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By L. C. de Kooker, K. Esmaeili, I. Musonda, M. Ferentinou

This paper presents the results of an investigation into the effect of pore pressure regime on the factor of safety (FS) and the anticipated critical failure mechanism for a fly ash storage facility. In this study, pore pressure measurements from standpipe piezometers and pore pressure estimated from seepage analysis were used for a comparison of the estimated FS for a fly ash slope. This comparison was applied for static and seismic scenarios. To account for the uncertainties resulting from the limited data available and support a qualitative risk assessment evaluation, a probabilistic analysis was performed. The slope stability analysis was conducted in 2D and 3D, adopting the limit equilibrium analysis approach, and a finite element seepage analysis. The results suggest consistency of failure surfaces for 2D and 3D and an increase in FS values of 5 percent for the 3D approach, limitations of standpipe piezometers. The study demonstrated the sensitivity of the FS value, and the implication of adopting representative material properties, and water table levels, especially in cases where limited data are available, and assumptions need to be made to assess the long-term stability of a fly ash dam facility.

Aug 1, 2024

By Richard A. Thomas, Liming Yuan, Wei Tang, JOHN SOLES

Lithium-ion (Li-ion) battery applications are increasing for battery-powered vehicles because of their high energy density and expected long cycle life. With the development of battery-powered vehicles, fire and explosion hazards associated with lithium-ion batteries are a safety issue that needs to be addressed. Li-ion batteries can go through a thermal runaway under different abuse conditions, including thermal, mechanical and electrical abuse, leading to a fire or explosion. The National Institute for Occupational Safety and Health (NIOSH) mining program is conducting research to prevent and respond to lithium-ion battery fires in battery-electric vehicles in the mining industry. In this study, experiments were conducted to investigate the effectiveness of different suppression systems including dry chemical, Class D extinguishing powder and water mist for lithium-iron-phosphate (LFP) battery pack fires. The effects of activation time and release time of the water-mist system on the suppression of the LFP battery (a type of Li-ion battery) fires were studied. The results of this study may be helpful for developing strategic firefighting and response plans for battery-powered vehicles used in mining.

Aug 1, 2024

By M. Frenzel, D. Ebert, K. Bachmann, A. D. Renno, R. Möckel, J. Gutzmer, J. Krause

With the increasing demand for metalliferous and mineral raw materials, and consequent depletion of the global natural resource base, the possible utilization of secondary raw material sources is receiving more and more attention. In the present study, we present results from a detailed vanadium deportment study of three basic oxygen furnace slag (BOS) samples known to containing elevated bulk concentrations of vanadium (V). Complementary analytical methods that were used to quantify the abundance and composition of V-containing phases include SEM-based automated mineralogy, Xray fluorescence (XRF) analysis, and X-ray powder diffraction as well as electron probe microanalysis. The vanadium deportment was quantified using Monte-Carlo simulations of the data obtained from automated mineralogy and electron microprobe analysis. The total V concentrations identified by XRF are between 1.7 and 2.2 weight percent V. The most important hosts of vanadium are larnite-, brownmillerite- and portlandite-solid solutions. In two samples, calcium carbonates also significantly contribute to the V deportment, while wuestite, lime and native iron do not contribute significantly to the vanadium deportment. A thorough consistency check identifies considerable uncertainties in the density of the Vbearing phases as the most likely reason to explain remaining discrepancies between measured and calculated V values.

Aug 1, 2024

By Philip-Mark Spanidis, Christos Roumpos, Francis Pavloudakis

This paper presents a quantitative research (QNR) methodology, collaboratively conducted with a group of mining experts, to assess the knowledge management (KM) landscape in the Greek mining industry. The methodology involves a framework for structured data collection using questionnaires, statistical analysis, discussion on critical methodological aspects, and interpretation of results focusing on key aspects of interest for designers of KM systems. The paper concludes by summarizing the methodology’s outcome and proposing perspectives for further research.

