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By M. Wrobel, J. Hammerschmidt, M. Runkel

Fluid-bed technology is a key pyrometallurgical step for processing a vast number of ores and concentrates. Over the past 50 years, considerable research and development efforts have been made by Metso Outotec to expand the application window of this technology. This paper illustrates different processing routes where fluid-bed technology plays an important role in the production of the copper. The fluid-bed processes utilized are partial, sulfate-producing, and dead roasting. The focus of this paper considers the advantages of the dead-roasting process. This “zero waste” process can provide copper oxides, steam, electrical power, and sulfuric acid for new and existing solvent extraction–electrowinning plants. In a case where an operation is running out of oxidic ores and concentrates, fluid-bed roasting can be applied to close this gap and provide the required copper oxides in a sustainable way.

Jan 1, 2023

By J. de Korte, Z. Loubser

"SynopsisThe aim of a blending stockpile is to minimize the natural variation in properties of a material. Two simulation models were written, for coneshell and chevcon stacking, and used to investigate the influence of different stockpile parameters on blending efficiency. The coneshell model is used to show that blending efficiency is highly sensitive to stacked height, with lower output variances observed for higher capacities. Output variance in both models also decreased when the stacker movement increment was decreased. For chevcon stacking, increasing stacker speed significantly increases the blending efficiencies. Increasing the length of the blending tail also reduces output variation, but this parameter would need to be weighed against the accompanying decrease in buffer capacity.IntroductionEven in the most uniform deposit of materials in nature, material properties will vary. The degree of variation can be measured, and usually resembles a normal distribution. The aim of blending and homogenization operations is to minimize the standard deviation of this normal distribution (De Wet, 1994). In general, the reduction in variation will result in a more efficient and cost-effective downstream process. Cement plants need a precise blend of raw materials to ensure desired kiln performance; boilers used in power generation are optimized for fuels of a constant specification; and even though the separation density in a coal washing plant can be adjusted, a constant product quality cannot be produced from highly variable feed (Denny and Harper, 1962). The process efficiency, product quality, and environmental compliance depend on consistency of characteristics in the material fed (Kumral, 2005) Many industries involved in"

Jan 1, 2015

By F. Navarro, F. Soto, G. Díaz, E. Jélvez, G. Morales, N. Morales

The increasing availability of tools on the web provides a great opportunity for the research community to boost investigation by accessing computational resources from all over the world. For example, data analytics libraries implemented in languages like Python can be accessed through many open and commercial platforms, therefore providing researchers with a common set of tools or shared datasets. Unfortunately, that is not the case with research in resource assessment and mine planning, where the most standardised tools are commercial applications designed to work on the desktop, but there are not many standard platforms for research. As a result, researchers from different groups often need to start from scratch in order to develop their work, and rarely share implementations details. Similarly, apart from a few publicly available examples, there is a lack of common datasets that are validated and can be used to compare results between different approaches. In this paper, we introduce a platform that provides tools for resource assessment and mine planning, which can be accessed remotely utilising Jupyter Notebooks. In its current version, the platform provides (i) definition and implementation of basic structures for managing samples and models (loading, saving, adding or removing columns, etc.), (ii) definition of experimental and modelled variograms for spatial continuity analysis, (iii) definition of standard interpolation methods in resource evaluation (inverse distance and kriging), (iv) definition of standard problems in mine planning (ultimate pit and precedence constrained production scheduling), (v) generation of 2D standard graphs like grade distribution, conditional means, tonnage-grade, and production plans (vi) a set of datasets, which can be used for case studies, and (vii) a set of notebooks with examples and documentation. In this paper, we introduce the platform and show some examples that illustrate some of the possibilities that it has for research and education in the area of resource assessment and mine planning.

