Tracer Selection (CTS) methods. Results indicate that non-mining zones dominate sediment sources, contributing approximately 58–60%, while mining-influenced zones contribute up to 31.5% in downstream areas. Although ZAM represents a lower contribution, it is associated with elevated concentrations of Zn, Pb, Cd, and As. The selected tracers (Ca, Mg, P, and Y) showed high discriminatory power. These findings demonstrate that sediment fingerprinting provides a robust framework for assessing sediment source contributions in mining-affected watersheds.

Mining doi: 10.3390/mining6030045

Authors: Justina Senam Lotsu Samuel Frimpong Muhammad Azeem Raza

The rapid deployment of autonomous haulage systems (AHSs) in open-pit mining has significantly altered haul road geometric design requirements, as autonomous trucks operate under strict kinematic constraints related to turning radius, gradient, and braking performance. Since haulage accounts for 50–60% of total mining costs, optimizing haul road geometry is critical for improving operational efficiency, energy consumption, and safety. This study presents a systematic review of 50 highly relevant studies selected from 81 candidate publications published between 2003 and 2025 through structured database searches and citation chaining. The review synthesizes current developments in haul road layout optimization, turning radius accommodation, gradient design, and safety integration for autonomous mining systems. The findings indicate that GIS-based and integrated optimization approaches consistently improve haulage performance, with reported productivity gains of 5–20%. Turning radius constraints emerged as the primary factor governing kinematic feasibility, while Hybrid A* and its advanced variants represent the dominant path-planning approaches. Recommended gradient limits of 8–12% remain important for balancing efficiency and safety, although emerging AHS-specific models suggest opportunities for controlled relaxation. The review identifies key research gaps in adaptive road design, integrated safety–geometry optimization, and field validation, providing a consolidated foundation for future AHS-compatible haul road design research.

Mining doi: 10.3390/mining6020044

Authors: Sang-hun Lee

The environmental impacts of mine dust in mining operations can be mitigated through improved prediction of its spatial distribution using dispersion models, particularly Gaussian-based air quality models. However, Gaussian-based models often predict concentrations that differ substantially from observed mine dust behavior, because dust properties and transport mechanisms vary markedly with particle size. In this study, particle-size-related mechanisms for dust dispersion behaviors were classified as dry/wet deposition, turbulent diffusivity, erosion, hygroscopicity, or agglomeration, and their effects on dust dispersion behaviors and effective simulation methods were reviewed. Currently, the most clearly established particle size influence is on deposition, especially for coarse dust emitted from mechanical mining processes. Other mechanisms, including erosion, hygroscopicity, and agglomeration, are more relevant to finer dust below 2.5 µm or in the submicron range. This study proposes that wind erosion, mainly saltation flux, can also be integrated into Gaussian dispersion models as near-ground boundary flux terms. Hygroscopic and agglomeration effects can be assessed using relative humidity and simplified particle size redistribution assumptions near dust emission sources. In particular, incorporation of agglomeration mechanisms may begin with a simple bimodal assumption: the agglomeration of PM2.5 into PM10. This can be incorporated into a modified Gaussian deposition equation. Finally, the size dependence of the turbulent diffusivity coefficient is relatively insignificant, so the diffusivity values can be regarded as constants. These findings provide a mechanistic basis for improving mine dust prediction and environmental management in open-pit mines, haul roads, tailings areas, and stockpile environments.

Mining doi: 10.3390/mining6020043

Authors: Amir Boustila Menal Zeroual Juan M. Menendez-Aguado Abdelmadjid Abdi Ali Messai Sami Yahyaoui

The foundational element of any ventilation system assessment is the precise definition of the primary airflow intake. In underground mine networks, even a marginal error in primary inputs triggers a series of inaccuracies, resulting in significant volumetric errors across the entire network. This study explores the sensitivity of the iterative Hardy Cross algorithm for ventilation network analysis towards the main intake, and demonstrates that the intake overestimation error reaches 77%, creating a false sense of security. Furthermore, when utilizing the Hardy Cross approach, evaluating a model based solely on its mathematical tendency to balance is misleading; analysis of relative error evolution demonstrates that a converged network can achieve mathematical balance while remaining fundamentally uncoupled from the mine’s physical reality due to flawed input data. While technical fields currently diverge into two primary paths for airflow definition, overly simplistic approximations or specialist-dependent numerical CFD models, this study proposes a middle ground alternative. The proposed methodology relies on direct anemometric field measurements synthesized through cartographic mapping integration techniques. The suggested technique offers a detailed graphical representation of air velocity across the excavation, derived from the isovel mapping. This visualization illustrates that airflow behaviour through rock excavations is fundamentally non-uniform and dictated by wall roughness and structural irregularities.