Aug 1, 2024

By Iga Trisnawati, Fitria Puspita, Himawan Tri Bayu Murti Petrus, Gyan Prameswara, Idi Amin, Andi Nurfaadhilah Ulfah

Laterite ores, rich in essential metals like nickel, iron and cobalt, are a crucial resource for modern technology. However, the extraction of nickel from laterite ores is a complex process due to their intricate mineral compositions and low nickel concentrations. This paper presents the results of a study to understand the leaching behavior of preroasted laterite ore and the impact of roasting on leaching kinetics. The ore was subjected to roasting at 280 and 610 °C for a duration of three hours, followed by leaching in sulfuric acid (H2SO4) under atmospheric conditions. The results show that preroasting the ore at 610 °C significantly improved the recovery of nickel during leaching, with recovery rate of up to 93 percent, and the leaching process of the preroasted ore was primarily controlled by diffusion through the ash layer. The activation energy values were found to be 20.97 kJ/mol for the ore roasted at 280 °C, and 18.97 kJ/mol for the ore roasted at 610°C. These findings suggest that preroasting can enhance the leaching performance of laterite ore, potentially paving the way for more efficient and sustainable nickel extraction processes.

Aug 1, 2024

By A. McQuillan, N. Bar

Geotechnical engineers are routinely tasked with advising suitable stand-off distances below highrisk sections of slopes in open-pit mines that are identified to have potential to deform or collapse. Accurate prediction of failed material runout can mean the difference between continuous safe mining and unwanted high-potential incidents that result in loss of production, equipment damage, injury, or loss of life. This paper updates previous empirical relationships presented by the authors for estimating the volume and runout distance of excavated slope failures, in an open-pit mine operation, using slope geometry as the primary predictor. Cases are sourced from varying slope geometries (fall heights up to 385 m, slope angles up to 80°) and a range of commodities (iron ore, coal, nickel, gold, copper, boron, and limestone), excavated in sedimentary, banded-sedimentary, epithermal, and copper-porphyry deposits, across all six inhabited continents. Analysis of these cases identified positive correlations between slope height and runout distance, and slope height and failed material volume. In general, negative correlations were identified between Fahrböschung angle and slope height, and Fahrböschung angle and failed material volume; however, significant scatter is observed in these datasets. A definitive relationship could not be derived comparing Fahrböschung angle with failed material runout. Slope angle was also found to be a poor indicator of runout. Of the parameters analysed, slope height (i.e., fall height) was found to be the simplest and best predictor of runout distance. This paper presents new charts for predicting failed material runout distance for rock slopes. Relationships are defined for structurally and rock-mass driven slope failure mechanisms at average, 75%, and 95% prediction intervals

Jul 10, 2024

By K. G. Philo, R. C. W. Webber-Youngman

mining, where data-driven decision making optimizes resource extraction, enhances safety, and ensures sustainability. The adoption of digital technologies like artificial intelligence (AI) and the Internet of Things has amplified the importance of digital information. However, the integrity and security of this information are paramount, leading to the exploration of blockchain technology as a potential solution for secure digital value exchange in mining. This research examines blockchain's capabilities, drawing insights from its applications in sectors like banking, government, healthcare, and entertainment, and evaluates their relevance to mining's core value chain processes. The study identifies blockchain's distributed ledger technology, cryptographic security, and decentralization as unique advantages that can revolutionize mining by enhancing transaction speed, reducing costs, and improving supply chain transparency and compliance with sustainability standards. Blockchain's transparent and auditable records can enhance business transparency, fostering trust among stakeholders, including investors and regulatory bodies. The technology's consensus mechanisms and smart contracts further promote trust in collaborative ventures. This research provides a foundational understanding for decision-makers in the mining industry to evaluate blockchain's feasibility and potential return on investment, guiding strategic planning and resource allocation for blockchain applications. By leveraging blockchain, mining companies can optimize operations, improve sustainability practices, and establish a robust foundation for future growth, positioning blockchain as a transformative technology in the sector

Jul 10, 2024

By N. Mutemeri, T. -L. Field, M. Chuma

The categorization of artisanal and small-scale mining has a significant impact on perception and understanding of the sector, particularly from a livelihood perspective. Several developing countries classify different types of artisanal and small-scale mining based on legal status. Given the nature such activities, the tragedy of the commons theory has been applied to understand the inevitable environmental, economic, sociocultural, safety, and health negative externalities – which are products of informality and illegality. Consequently, formalization is a panacea to sustainability. This article aims to offer a conceptual organization and foundational knowledge for characterization of artisanal and small-scale mining. It seeks to identify existing literature on the subject to avoid replication and acknowledge other scholars. Moreover, the article aims to place the study within the context of existing literature, establishing relationships with other studies and why the research is necessary. This paper pinpoints gaps left from other studies in so far as the characterization of artisanal and small-scale mining is concerned. Thus, reviewing literature abetted in finding similarities and differences on how artisanal and small-scale mining is defined from a scholarly and legal basis. The paper ascertains major claims made by earlier research on this topic, such as environmental impacts, the lack of adequate regulatory framework, and presents querying and probing questions lacking from other studies.

