Abstract: Sluice box washing continues to face operational limitations arising from inconsistent water velocity and the need to tailor slope designs to varying particle sizes. These interrelated factors significantly diminish recovery efficiency, thereby underscoring the necessity of this study. The samples were collected each sample were homogenized into uniformly. Varied sieve size and sluice box angles were utilized. Fractional sieve analysis of a 100g sample was carried out from each site using sieves. Based on this analysis the resulted particle size distribution from the site Wolansa (30, 50, 20), Qori (25, 60, 25) and Bore (35, 47, 18) in percent is coarse, medium and fine respectively. For optimum angle 100kg of alluvial material washed at constant water pressure and mesh size. This was done for 3 different angles of inclinations (5o, 10o, and 15o). From the result, the optimum angle for artisanal gold recovery for 3 sites were 10 o since it yielded the highest amount of recovery from site Wolansa 0.43, Qori 0.46 While Bore is 0.45. Therefore, this study advice to change the sluice boxes angle from 5o to 10o for Wolansa and 15o to 10o for Bore site to increase the recovery by 85%. and 51% respectively.

Abstract: The Tala Hamza zinc–lead deposit, located in the Amizour region south of Béjaïa (Northern Algeria), is one of the largest base-metal resources in the Maghreb. This study presents an integrated geological, geostatistical, and geotechnical assessment to improve resource estimation and optimise the mining strategy. Geostatistical analyses of drilling data revealed moderate to strong spatial continuity of zinc and lead grades, with variogram ranges of 120–200 m along the main structural trends. Ordinary Kriging and conditional simulations produced three-dimensional grade and uncertainty models, confirming anisotropy consistent with the tectonic framework and identifying higher uncertainty near fault zones. These results were integrated with geotechnical investigations and FLAC3D numerical modelling to validate the Descending Backfilled Chamber (DBC) mining method. The DBC approach, combined with cemented backfilling, ensures mechanical stability, limits dilution, and maximises ore recovery. This multidisciplinary framework demonstrates the effectiveness of coupling geostatistical and geotechnical modelling for reliable resource evaluation and sustainable mine design, providing a reference for similar base-metal deposits in Algeria and beyond.

Abstract:

The growing global demand for strategic minerals such as lithium, driven primarily by the battery industry, has made rapid and effective control of mineral quality an urgent necessity. Conventional analytical methods, although accurate, often require considerable time and complex sample preparation, which can delay process control. To overcome this challenge, this work proposes the use of Fourier Transform Infrared (FTIR) spectroscopy combined with Partial Least Squares (PLS) modeling as an efficient alternative. This approach aims to provide immediate response for predicting grades in lithium-bearing ores, such as spodumene, ensuring agility and precision to meet industry demands. This study evaluated the application of FTIR spectroscopy coupled with chemometric modeling for the simultaneous prediction of lithium oxide (Li₂O) and spodumene contents in pegmatitic samples. Two independent PLS models were developed, using spectra preprocessed with first derivative and/or Standard Normal Variate (SNV). Spectral regions were selected based on the structural response of Al–O, Si–O, and OH⁻ groups, which are indirectly influenced by the presence of lithium. The spectral datasets were split into calibration and external test sets, and the models were evaluated based on statistical metrics and Principal Component Analysis (PCA). The Li₂O model achieved an R² of 0.9934 and an RMSEP of 0.185 in external validation, with a mean absolute error below 0.15%. The spodumene model achieved an R² of 0.9961, an RMSEP of 1.79, and a mean absolute error of 2.80%. The results indicate that the FTIR-PLS approach enables efficient quantitative estimation of lithium-bearing minerals, with reduced analytical time, good accuracy, and feasibility for application in process control and mineralogical sorting environments. PCA confirmed the statistical representativeness of the test sets, with no occurrence of spectral extrapolation.

