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By L. A. Cisternas, A. Lopez-Valdivieso, Y. L. Botero, L. Cortes

In the processing of sulfidic ores, pyrite is usually depressed and ends up in the tailings. However, pyrite is the most common species responsible for acid mine drainage (AMD) due to its spontaneous oxidation. This AMD affects the tailing chemical stability by dissolving some toxic or heavy metals species such as As, Cd, Co, Pb, and Zn, which can migrate into the surrounding ecosystems. Therefore, the strategies to reduce pyrite’s environmental impacts are a crucial point to produce more chemically stable tailings. Consequently, numerous studies have been made to find procedures that could inhibit or restrain AMD. This work aims to develop a procedure for designing conceptual flotation circuits that can produce tailings with low content of pyrite and to assess this type of circuit with traditional flotation circuits. The method consists of applying optimal flotation design where three products are considered: metal concentrate, pyrite concentrate, and tailing with low content of pyrite. Two approaches are considered; in the first, a flotation circuit is designed to generate a concentrate rich in all sulfide minerals and to obtain a tail with low pyrite content. Then, a second flotation circuit is designed for the selective separation of the bulk into metal concentrate and pyrite concentrate. This is called fractional separation design. In the second approach, a flotation circuit design is realised that generate the three products simultaneously. This is called integrated separation design. Both fractional separation design and integrated separation design are assessed in this paper. This methodology is focused on cleaner production (waste prevention and resource minimisation) rather than end-of-pipe technology (treat existing waste). The methodology was applied to a copper sulfide ore from a local company in the Antofagasta region (Chile). This ore contains chalcocite, covellite, iron oxides, and pyrite. Keywords: Flotation, tailing, pyrite, cleaner production

Jan 1, 2020

By S. W. Jacobsz, E. P. Kearsley, N. K. Schoeman

A physical modelling approach was adopted to simulate the process of cave mining propagation at various horizontal to vertical stress state ratios, and image data was captured and used to characterize the resulting failure mechanisms. Image processing was integrated into the study to determine minor principal strains in models to identify where critical extensional strains had been exceeded relative to crack propagation. The study exhibited a scale factor magnitude of 119 using a calculated critical extensional strain value of 0.014% for the modelling material used. It was perceived that cave propagation occurred through successive parallel extensional ‘fracture bands’ in all cases, as noticed in models of prior studies, deviating from that described by the Duplancic model. Cracks tended to bisect regions of minor principal strain equal to the critical extensional strain, which suggests ‘fracture banding’ is an acceptable failure mode for brittle, rock-like materials. Moreover, it was found that models with lower horizontal to vertical stress ratios (K ratios) showed a greater degree of vertical development of the caving mechanism (at similar vertical stresses), while the vertical extent of the cave was suppressed in models with higher K ratios. Models subjected to larger vertical stresses experienced slower cave formation in latter time-steps. These models exhibited larger two-dimensional caved perimeters and areas, respectively.

Nov 30, 2022

By K. Sasaki, Y. Oriia, Shigeto Kuroiwa, H. Miki, Yuji Aoki, T. Hirajima, G. P. W. Suyantara

The effect of a sulfite reagent on the floatability of chalcopyrite and enargite was investigated in this paper. The flotation tests using single and mixed minerals were performed under various concentrations of sulfite. The flotation tests using a single mineral showed that the sulfite reagent depressed the natural floatability of both minerals at pH 9. Surprisingly, enargite was floated after the addition of potassium amyl xanthate (PAX) following the sulfite treatment, and the floatability of chalcopyrite depressed under a similar condition. X-ray photoelectron spectroscopy analysis results showed that the sulfate species increased after the sulfite treatment on both minerals. However, the addition of PAX removed this sulfate species and rendered the enargite surface hydrophobic. This phenomenon was not observed on the chalcopyrite surface. FTIR analysis and PAX adsorption studies were performed to support this finding. The flotation of a mixed mineral was in agreement with the flotation of a single mineral, indicating a possibility for selective flotation of chalcopyrite and enargite using the proposed method. Keywords: Flotation, chalcopyrite, enargite, sulfite, potassium amyl xanthate