Jul 10, 2024

By L. W. Palmer

Compositing or regularization of drillhole data is common practice in mineral resource estimation and is deemed a necessary step in producing unbiased estimates of mineral resources and reserves. Commonly, data are collected over irregular distances due to the varying relative thicknesses of lithologies drilled or sampling/assaying strategies. This necessitates data transformation to regular lengths of equal size to ensure that all data have the same sample support. However, there have been few detailed publications on the effect of this process on the composited data that are subsequently taken forward for the estimation process. In this paper, three currently available compositing methods are reviewed and the effects of inappropriate compositing methodologies presented. It is shown through a case study that compositing samples to different lengths leads to changes in the average and variance of the grades in the drillcores in the dataset, which will impact the final estimated value. These differences are exacerbated by breaks or gaps in data where, for a variety of reasons, there has been no data collection or data have been lost. The importance of appropriately treating blank and zero data is also presented. Globally, these differences might be minimal, but locally may be substantial, affecting the efficiency of the estimation and subsequent use of the results in, for example, mine planning and reconciliation. Further detailed investigation of compositing practices is required if the full implications of compositing are to be understood and any induced bias effectively defined.

Jul 10, 2024

By J. Maritz, K. de Beer, S. M. Buthelezi

The economic upheaval of COVID-19 forced companies to invest in emerging technologies to aid recovery. One such technology is extended reality, which is becoming a mature and innovative tool. Early adopters are seeing significant benefits in learning, training, immersive data visualization, and remote assistance. In South Africa, the mining industry is increasingly interested in using extended reality to optimize and innovate operations. The Minerals Council of South Africa's July 2021 report highlighted the potential of extended reality's to achieve zero-harm production and modernize the industry. However, the extent of extended reality adoption in mining remains unclear due to limited information on its usage. This study addressed this gap by distributing an online survey to assess awareness, knowledge, and current uses of extended reality in South Africa’s mining sector. The results indicated that virtual and augmented reality had the highest levels of awareness and usage, primarily for learning and training. Mixed reality, however, had the lowest awareness and knowledge levels. In terms of applications, visualization and remote assistance had the least use cases. These findings highlight that the South African mining industry is deficient in its understanding and use of extended reality technologies. Without better awareness and application, the South African industry risks missing out on the full benefits of extended reality. The study underlines the need for the South African mining industry to improve its outlook on extended reality technologies to fully leverage their potential applications and benefits.

Jul 10, 2024

By T. T. Chiweshe, L. S. Mokhahlane, M. Welman-Purchase

This study examined an alternative technique of extracting tungsten from wolframite ore using a fusion method with ammonium phosphate salt. Current techniques use alkali salts to decompose tungsten ores and use various purification methods to produce ammonium paratungstate, which is a key intermediate precursor in the extraction of tungsten. In this study, a two-step extraction process, which involves thermal decomposition of the ore using fusion and a separation stage, is examined. The novelty of this technique is the ability to completely decompose wolframite ore and form an unstable tungsten oxide phosphate (WO2(PO3)2) compound. The instability of WO2(PO3)2 in deionized water enables selective isolation of tungsten as insoluble precipitates of WO3 and WO2. The decomposition reaction of WO2(PO3)2 is influenced by the presence of oxygen and determined to be first order under ambient conditions. Scanning electron micrographs and X-ray diffraction analysis showed above 80% of the tungsten precipitated compared with the amount that remained in the filtrate solution.

Jul 10, 2024

By B. Ceki, A. Mabentsela

The BCL furnace is scheduled to restart operations after being placed on care and maintenance in 2016 due to depressed nickel prices. The decision to start operations after such a stoppage ought to be led by a techno-economic evaluation of process options to make operations more resilient. For BCL, the decision lies between using the existing flash-smelting furnace (FSF) or a top-submerged lance (TSL) furnace. Available studies show that the FSF combined with other converting technologies is cheaper to operate; however, such studies are based on flowsheet simulation results of single copper concentrates and therefore do not provide a full scope of practical capabilities based on smelter operator skills. Using a t-test on normalized prior operational data from three Cu FSF and two Cu TSL, it was found that the only statistical differences between the operating costs of the FSF and TSL technologies are in the coal use for heating the feed blow and number of rebuilds: the FSF consumes coal to heat the feed blow and the TSL requires 2.4 rebuilds during a course of a single FSF campaign. A summative operating cost comparison over the existing BCL FSF 11-year life shows that BCL can decrease operational costs by some BWP 55.5 million if the operation were to change to the newer TSL technology. The savings derive from reduced coal use, which is normally associated with heating the blow when using the FSF. Despite the TSL carrying added costs of 2.4 rebuilds during a life time of one FSF furnace campaign, the cost associated with the TSL rebuilds of approximately BWP 1.3 million is minimal compared with the overall operational expenditure decrease that BCL will incur on using the TSL technology. In terms of the technology, BCL can have higher Ni–Cu recoveries at lower operational costs by elimination of Ni–Cu losses and eliminating the slag-cleaning furnace by converting to a TSL furnace.