Abstract: This paper examines the empirical foundations of rock engineering. We have adopted a narrative style throughout, as the philosophical nature of the questions raised in the paper is better served by discourse than conventional technical structure. In the first part of the paper, we revisit the Hoek-Brown failure criterion using synthetic rock mass models, validating the general framework while revealing critical distinctions between data-driven parameter emergence and classification-dependent derivation. The analysis reveals fundamental challenges, including the conflation of calibration with validation, the transformation of qualitative geological assessments into seemingly quantitative parameters, and the false similarity problem, where different parameter combinations yield equivalent failure envelopes. In its second part, the paper explores broader implications for professional practice, revealing a significant gap between methodological validation and professional acceptance. What satisfies the professional standard of "balance of probabilities" for establishing reasonable practice may fall short of the scientific standard of "evidence beyond a reasonable doubt" required to claim genuine predictive validity. We propose "epistemological integrity" as a framework for responsible practice: acknowledging the false similarity problem, communicating uncertainty transparently, applying validation standards consistently, and aligning professional claims with actual knowledge limitations rather than projecting false precision through computational sophistication.

Abstract: The aim of the study was to analyse the impact of carbonaceous and mineral contami-nants present in mineral oils on the tribological wear of the 42CrMo-4 steel under mixed friction conditions. A range of advanced analytical techniques was employed, including polarised light optical microscopy, SEM, XRF, EDS, XRD, as well as Raman spectroscopy and profilometry. Wear tests were conducted using a roller-on-roller tribological test rig to evaluate changes in surface topography and the extent of surface damage. The results showed no clear functional correlation between the mass loss of the samples and the con-tent of non-combustible fractions in the carbonaceous contaminants. The most favourable tribological performance was observed for the abrasive variant with low ash content and high elemental carbon content. In this case, a thin graphite-like carbon layer formed on the surface, significantly improving lubrication, reducing friction, limiting surface spalling, and reducing damage depth (to approx. 10 µm). In other variants, despite the formation of compressed carbon–mineral layers, the higher content of hard mineral particles reduced their durability and led to increased wear. Local temperature and particle size were found to significantly influence wear intensity – smaller particles contributed to lower flash temperatures and reduced surface damage. The variant with pure oil, lacking any abra-sive additives, showed no protective effects, resulting in intense microscratching and sur-face spalling due to direct asperity contact.

Abstract: Tailings reservoir is an important part of the mine. The monitoring and assessment of the stability of their key structures have always been the focus of research by many scholars. In this experiment, Interferometric Synthetic Aperture Radar (InSAR) and the Global Navigation Satellite System (GNSS) were employed to obtain 30 sets of longitudinal deformation data of 6 feature monitoring points on the surface of a tailings reservoir in Anhui Province. Considering the complementarity of InSAR and GNSS in surface monitoring, it is proposed to calculate the optimal initial parameters Q and R of Kalman filter by using Particle Swarm Optimization ( PSO ), so as to construct the optimal PSO-Kalman data assimilation model to achieve bidirectional data assimilation between InSAR and GNSS data, improve the accuracy of InSAR data, and comprehensively analyze the stability of key dams. After that, the Long Short Term Memory (LSTM) recurrent neural network is utilized to conduct time series predictions on the assimilated data and the buried depth data of the saturation line of the monitoring points of the mine dam during the same period. The experimental results show that using PSO-Kalman filter for data assimilation, compared with the original InSAR data, the overall mean absolute error ( MAE ) is reduced by 52.7 %, and the overall root mean square error ( RMSE ) is reduced by 53.6 %. By using LSTM to predict the time series data, the RMSE of the key dam deformation data test output set is less than 2.5mm, and the RMSE of the saturation line buried depth test output set is less than 1.5mm. Finally, the existing data is used to train the dam stability evaluation model. Under the condition that the correct rate of the evaluation model is 88.89 % and the AUC value of the model stability is 0.88889, the LSTM prediction data and the stability evaluation model are used to analyze the future stability of the key structure. This paper innovatively proposes to jointly evaluate the stability of the key dam structure by combining the deformation data and the saturation line height data. It also presents the first relatively complete integrated research method of ' monitoring-prediction-evaluation ' for the key dam body of the tailings reservoirs. The experimental results show that this method can provide reliable data and technical support for the monitoring, stability analysis and evaluation of the key dam body of tailings reservoirs.