Sep 1, 2021

By Z. Zhang, J. Niu, H. Wang, Y. Xu, J. Shi

Tribo-electrostatic separation is a promising method for effectively utiliing low-grade magnesite resources by removing quartz and improving the grade of magnesite. To determine the chargeto- mass ratios of pure magnesite and quartz, a triboelectric measurement system was employed, and a laboratory tribo-electrostatic separation system was used to separate low-grade magnesite. The results showed that the maximum difference in charge-to-mass ratio between pure magnesite and quartz particles was observed after friction with polyvinyl chloride. The grade and recovery of magnesite increased with temperature and initially increased with increasing voltage, feed rate, and air flowrate before gradually decreasing. The optimal conditions resulted in a concentrate with 46.91% MgO content and 77.36% recovery, while the quartz content decreased from 7.02% to 1.95%. These experimental results demonstrate the effectiveness and potential of tribo-electrostatic separation in removing quartz and upgrading magnesite.

Apr 14, 2024

By T. C. Maswanganyi, G. L. Smith, R. C. A. Minnitt

This paper identifies the strategic gaps and opportunities for the South African mining industry’s contribution towards advancing sustainable development. Mineral resources companies are confronted by a range of complex social performance challenges, which largely manifest in sporadic community and labour unrest, undermining the sustainability and profitability of these companies. Integrating supply chain management, strategic long-term planning and sustainability planning is identified as a strategic gap that can contribute towards the sustainability of mining companies, if effectively implemented. Contributing towards sustainable development by the South African mining industry is not merely a voluntary requirement on the industry but a legal requirement in terms of the Minerals and Petroleum Resources Development Act No. 28 of 2002. This Act is legislation aimed at advancing socioeconomic development in communities that host mining operations and in areas that provide labour to the South African mining industry. In contributing towards the advancement of sustainable development in mining host communities, not only will mining companies fulfil a legal requirement in terms of the Minerals and Petroleum Resources Development Act, but they will also prevent negative social and economic impacts in those communities. This paper identifies innovative and cost-effective ways of advancing sustainable development by integrating strategic supply chain management, strategic long-term planning, and sustainability planning.

Dec 15, 2025

By A. Adeli, A. V. Metcalfe, E. Addo, E. Sepulveda

"The accurate modelling of geometallurgical data can significantly improve decision-making and help optimize mining operations. This case study compares models for predicting copper recovery from three indirect test measurements that are typically available, to avoid the cost of direct measurement of recovery. Geometallurgical data from 930 drill core samples, with an average length of 19 m, from an orebody in South America have been analysed. The data includes copper recovery and the results of three other tests: Bond mill index test; resistance to abrasion and breakage index; and semi-autogenous grinding power index test. A genetic algorithm is used to impute missing data at some locations so as to make use of all 930 samples. The distribution of the variables is modelled with D-vine copula and predictions of copper recovery are compared with those from regressions fitted by ordinary least squares and generalized least squares. The D-vine copula model had the least mean absolute error. IntroductionIn this paper we compare the use of D-vine copula, generalized least squares (GLS), and ordinary least squares (OLS) for modelling geometallurgical data from an orebody in South America. The first objective is to construct models for predicting copper recovery (Rec) from the Bond mill index test (BWi); resistance to abrasion and breakage index (A*b); and semi-autogenous grinding (SAG) power index test (Spi). This involves fitting a D-vine copula and regression models fitted by OLS and GLS. The second objective is to investigate the performance of the fitted models for predicting Rec (Willmott and Matsuura 2005).Traditional resource model approaches either ignore the mineral processing characteristics of extracted tonnages or treat processing as an independent component of a mining operation. The net present value (or any other objective) can be truly optimized only by considering the mining operation as an integrated system in which net value is defined as the end-product that the company sells. This approach requires the resource model to be extended to include all relevant rock properties and processing responses."

