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By L. Zhou, J. Qiu, M. Tang, J. Wang, G. Dai

Coal spontaneous combustion in longwall gobs is a major concern in coal mines. In comparison to other hazards, this phenomenon is difficult to detect. Fifteen factors influencing coal spontaneous combustion in longwall gobs were identified from the literature. The logical relationships between these factors were evaluated and quantified by decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modelling (ISM) methods. A four-level hierarchical structure model was established. The research shows that combining DEMATEL and ISM can reveal the key factors that influence coal spontaneous combustion in longwall gobs and establishthe interactions and relationships among these factors. The results can provide the basis for preventing and controlling coal spontaneous combustion in longwall gobs.

Jun 10, 2024

By R. MacRosty, R. Pula, P. Gebski, W. Braun

"This paper provides a progress update on three tapblock monitoring technologies that Hatch has been developing with our clients for non-ferrous smelting furnaces.The Tapblock Diagnostic System (TDS) is an advanced on-line monitoring system that uses temperature data along with embedded thermal model results to evaluate the condition of a tapblock over its campaign life. Hatch recently installed a second Tapblock Diagnostic System, some details of which are provided in this paper.The Tap-hole Acoustic Monitoring (TAM) system is installed on water-cooled copper tapblocks and uses the noise from the tapping channel to provide a qualitative indication of wear and deterioration of the tapping channel refractory. In addition, TAM can be used to monitor drilling and lancing performance, and potentially could also be used in the future as a guide for automatic drilling and lancing systems (Sadri et al., 2008).The third technology is the use of fibre optic sensors to measure temperature on the hot face and in the tapping channel of a tapblock. Fibre optic technology allows installation of numerous sensors in key locations where they are very sensitive to tapblock condition and also provide more extensive spatial coverage than is possible with traditional instruments. This paper provides an update on our efforts to address issues with premature failure of the sensor cables due to corrosion, and also converting the vast amount of data from the sensor cable into information that can be used by furnace operators."

Jan 1, 2014

By G. P. O’Malley, A. N. Nikoloski

One of the most promising options for extraction of copper from low-grade chalcopyrite ores by heap leaching, however, chalcopyrite is refractory and suffers slow leaching kinetics and poor overall extraction due to formation of a passivation layer on the particles. The solution composition is believed to strongly affect the formation of this layer. This paper examines the effects of the major cationic species of Fe3+/2+, Mg2+, Cu2+, and Al3+ and the anionic SO42− species in acidic ferric sulfate media with a composition simulating recycle heap leach conditions. It was found that altering the sulfate, iron or aluminium concentration had significant effect on the copper extraction, the concentration of copper slightly influenced the extraction, and the amount of magnesium had no appreciable effect. Also, iron and aluminium caused a change in the sulfate concentration, and the sulfate ions had the greatest influence on the extraction of copper under recycle leach conditions

Jan 1, 2023

By B. Genc, C. Gous

Spontaneous combustion during coal mining operations is a major problem that affects the health and safety of workers and causes environmental problems. The phenomenon is associated with the presence of coal, coal shale, and pyrite. In 2020, a premature detonation incident occurred at an iron ore mine where the waste material contains black carbonaceous shale units known to be associated with pyrite. The spontaneous combustion propensity and properties of samples of the black carbonaceous shales from the mine were examined and compared with samples from the Witbank Coalfield. The spontaneous combustion liability indexes of these samples were correlated with X-ray fluorescence (XRF) and proximate and ultimate analyses using linear regression. The Wits-Ehac Index classification results show that the samples were between medium and high risk. The linear regression analysis showed very poor correlations between the Wits-Ehac Index results and the XRF and proximate and ultimate results. The most valuable relationship found is between the presence of relatively high sulphur (greater than 3%) and ground reactivity with nitrate-bearing explosive emulsion.

