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By M. Balamurali, K. M. Seiler

Modelling stockpiles is a key factor of a project’s economics and operation in mining, because not all the mined ores are not able to mill for many reasons. Furthermore, the financial value of the ore in the stockpile needs to be reflected on the balance sheet. Therefore, automatically tracking the boundaries of the stockpile facilitates the mine scheduling engineers to calculate the tonnage of the ore remaining in the stockpile. This paper suggests how the dynamic of stockpile shape changes caused by dumping and reclaiming operations can be inferred using polygon models. The paper also demonstrates how the geometry of stockpiles can be inferred in the absence of reclaimed bucket information, in which case the reclaim polygons are established using the digger’s global positioning system (GPS) positional data at the time of truck loading. This work further compares two polygon models for creating 2D shapes.

Sep 1, 2021

By M. M. Ali, C. Musingwini, R. A. Phillips

The long-term open-pit mine production scheduling problem (OPMPSP) is typically solved in two broad stages. The first stage entails optimisation of the ultimate pit limit, which delimits the economical final pit and maximises the undiscounted value of the deposit. The second stage entails optimisation of the long-term open-pit mine production scheduling, which maximises the discounted value of the deposit. The long-term OPMPSP is a type of an NP-hard problem, such as the travelling salesman problem (TSP), because it is intrinsically complex to solve since it incorporates both hard and soft constraints. Therefore, metaheuristic approaches have been used to find global optimum solutions to the long-term OPMPSP. This paper presents a metaheuristic approach utilising a dual interchange algorithm (DIA) to solve the long-term OPMPSP. The DIA is a parent algorithm which supervises two subservient algorithms, namely, simulated annealing (SA) and Tabu search (TS). The DIA selects the better solution generated in each run from the two algorithms, and simultaneously penalises the algorithm that produced an inferior solution, while rewarding the one that produced a better solution. The DIA was tested on the three-dimensional Arizona Copper Deposit (KD) dataset, which is publicly available for research purposes from the online MineLib repository. It was set to generate net present values (NPVs) in five-minute intervals and the solution improved until it plateaued at about 30 minutes of runtime. The NPVs compared favourably to those obtained on the same KD dataset but obtained over 24-hour runtimes, when solved using simulated annealing and Tabu search algorithms, and the NPV generated from the work of Muñoz (2012) using the modified TopoSort as found on the MineLib repository at the time of this study. Therefore, this paper demonstrates that DIAs can be developed and used to solve the three-dimensional long-term OPMPSP.

Sep 1, 2021

By F. Dinter, S. A. C. Hockaday, Q. G. Reynolds

The thermal decomposition of carbonate minerals as pre-treatment before smelting reduces the energy requirement for smelting. It can also make the combustion of fossil fuels for heating unnecassary. Thermal decomposition may become important in reducing greenhouse gas emissions when producing ferromanganese alloys while simultaneously reducing electrical energy demand during smelting. A kinetic reaction rate model for the thermal decomposition of manganese ores is presented, based on published reaction rate kinetics for the decomposition of manganese oxides and calcium carbonate. The model was validated against thermogravimetric data for two carbonaceous manganese ore samples and one ferruginous manganese ore sample. The reaction rate model shows that carbonate minerals in the manganese ores are decomposed at temperatures above 900 °C while pyrolusite is decomposed at temperatures from 450 °C to 500 °C. Mn2O3 decomposes rapidly at 550 °C. Braunite decomposition at temperatures below 1000 °C was negligible. The presence of organic carbon in the samples led to further reduction of the samples during thermal treatment.

Aug 3, 2023

By R. H. Matjie, J. R. Bunt, A. C. Collins, J. C. van Dyk, C. A. Strydom

South African discard coal fines and K₂CO₃ blends were heated in a laboratory-scale rotary kiln to produce ashes for H₂SO₄ leaching tests. The optimized H₂SO₄ leaching conditions of 6.12 mol.dm³ (M) H₂SO₄, solid to liquid ratios 1:5 and 1:10, and 80°C for 8 hours were used. K₂CO₃ was added to increase the dissolution efficiency of K. The objective was to determine if the Al present in metakaolinite (Al₂O₃.2SiO₂), the Al, K, and Ti in the alumino-silicate glasses, and the Ti in rutile (TiO₂) in the ashes could be selectively dissolved in H₂SO₄. XRF results show that the ashes formed at 700°C dissolved more efficiently (87% Al, 89% K and 23% Ti) compared to the ashes formed at 1050°C. This can be attributed to the presence of Al₂O₃.2SiO₂, K₂CO₃ melt, K₂CO₃ remnants, KAl(SO₄)₂, and K-aluminosilicate glass in these ashes. XRD results indicate that the ashes prepared at 1050°C contained anorthite (CaAl₂Si₂O₈), microcline (KAlSi₃O₈), pseudomullite (Al₂O₃.SiO₂), and silicon spinel (2Al₂O₃.3SiO₂), which are either insoluble or only sparingly soluble in H₂SO₄. These minerals resulted in the lower dissolution efficiencies of Al and K. Based on the high dissolution efficiencies of Al and K for the ashes produced at 700°C, coal fines blended with K₂CO₃ could possibly be utilized as feedstocks for the production of aluminium(III), potassium(I), and titanium(IV) and a sulphate-containing leach liquor. Furthermore, the environmental issues and costs associated with the handling and disposal of large volumes of coal fines will also be resolved.