Mar 1, 2019

By L. Zhang, Y. Zhou, H. Wang, C. Mo

Fluorination of magnetite (Fe₃O₄) by NH₄HF₂ was investigated using simultaneous thermogravimetry and differential thermal analysis (TG-DTA), and observing the morphology and phase changes using scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDS) and X-ray diffractometry (XRD). The results indicate that fluorination with the involvement of oxygen begins at room temperature, peaks at 178.40C, and is completed at 2000C with the formation of only (NH₄)₃FeF₆. On heating, (NH₄)₃FeF₆ gradually releases NH₄F by the formation of NH₄FeF₄ at 2590C, then (NH₄)0.18FeF₃ at 3270C, and finally FeF₃ with minor FeF₂ at 4000C due to the partial reduction of Fe (III) to Fe (II). At 5500C, FeF₃ is oxidized to FeOF/Fe₂O₃.

Dec 13, 2022

By S. Sekhar, S. Bhargava, A. K. Godugu, J. L. Porathur

Cemented backfilling has enabled underground hard rock mines to extract orebodies more safely with improved ore recovery. It is important to estimate the minimum required strength parameters for a backfill mix by optimizing the binder percentage to enable cost-effective and safe stoping operations. We conducted three-dimensional numerical modelling to study the effect of various stoping parameters on the stability of a free-standing backfill wall. A Mohr-Coulomb material model was used for the backfill material and the rock-fill interface. A strength reduction technique, excluding friction angle, was employed to arrive at a minimum stable strength value for the backfill. For a given combination of strength values, the stability state of the backfill wall could be demarcated using a displacement and yield zone tracking method. The numerical modelling results are compared to some earlier theoretical models. From the simulations, a predictive equation is developed to predict the required strength parameters for a backfill mix to ensure a stable free-standing wall. Examples are given of the successful use of the predictive equation at some underground hard rock mine sites in India.

May 2, 2022

By A. Doroudgar, H. Noferesti

Unstable rock failure or rock bursting is one of the most dangerous problems in deep hard rock mines. This type of failure, that occurs uncontrollably, is associated with a significant release of strain energy from the surrounding rock. In this study, the numerical simulation of unstable rock failure was carried out using the three-dimensional explicit Lagranian finite-volume finite difference method to identify the onset and location of unstable failure events in the model. On this basis, a numerical simulation of mine pillars with width-to-height ratios of 0.5, 2 and 3 was performed. A criterion was developed, based on the calculation of the elastic strain energy, to determine the prone areas for the initiation of rockburst in the models. The results of this study showed that, in softer loading systems, due to large amounts of stored elastic strain energy, an unstable equilibrium is established, which leads to the rapid transfer of strain energy to the rock in the form of violent failure. It was also found that the unstable failure starts at the corners and free surface of the model. The new criterion developed in this study may help predict the occurrence of rockbursts in slender pillars and the design of pillars to control human and financial losses caused by this phenomenon.

Nov 27, 2024

By F. Hörtkorn, Y. Narainsamy

Rather quietly, a new generation of European norms dealing with earthworks has been developed over the past few years, in particular a part of EN 16907 pertaining to extractive waste. Whereas the majority of the parts deal with routine geotechnical aspects, one part deals specifically with tailings dams. The standard is currently in draft form but if this becomes a European Standard, members of the European Union are bound to comply with the regulations. As such, the standard has the capacity to influence mining in Europe and potentially in South Africa. In this paper we review the standard and compare it to the South African standard on mine residues and the recently published Global Industry Standard on Tailings Management (GISTM). We conclude found that although the European norm makes great strides towards increasing tailings dam safety, there is room for improvement. The current South African standard has served well since its inception, but can be improved by using concepts from the European and global tailings standards.