Jan 1, 2020

By Yuandong Qiao, Erdong Li, Chao Lv, Junjian Ye

The gas-based CO reduction of Panzhihua vanadium titanomagnetite concentrate from 1100°C- 1250°C was investigated in this paper. The reduction degree increased with increasing temperature and increasing reduction time. At a temperature of 1250°C and a reduction time of 20 minutes, the metallisation degree reached 92%. The iron-titanium oxide phase transformation during reduction process was Fe2.75Ti0.25O5→Fe2.5Ti0.5O4→FeTiO3→FeTi2O5 according to the X-ray diffraction analysis. The SEM and map scan by energy spectrum of results of reduced samples at different temperatures indicated that the metallic iron particle size increased gradually as the reduction temperature increased. These results can serve as a reference for the reduction of vanadium titanomagnetite by CO. Keywords: Vanadium titanomagnetite concentrate, CO reduction, phase transformation, reaction mechanism

Jan 1, 2020

By Y. Zhang, F. Zhu, Y. Zhao, L. Dong, Y. Li

In order to obtain a more suitable separation medium for fine coal, in this paper a pulsed fluidised bed was used to measure the pressure fluctuation, density characteristics, bubble diameter and rising velocity of Geldart A and B particles in the bed by controlling the pulsation frequency and gas velocity, in order to study the fluidisation effect and two-phase distribution of the bed. The results indicated that with the increase of pulsation frequency, the breakthrough point on the fluidisation characteristic curve caused by particle adhesion disappeared, and there was an optimal frequency, which made the minimum fluidisation velocity of particles reach the minimum. In addition, the bubble rising velocity was also simulated. The relationship between them was established using a model, and the error was within 5%. This provides an effective way to predict the bubble velocity, study the distribution of bubble phase, and improve the stability of bed density. Keywords：Frequency, flow velocity, pressure fluctuation, bed density, bubble

Jan 1, 2020

By J. Petersen, H. Naderi, H. Zare, M. H. Nikzad, M. Karimi

In the copper electrorefining process, the dissolution of anodes is significantly reduced or even stopped when the passivation phenomenon occurs. The results of this phenomenon are increasing energy consumption, residual formatting, and voltage levels in the cell. In this study, the electrochemical behaviour of blister copper in the presence of sodium persulfate (PDS) was studied. The electrochemical methods of LPR, Tafel, and Electrochemical Impedance Spectroscopy (EIS) were used. The results showed that the addition of sodium persulfate activates the electrode surface and increases the open circuit potential. In the presence of PDS, the polarisation resistance of the electrode shows an increasing or decreasing tendency, based on the PDS concentration. This tendency is probably due to the formation of surface layers (such as slime layer or copper sulfate) and dissolution of this layer at various concentrations of PDS. The lowest polarisation resistance of 1.8 ohms and the highest corrosion current of 60.6×10-3 and 36.6×10-3 A/cm2 from LPR and Tafel techniques respectively were obtained at the concentration of 40 g/l PDS. Based on the results of potentiodynamic and electrochemical impedance spectroscopy tests, the addition of sodium persulfate to the solution reduces the corrosion resistance, therefore the passivation time of the blister copper anode increases. Keywords: Blister copper, electrorefining, sodium persulfate, anodic passivation

Jan 1, 2020

By M. Khodadazadeh, K. G. van den Boogaart, T. Leißner, L. Tusa, J. Gutzmer, R. Gloaguen, M. Kern

Ore sorting is a technology that is increasingly used to process primary raw materials. Timeconsuming and expensive empirical state-of-the-art test work is carried out to assess whether the use of ore sorting for the enrichment of a particular ore makes technical and economic sense. With the innovative simulation-based approach presented here, it is possible to direct the selection of a suitable sensor based on quantitative mineralogical and textural data, thus avoiding much of the empirical studies. Required data can be collected quickly and cost-effectively using available methods of automated mineralogy. The obtained parameters such as mineral grain size distribution, modal mineralogy, mineral area and mineral density distribution have been utilised in this study to simulate the prospects of success of ore sorting, applying different types of sensors. Empirical tests with commercially available sensor systems have been conducted to experimentally validate the predictions of the simulations. The estimation of the target mineral grade can be further optimised by the use of machine learning algorithms for the integration of automated mineralogy data and sensor data. The approach can easily be adapted to other types of raw materials and thus has great potential to become a key technology for the optimisation of processing experiments. Keywords: Automated mineralogy, hyperspectral imaging, machine learning, ore sorting