Abstract: In the mines of the Karaganda Basin, in addition to methane, there are instances of intense hydrogen sulfide and sulfur dioxide emissions during coal seam extraction. Methane content in the extraction areas ranges from 25 to 38 m³/t. Consequently, degassing is applied in all extraction areas. Before degassing operations, methane is extracted from the unreleased coal seam. In seams exhibiting methane-hydrogen sulfide zones, the methane zone is prioritized for extraction, followed by the hydrogen sulfide zone. The aim of the article is to determine the specific content of hydrogen sulfide and sulfur dioxide in seams D6 and D10 during the extraction of hydrogen sulfide zones in the Karaganda Basin mines, identify the causes of gas abundance in the seams, and determine the factors influencing the intensity of sulfur-containing gas emissions. The article presents the results of research on the gas content of seams K10 and D6, based on a comparison of laboratory results obtained through coal sample analysis. It includes data on the natural gas content of seam K10, results from sampling and processing coal samples using DMT methodology, and actual gas emissions from seam K10 during its extraction at the Abai mine of ArcelorMittal Temirtau's coal department. For the first time in the Karaganda Basin, comprehensive studies of coal seam gas content and the impact of degassing on its magnitude have been conducted. Accurate knowledge of gas content is essential for designing seam extraction operations, including daily loads, ventilation parameters, degassing, and other factors dependent on methane content and its potential release during mining.

Abstract: With the increasing harsh drilling environments encountered more frequently than ever before, developing environmental benign and multifunctional additives is essential to formulate high performance drilling fluid. Herein, hydrothermal carbon/bentonite composites (HCBCs) were prepared by hydrothermal carbonization reaction using soluble starch and sodium bentonite as raw materials. A systematic investigation was conducted into the effects of HCBC concentration on the rheological, filtration, and lubricating characteristics of xanthan gum, modified starch, and high-temperature polymer slurries. These properties were evaluated before and after exposure to hot rolling at different temperatures. The hydroxyl radical scavenging properties of HCBC was evaluated. Observation showed plentiful micro- and nano-sized carbon spheres deposited on the bentonite particles, endowing the bentonite better dispersion. HCBCs could maintain the water-based drilling fluids’ rheological profile stable, decrease filtration loss and improve the lubrication with relatively low concentrations. The excellent properties were attributed to the highly efficient scavenging of free radicals and stabilization of bentonite particle dispersion.

Abstract: Optimizing beneficiation processes of iron ore industry is essential to meet the increasing demand while coping with decreasing grade deposits. As grinding largely impacts the quality and production costs, the implementation of Advanced Process Control (APC) emerges as a solution to increase efficiency and operational stability. This study evaluates the improvements obtained with the application of an APC system in the ball griding circuit of the Mineração Usiminas industrial processing plant. The adopted methodology involved the collection and analysis of operational data with the system enabled and disabled, using statistical tests and literature review to support the analyses. The results indicate significant gains in throughput and stability. This work thus contributes to the assess the benefits of Advanced Process Control in an industrial operation.

Abstract: The classification of mineral resources and reserves establishes a structured framework to quantify the contents of mineral deposits, covering continuity, grade distribution, tonnages, and the legal, technical, and economic feasibility of extraction within a defined timeframe and production rate. To reduce subjectivity and improve reliability, international reporting standards were developed on the principles of transparency, materiality, and competence. Compliance with these standards enables professionals and investors to evaluate mineral assets using consistent and comparable information across jurisdictions. Many mining operations are now seeking to align their disclosure practices with these frameworks to strengthen governance, improve credibility, and facilitate access to global capital. Within this context, the Mineral Re-sources and Reserves Readiness Index (MR³ Index) is introduced as a methodological tool to assess the degree of alignment of mining operations with international report-ing requirements. For operating mines, one of the key variables in the MR³ Index is the success in converting Inferred Mineral Resources directly into mine production, even in the absence of prior classification as Indicated or Measured Resources. This measure functions as a proxy for geological robustness and operational maturity. The applica-tion of the proposed methodology to an underground lithium mine in Brazil indicated a readiness level of 95.5%.