Jun 5, 2023

By P. Linzer, L. M. Linzer

The gravity method is often applied in mining-related scenarios such as geological and mineral exploration, detecting subsurface cavities and voids (“receptacles”) that may become sinkholes, siting of surface structures, fault-mapping, and more. It is also widely applied in geotechnical engineering to map subsurface karst profiles and to detect subsurface cavities, such as can occur in open pit mines. While it is widely acknowledged that, compared with other available geophysical methods, this method is the most applicable to the karst profiling problem, survey geometries applied in the field are often far from optimal. The gravity surveying specifications prescribed in SANS 1936 omit some key requirements for optimal survey outcomes, and this paper is intended to fill those gaps. The authors have seen scopes of work that require only a few measurements over the footprint of a proposed structure, indicating a lack of understanding of the nature of the gravitational field. A single gravity measurement is subject to the camouflaging effects of several influences, many of which can be larger than the anomaly caused by the subsurface density variation itself. Papers in the body of literature show an awareness of the need to map the regional field so that it can be subtracted to unmask the residual gravity anomaly, but rarely do they examine how instrument sensitivity governs the size of detectable anomalies or discuss how a detailed terrain correction can be instrumental for isolating faint targets. This paper aims to explain how to apply the gravity method correctly to mining and geotechnical problems, specifically in the detection of subsurface cavities. It discusses various factors to assist with optimising the acquisition of gravity data and its processing so as to maximise the practical value of gravity surveys.

Sep 1, 2025

By J. P. T. Kapusta

"The copper smelting industry faces increasingly stringent environmental regulations and must continue driving innovation to reduce energy usage in its production chain. With the coming of age of ‘bottom-blowing’ copper technologies in China over the last decade, much renewed attention has been brought to tuyere bath smelting for clean copper-making. Since bottom-blowing sonic injection was originally developed and implemented in steelmaking in the 1970s and lead smelting in the 1990s, the time seems appropriate to revisit the sonic injection concepts and dispel some myths. After reviewing the trends in the copper industry and providing a brief historical context of research and development related to sonic injection, the author presents a comparison of the main submerged tuyere bath smelting technologies, namely the Noranda Reactor (NR), the Teniente Converter (TC), and the Chinese Bottom-Blowing Smelting Furnace (SKS/BBS) for copper, and the Queneau-Schuhmann-Lurgi Reactor (QSL) for lead. The core of this article, however, consists of a brief description of the fundamental theories for sonic injection (jetting regime) and ‘sonic flow mapping’ to illustrate the relationship between the minimum tuyere back-pressure required to achieve sonic flow and the tuyere internal diameter. The article also offers a comparison between side- and bottom-blowing in jetting regime before concluding with the author’s vision of the new trend in submerged tuyere bath smelting. IntroductionIn the last decade, developments in the copper smelting industry have been driven by two key concepts: (1) increasing cleaner smelting capacity to meet the world’s growing copper demand, as illustrated in Figure 1, and (2) increasing process off-gas capture to comply with more stringent environmental regulations and abide by a corporate social responsibility ethic of a clean work environment (for smelter employees) and clean air (for families living around smelters). The copper smelting industry has also faced some major challenges in the last few decades, including (1) low treatment and refining charges (TC/RC or processing fees) impacting custom smelters, (2) lower concentrate quality and grades with higher levels of impurities (e.g. As and Hg), (3) higher processing and transportation costs due to the rising cost of energy, (4) restrictions in process intensification (tonnage oxygen usage) due to furnace integrity limits, and (5) scarcity of educated and trained personnel due to fewer metallurgists graduating from pyrometallurgical school programmes combined with a high retirement rate of skilled workers."

Nov 1, 2018

By S. Swanepoel, A. V. Cherkaev, Q. G. Reynolds, M. Erwee

Ferrochrome (FeCr) is a vital ingredient in stainless steel production and is commonly produced by smelting chromite ores in submerged arc furnaces. Silicon (Si) is a componrnt of the FeCr alloy from the smelting process. Being both a contaminant and an indicator of the state of the process, its content needs to be kept within a narrow range. The complex chemistry of the smelting process and interactions between various factors make Si prediction by fundamental models infeasible. A data-driven approach offers an alternative by formulating the model based on historical data. This paper presents a systematic development of a data-driven model for predicting Si content. The model includes dimensionality reduction, regularized linear regression, and a boosting method to reduce the variability of the linear model residuals. It shows a good performance on testing data (R2 = 0.63). The most significant predictors, as determined by linear model analysis and permutation testing, are previous Si content, carbon and titanium in the alloy, calcium oxide in the slag, resistance between electrodes, and electrode slips. Further analysis using thermodynamic data and models, links these predictors to electrode control and slag chemistry. This analysis lays the foundation for implementing Si content control on a ferrochrome smelter.