Mining doi: 10.3390/mining6020042

Authors: Mahin Rostami Amin Beiranvand Pour

Hydrothermal alteration mapping is a critical component of porphyry copper exploration because alteration assemblages provide important vectors toward mineralization. This study presents a systematic evaluation of supervised machine learning algorithms for delineating hydrothermal alteration zones using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) short-wave infrared (SWIR) surface reflectance data (AST_07XT). The investigation focuses on the Nain region within the central Urumieh–Dokhtar Magmatic Arc (UDMA), Iran, a major metallogenic belt hosting numerous porphyry copper systems. Representative spectral endmembers corresponding to Al–OH-bearing and Mg–OH-bearing hydrothermal alteration minerals were extracted using Minimum Noise Fraction (MNF), Pixel Purity Index (PPI), and n-dimensional visualization techniques. These endmembers were subsequently used to train and evaluate a comprehensive suite of supervised machine learning classifiers, including linear, kernel-based, tree-based, ensemble, probabilistic, boosting, and neural-network algorithms for pixel-wise hydrothermal alteration mapping. Model performance was evaluated using multiple statistical metrics, including overall accuracy (OA), average accuracy (AA), precision, recall, F1-score, Cohen’s kappa coefficient, area under the ROC curve (AUC), spatial cross-validation accuracy, uncertainty analysis, and spatial agreement analysis. Among the evaluated classifiers, SVM_Linear, SVM_RBF, LDA, and MLP achieved the highest classification performance, with overall accuracies exceeding 94% and strong spatial consistency between classified maps. The resulting alteration maps display spatially coherent distributions of Al–OH and Mg–OH minerals that are consistent with established hydrothermal alteration zoning models in porphyry–epithermal systems. The mapped hydrothermal alteration zones show strong spatial correspondence with known mineralized areas and alteration patterns within the Urumieh–Dokhtar Magmatic Arc, confirming the geological reliability of the classification results. Uncertainty analysis further indicates high model confidence across most alteration zones, with higher uncertainty values mainly restricted to transitional and spectrally heterogeneous regions. The results demonstrate that integrating ASTER SWIR imagery with supervised machine learning algorithms provides a robust, scalable, and transferable framework for regional-scale hydrothermal alteration mapping and mineral exploration in porphyry copper provinces.

Mining doi: 10.3390/mining6020041

Authors: Bui Thanh Hoa Klaudia Zwolińska-Glądys Marek Borowski

Accurate modeling of underground mine ventilation requires reliable estimates of roadway aerodynamic resistance. Conventional methods, based on geometric surveys or barometric pressure measurements, have notable limitations, including neglect of local losses, high time requirements, and sensitivity to environmental disturbances. This paper introduces a two-point flow-based method for determining roadway resistance directly from in situ measurements. Using basic instruments (anemometer, differential manometer, thermometer, and hygrometer), measurements are taken at two points along a straight airway. The pressure drop is calculated via the Bernoulli equation, allowing resistance to be determined without relying on geometric data or friction assumptions. This method captures both frictional and local losses inherently. Field testing in five roadway sections of a coal mine in Vietnam yielded resistance values 10–15 times higher than theoretical friction-only estimates, highlighting the importance of local losses. The equivalent cross-sectional areas back-calculated from the measured resistance using literature-based friction factors showed consistency with geometric survey data (typical deviation 3–6%), indicating internal coherence of the measurements. Full validation against independent barometric or CFD methods remains a subject of ongoing research. The method is simple, fast, minimally disruptive, and compatible with ventilation modeling tools. It provides a practical and accurate alternative for resistance estimation under real operating conditions.