Abstract: Determination of the elemental composition of minerals and their derivatives at mining enterprises is important at all stages of minerals processing. This paper is devoted to the results of development and application of an online X-ray fluorescence (XRF) analysis method for monitoring mineral elements on a conveyor belt of mining enterprises. Evaluation of metrological characteristics achieved in the online analysis of lump, ore, charge feed, cake and slag materials on conveyor belt is presented. Each implementation of the online XRF analysis at mining enterprises was preceded by laboratory studies, development of measurement methods, calibration of a specific XRF analyzer using standard reference samples for a specific concentration range of the monitored elements. Typical areas of application for monitoring the concentration of elements in rocks on conveyor belts of mining enterprises and those solutions that made it possible to achieve the required measurement accuracy of an X-ray fluorescence analyzer in online mode are presented.

Abstract: The issue of water disasters in the mining floor is extremely severe. Despite significant progress in the on-site monitoring and identification of water inrush channels, research on the spatial development characteristics of cracks and the temporal evolution patterns remains insufficient, resulting in the incomplete development of microseismic (MS)-based water disaster early warning theory and practice. Based on this, the present study first derives the expressions for the diameter and length of water inrush channels according to the damage characteristics of MS events and the glazed porcelain shape features of the channels. A theoretical model for the correlation between MS-water inrush volume is established, and the relationship between MS and water level is revealed. Analysis of field monitoring data further indicates that when high-energy MS features (such as single high-energy events and higher daily cumulative energy) are detected, the aquifer water level begins to decline, followed by high water inrush events. Therefore, a decrease in water level accompanied by high-energy MS features can serve as an important early warning marker for water disasters. Finally, advanced machine learning methods are applied, in which the optimal index combination for floor water inrush prediction is obtained through the genetic algorithm (GA), and the weights of each index are determined by integrating the analytic hierarchy process (AHP) with the random forest (RF) model. The results show that the consistency ratio (CR), mean absolute error (MAE), and root mean square error (RMSE) are 0.024, 0.027, and 0.046, respectively. Field engineering verification demonstrates that the integrated early warning system performs significantly better than any single monitoring indicator, and all high water inrush events are successfully predicted within four days. Theoretical model; Crack monitoring; Water level response; Machine learning; Floor water disaster early warning

Abstract: Roof accidents, as typical accidents in mine safety production, occur frequently and are highly harmful, posing a significant threat to the life safety of miners. Through the causal analysis of the occurrence process of roof accidents, this study creatively constructs an accident causation matrix to realize the characteristic description of accident causes, which serves as the data support for the Bayesian network built based on fault tree modeling. Ultimately, a new analysis framework integrating the accident causation matrix and the Bayesian network model is established. In the process of accident analysis, first, based on the 2-4 causation model theory and combined with the association rule algorithm, the key factors of the accident and their internal correlations are obtained, and the accident causation matrix is constructed. Second, the fault tree is transformed into a Bayesian network model, and the accident causation matrix is used for parameter learning and optimization. Finally, two methods-model comparative analysis and real case verification are adopted to prove the advancement and effectiveness of this study. Researching results indicate that the accident causation matrix can effectively characterize accident causation factors, providing precise input data for Bayesian network models and significantly enhancing their reliability. Through the reverse reasoning function of Bayesian networks, dynamic diagnosis of accident causes and identification of key risk factors are achieved, enabling a more dynamic and detailed analysis of accident causes. This offers a scientific basis for coal mining enterprises to formulate preventive measures.

