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By K S. Park, J K. Kim, J H. Park, Y Su

The present study investigates the possibility of the direct removal of oxygen from the Ti-30Ni (wt per cent) alloy melt through the thermodynamic equilibrium reactions at 1623 K in the vertical tube furnace. The deoxidation efficiency of Ti-Ni alloy melt by adding different contents of metallic calcium (Ca) as a deoxidant was evaluated with the binary CaF2-MgCl2 flux. The thermodynamic equilibrium experiments showed that the total oxygen content in the alloy decreased from about 650 ppm to 350 ppm when 3.5 wt per cent Ca was added to the Ti-30Ni (wt per cent) alloy. Alternatively, the effect of flux composition in the CaF2-MgCl2 flux on the oxygen content was also investigated at 1623 K. Therefore, the effect of binary flux systems on the deoxidation ability was compared at 1623 K. According to the results, the flux system with 80 per centCaF2– 20 per centMgCl2 exhibited the best deoxidation capability, ie total oxygen content in the alloy reduced from 1450 to 550 ppm.

Aug 21, 2024

By J Zhang, O Ostrovski, C Zhang D Cai, Q Wang

The conventional CaO-SiO2-based mould fluxes are not suitable for high-Al steel casting because of the strong reaction between silica in the flux and aluminium in the steel strand. In the process of casting of high-Al steel, flux composition changes; with the decrease of the silica concentration and increase of alumina. Knowledge and understanding of the effect of the Al2O3/SiO2 ratio on flux structure and properties are useful for flux design for the high Al-steel continuous casting. This paper investigated the effect of the Al2O3/SiO2 ratio on structure, viscosity, phase composition of fluxes quenched at different temperatures and heat transfer of CaO-Al2O3-SiO2-B2O3-Na2O-Li2OMgO- F fluxes. It was found that flux melting temperature increased with the increase in Al2O3/SiO2 ratio. Viscosity of the flux melts increased significantly with the increase of the Al2O3/SiO2 ratio from 0.7 to 1.2, reaching the maximum value, and then decreased with further increase of the Al2O3/SiO2 ratio. Raman spectroscopy analysis revealed that the change of the Al2O3/SiO2 ratio led to the change of aluminate and silicate structural units. The turning point for viscosity was attributed to the change in the degree of flux polymerisation. X-ray diffraction (XRD) analysis showed that increasing Al2O3/SiO2 ratio increased crystallisation tendency of the fluxes. Heat transfer measurement by infrared emitter technique (IET) revealed that increasing Al2O3/SiO2 ratio led to the decrease in heat flux which is correlated well with the increased crystallinity of the flux. The results suggested that the flux with Al2O3/SiO2 ratio 4.3 is the best candidate among the studied CaO-Al2O3-based mould fluxes for casting of high-Al steel.

Aug 21, 2024

By E Jak, M Shevchenko, D Shishin

One of the key aspects to develop sustainable metallurgical production is to ensure that the predictive power of thermodynamic tools is brought up to a new level of accuracy and reliability. Exploring new polymetallic processes, integrating primary and recycled materials, means utilising the uncharted areas within the Cu-Pb-Zn-Fe-Ca-Al-Mg-Si-O (major) – Cr-Na (slagging) – As-Sn-Sb- Bi-Ag-Au-Ni-Co (minor) slag-solids-metal-matte-speiss-sulfate system. This requires extensive integrated experimental and thermodynamic modelling study, which is underway at PyroSearch at the University of Queensland (UQ).