Mining doi: 10.3390/mining6020040

Authors: Murat Tolunay Bulgurcu Cuneyt Atilla Ozturk

Slope stability in open-pit mining is not a static condition but evolves continuously as excavation progresses and geomechanical conditions change. In this study, an integrated approach combining ground-based radar monitoring, satellite-based InSAR time-series analysis, and numerical stability modeling was applied to evaluate slope behavior in a large-scale open-pit copper mine with complex geological and structural characteristics. Radar data revealed progressive and episodic deformation concentrated in specific slope sectors, while InSAR observations showed that deformation continued at lower rates after the main movement phase, providing a longer-term perspective of slope response. Stability analyses using limit equilibrium and finite element methods indicate that the slope operates close to a limit equilibrium condition, particularly under saturated scenarios where factors of safety approach critical levels and strain localization becomes more pronounced. The results show a clear link between observed deformation patterns and calculated stability conditions, with structural discontinuities and groundwater playing a dominant role in controlling slope behavior. Based on these findings, an integrated workflow is proposed that links monitoring data with stability assessment, enabling the identification of critical zones and supporting the evaluation of slope conditions during ongoing mining operations. This approach contributes to more reliable decision-making and supports safer and more sustainable open-pit mining practices.

Mining doi: 10.3390/mining6020039

Authors: Ulises Miranda Ordóñez Pavels Kapitulskis Vitalijs Kuzmovs Aleksandr Sokolov Vladimir Gostilo

An X-ray fluorescence online analyzer was applied to the analysis of samples of known composition and concentration containing rare earth elements (REEs) and heavy metals (HMs), which were specially prepared by the authors (working samples). Reference samples were used for Th and U. The statistical parameters (detection limit, accuracy, and sensitivity) of the measurements of the spectra were calculated and a thorough assessment of the results was carried out. For large-volume samples, detection limits of 20–100 ppm for REEs and 10–140 ppm for HMs were achieved within 600 s. For thin-layer samples and similar geometries, detection limits for light and medium REEs improved to 3–20 ppm. The methodological possibilities for quantitative analysis of the REEs and HMs were examined and a rather simple approach with an easy implementation was developed. The method was tested in automatic measurements using concentrations in the range of 1000–4000 ppm, as a simulation of real-life measurements, and to determine the stability of the analyzer and the consistency of the results obtained. The results show that the online XRF analyzer can be applied for reliable detection and quantification of REEs and HMs at the ppm level. With these results, we are closer to obtaining results under conditions representative of those on real-world mining conveyor belts.

Mining doi: 10.3390/mining6020038

Authors: Abdurauf Abdukodirov Jörg Benndorf

Autonomous navigation is a key requirement for underground mine automation, where the choice of a suitable global path planner plays a significant role. In this study, four representative planning approaches—Dijkstra’s algorithm, A*, Rapidly exploring Random Tree (RRT*), and Particle Swarm Optimization (PSO)—were evaluated on a differential-drive mobile robot within the ROS navigation framework. The algorithms were tested in two simulated underground environments: a room-and-pillar layout with relatively open space and multiple path alternatives and a narrow tunnel scenario designed to reflect more constrained mining conditions. The results indicate that Dijkstra’s algorithm consistently produced the shortest paths with the lowest computation times, while A* showed comparable performance with slightly higher computational effort. RRT* required modifications to operate effectively in narrow tunnels and exhibited significantly longer planning times. PSO, although capable of generating near-optimal solutions in open spaces, showed limitations in constrained environments due to collision handling and path feasibility issues. Differences in replanning behavior were observed when unknown obstacles were introduced. Overall, graph-based planners such as A* and Dijkstra’s algorithm demonstrated more stable and predictable performance. Future work will focus on validating these findings in real mining environments, particularly considering wheel slippage, sensor noise, and path generation challenges in narrow tunnel conditions.