Jan 1, 2020

Since 2001, the Hybrid Stress Blast Model (HSBM) project members have developed a software suite to model the complete blasting process from non-ideal detonation to muck pile formation. To preserve the physics and improve solution time, the breakage engine uses a combination of analytical models and 2D axisym-metric finite differences to model near-field crushing, coupled to 3D discrete lattice fracturing and distinct element numerical methods to model throw and muck pile development. The model has been validated by comparison with laboratory and field tests in kimberlite. Multiple blasthole simulations are used to demonstrate how changes to blasting parameters can influence downstream efficiencies. Case studies of wall control blasting show that the presplit design must balance the two opposing effects of increased damage with increased charge and decreasing attenuation of the seismic waves with decreasing charge. Modelling of decoupled explosives needs further development. Reducing the charge towards the back of the trim blast results in a much more significant decrease in back damage than altering the timing. The model demonstrates how separation along the weaker planes in a jointed rock can coarsen the fragmentation, leading to inefficient beneficiation, and extends the damage to a distance of at least twice the burden behind from the blasthole, severely compromising the wall stability.

Jan 1, 2012

By M. Tang, X. Tong

"SynopsisSlime coating is one of the most common ways for serpentines to contaminate metallic mineral concentrates during traditional flotation of coarse sulphide particles. This could pose quite a complicated and challenging problem in the case of some types of low-grade and finely disseminated Cu-Ni ores bearing high serpentine contents. This is the case for the copper and nickel sulphides from the Yunnan Mine, China. Previous batch flotation tests of this ore resulted in satisfactory recoveries of 86.92% Cu, 54.92% Ni, and 74.73% Pt+Pd, and concentrate grades of 4.02% Cu, 3.24% Ni, and 76.61 g/t Pt+Pd. However, the MgO content in these concentrates was more than 19%. In the current study, microflotation tests and settling rate tests were introduced to investigate the effects of a combination of strong collectors (a 2:1 weight ratio of butyl xanthate and butyl ammonium dithophosphate) on entrainment of serpentines in metallic mineral concentrate, as well as visual observations of the concentrates in suspension using still photography. All test results indicated the presence of serpentines entrapped in the hydrophobic flocs that resulted from these collectors, even with the use of effective gangue depressants. These strong collectors are used to flocculate the ultra-fine sulphides by forming loose and ‘fluffy’ hydrophobic flocs. However, these hydrophobic flocs may also be able to load or entrap some serpentine slimes into the concentrate, and this entrained serpentine could be harder to remove by using depressants or intensified conditioning than serpentine slime coating on the particle surfaces.IntroductionSerpentine minerals, which have the generalized composition (Mg,Fe)3Si2O5(OH)4, can be easy to crush and grind due to their convoluted and bent layered structures. These serpentines can hinder the enrichment of some metallic minerals and dilute their concentrates by entrainment during flotation. The resulting high pulp viscosities, slime coatings, and high content of dissolved ions adversely affect the flotation recoveries of copper and nickel sulphides, and high levels of MgO entrained in the concentrates lead to heavy penalties from smelters. Since the quality of nickel flotation concentrate depends heavily on its MgO content (generally less than 6–7% for No.1 or 2 grade nickel concentrate according to the standard requirement from National Nonferrous Industry), reducing the entrainment of serpentine during flotation is becoming more and more pressing. Previous research has focused on the collectors and depressants that are commonly used in copper-nickel flotation, as well as their interaction mechanisms."

Jan 1, 2015

By J. van der Merwe, C. Phetolo, V. Matjeke

The mechanical properties and microstructure of AlSi10Mg alloy samples that were printed by selective laser melting (SLM) were studied to determine the effect of processing parameters and building orientation. After printing, the alloy was stress relieved at 250°C for 2 hours. The microstructures were analysed by optical microscopy and scanning electron microscopy (SEM) to determine the alloy phases and distribution. Phase transformation characteristics of the material were evaluated using differential scanning calorimetry (DSC). Mechanical properties were determined by subjecting the XY- and Z-built samples to tensile and nano-indentation testing. The samples from the tensile tests were then used to perform fractographic analysis by SEM. The microstructural properties in each orientation revealed a non-homogeneous microstructure which was characterized by a semi-elliptical tract and fine silicon precipitates, which were found to be softer along the fusion zone. The DSC thermograms revealed that the material underwent two phase transformations during the first heating cycle. The mechanical properties revealed a higher UTS, higher yield strength, and a lower percentage elongation in the Z orientation than in the XY orientation. Fractographic analysis showed that crack initiation in both orientations started from the surface in a brittle manner due to surface flows, and then propagated via microvoid coalescence.