Abstract: To improve the MWD technology and explore the relationship between rock parameters and drilling parameters, this paper carried out physical and mechanical experiments, built a small drilling platform ( including magnetic suction drilling, data monitoring system, rock confining pressure system ), and carried out 330 r/min, 360 r/min, 390 r/min three different specifications of the initial speed of the drilling experiment, and added 330 r/min initial speed drilling different strength rock drilling experiments. The experimental results show that rock drilling is divided into three stages: the initial stage of drilling, the crack propagation stage, and the bit retreating stage. The rotation speed has a great influence on the drilling speed, torque, weight on bit, and drilling time. According to the Pearson fitting relationship of drilling parameters, the correlation between F and PR is -0.783, indicating a strong positive correlation, and the correlation between RPM and PR is 0.827, indicating a strong negative correlation. The power function y=ax^b is used to fit the drilling parameters and rock parameters. The fitting effect is good, and the torque and uniaxial tensile strength R2 is as high as 0.9966. The experimental conclusion provides a theoretical basis for lithology identification in intelligent drilling and discusses the feasibility of a dynamic monitoring scheme for the drilling rig.

Abstract: The recent increase in end-of-life (EoL) lithium-ion batteries (LiBs) has become a significant concern worldwide. Most studies in the literature have primarily focused on recovering cathode active metals from black mass, whereas the separation of anode–cathode foils, plastics, and casing metals which are the essential components of LiBs has received relatively little attention. To reduce costs and maximize the recovery of valuable metals in subsequent hydrometallurgical or pyrometallurgical processes, EoL LiBs require appropriate pre-treatment. This study aims to scrape off the black mass (battery dust) adhering to the electrode foils resulting from gradual crushing and subsequently separate the plastics and copper (Cu) from other metals through a two-step selective flotation process. The results demonstrated that plastics, due to their natural hydrophobicity, could be effectively removed using a frother. Following plastic flotation, Cu particles were floated in the presence of Aerophine 3418A, yielding a Cu concentrate containing 65.13% Cu with a recovery rate of 96.4%. Additionally, the aluminum (Al) content in the non-floating material, remaining in the cell, increased to approximately 77%.

Abstract:

Background: Accurate operational cycle detection underpins maintenance, production analytics and energy management for mobile equipment in mining. Yet no review has investigated the landscape of operational cycle detection literature in mining. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses, Scoping Review extension (PRISMA-ScR) framework, we searched the Lens database on June 27, 2025, for records published 2000–2025 that segment mobile mining vehicle telemetry into discrete operating modes. After de-duplication (n = 1,757) and two-stage screening, 20 empirical studies met all criteria (19 diesel, 1 battery-electric). Due to the sparse research involving battery electric vehicles (BEVs) in mining, three articles performing cycle detection on heavy-duty vehicles in a similar operational context to mining are synthesized. A bespoke three-axis Transferability Lens—created to measure cross-domain applicability of modelling approaches—was applied to four expert-selected passenger BEV studies to investigate cross-domain synthesis. Results: Early diesel work used single-sensor thresholds, often achieving >90\% site-specific accuracy, while recent studies increasingly employ types of neural networks using multivariate datasets. While the cycle detection research on mining BEVs, even supplanted with additional heavy-duty BEV studies, is sparse, similar approaches are favoured. The transferability appraisal suggests only moderate sensor-mapping and retraining effort when adapting automotive BEV classifiers to mining vehicle cycle detection. Conclusions: Persisting gaps in the literature include the absence of public mining datasets, inconsistent evaluation metrics, and limited real-time validation.

Abstract: Efficient material handling is critical for mining productivity, safety energy and cost control. This paper analyzes the energy efficiency of five alternative designs for a 3 km inclined underground conveyor system for copper ore transport, considering route geometry, belt specifications, drive configurations, and operational parameters. Two main design approaches were examined: a single long conveyor and two shorter conveyors. Variants differed in belt tensile strength, use of intermediate drives, and system layout. Calculations results achieved by using dedicated QNK-TT software show differences in specific energy consumption index between variants for both average and peak capacities and highlight that high-capacity performance requires non-standard solutions: either higher belt strength or an intermediate drive system. The study shows that conveyor energy efficiency depends strongly on load level, with near-maximum throughput yielding the best performance. The authors conclude that conveyor system components selection should be based on a multi-criteria evaluation—including capacity margin, operational safety and maintenance complexity — rather than energy efficiency alone.