Jun 2, 2022

By V. Miguel-Silva, B. C. Afonseca

Drill-hole spacing analysis (DHSA) and optimization are becoming commonplace for uncertainty assessment and management in the mining industry. However, there is no standardized DHSA workflow, and the outputs of certain methodologies are not interchangeable. We group available simulation-based DHSA methods according to their accounted uncertainty into (i) raw uncertainty, assessed by drawing realizations from synthetic data-sets with the drilling spacings to be tested; and (ii) model uncertainty, in which these synthetic data-sets are used to assess the variation between the estimated model and the (unknown) actual value. DHSA workflows available in the literature ignore the differences between both types of uncertainty. Commonly, the DHSA algorithm is chosen without a detailed analysis of its uncertainty output, which may lead to misleading results and suboptimal decisions. While available solutions are based only on assessing raw or model uncertainty, the proposed approach simultaneously analyses both and their relationship for models at different stages of the mine. The integrated analysis results deliver more information to support decision-making than available methods. Principles, practical considerations, and discussions of the advantages of the proposed integrated analysis are presented. The approach is applied to a real gold deposit to illustrate its use.

Jun 2, 2022

By L. Uotinen, M. Rinne, R. Mishra

Underground mining gives rise to geotechnical hazards. A formal geotechnical risk assessment can help to forecast and mitigate these hazards. Frequentist probability methods can be used when the hazard does not have many variables and a lot of data is available. However, often there is not enough data for probability distributions, such as in the case of new projects. The risk assessment is often subjective and qualitative, based on expert judgement. The purpose of this research is to present the use of Bayesian networks (BNs) as an alternative to existing risk assessment methods in underground mines by combining expert knowledge with data as it becomes available. Roof fall frequency forecasting using parameter learning is demonstrated with 1141 sets of roof fall data across 12 coal mines in the USA. The prediction is nearly identical for individual mines, but when multiple mines are evaluated it is difficult to find a single best fit distribution for annual roof fall frequency. The BN approach with TNormal distribution was twice as likely to fit the observed data compared to the Poisson distribution assumed in the past. A hybrid approach using BN combining multiple probability distribution curves from historical data to predict annual roof fall is proposed. The BN models can account for variability for multiple parameters without increasing the complexity of the calculation. BNs can work with varying amounts of data, which makes them a good tool for real-time risk assessment in mines.

Jun 1, 2021

By M. Z. Emad, Y. Majeed, G. Rehman

Massive deposits of rock salt are mined in the Salt Range area of Pakistan. The main export products of rock salt include salt lamps, blocks, and tiles, while local consumption includes the chemical industry and domestic use. The profitable production of salt for value addition depends on the quality, size, and shape of the block. Salt processing for value addition is easier when very few cracks are present in the blocks. The current salt mining practice involves drilling and blasting, which introduces undesired fractures in the material. This paper focuses on the extraction of rock salt blocks by applying conventional cuboidshaped block mining methods used in quarries. The techniques include wedges and feathers, expansion chemicals, and blasting with low-yield explosives. Experimental work involved both laboratory-scale and in-situ field testing. Laboratory experiments assisted with the determination of splitting force, loaddeformation curves, and other rock mechanics parameters. Regression analysis proposes a relationship for the estimation of radial strain from the load in the case of the wedges and feathers method. The splitting force obtained from the laboratory tests was used to confirm the accuracy of the already published empirical relationship. The results of the laboratory as well as in-situ tests showed that the wedges and feathers technique is the most suitable method for mining rock salt blocks of the desired size, shape, while minimizing cracking.

Mar 2, 2022

By R. J. Durrheim, Y. Yabe, M. S. D. Manzi, DSeis team, N. Z. Nkosi, S. B. Mngadi, Jr. H. Ogasawara