Aug 2, 2022

By E. C. de Beer

"SynopsisA number of important areas in nuclear fuel cycle, at both the front end and back end, offer ideal opportunities for the application of non-destructive evaluation techniques. These techniques do not only provide opportunities for non-invasive testing of e.g. irradiated materials, but also play an important role in the development of new materials in the nuclear sector. The advantage of penetrating radiation used as probe in the investigation and testing of nuclear materials makes X-ray and neutron radiography (2D) and tomography (3D) suitable for various applications in the total nuclear fuel cycle. The unique and different interaction modes of the two radiation probes with materials provide several opportunities. Their complementary nature and non-destructive character makes them most suitable for nuclear material analyses, analytical method development, and the evaluation of the performance of existing nuclear material compositions. This article gives an overview of the X-ray and neutron radiography/tomography applications in the field of nuclear material testing, and highlights a few of the success stories. Several selected areas of application in the nuclear fuel cycle are discussed to illustrate the complementary nature of these techniques as applied to nuclear materials.IntroductionDuring the development of new materials for the nuclear industry, materials testing and characterization are of the outmost importance to maintain safety standards and reliability. No compromise on safety in the workplace in any area within the total nuclear fuel cycle can be tolerated, and therefore most in-situ material characterization and testing is conducted by certified and qualified personnel schooled in destructive and non-destructive testing (DT and NDT) methods. Certification and qualification in NDT can be obtained through many training centres in South Africa in accordance with European, American, and other international standards (SGS, n.d.; SAIW, n.d.; African NTD Centre, n.d.)."

Jan 1, 2015

By F. Dutoy, M. B. Stella, C. F. Carrozza

Rare earth elements (REEs) are indispensable components in the manufacturing of high-tech devices, renewable energy technologies, and defence applications. As global demand for these elements continues to rise, there is a pressing need to optimize extraction processes for both efficiency and environmental sustainability. This study explores approaches to rare earth extraction using Ionquest® 801 and integrates a predictive modelling to enhance process understanding and optimization. We conducted a screening test varying pH process to evaluate the best extraction efficiency. Starting pregnant leach solution (PLS), solution was prepared in the lab with the following rare earth elements: La, Ce, Gd, Dy, and Υ, at 0.02 M for each element. The data obtained were used to develop empirical and mechanistic models to predict rare earth extraction yields and flowsheet. Further tests were performed by mixing specific concentrations of different extractant and/or phase modifier. Our experimental results demonstrated the effectiveness of the proposedextraction methods, highlighting improvements in both yield and selectivity. The developedmodels successfully captured the complex relationships between process parameters and extraction efficiency, providing valuable insights for process optimization.

Nov 6, 2024

By H. Brüggemann

The exploration of deposits generates geological data which are suitable for creating a preliminary tectonic and stratigraphic model. Linked with the topographical map and analysis data from exploration drillings, this information forms a numeric representation of the deposit. The following example demonstrates an expert system which connects chemical quality requirements and quarrying criteria, and develops a quarrying strategy based on the calculated model. Additional constraining factors like process technology, quarrying methods, landscape protection regulations, etc. are included. The goal is to guarantee a long-term, homogeneous material flow from the quarry at acceptable production costs - even in the case of an extraordinarily inhomogeneous deposit. In order to fulfil this requirement it is necessary to consider a large number of rules, criteria and instructions which can be structured as an expert system and programmed with LISP at a comparably low cost. The chosen strategy is not necessarily final, but can be changed any time by altering or varying the framework of conditions. The output consists of a block-working sequence which best satisfies the set requirements for appropriate points of quarry opening.