Jul 1, 2021

By M. Rudolph, R. Tolosana-Delgado, E. Schach, M. Buchmanna, G. van den Boogaart, U. Peuker

The multidimensional characterisation of processes based on various particle properties is a key requirement for a detailed prediction on certain process streams. To access the relevant particle properties (e.g. particle size, particle density and mineral content) automated mineralogy (i.e. Mineral Liberation Analyser) is applied. The kernel density estimation is used to transfer the received discrete particle data into continuous distributions without the necessity of binning the information and the related loss of information. From these continuous distributions, multidimensional separation curves are estimated. The uncertainty of these representations is tracked via bootstrap resampling. For the evaluation of the separation efficiency of the multidimensional separation curves, the statistical entropy is calculated. The statistical entropy represents a local (for each property combination) as well as a global (for the investigated property range) measure of separation efficiency and can be weighted with various property distributions (e.g. mass or mineral mass distribution) to allow for a comparison of different parameter settings and processes. With the help of a case study of a dry magnetic separation of a cassiterite bearing skarn ore from the Erzgebirge (Germany), the methodology is presented and the results are discussed in detail. Keywords: Multidimensional, magnetic separation, kernel density estimation, mineral liberation, statistical entropy

Jan 1, 2020

By M. Rudolph, J. Sygusch

Froth flotation is well-established and efficient in the selective separation of valuable particles from unwanted material with sizes ranging from 10 μm to 200 μm. However, when it comes to the separation of ultrafine particles (< 10 μm) there are still some challenges, or rather opportunities. This research aims at developing a method for the separation of ultrafine particles based on multiple particle properties. Amongst such properties are wettability, morphology (shape or roughness) and size with applications not only in mineral processing but in general chemical engineering. In this study, three differently shaped fractions are used as valuables for testing: spherical particles, elongated particles and irregularly shaped particle fragments; together with ultrafine magnetite as the gangue material, in order to investigate the effect of particle morphology on ultrafine particle flotation, as well as wettability, which is varied by esterification using alcohols. Flotation tests are carried out using a novel flotation device that was designed especially for the flotation of ultrafine particles, combining advantages from machine-type froth flotation and column flotation. The results showed that, in contrast to previous studies, recoveries for ultrafine spheres were higher than for ultrafine fragments for all wettability conditions, and hydrophobisation generally increased particle recoveries for said morphologies. Tests using fibres showed different behaviour as hydrophobisation had negative effects on their recovery, despite increased selectivities and kinetics. These findings suggest that apart from influences of particle properties within the suspension zone, their effects on the froth characteristics should be studied in more depth. Keywords: Ultrafine particles, Flotation, Particle shape, Wettability, Esterification of glass, Hydrophobisation

Jan 1, 2020

By M. L. Mahlatji

Mechanical alloying of an equiatomic mixture of crystalline Ti and Pt elemental powders in a high-energy ball mill formed an amorphous alloy by solid-state reactions. Mechanical alloying was carried out in an argon atmosphere at a rotation speed of 1200 r/min and a 20:1 ball-to-powder weight ratio, for time intervals of 4 to 40 hours. At an intermediate stage of mechanical alloying, scanning electron microscopy showed the formation of characteristic layered structures of inhomogeneous composition within the powder particles. X-ray diffraction analysis showed the gradual disappearance of crystalline Bragg peaks and the emergence of broad amorphous maxima as milling progressed. The amorphization process was completed after 8?12 hours. The amorphous state of the product indicated that temperatures during processing did not exceed the crystallization temperature of the alloy.