Aug 21, 2024

By G Tranell, E Pastor-Vallés, A Vallejo-Olivares, J B. Pettersen

Metals are essential for the sustainability transition and decarbonisation of society. Yet, it will be paramount to produce them sustainably and minimise the affiliated resource and energy use and the associated emissions. In the circular economy, the metallurgical industry should recycle existing material stocks, and improve its utilisation of wastes, residues and side streams. This increases the complexity of processes, as they become both (often multi-fraction) waste treatment as well as material production processes and brings complexity to the assessment of environmental benefits. Assessing the environmental impact of technological developments frequently is supported by life cycle assessment (LCA). While the method is well documented, its implementation involves several methodological choices that deserve reasoning and analysis, such as how to define the product when former wastes are turned into new products, the selection of impact methodology when converting emissions to environmental indicators, the definition of system boundaries and co-product allocation and the interpretation of sensitivity and uncertainty in final outcomes. In this exploratory study, we investigate how the variation of LCA set-up affects the environmental burden of the system. We consider a metallurgical process where a mix of hard-to-recycle aluminium-containing streams is used to produce aluminium cast alloys in a rotary furnace. Remelting with salt-fluxes allows recovering metals from partly oxidised/contaminated streams, such as dross, bottom ash and industrial shavings, but at the expense of generating significant amounts of salt-slag/salt-cake hazardous waste. The study considers different system alternatives such as landfilling the salt-slag residues versus valourising them into salts, aluminium concentrates, ammonium sulfate and non-metallic-compounds to be used by the metallurgical, construction or chemical industries. Practical recommendations are outlined to facilitate the implementation of LCA in assessing the potential benefits of the circular economy in the metallurgical sector.

Aug 21, 2024

By M K. Nahian, R G. Reddy

The thermodynamic model for species distribution in aluminium chloride (AlCl3) and 1-butyl-3- methylimidazolium chloride (BMIC) system was developed. The experimental thermodynamic data, considering a range of aluminium chloride species, such as AlCl4-, Al2Cl7-, Al3Cl10-, Al4Cl13-, and Al2Cl6 were used in developing the model. When the XAlCl3 was in the range of 0 to 0.50, only anion species Cl- and AlCl4- were existing in the solution. As the XAlCl3 value increased more than 0.50, the available anions were Al2Cl7-, Al3Cl10-, Al4Cl13-, and Al2Cl6. Specifically, the concentration of Al2Cl7- increased in the composition range from 0.50 to 0.67 XAlCl3, after which it decreased. This change in the concentration of Al2Cl7- was due to its reaction with excess AlCl3, leading to the formation of Al3Cl10-. The average cathode current density was determined by the electrochemical experiments varying XAlCl3 from 0.50 to 0.71 in the AlCl3:BMIC solutions. The average cathode current density increased as the XAlCl3 increased from 0.50 to 0.67. However, it decreased when the XAlCl3 > 0.67. This trend can be attributed to the electroactive species Al2Cl7-. The Al2Cl7- promotes the reduction rate at the cathode, resulting in an increase in the average cathode current density.

Aug 21, 2024

By J H. Zietsman

The transition to more sustainable metal production is receiving much attention at present, and the iron and steel industry is at the centre of the conversation. New, more environmentally friendly production technologies, such as direct reduced iron (DRI) smelting furnaces, need to be developed in a short period of time. This necessitates increased use of computational modelling that incorporates more accurate material descriptions. The combination of large-scale multiphysics models of high-temperature processes with CALPHAD material descriptions leads to infeasible computation times. This can be resolved with the previously reported RapidThermo framework, which has been demonstrated to make equilibrium calculations orders of magnitude faster, within controllable limits of accuracy. In this paper, we explain how further material properties, which are important to modelling hightemperature reactors, can be added to the RapidThermo framework. This can improve the accuracy and usefulness of process and multiphysics models in the development of new technologies, which can significantly accelerate development cycles.