Jan 1, 1987

By A. P. I. Popoola, D. O. Okanigbe

Copper smelter dust (CSD) is a byproduct of copper smelting and is composed of considerable amounts of copper values and also contaminants (like silica and mullite). Silica in CSD forms Siloxane, a low density material, which is difficult to separate from the aqueous phase during solvent extraction. The need therefore arises to reduce/remove the aluminosilicates for better grade and recovery of copper in subsequent processes. This paper reports the use of two types of centrifugal gravity concentrators, namely Knelson (KGC) and Falcon (FGC), for upgrade of copper in CSD. The aim was achieved by an initial characterisation (Particle Size Distribution (PSD) and mineralogical analysis), together with Density Separation (DS) experimentation, premised on a hypothetical density difference between copper oxide and silicon/aluminum oxide. Wet screening results showed that 88.52 % of CSD particles were in -53 μm fraction. Further PSD study using laser diffraction showed the -53 μm fraction to be composed mainly of 26 μm, 22 μm and 18.5 μm fractions. Mineralogical analysis showed copper to occur mainly as oxides (24.34 wt%), but also as sulphides (7.95 wt%), and a substantial amount of aluminosilicates (42.97 wt%) were identified. Density of CSD was determined as 2.83 g/cm3. Copper content (18.02 wt%) in CSD was upgraded to 35.94 wt% in concentrate using KGC. In conclusion, the results showed good convergence between hypothesis and experiment. Additionally, it was also concluded that KGC performed better than FGC for copper upgrade in CSD. However, roasting CSD prior density separation was recommended for enhanced copper upgrade. Keywords: Copper smelter dust, density separation, solvent extraction, mineralogy

Jan 1, 2020

By P. Ramsaywok, S Ndanduleni, G. Legodi

The objective of this paper is to share the optimisation journey of a pilot Reflux classifier (RC) circuit in the Exxaro GG1 plant, at Grootegeluk beneficiation complex in Lephalale, South Africa. The RC circuit was commissioned in 2016 to produce semi-soft coking coal at its fines circuit; however the stability of operation as well as the quality control of the coal product was not fully achieved. Various test campaigns and optimisation studies were conducted to understand and optimise the RC circuit at GG1. The studies revealed circuit design inefficiencies; provided an improved technical understanding of the current pilot circuit and the parameters required for the circuit to reach a stable operation. The operation was stabilised with its current inefficiencies to produce an average 12.5% ash semi-soft coking coal product for sustained periods, above the initial target of 10.3% ash. Keywords: Reflux classifier, coal

Jan 1, 2020

By R. Rumpold

The platinum group metals (PGMs) palladium, platinum, and rhodium represent the key materials for automotive exhaust gas treatment. Since there are currently no adequate alternatives, the importance of these metals for the automotive industry is steadily rising. The high value of PGMs in spent catalysts justifies their recycling. The state-of the-art technology is to melt the ceramic carrier and collect the precious fraction in a liquid metal bath. As the feed material has quite high melting points, huge amounts of energy are required for this process. Hydrometallurgical treatments of the spent catalysts offer the possibility to recycle the PGMs with less energy and time demands. Moreover, automotive catalysts contain further valuable materials to improve the exhaust gas treatment. These compounds, like cerium oxide, cannot be recovered in pyrometallurgical processes. This paper deals with a special process that uses hydrometallurgical principles to recycle the valuable metal fraction from spent automotive catalytic converters. Hydrochloric acid in combination with hydrogen peroxide is used as leaching agent. This combination selectively dissolves the PGMs and the cerium, which can be recovered in separate steps. As the leaching solution is regenerated and reused, wastewater generation is minimized. Furthermore, the process residues constitute potential byproducts.

Jan 1, 2012

By A. Pareek, V. S. Masampally, V. Runkana

Mineral processing plants, in general, consist of comminution and separation circuits. Rougher flotation is considered as the heart of the separation circuit with concentrate grade and mineral recovery being the key productivity and quality parameters that affect the downstream operations and profitability. Online prediction of these parameters can help improve process performance in real-time. Past efforts to predict flotation cell performance have focused on building physics-based or machinelearning (ML) based models. Although physics-based models are popular in process design applications, ML models are more appropriate for online monitoring, control and optimisation due to their lower computational requirements. Deep learning (DL) is gaining prominence nowadays for application in industrial operations where a large amount of data is available. We have developed a DL model based on long short-term memory (LSTM) neural networks to forecast the two key performance indicators (KPIs), namely, mineral recovery and concentrate grade in a mineral processing plant. Rougher feed characteristics such as mineral grade and particle size distribution, upstream measurable disturbances such as throughput of the comminution circuit and pulp density, and control variables such as aeration rate, pH, and collector addition rate are considered as explanatory variables to train the model. The model was tested with data from an industrial mineral processing plant. For real-time dynamic predictions, the trained model appropriately accounts for mismatch in measurement frequency of real-time process data and off-line laboratory analysis data. Such a time series model can be used as a state observer in model predictive control techniques for optimal control of unit operations in a mineral processing plant. Keywords: Mineral processing, flotation, time-series, dynamic modelling, deep learning