Jan 1, 2014

By M. I. Mabala, B. P. Watson, M. J. Kanda

A failed and stable Upper Group 2 chromitite pillar database was collected in 2007 as part of the PlatMine 1.2 pillar strength project. The database consisted of 177 pillars, of which 33 had failed. Most of the data were collected from various intermediate-depth mines near the town of Thabazimbi. Spans between rows of chain pillars were about 30 m. Pillar loads were estimated using pseudo-3D, elastic, boundary element modelling software. The pillar-load data were evaluated using a maximum likelihood regression analysis to determine strength parameters, following a similar approach to historically acceptable practice. The original formula was named the PlatMine Formula. This paper describes re-evaluations of the database, using a linear formula and several variations of the power formula. The formula providing the lowest standard deviation to the data in the database was considered the best representation of the pillars in the database. Through this rigorous process, a new formula for peak pillar strength was developed for Upper Group 2 chromitite pillars, which is unaffected by volume. The small standard deviation provided by this formula suggests a reliable relationship between strength and w/h ratio, in the w/h ratio range between 1.5 and 4.7. Accuracy, precision, and recall analysis confirmed the efficacy of this equation to the data in the database. Importantly, the new formula provided in the paper does not predict a significantly different strength to the current PlatMine formula, within the confines of the database.

Nov 27, 2024

By C. A. Young, J. L. Bowden

"Cyclic voltammetry experiments were conducted on copper and chalcopyrite (CuFeS2) in the absence and presence of ethyl xanthate, and compared to mass-balanced EH–pH diagrams. The results for copper duplicate those found in the literature and confirm xanthate chemisorption. However, the, results indicate that chalcopyrite oxidizes to chalcocite (Cu2S) and only afterwards is chemisorption observed due to small currents appearing with xanthate. This phenomenon suggests that the mineral's hydrophobicity is induced by more than dixanthogen and copper xanthate. Hydrophobicity was found to be pH-dependent over a range of alkaline conditions (pH 7–11) at narrow potentials (0 to –200 mV). An EH–pH diagram for chalcopyrite with xanthate is presented to illustrate the conditions under which chalcopyrite would be hydrophobic and thereby more thoroughly explain the results in the literature. IntroductionSulphide minerals are generally concentrated from ores by froth flotation, a physiochemical process that induces separation based on differences in hydrophobicity. In this process, a gas is bubbled into a slurry and the minerals that are hydrophobic (water-repelling) adhere to the bubbles and float to the surface while the hydrophilic (water-loving) minerals remain in the slurry. With sulphide minerals, the hydrophobicity is generally established in two ways. The first is by the addition of a collector, which is a heteropolar molecule with a reactive inorganic head group and an inert organic tail. Typically, the head group bonds with the sulphide mineral surface by adsorbtion either chemically (chemisorption) or physically (physisorption) or by complexing with atoms that solubilize somewhat at the surface (surface precipitation). These interactions leave the organic tail protruding from the mineral surface, thereby inducing hydrophobicity. The second method is by oxidation of the mineral surface to form a layer that is metal-deficient/sulphide-rich or comprised of elemental sulphur. Because the layer mimics naturally hydrophobic sulphur, this enables ‘collectorless’ flotation. Furthermore, this oxidation phenomenon adds an electrochemical dimension to the understanding of sulphide mineral flotation."

Jan 1, 2016

By F. Reyes, M. Hilden, G. Forbes, M. Yahyaei

Since AlphaGo defeated the best human player in the game of Go in 2016 - something thought to be an impossible achievement - machine learning, deep learning and reinforcement learning have caught the attention of scientists, the media and the general public alike. This recent development in machine learning (let us remember that neural networks have been available for decades now) opens new possibilities in the areas of modelling and process control. However, little has been reported in the minerals processing industry about these new possibilities and opportunities. This paper presents and introduces the topic of reinforcement learning and the different platforms that allow its implementation. The paper shows the consequences of using reinforcement learning for the specific area of process control and optimisation. As an example, the authors present the use of reinforcement learning for the control of a SAG mill closed with a pebble crusher using industrial data from an operation. A comparison with advanced model-based process control is provided, showing the benefits and shortcomings of reinforcement learning as a new control and optimisation technique. Keywords: Reinforcement learning, deep learning, process control, process optimisation

Jan 1, 2020

By B. Yu, M-H. Cao, C. Zhou, X-Z. Zhang

The transient infiltration and lubrication behaviour of slag during continuous casting of steel is important for billet quality. A two-dimensional coupled mathematical mould model was developed to investigate these phenomena. The accuracy of the model was verified by comparing the calculated slag consumption with measurements by the plant. The results show that the liquid slag is consumed from the middle and late period of positive strip time to the next early period of positive strip time, including the entire negative strip time. The maximum downward infiltration velocity and positive pressure in the slag channel is at the middle of the negative strip time. Increasing the positive pressure of the slag channel is conducive to lubrication. The shear stresses acting on the shell surface and at the mould side were determined by the lubrication slag consumption and total slag consumption, respectively, and gradually decreased with increasing slag consumption. The negative strip time was lengthened to increase the slag consumption and prolong the time near the maximum downward shear stress, so as to be conducive to the demould.