Jul 10, 2024

By Juan L. Yarmuch, Gonzalo Sepulveda

Medium- and short-term mine planning holds immense significance in optimizing production and resource utilization. It serves as a vital link between the long-term strategic plans and the day-to-day operational activities of a mine. In this context, a mathematical formulation is proposed to incorporate mining width constraints into the production scheduling process, aiming to maximize the net present value (NPV) of the schedule while ensuring enough room for the operation of mining equipment.

Jul 1, 2024

By G. M. Wali Ullah, Micah Nehring, MEHMET KIZIL, PETER KNIGHTS

In operations that use the sublevel stoping mining method, production scheduling takes into account factors — including ore reserve envelopes, ore grade averages, equipment capacity, feed controls to the mill, and geotechnical restrictions — across the scheduling horizon. Mathematical programming is one of the most effective methods for enhancing the decision-making process in regard to the most viable production schedule in light of a given set of limitations. The majority of research on sublevel stope mining focuses primarily on a single objective of optimization, which is to maximize the net present value (NPV). Environmental, social and governance (ESG) considerations are becoming more prevalent in the mining industry. This includes aspects relating to deforestation, land disturbances, gas emissions, community relations and water usage, among many others. Institutional and other kinds of investors are becoming more interested in the work that resource companies do regarding their ESG obligations. This review article identifies the gap in the existing literature and proposes to simultaneously optimize the production schedule around three objectives. Two of these relate directly to ESG aspects

Jul 1, 2024

By Manoj Khandelwal, Bright Akuinor Tsidi, Newton Amegbey, Daniel Mireku-Gyimah

This study emphasizes the importance of understanding the factors that influence the throwing of flyrock in mining operations, a significant hazard to both workers and nearby structures. Moreover, it highlights how blasting engineers, when estimating flyrock occurrences and their travel distance, typically rely on input parameters such as powder factor (PF), hole length (HL), subdrill (SD), spacing (S), hole diameter (D), burden (B) and stemming length (ST), while overlooking crucial factors like velocity of detonation (VOD) and charge per bank cubic meter (CPBCM). Through analysis using support vector machine (SVM) modeling in MATLAB, the study underscores the impact of including or excluding VOD and CPBCM on flyrock throw distance.

Jul 1, 2024

By Wei Victor Liu, Omer Faruk Ugurlu, Chengkai Fan, Bei Jiang

Accurate prediction of truck productivity plays a pivotal role in improving the efficiency and profitability of openpit mining operations. This paper proposes a deep neural network (DNN) model to overcome the challenge of predicting truck productivity in openpit mines. The prediction model was built using eight variables and was optimized by considering different train-test split ratios, numbers of hidden layers and neurons, and activation functions. The proposed model’s performance was evaluated using various metrics and compared with other commonly used machine learning algorithms. The results showed that the proposed model outperformed traditional machine learning models by achieving higher prediction accuracy. Moreover, a single-variable sensitivity analysis showed that haul distance is the most influential variable for predicting truck productivity. This study marks a pioneering effort in employing DNN to predict truck productivity in openpit mining, signifying a notable advancement in the field.