Mar 14, 2024

By J. W. van der Merwe, K. G. Moloko

Furnace wall tubes from 600 MW subcritical boilers at three coal-fired power stations were sampled and the fireside deposits examined to determine the mechanism of fireside corrosion. This involved an indepth investigation into the morphology and composition of the fireside deposits and the conditions of the furnace that enable this type of attack. SEM-EDS analysis revealed high concentrations of oxygen, iron, and sulphur, QEMSCAN and XRD analyses identified the presence of Fe3O4, Fe2O3, FeS, and FeS2. Differential thermal analysis showed thermal activities at temperatures of 500–600°C, 900–1100°C, and 1100–1250°C, which are associated, respectively, with FeS2 oxidation to FeS and Fe2O3, at 475–525°C, formation of aluminosilicates at 925–1100°C, and melting of FeS around 1190°C. The absence of sodium and potassium eliminates the contribution of molten alkali sulphates to the corrosion. The consistent coexistence of iron sulphide and iron oxide is indicative of the substoichiometric conditions in the furnace, while the detection of pyrite suggests that the coal is not completely combusted, which points to a poor combustion process. These observations were affirmed by gas analysis at one of the stations, where very high levels of carbon monoxide were measured at the furnace wall (≥ 14 000 ppm) and furnace exit (≥ 3500 ppm). The high CO concentrations are indicative of limited combustion caused by limited O2. These reducing conditions promote the formation of FeS-rich deposit, which is the corrosive species responsible for degradation.

Jun 1, 2021

By S. J. van Wyk, A. S. H. Haagner

Land rehabilitation transcends the mere establishment of vegetation across disturbed landscapes; it should be conceptualised as a specialised ecological reconstruction process. This process necessitates a long-term perspective on the success of land repurposing. It requires a continuum of inputs specified and managed by a dedicated and qualified custodian to ensure the sustained economic viability and ecological sustainability of the land. Based on the authors’ combined experience and field observations over more than five decades, they advocate for an urgent shift away from traditional land rehabilitation practices toward a paradigm centred on land capability reconstruction and active stewardship. The prevailing rehabilitation culture has overly simplified the process to a mere revegetation exercise, which is fundamentally incompatible with the comprehensive requirements for sustainable land capability. While the regulatory framework provides valuable guidance for obtaining a mine’s social license to operate, a paradigm reset is essential. Mining companies must prioritise rehabilitation quality, set achievable sustainability goals, and establish clear pathways and milestones to meet relinquishment criteria. Currently, the status quo view—a model reliant on outsourced contracting and agricultural approaches—is that mine rehabilitation is a one-time intervention rather than a complex, systemic, and long-term process. This perspective presents significant challenges, as the success of ecological interventions can only be accurately assessed over extended timeframes, often spanning decades. Shortsighted rehabilitation specifications, coupled with practitioners operating within agricultural decision frameworks, frequently overlook the necessity for integrated rehabilitation expertise and the scientific foundation essential for designing and implementing effective ecological outcomes. A lack of long-term monitoring information impedes the required adaptive management of rehabilitated systems and, therefore, delays the transition towards final land use. This short approach costs the mining industry millions annually, often without recognising the inadequacies in long-term liability mitigation and the substandard ecological success achieved. The disconnect between procurement processes, the qualifications of service providers, and the unclear pathways to relinquishment can impede successful rehabilitation outcomes, frequently undermining progress toward sustainability milestones. Unless there is a fundamental reset of the land rehabilitation culture, pursuing sustainability will remain an elusive and perhaps impossible objective. Consequently, mining companies may hesitate to fully commit to sustainable land rehabilitation practices, as the prospects for relinquishment and final closure remain uncertain at best.