Aug 21, 2024

By A. Drumond, J. F. C. L. Costa, M. G. Lemos, A. L. Rodrigues, F. G. Niquini

The past decade has seen a renewed possibility of using machine learning algorithms to solve a large collection of problems in several fields. Data acquisition for mining operations has increased with the growth in sensor-based technologies, and therefore the amount of information available for mining applications has dramatically increased. Ore sorting equipment is available for separating ore from waste based on differences in physical properties detected by a real-time analyser. The separation efficiency depends on the contrast in these properties. In this study we investigate the application of machine learning models trained using data from the output of a dual-energy X-ray ore sorting apparatus at a gold mine. The particles were first hand-sorted into ore and gangue classes based on their mineralogical composition. Classification models were then used to help decide the balance between the number of true and false positives for ore in the concentrate, with a view to economic parameters, using their receiver operator characteristic (ROC) curves. The results showed AUC (area under the ROC curve) scores of up to 0.85 for the classification models and a maximum reward condition Fpr/Tpr around 0.5/0.9 for a simplified economic model.

Aug 8, 2024

By T. Marin, J. E. Seccatore, M. Cardu

The most energy-intensive process in the mining industry is particle size reduction – comminution. The first phase of this process is blasting to fragment the rock from the initial Boussinesq’s halfspace size. Scientific literature demonstrates that the output of a blast in terms of fragment size distribution can be manipulated by varying the specific charge (powder factor) and charge distribution. This study focuses on the influence of blasting on the internal resistance of the blasted fragments; in particular the influence of the spatial distribution of charges. Small-scale blasts were performed on 14 marble blocks using different powder factors and charge distributions. Three control blocks were fragmented by mechanical means for comparison. The results show the correlations between charge distributions and the specific energy of mechanical comminution. Opportunities for adjusting charge diameter and distribution in opencast blasts to improve the performancet of comminution circuits are discussed.

Aug 8, 2024

By K. Dagdelen , S. K. A. Owusu

Uncertainty with regard to estimated grades and tonnages of a mineral deposit demands risk assessment in order to build investor confidence and attract the interest of other stakeholders in the success of a project. Uncertainties associated with Mineral Resource estimates can lead to unreliable production schedules and unpredictable cash flows. However, the techniques used in the mining industry to determine these uncertainties are inconsistent, because the important decisions taken in the process are solely dependent on the responsible Competent Person (CP), without limitations. This leads to disparities between different CPs’ results, using data-sets from the same drill-holes. The various standard codes for public disclosure provide guidelines and recommendations for the classification of Mineral Resources and Reserves but do not provide details on, for example, the amount of geological and geostatistical information needed to qualify for each category of Resources and Reserves. The parameters used to generate the classification categories are subjectively assumed by the responsible CP. In this paper we investigate the impacts of different CPs’ judgements on resource classification, using the same data-sets. The results underpin the need for the mining industry to develop a uniform Mineral Resources and Reserves classification framework that can minimize or avoid significant discrepancies that lead to potential misleading public disclosures.

Aug 8, 2024

By F. T. Cawood, C. C. Birc

The South African mineral resource royalty system, initiated in 2010, employs a hybrid ad valorem approach tied to profitability ratios. This rate is then applied to the total revenue from mineral sales. In this article we explore how the profitability ratio in the mineral resource royalty formulae interacts with the gold tax formula as applied to South African gold mines, devising a strategy for cut-off grade optimization. The study focuses on nine narrow, tabular-reef (Witwatersrand) gold mines. The approach involves a mixed-integer cut-off grade optimizer utilizing Excel Solver, incorporating relevant royalty and income tax formulae. Different mineral resource royalty cost scenarios were examined. Ignoring these costs in the break-even analysis lowers the cut-off grade but slightly boosts profits compared to considering expected costs. The developed optimizer model, recognizing the profitability aspect of the mineral resource royalty and income tax formulae, yielded a 6% lower cut-off grade than the base case. This is significant for increasing mine life. While the profit differences are marginal (0.2% compared to the break-even base case), substantial improvements were noted: a 6% increase in stope tons above cut-off grade, and a 4% rise in total revenue. Enhanced resource utilization (3% extra gold kilograms) reduces necessary development and overall costs, allowing for a reduction in the cut-off grade and ultimately, more profit.

Aug 8, 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 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 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 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