On 5 August 2014, the Orkney M5.5 earthquake, the largest in South African gold mining districts, occurred with an unusual strike-slip mechanism at great depth of 4.78 km below the surface. In a rare case, the ML 5.5 earthquake occurred within the area covered by the legacy 2D and 3D reflection seismic data acquired in the 1990s and 2000s for gold exploration and mine development. In addition, the earthquake ML 5.5 rupture plane was recorded and accurately delineated by the underground in-mine seismic network near the source region. The integration of the legacy 2D reflection seismic data and mine seismicity data allowed us to identify a near-vertical structure, striking northnorthwest-south southeast (NNW-SSE). The ICDP-DSeis team drilled three holes (Hole A, Hole B, and Hole C), and two holes (Hole B and Hole C), intersected the upper edges of the ML 5.5 rupture. These holes recovered metasediments, metabasalts, intrusive rocks including dolerite sills and lamprophyre dykes adjacent to the fault zone, and the fault gouge. Late Prof. Tullis Onstott and geomicrobiologists installed a packer in Hole A and successfully recovered saline water and detected gas (~10 MPa). Slip weakening and rupture propagation are significantly influenced by the existence of fault gouges and the production of wear material between two sliding rock surfaces. Using the fault gouge material recovered from Hole C, we conducted friction experiments under dry and room temperature conditions at high slip velocity of ~100 mm/s and normal stress of 2 MPa. The resulting steady-state frictional strength was ~0.66 over a slip weakening distance of ~9.1 m. The steady-state frictional strength was high, which may be caused by large gouge thickness, and the rate of wear generation. As a result, it is proposed that the Moab Khotsong ML 5.5 seismogenic zone is complex and could be controlled by three main processes: a) the complex structural architecture of the seismogenic zone (e.g., intersection of fault, lamprophyre dykes, and dolerite sills); b) the mechanical process induced by tectonic and/or mining related stresses; and c) the mechanical and chemical processes caused by the water and rock interaction.

Jan 12, 2025

By G. Akdogan, M. Tadie, A. Tapfuma

The Southern African region contains abundant gold tailing heaps that are an environmental concern due to dust pollution and chemical contamination of nearby water bodies. Nevertheless, these heaps contain gold with potential to be extracted for financial gain. In this study, the feasibility of extraction of gold from a Witwatersrand gold tailings using glycine was investigated using a two-level full factorial design. Effects of variables such as glycine concentration at levels of 0.5–1.5 M with a solid–liquid ratio of 50–200 g/L were investigated. Although the solid–liquid ratio used in this study was below the industrial norm, it provides a starting point for investigating the applicability of this technology. To enhance the gold extraction, potassium permanganate pretreatment and copper ion addition were adopted. The results revealed that 91.4% gold extraction was achieved after 24 h pre-treatment of the tailings using 2 g/L potassium permanganate followed by subsequent leaching using 1.5 M glycine at pH 12, with 50 g/L solid–liquid ratio and 2 g/L copper ions. Statistically, the solid–liquid ratio and potassium permanganate pre-treatment of the tailings were found to be significant at 95% confidence interval, whilst interactions of copper ions and glycine concentration were significant factors. The work demonstrates that potassium permanganate pre-treatment prior to glycine leaching of low-grade secondary gold resources, such as tailings, can be beneficial. Furthermore, the methodology developed in this work provides an opportunity for further investigation of the recovery of gold hosted in complex mineralogical matrices.

Apr 14, 2024

By A. Mabentsela

A furnace freeze lining is necessary for safety and economic reasons in several smelting operations. The integrity of the freeze lining is put at risk by furnace power imbalances. Although numerous models have been derived to model the growth and depletion of the freeze lining due to power imbalances, no model exists for thermomechanical damage to the freeze lining. This study provides an initial pathway for modelling thermomechanical damage to the freeze lining in an ilmenite smelting furnace using information from the literature and experimental work. A methodology under the framework of continuum damage mechanics is proposed to model mechanical damage to the freeze lining due to phase changes, thermophysical changes, and constrained thermal expansion. Drill cores of solidified slag ingots were used to represent the freeze lining. The modified power law proved to be the best predictor of the softening response of the drill cores. Damage driving parameters were extracted from the raw data, and governing equations of the parameters with respect to temperature were derived for use in a finite element method (FEM) code.