Apr 16, 2024

By J. P. De Carvalho, R. Dimitrakopoulos

This paper presents an actor-critic reinforcement learning (RL) method to allocate trucks and shovels in open-pit mines, while defining short-term production scheduling of an industrial mining complex, given new information collected during operations. This new data obtained from sensors update the uncertainty of the orebody models. The RL agents interact with the mining complex environment; exploring the solution space, learning actions to improve metal production and equipment utilisation. A case study is presented at a copper mining complex, highlighting the method’s ability to adapt and make informed decisions while collecting new information.

Sep 1, 2021

By S. M. H. Ahmadi, K. Barani, F. Moradpouri, R. Ghaedrahmati

As exploration is time-consuming, costly, and risky, determination of the erosion surface of a metalliferous deposit before geophysical surveying and exploration drilling might be very helpful. Geochemical haloes can be used to determine whether the erosion surface is supra-ore or sub-ore and thus reduce the risk of exploration operations. The aim of this investigation is to determine the erosion surface of the North ROK porphyry deposit (NRPD) in northwestern British Columbia in Canada using linear productivity (LP), which is the content of an element defining the halo multiplied by the width of the halo. A total of 2045 soil samples from the B horizon were analysed using ICP-MS for 36 elements, including Cu, Mo, Pb, Zn, Au, As, Ag, Ni, Co, Fe, and Mn. The data-set was snalysed to obtain the statistical parameters and the elements Cu, Mo, Pb, and Zn were chosen to calculate the linear productivity and the total linear productivity. These four elements were modelled using probability plots to identify and separate subpopulations in terms of anomalous haloes and background, including the threshold values of each subpopulation. The results of the probability plot modelling and thresholds values were then used to map the distribution of each element in a GIS to calculate the linear productivity. The total linear productivity indicated that the erosion surface is supra-ore. Finally, a 3D orebody model of the Cu, Mo, Pb, and Zn distributions was constructed using borehole data and used to validate the results.

Feb 6, 2023

By M. Frenzel, K. Bachmann, M. Rudolph, R. Tolosana-Delgado, E. Schach, M. Buchmann, L. Pereiraa, K. G. van den Boogaart, N. Kupka

Geometallurgy - the science of predicting the behaviour of ores along the value chain based on their geological and mineralogical characteristics - has barely moved beyond process minerology studies. These studies typically link process behaviour to the mineralogical and microstructural characteristics of pristine or processed ores in a qualitative or semi-quantitative manner. Eventually, a trial-and-error optimisation of the operation is achieved. However, to deliver on its promise, geometallurgy should progress beyond this current approach to a fully quantitative understanding of process behaviour, including the various uncertainties involved, namely predictive geometallurgy. One of the barriers currently hindering this development is the neglect of most ore characterisation data obtained in geometallurgical studies. This is mostly due to the large extent of this information exceeding the capacity of conventional software. To address this challenge, we developed a data mining platform consisting of an SQL database, an R front-end in-house package, and back-ends to interpret data from several analytical instruments. This platform enables the use of the statistical and data mining power of the R open-source environment for any geometallurgical study. Potential applications range from ore characterisation to process understanding and forecasting, and from geostatistical prediction to operational control and optimisation. The scripting abilities of R allow for the: 1) processing of many streams in loops, thus freeing the user from repeating tedious click-and-drop tasks; 2) computation of virtually any derivate or aggregate quantity from the data; 3) distribution of the work among several processor clusters; and 4) keeping of a log file for the calculations done. This contribution presents the building blocks of this platform, and illustrates with several examples its potential to enable predictive geometallurgy. Keywords: Data mining, entropy, kernel methods, LASSO regression, predictive geometallurgy

Jan 1, 2020