Mining doi: 10.3390/mining6020037

Authors: Bakhtiyor Urolov Hideki Shimada Takashi Sasaoka Akihiro Hamanaka Bugunei Bat-Erdene Samandar Khidirov

While conventional numerical studies often treat excavated stopes as empty voids or as backfilled, few investigations have simulated the post-mining void as a weak granular caved rock material that evolves naturally from a hanging wall failure. This study addresses this gap by modeling the caved rock progressively, which makes the excavation representation more realistic for sublevel caving operations. This study introduces stope stability for the Zarmitan gold mine in Uzbekistan, where mining occurs at about a 500 m depth in a narrow quartz vein. A hybrid approach combining empirical and numerical methods was adopted. The Mathews stability graph method provided initial design guidance, while three-dimensional FLAC3D numerical modeling was used to simulate the mining sequence with explicit representation of caved rock behavior. A various study was conducted, which included the effects of stress ratio, stope length along strike, and pillar thickness on overall stability. The obtained results show that the stress ratio is the dominant factor controlling stope behavior. Stope length significantly affects failure extent, with shorter stopes showing better performance under similar conditions. Pillar thickness was found to improve stability and reduce tensile stresses in critical areas, though in all cases, hanging wall support remains essential. The numerical results confirm empirical predictions while providing quantitative insights into stress distributions and failure mechanisms not captured by empirical methods alone. These results provide mine operators with quantitative, site-specific design criteria, most notably that, under the measured high horizontal stress, limiting stope length to 40 m and increasing pillar thickness to 8 m substantially improves hanging wall stability, which demonstrates how a hybrid empirical-numerical methodology can directly support safer and more economic extraction in deep, narrow-vein operations.

Mining doi: 10.3390/mining6020036

Authors: Augusto Henrique Lacerda Paiva Mario Guimarães Junior Matheus Moreira De Almeida Julia Xavier Prado Michelly Dos Santos Oliveira

Flotation is a fundamental unit operation in mineral processing; however, achieving high selectivity while reducing the environmental impact of reagents remains a major challenge in phosphate ore beneficiation. Conventional depressants often exhibit limited selectivity and may pose environmental concerns, highlighting the need for sustainable alternatives. This study reports, for the first time, the application of starch nanostructures derived from potato pulp processing residues as a depressant in phosphate flotation, representing an innovative and eco-friendly approach. An exploratory and experimental methodology was adopted, including nanostarch synthesis via acid hydrolysis followed by centrifugation and sonication, as well as comprehensive physicochemical characterization. The primary objective was to evaluate the selective depressant performance of the nanomaterial in apatite–calcite flotation systems. The synthesized nanostructures exhibited particle diameters ranging from 179 to 443.6 nm. Microflotation tests conducted in a Hallimond tube using pure mineral samples under alkaline conditions (pH ≈ 9), at a depressant dosage of 500 mg/L and in combination with a plant-based fatty acid collector, revealed a pronounced selectivity window, resulting in an approximately 77% difference in flotation recovery between apatite and calcite. These findings demonstrate that nanostarch derived from agro-industrial residues is a promising, biodegradable, and sustainable depressant capable of enhancing selectivity in phosphate flotation. The results contribute to the advancement of greener mineral processing Technologies, although Further studies are required to elucidate the underlying interaction mechanisms.

Mining doi: 10.3390/mining6020035

Authors: Kristie Jingyi Hu Yutong Chai Soheil Asgarpour Richard Boudreault Jonathan Li Shunde Yin

Metallurgical coal operations are a significant but poorly constrained source of methane (CH4) in Canada. We present a multi-instrument analysis of 63 methane plume detections at Fording River Operations, British Columbia (January 2022–March 2026), using the Airborne Visible/Infrared Imaging Spectrometer—Next Generation (AVIRIS-NG; n = 39), the Earth Surface Mineral Dust Source Investigation (EMIT; n = 4) and Tanager-1 (n = 20). Of these, 41 plumes (65%) were quantified, with retrieved emission rates of 34–3622 kg CH4 h−1; 54% exceeded the 500 kg h−1 super-emitter threshold. Because 73% of detections fall in September and no detections are available for 2023, results characterize the late-summer overpass window and should not be extrapolated seasonally without further coverage. The central finding is a systematic, asymmetric wind-speed disagreement between two numerical weather prediction (NWP) products that maps onto the Integrated Mass Enhancement (IME) quantification outcome. A univariate logistic regression identifies HRRR wind speed as a significant predictor of quantification success (OR = 0.29 per m s−1, 95% CI [0.15, 0.56], p < 0.001; AUC = 0.80; 5-fold cross-validated AUC = 0.79 ± 0.20, fold range 0.45–1.00). Cross-validation against ERA5-Land shows that HRRR exceeds ERA5 by a mean of +0.86 m s−1 (+43%) for unquantified events but shows near-zero disagreement for quantified events (–0.09 m s−1, –6%). A sensitivity analysis restricted to HRRR-forced retrievals (EMIT + Tanager-1, n = 24) confirms the finding is not an artefact of mixed wind data sources (OR = 0.28, AUC = 0.83, p = 0.018).