Jan 26, 2023

By A. K. Raji, E. F. Orumwense, M. O. Ojumu

This research paper introduces a novel passive method for ocean mining using an electricpowered robotic subsea dredging crawler designed to operate in various subsea conditions, including unstructured and rough terrain. The electric-powered robotic subsea dredging crawler is equipped with two driving tracks and features a complex assembly of tank tread chain link, tank tread idler wheels, tank tread sprockets, bronze bushings, motor hub, motor mount, and a 12-volt direct current motor. To evaluate the performance of the electric-powered robotic subsea dredging crawler, it was compared with existing ocean hydraulic exploration crawlers, such as MK3 ROST, in terms of drive performance on an inclined ramp with five angles of inclination (0°, 15°, 20°, 25°, 30°). The experiment aimed to determine the maximum velocity, torque, and efficiency of the crawler at different angles of inclination. The collected data were analysed and plotted using Python, and the effect of the electric-powered robotic subsea dredging crawler’s weight on its driving performance was also considered. The results of this study demonstrate a quadratic relationship between driving performance and inclination angle, which can be used to optimise the electric-powered robotic subsea dredging crawler’s performance for future ocean mining robot drive applications.

Oct 2, 2025

By M. Ataei, F. Sereshki, R. N. Masir

Given the inherent risks and disruptions in underground coal mining operations, strengthening the resilience of critical infrastructure has become a vital priority. This paper aims to evaluate the resilience of the underground coal mining environment using historical data and expert judgment. The study serves as a framework for optimising the utilisation of critical infrastructure to minimise operational disturbances. To achieve this, a practical methodology has been developed, incorporating nearly two and a half years of collected operational data, a hierarchical structure, and a systematic approach. Furthermore, a case study is conducted to demonstrate the real-world applicability of the proposed method. Finally, the resilience index isintroduced as a straightforward summation of ranked impact factors, providing a clear metric for resilience assessment.

Dec 15, 2025

By R. J. Quevedo, Y. A. Sari, S. D. McKinnon

The large scale of cave mines leads to many challenges, including operational logistics and geomechanics design. In current practice, pillar stability assessment relies almost exclusively on stress analysis. However, stability is also affected by other factors including those related to operational aspects of the mining method, the effects of which are difficult to account for during the design stages. In this paper we present a case study of the application of a machine learning approach to evaluate the influence of these operational factors on pillar stability at the Chuquicamata underground cave mine in northern Chile. Due to the likely multi-factorial damage process leading to collapses and considering the different pillar conditions, a tree-based machine learning method was used and analysed to improve the understanding of the relative importance of the various contributing factors. Unlike stress analysis methods, it does not require any a priori knowledge of failure mechanisms, nor the calibration of associated controlling parameters. The proposed random forest model predicted pillar collapses with 80% accuracy despite limited samples to model from. The main contributing factors to collapses were found to be related to available pillar volume, cave front geometry, and time under abutment stress conditions. The effects and interactions of such factors were also studied, showing that careful and improved control over operational conditions can significantly reduce the likelihood of pillar collapses. These conclusions could not have been obtained from stress analysis alone, illustrating the complementary nature of conventional stress analysis and machine learning approaches.

Mar 14, 2024

By V. Quezada, Á. Astudillo, L. Valásquez, M. Garcia

Seawater has become a viable alternative for different uses in copper hydrometallurgy. In this paper we review the main physical and chemical characteristics of seawater and how these influence copper production. Reliable data on the use of continental water are reported, and the current use and consumption of seawater in the Chilean mining industry is analysed, indicating the main areas of use and the main problems encountered. Additionally, the influence of the elements in seawaterthat have the most influence on the extractive metallurgy of copper are considered. The Chilean copper mining industry currently consumes approximately 4.1 m3/s of seawater, which corresponds to 25% of the total water used. The use of seawater for the leaching of copper sulphide minerals, such as chalcopyrite, is beneficial because it provides 20 g/L of chloride, thereby improving copper dissolution kinetics.

Jul 5, 2023