Abstract: This study investigates the application of triboelectrostatic belt separator (TBS) as an alternative to conventional magnetic methods for concentrating apatite from a complex phosphate ore rich in phyllosilicates. The testing material, containing 22.9% P₂O₅ and exhibiting over 90% mineral liberation even in coarser fractions (+0.6mm), was mainly composed of apatite and Mg/Al-bearing phyllosilicates, with minor quantities of car-bonates, amphibole, and feldspar. Pilot-scale experiments using an M6c TBS model were conducted in rougher and cleaner stages. Apatite’s strong tendency to acquire a positive charge enabled selective separation from the negatively charged gangue. Under optimal rougher conditions (run#4), the process yielded a concentrate with 25.3% P₂O₅ and 85.1% recovery. Subsequent cleaner tests improved product quality, with two configurations (run#15 and run#18) producing final concentrates assaying 29.0% and 28.9% P₂O₅ and overall P₂O₅ recoveries of 69.3% and 74.5%, respectively. Compared to high-intensity magnetic separation conducted at Unidade de Mineração de Angico, TBS demonstrated superior mass and P₂O₅ recoveries and improved MgO removal, although R₂O₃ levels remained slightly above commercial limits. These findings point out TBS as a viable, efficient, and selective technique for apatite concentration. Future research should focus on finer particles (-0.3 mm), electrode configurations, and charge-modifying agents to further enhance performance and industrial applicability.

Abstract: Open-pit mine production scheduling plays a critical role in maximizing economic returns while meeting environmental and operational constraints. However, the widespread use of proprietary software and rigid deterministic frameworks often limits accessibility, scalability, and adaptability; particularly for small and medium scale operations. This study presents a scalable and sustainable production scheduling model developed entirely in Python, using open-source libraries to bridge this gap. The model employs linear integer programming to optimize the extraction sequence of ore blocks, maximizing Net Present Value (NPV) while respecting precedence relationships, production capacity limits, and environmental penalties embedded in block valuations. Using synthetic block model data, the framework achieved simulated returns exceeding $1.6 billion USD, with integrated visualization tools including 3D diagrams, histograms, and boxplots; enhancing result interpretation. The model's modular and transparent design allows easy adaptation to different mine contexts and planning scenarios. By eliminating reliance on costly platforms and embedding sustainability into the optimization process, this work contributes a practical, technically rigorous, and accessible alternative for modern mine planning. It supports the broader transition toward intelligent, responsible, and inclusive scheduling systems aligned with environmental, social, and governance (ESG) expectations.

Abstract: With the advancement of oil and gas exploration and development technologies into deeper and ultra-deep reservoirs, complex geological conditions here render them highly susceptible to severe lost circulation. However, conventional bridging plugging methods struggle with large-sized lost circulation channels, while chemical gel plugging faces challenges like low success rates and insufficient pressure-bearing capacity. To address this, a novel leak plugging method combining bridging and gel plugging is proposed herein. From structural stability and mechanical properties perspectives, the enhancing effect of nanomaterials on the gel system is revealed, and the synergistic mechanism of coupled plugging is elucidated. For experimental setup, orthogonal experiments determined a base formulation with controllable gelation time: 10 wt% main agent, 2 wt% crosslinking agent, and 1:1 pH regulator ratio. Introducing 1.0 wt% nanosilica enhanced gel properties, achieving 30 N strength at 120°C aging. An optimized walnut shell bridging agent constructed the supporting skeleton, yielding a coupled plugging formulation with up to 8 MPa pressure for a 7 mm fracture. Lost circulation volume is controlled at 163 mL, outperforming single plugging methods. Research results demonstrate gel-bridging coupled plugging’s advantages for large fractures, providing new technical insights for severe lost circulation field construction.