Mining doi: 10.3390/mining6020034

Authors: Rayara do Socorro Souza da Silva Marcondes Lima da Costa Pabllo Henrique Costa dos Santos

The Carajás Province, located in the southeastern Amazon, hosts some of the world’s largest high-grade iron deposits. Despite their economic importance, the processes linking lateritic weathering and iron enrichment remain incompletely understood. This study investigates the role of lateritic weathering in the evolution of the Serra Leste iron deposit through the characterization of a weathering profile and its parent rocks using drill-core samples. Analytical methods included X-ray diffraction (XRD), optical microscopy, scanning electron microscopy coupled with energy-dispersive spectroscopy (SEM-EDS), whole-rock geochemistry, and Mössbauer spectroscopy. Jaspilites weathered into ferruginous saprolite while preserving relic banding and mineral textures. Magnetite alteration produced pseudomorphic hematite with dissolution cavities progressively infilled by goethite, indicating iron remobilization during weathering. Weathering of chloritites generated clayey saprolite enriched in kaolinite and iron oxyhydroxides, with gibbsite occurring in more advanced stages. The uppermost horizon consists of a ferroaluminous duricrust composed of massive, spherulitic, and brecciated iron oxyhydroxides associated with gibbsite. Up-profile geochemical trends are marked by decreasing SiO2 and increasing Fe2O3. The mineralogical, textural, and geochemical relationships indicate that the ferroaluminous duricrust was developed through contributions from both ferruginous and clayey saprolitic systems, particularly from the latter. These results support the interpretation that lateritic weathering played an important role in iron redistribution and supergene enrichment within the Serra Leste deposit, consistent with mature Amazonian lateritic systems.

Mining doi: 10.3390/mining6020033

Authors: Jingyu Huang Yutong Chai Jennifer Williams Shunde Yin

Compressed CO2 energy storage (CCES) in deep sedimentary basins offers a promising option to integrate carbon management with long-duration energy storage. However, most existing subsurface energy-storage studies focus on salt caverns or generic porous reservoirs, while the potential of evaporite-bounded carbonate reservoirs remains insufficiently explored. This study presents the first application-oriented numerical assessment of CCES in Southern Ontario. It investigates the feasibility of CCES in the Upper Silurian Salina Group beneath offshore Lake Huron, focusing on a porous A-2 carbonate interval vertically confined by B and A-2 halite caprocks. A fully coupled three-dimensional thermo-hydro-mechanical model is developed in COMSOL Multiphysics 6.3 to simulate two-phase (brine-CO2) Darcy flow, heat transfer, and poroelastic deformation under a realistic Michigan Basin stress, pressure and geothermal regime. After an initial cushion-gas stage at 8 kg/s that establishes a caprock-parallel supercritical CO2 wedge beneath the B-salt, 24 h injection-production cycles are imposed for two years, followed by a five-month high-resolution window. Three well completion strategies are compared: full-length, upper-only, and split (upper + lower) perforations. Results indicate that in all simulations the CO2 plume stabilizes as a persistent gas cap beneath the B-salt, far-field pressures remain close to hydrostatic, and reservoir deformations are very small, pointing to a substantial geomechanical safety margin. Among the three completion strategies, the split completion provides the best compromise: it maintains high and relatively stable CO2 production while avoiding the stronger lower-zone depressurisation seen in the full-length case and the more limited working volume of the upper-only case. These findings suggest that a Salina A-2 carbonate reservoir bounded by B and A-2 salts can accommodate cyclic CCES under realistic basin conditions, and that appropriately designed split completions offer a practical balance between storage utilisation and operational robustness in this setting.

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 Is(50) 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.