Jul 1, 2024

By Jodie Robertson, Isabel Barton, Cristian Caro

Prior to mining, all rocks contained in a mineral deposit must be placed in one of several categories known as ore types. Each ore type describes a different way that the rock will behave in processing. The ore type determines which process stream a particular mined unit will be sent to, sets expectations for process engineers and metallurgists, and forms the basis for recovery predictions and production estimates. At first, ore types are assigned mainly by geologists based on visible geological criteria (dominant ore mineralogy, estimated grade, rock type, alteration type). As metallurgical tests are carried out and process data accumulate, the resulting criteria may be factored into the ore typing process, typically as assays and recoverable metal using the relevant process(es). Other variables may also be incorporated into ore typing at operations if they are particularly important, such as grindability, preg-robbing, gangue reagent consumption, and the presence of especially deleterious minerals such as talc or smectite. The mine operation department may also redefine ore types and/or process destinations based on economic criteria. A “best” ore type is designated that (in theory) best describes how the rock will behave in processing. Codes representing this ore type are entered into the drill-hole database, then interpreted on cross sections and level plans, and finally added to the block model. Ore types are iteratively reexamined and adjusted over the life of a project. Major difficulties in effective ore typing are (1) lack of communication between geologists and metallurgists, (2) the imprecision inherent in imposing clean categories on messy natural systems without discrete divisions, (3) the need for ore types to provide useful information for a wide range of processes, (4) difficulties in scaling up laboratory test results to mine production, and (5) conflict among geological, metallurgical, and economic criteria for ore typing.

Jul 1, 2024

By Elif Emil-Kaya, Bernd Friedrich, Merve Papakci

Samarium (Sm), one of the rare earth elements (REEs), and cobalt (Co) are used in the production of SmCo permanent magnets, which have excellent temperature stability, corrosion resistance and oxidation resistance. Of the two types of SmCo magnets, one contains a high amount of iron, approximately 15.2 percent. This paper focuses on the recycling of iron (Fe)-bearing SmCo. In this study, an oxidative leaching process with nitric acid was developed to eliminate iron through in situ hydrolysis and to dissolve REEs and Co. The influence of experimental conditions on the formation of an amorphous iron compound through the hydrolysis of Fe3+ in a nitric acid environment was thoroughly examined based on a Taguchi orthogonal array. The optimal parameters for oxidative leaching were determined to be an acid concentration of 3 mol/L, a solid-to-liquid ratio of 1/10, and a process temperature of 60 °C.

Jul 1, 2024

By Guy Reed, Russell Frith

In situ or pre-mining horizontal stresses are arguably the least well understood of the principal inputs into underground coal mining geotechnical engineering design, whether analytical, empirical, or numerical. This is a direct result of both the cost and difficulty of obtaining meaningful stress measurements, the various limitations of the measurement method in terms of sourcing strata types that approximate the assumed conditions of the post-measurement mathematics to convert measured strains into stresses, and a common practice by some geotechnical professionals to preferentially utilise generic values rather than interrogate the available measurement data for cause and effect relationships between horizontal stress magnitudes, directions and a range of associated controls. That numerical modelling simulations attempt to mimic reality but often rely on simplified generic horizontal stress input assumptions is a particular cause for further consideratio The paper attempts to further explore the nature of in situ horizontal stresses using a range of stress measurement results from the Australian coal sector supplemented by several international studies addressing the same basic issue, the result being a number of credible and highly relevant “cause and effect" inter-relationships between the three principal in situ stresses in addition to the influence of rock properties (e. Young's Modulus and Poisson's Ratio), cover depth and the larger-scale structural geological environment. In particular, the paper demonstrates that despite being commonly overlooked as a primary rock/coal material property, Poisson's Ratio and the associated K Effect are intrinsic to understanding 3D in situ stress measurement results and therefore, predicting in situ stress magni- tudes more generally for geotechnical analyses purposes. As a fundamental question, the paper addresses whether it is necessary and of engineering value to characterise in situ horizontal stresses: according to distinct "domains," in the same way that more easily identifiable geotechnical properties such as rock mass ratings, coal seam thickness, ply splits, and cover depth are often treated.

Jun 25, 2024

By Scott Burchmore, Jason Emery, Michael Melville

This paper presents best practice data management for monitoring of extensometers in Australian underground coal mines. This work is based on the combined experience of the authors and the available literature. The information and ideas presented herein are a culmination of many years of database development founded from mine site-based ground support design, underground inspections, extensometer data management and data analysis. Each author has more than ten years’ experience as a practicing geotechnical engineer at several operating industry wide research project focused on utilizing mechanical extensometer data for data analytics and machine learning. Principal hazard ground control management plans, stipulated in Australian coal mining legislation, outline the mandatory installation of ground monitoring devices during routine mining activities. After 20+ years of data gathering the barrier to implementing modern data analytics remains the challenges imposed by inconsistent data structure and data quality. This inconsistency is still routinely found between sites, companies and mining regions. Through the relatively simple application of a standardized database structure, the potential to shift from simplistic tracking of trigger levels, siloed at individual sites, to an industry standard method for compilation & comparison of monitoring data is enabled.

Jun 25, 2024