Apr 25, 2025

By J. van der Walt, W. Spiteri

Flyrock remains a significant threat to the health and safety of mine employees and integrity of infrastructure, as well as to the safety of the neighbouring communities and their property. This investigation was motivated by the general lack of fundamental research and mathematically quantifiable data in the literature regarding the relationship between blast design parameters and their impact on flyrock. The focus was to develop a concept that can be used to mathematically quantify the trajectory of flyrock resulting from a blast, which can be used for future research. The ultimate goal for this technique, once it has been fully developed, is to: ➤ Enable mining operations to generate a database with accurate historical flyrock measurements resulting from their blasting operations ➤ Allow research teams to conduct scientific investigations into flyrock and the impact of various blast design parameters ➤ Generate point-cloud data to visualize blasts and flyrock in a virtual reality environment for training and education purposes. This paper summarizes a conceptual technique and preliminary fieldwork that was carried out to determine the technique’s feasibility and motivate further development. The results show conclusively that a modified photogrammetric technique is capable of capturing flyrock data for further processing and analysis. The data acquisition procedure can, at this point, be used to meet the first aim of the project, namely to gather a field database of historical flyrock generation. Further development of the technique is ongoing and it is envisioned that the scientific-based technique will provide a method whereby future flyrock studies will be comparable and that assumptions will be limited.

Apr 5, 2023

By H. Dudycz, A. Skoczylas, P. Stefaniak, P. Pyda

In the era of Industry 4.0, technologies such as Big Data (BD) and the Internet of Things (IoT) play a key role, especially for multi-site manufacturing companies. In such companies, the challenge is to collect and process massive amounts of data from industrial devices and extract key information from this data in real-time for ad hoc decision-making. The ability to analyse data from industrial devices translates directly into streamlined production processes, cost optimisation, prevention of unplanned events, and safety during operation. In this context, particular attention should be paid to Big Data Analytics (BDA), whose main source is the Industrial Internet of Things (IIoT). The purpose of this paper is to propose an IT system architecture incorporating BD and the IoT for a mining company. The paper presents results from a literature review focusing on available BD and the IoT solutions for industry (mining in particular) for the purposes of the acquisition, integration, and advanced analysis of data. The advantages and disadvantages of the different solutions were indicated and gaps in the accessibility to dedicated functionality are identified. Based on the analysis of a multi-site mining company, the main challenges faced by such companies planning to implement BD and IoT solutions are identified. Also, a proposal for an IT system architecture incorporating BD and IoT for a mining company is described in the paper. The contribution of the article consists of the identification of the challenges faced by mining companies planning to implement BD and the IoT solutions, and the proposal of an IT system architecture that allows BDA whose main source is the IIoT.

Sep 1, 2021

By H. Manurung, I. M. Bendiayasa, W. Astuti, and H. T. B. M. Petrus, F Anggara, K. C. Wanta

The leaching kinetics of cerium (Ce) and yttrium (Y) in sodium-hydroxide-digested non-magnetic coal fly ash using acetic acid were investigated. The variables analysed were pH, solid-to-liquid ratio (S/L), and temperature. The results show that cerium and yttrium's maximum recovery was 57.33% and 58.36%, respectively, under leaching temperature of 90°C for Ce and 60°C for Y at pH of 1,74 and 10 g/mL solid-liquid ratio in 240 minutes. Increasing the leaching time to more than 120 minutes did not significantly improve the results. After the magnetic separation process, the ICP-OES analysis shows a slight increase in the concentration of cerium and yttrium on nonmagnetic components. The XRD and ICP-OES analysis for the sample before and after silicate digestion shows that 40% silicate was dissolved. The calculation of apparent activation energies of leaching using the Arrhenius law for the leaching of cerium and yttrium gives 22.72 kJ/mol and 35.84 kJ/mol, respectively. The kinetic leaching model of cerium and yttrium all fit Dickinson's new shrinking core model. The calculation results show that the leaching reaction is controlled by combining interface transfer and diffusion across the product layer.

Nov 6, 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 M. A. Mahboob, T. Celik, B. Genc, I. Atif, S. Ali