Jan 1, 2020

By S. Chatterjee, F. Suparno, A. Paithankar

Estimating reserves and quantifying resources stand as pivotal and intricate endeavours within the realm of coal mining operations. Intricate geological formations compound the challenges in resource estimation, thereby complicating reserve calculations. The uncertainties tied to geological attributes of coal, encompassing parameters like tonnage and coal quality, wield significant sway over resource and reserve computations within coal mines. This research delves into the domain of geological uncertainties, with a specific focus on calorific value, aiming to numerically characterise resources and reserves within an open-pit coal mine situated in Indonesia. To quantify resources, the coal seam geometry underwent simulation via a multipoint geostatistical technique known as single normal equation simulation. A geologically established coal seam served as the training image for generating 20 equiprobable coal models. To simulate CV, 50 realisations were generated for each simulated coal seam, utilising sequential Gaussian simulation. Deviations of the simulated coal seams ranged from -0.07% to 5.48% in comparison to the training image. The CV simulation yielded an average value of 5,920.29 kcal/kg, accompanied by a standard deviation of 586.54 kcal/kg. However, the average CV spanned from 5,305.26 kcal/kg to 6,526.55 kcal/kg across diverse simulations. For reserve calculation within the context of geological uncertainties, an algorithm rooted in maximum flow graph theory was employed to construct the ultimate pit for the coal mine. Within this final pit, the average stripping ratio was 1.62, coupled with a CV value of 6,019.66 kcal/kg. When juxtaposed with the deterministic model, the findings underscore that the stochastic ultimate pit delineates a more expansive excavation, accompanied by a heightened undiscounted cash flow.

Oct 2, 2025

Visit to Premier (Transvaal) Diamond Mining Company Limited On the 14th February, 1973, 44 members of the Institute were the guests of Premier (Transvaal) Diamond Mining Company Limited. Metrication News PRESSURE GAUGES There appears to be doubt in some circles about the general acceptance of the pascal (Pa) as a unit of pressure and stress. NATIONAL INSTITUTE FOR METALLURGY / NASIONALE INSTITUUT VIR METALLURGIE REPORT. VERSLAG No. 1430 THE USE OF THE EKCO MINERAL ANALYSER FOR THE DETERMINATION OF COPPER AND ZINC IN THE PRESENCE OF IRON 27th June, 1972 Investigator: Gisela Domel SYNOPSIS The Ekco Mineral Analyser-a portable, radio-isotopic X-rayfluorescence instrument-is briefly described,

By M. U. Ozbay

This paper presents an overview of the research that has been carried out to improve the understanding of the fracture processes occurring in rock under high levels of stress. The onset and growth of fractures are studied by means of laboratory model testing, and the results obtained are used in the calibration and validation of the numerical model DIGS, which is based on displacement discontinuity. The results obtained so far have shown that, while there are overall similarities between the experimental results and the numerical simulations, improvements to the experimental procedures and the DIGS are required for a detailed mechanistic understanding of shear-band orientations and extension fractures.

Jan 1, 1996

By R. W. O. Kersten

This paper describes the method used at Agnes Gold Mine in the calculation of pillar strengths, which involves a back-analysis type of approach. The results obtained there are comparable with those obtained by accepted formulae for pillar strength. It was found that a stress level of 70 MPa for the width of combined pillars (Le. crown and sill pillars) causes failure of the reef drives as well as the tops and bottoms of the stope side walls. As shrinkage stoping to depths of more than 650 m would result in very low percentage extractions, alternative methods of stoping will have to be investigated for these depths.

Jan 1, 1984

By J. Cilliers, R. Seitz, D. Drinkwater

Mineral processing produces a saleable product from high-cost ore. The Mineral Processing Engineer must constantly improve the separation to create the most value from the ore and reduce the associated costs. Graduate Metallurgists (or Chemical Engineers) have had the university theoretical training required, but often are illprepared to perform their plant roles. The in-work Metcelerate programme was designed specifically to develop the practical skills that Mineral Process Engineers require, by combining three key elements: 1. Knowledge transfer through self-paced, on-line training; 2. Practical skills acquisition through assessed, practical plant exercises; 3. Skills development through online tutorials. A final process improvement project adds significant value to the operation that far exceeds the training cost. Experience from Metcelerate clients has indicated improved staff retention, greater confidence, and pro-active process intervention.

Jan 1, 2023

By K. C. Sole, M. Makonese

Bushveld Belco is commissioning a plant for production of electrolyte used in vanadium redox flow batteries. Owing to the source material, the electrolyte is contaminated with Fe, at concentrations up to 140 mg/L, which negatively affects battery performance. This study examined the use of ion exchange to reduce the Fe concentration to the target value of < 100 mg/L from a feed solution containing 100 g/L V in 4 M H2SO4. Four resins with possible application were identified: Puromet MTS9570, Puromet MTX7010, Puromet MTS9500, and Puromet MTC1600H. Puromet MTS9570 outperformed the other three resins in all batch experiments with respect to loading capacity and selectivity over V, and was evaluated for Fe removal in fixed-bed column loading tests. Based on these data, preliminary sizing and design of a full-scale column was undertaken. Owing to the difficulty of eluting this resin, a philosophy of discarding the resin on loading to full capacity was considered. These data revealed that, despite the high selectivity of this resin for Fe over V, it would be too expensive and impractical to use this resin for full-scale operation under such conditions. It is recommended to remove iron earlier in the flowsheet prior to generation of the 4 M H2SO4 electrolyte.

Dec 11, 2024

By Q. Liu, S. Liu, Y. Cui

To reduce the frequency of mining incidents and improve safety and production efficiency, it is important to develop technology for the autonomous positioning and navigation of mining equipment, without the assistance of satellite navigation signals. In this study we review the current technological environment for positioning and navigation underground and present several integrated navigation strategies. Existing underground positioning and navigation technology is described, and the performances of different methods based on this technology analysed and compared. The combination types and positioning effects of underground positioning and navigation strategies are discussed. Recent research directions for filtering methods and positioning estimation algorithms for underground positioning and navigation are reviewed. Finally, we summarize the future direction of underground positioning and navigation technology and related algorithms.

Jun 1, 2021

By A. Kotze, D. Messina, E. Nagels, Y. Cryns, S. Arnout

The FlashPhos process aims to recover white phosphorus (P4) from sewage sludge by drying, flash combustion/gasification, and carbothermic refining steps. This study evaluates the material behaviour of sewage sludge ash melting and reduction in a refining furnace for the novel FlashPhos process. Thermodynamic modelling in FactSage 8.2 is combined with experiments from a tube furnace to determine the possible phosphorus recovery and minor element behaviour. For the two studied sludges, a yield of 40% and 75% white phosphorus is achieved after 1 hour at 1600°C, corresponding with a 60% and 25% loss to the metal phase. This is slightly above the calculated equilibrium yield of 28%–73%, which depends mainly on the Fe/P ratio of the sludge. Temperature is found to have a significant influence on the final phosphorus yield when leading to incomplete melting of the ash. A clean slag is produced in the process free of heavy metals making it suitable to be used as a cement-like binder material. The main heavy metals that co-evaporate with the phosphorus are Zn, Pb, As, Sb, and Sn. Additional processing steps will be required to remove these to produce a pure P4 product. The metal alloy consists of mostly Fe and P with smaller amounts of other components such as Mo, Cr, Cu, Mn, Sn, Sb, and V. The final slag consists of CaO, SiO2, MgO, and Al2O3 with virtually complete removal of P and heavy metals.

Oct 2, 2025

By E. Lutz, M. Momayez, K. W. Brown Requist

As real-time air quality monitoring becomes more prevalent in US underground mines, it is important to provide the highest data reliability with the fewest possible sensors. Real-time sensors remain costly, and these costs are not exclusively financial; the time required to install, calibrate, and maintain real-time sensors poses a large barrier to widespread implementation. Current atmospheric monitoring systems typically rely on displaying point-specific values. This requires operators to infer real-time airborne contamination distributions. Monitoring and control software utilizing mine ventilation network (MVN) solvers has been implemented in limited cases because of their ability to simulate ventilation systems quickly, but these solvers use a one-dimensional representation of the mine, limiting spatial resolution of estimated distributions. Computational fluid dynamics (CFD) has likewise been considered as a means to improve spatial resolution, but processing times prevent its use as a basis for monitoring and control. For the real-time monitoring of airborne contamination distributions, we propose a spatial interpolation method that can estimate the distribution of airborne contaminants in near-real time. This method provides a middle ground between fast processing times and increased spatial resolution. With the use of a pathfinding algorithm and optimization through absolute percentage error minimization, this method outperforms spatial interpolation with a Euclidean distance. By providing contamination distribution information to operators, this method and its derivatives stand to outperform current atmospheric monitoring systems.

Apr 16, 2024