"Mapping of hydrothermally altered areas, which are usually associated with mineralization, is essential in mineral exploration. In this research, open source reflectance spectroscopy data from the multispectral moderate-resolution Landsat 8 satellite was used to map altered rocks in the Gauteng and Mpumalanga provinces of South Africa. The unique spectral reflectance and absorption characteristics of remotely sensed Landsat data in the visible, near-infrared (NIR), shortwave-infrared (SWIR) and thermal infrared (TIR) regions of the electromagnetic spectrum were used in different digital image processing techniques. The band ratios (red/blue, SWIR 2/NIR, SWIR 1/NIR), spectral band combinations (Kaufmann ratio, Sabins ratio) and principal component analysis (Crosta technique) were applied to efficiently and successfully map hydrothermal alteration minerals. The results showed that the combination of spectral bands and the principal component analysis method is effective in delineating mineral alteration through remotely sensed satellite data. The validation of results by using the published mineral maps of the Council for Geoscience South Africa showed a good relationship with the identified zones of mineralization. The methodology developed in this study is cost-effective and time-saving, and can be applied to inaccessible and/or new areas with limited ground-based knowledge to obtain reliable and up-to-date mineral information.IntroductionMany developing nations depend on exploration and exploitation of mineral resources to sustain their economic growth. Usually, the traditional mineral exploration techniques require enormous finances, prolonged time, and tremendous manpower, particularly in areas that are not easily reachable (Maduaka, 2014). Furthermore, mineral exploration required state-of-the-art techniques and expertise along with geological, geochemical, and geophysical datasets, which may not be easily available or may be lacking where access is problematic (Kaiser et al., 2002; Bemis et al., 2014). Modern remote sensing technology has proved to be one of the highly efficient and robust techniques used for mineral exploration. The use of remote sensing satellite images for geological mapping and mineral exploration usually involves studying the physicochemical properties of rocks and weathering soils, such as mineralogy, landforms, geochemical signatures, and the spatiall distribution of lineaments (Bhattacharya et al., 2012)."

Mar 1, 2019

By E. Y. Baafi, H. Fan, W. Zeng

We present a discrete event simulator, TSJSim (Truck-Shovel JaamSim Simulator), for evaluating the stochastic and dynamic operational variables in a truck-shovel system. TSJSim offers four truck allocation strategies: Fixed truck assignment (FTA), Minimizing shovel production requirement (MSPR), Minimizing truck waiting time (MTWT), and Minimizing truck semi-cycle time (MTSCT) including the genetic algorithm (GA) optimization and the frozen dispatching algorithm (FDA) optimization rules. Multiple decision points along the haul routes for all the trucks close to the decision points were included in the model. The simulation results indicate that the trends associated with production tons and queuing time utilizing the four truck allocation strategies (MSPR, MTWT, FDA, and GA) all demonstrated similar patterns as the fleet size varied. As the system fleet size increased, the system production tons under these strategies at first increased significantly and then remained relatively constant; the queuing time relating to these strategies showed a positive relationship with the system fleet size. The bunching time decreased when the truck allocation strategies were applied in the model. In the simulated truck-shovel network system with multiple traffic intersections, by assigning the trucks at the intersections, both productivity and fleet utilization increased.

Dec 13, 2022

By B. Maybee, J. Venter, J. Wesseloo

The selection of open-pit slope angles involves high-value decisions with small changes in slope angle, often representing significant changes in net present value. The existing methods used to define design acceptance criteria have evolved from factor of safety to probability of failure (P[F]) to risk consequence to risk frontiers, which represents current state of the art. Current design acceptance measures are based on references to published tables representing the experience and judgement of their authors, who did not specify the purpose of the measures contained therein. As the purpose of the published design acceptance criteria is not specified (i.e., definite stability, marginal stability, optimization, etc.), such tables cannot be used to achieve optimum slope angles that maximize profitability. This paper develops a design acceptance criterion that maximizes profitability by defining a formulation for optimum risk that balances expected risk and reward. The model developed is titled the Mining Risk Model (MRM), and is applied to open-pit slope angle selection through an equation for optimum probability of downside (P[D]O) that balances the upside or opportunity, the P[F], and the downside impact. This formulation for optimum risk is unique, as many authors have presented objective functions for their risk models that can be optimized, but none of the sources reviewed contained a formulation for optimum risk. The MRM is sufficiently flexible to allow the design performance measure that drives P[F], and hence P[D]O, to be selected based on the intended goal. Furthermore, the essential information that must be known to quantify optimum risk is defined. This allows users to determine what information to collect for optimum risk decisions. A further benefit of the MRM is that slope angle decisions and pit shells can be ranked to select the best option, and a threshold is provided that separates acceptable from unacceptable decisions. Finally, the workflow and information required to determine optimum risk are presented.

Sep 9, 2024