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By A. D. Pienaar

The aqueous chemistry of niobium and tantalum compounds with hydrofluoric acid is a mature field of investigation. In contrast, very little attention has been paid to reactions of these compounds in non-aqueous environments. Similarly, reactions of elemental fluorine with niobium and tantalum compounds have received little more than cursory attention in literature. This work discusses the isothermal reaction kinetics derived from thermogravimetry, using a less redundant approach than is currently the standard. We also discuss the most likely kinetic models for this reaction.

Jan 1, 2012

By E. Moosavi, K. Tolouei

In mine production scheduling problems are well-known, where most are categorised into deterministic and non-deterministic NP-hard problems because of their complexity. Many researchers have attempted to solve the problem by applying various optimisation techniques. While using traditional methods they observed extreme difficulty in solving highly complex problems. In the 1990s, many researchers addressed long-term production scheduling (LTPS) by using simulated annealing, the genetic algorithm, the tabu search algorithm, and the ant colony algorithm. These algorithms are known as the meta-heuristic algorithms, and have proved to be the most efficient algorithms for solving LTPS thus far. The firefly algorithm is one of the best methods for visualising problems related to LTPS, and provides the best possible optimisation. It is one of the simplest methods, and easy to apply to any NP-hard problem. The experimental, and comparison with other recently published algorithms shows that the proposed algorithm is feasible, and is an effective approach for long-term production scheduling problems. The results indicated that a better solution is obtained by the proposed method, compared to other methods in terms of cumulative net present value, and average ore grade. Additionally, the CPU time via the proposed model is roughly 2.52% higher than the other method.

Sep 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 Thomas V. Fame, William E. Porter

"As geological and mining conditions become more complex, and as overall mining economics become more marginal, short- and long-range decision-making regarding multiple-seam surface mining becomes more difficult. The decision-making problem involves a study of economics, cut-off grades and ratios, equipment capabilities, sequencing and selective mining practices.This paper is concerned primarily with multiple-seam mining of bituminous coal. The research has led to the development of an economic decision-making model for use as a day-to-day tool to aid mine operators and pit geologists to decide what and how to mine.The model is designed as an aid for feasibility decision-making in multiple-scam situations and for situations where selective mining is needed or desired. In effect, a simulation of the feasibility and preliminary mine planning phases has been developed. The model is divided into four separate segments: decision-making, simulated mining, cost calculations and the determination of the discounted cash flow return on investment."

Jan 1, 2014

By R. Degel

Submerged arc furnaces and electric smelters are applied in numerous metal and slag production lines. Particularly in ferroalloy and non-ferrous metal production, like silicon metal, platinum group metals, calcium carbide, and copper, the units are an essential part of the production technology. Most of these electric furnaces are considered to be highly energy-intensive units. The high level of required electrical power is defined by the process. SMS developed several measures to reduce the overall electrical energy consumption of these metal production lines. In particular, the following measures contributes to a lower energy consumption: improved electrical efficiency with intelligent design and application of components, minimizing the heat losses from the furnaces with a balanced cooling/refractory systems, minimization of process steps (such as elimination of agglomeration), recovery of energy, process optimization (resulting in higher metal yield) and the achievement of higher recovery rates, enlarging furnace capacity to reduce heat losses, and maximizing the power-on time. This paper gives an overview of the above-mentioned solutions.

Jan 1, 2012

By W. A. Hodgson

"In order to be able to map the variation in the concentration of elements in soils, it is necessary to sample at intervals that will give adequate coverage of the area and will allow determination of the rate of fluctuation of concentration with distance in any environment. This rate of fluctuation with distance can be referred to as the continuity of concentration.The continuity of concentration in soils varies according to the chemical characteristics of the element being considered, the underlying rock type or orebody and in response to the dispersion processes that operated during soil formation. Within any environment there is a maximum distance between sampling points within which adjacent sample values are related. This distance, the critical sampling interval, can be determined by means of a correlograrm.Where the sampling grid has been chosen to provide an adequate coverage over unmineralized rock, adjacent samples being related, anomalies may be missed if the element continuity in the anomaly is less than in the background. Results show that a knowledge of the critical sampling interval of the environment being examined may used to select a more efficient sampling pattern for a geochemical survey."

Jan 1, 2014

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 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 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

By A. J. Dickson, A. M. Starfield

This paper reviews the progress made to date in the development of computer models of heat and moisture transfer from rock surfaces to the ventilating air in deep-level mines. The application of these programs to ventilation planning and design is discussed.

Jan 1, 2014

By A. Navarra, A. Quelopana

The mine production scheduling problem (MPSP) has been studied since the 1960s, and remains an active area of computational research. In extending the concepts of the MPSP, the automated mine may now be regarded as a hierarchical intelligent agent in which the bottom layer consists of distributed robotic equipment, while strategic functionality occupies the higher layers. Here we present a disambiguation of artificial intelligence, machine learning, computational optimization, and automation within the mining context. Specifically, the Q-learning algorithm has been adapted to generate the initial solutions for a high-performing strategic mine planning algorithm, originally developed by Lamghari, Dimitrakopoulos and Ferland, based on the variable neighbourhood descent (VND) metaheuristic. The hierarchical intelligent agent is presented as an integrative conceptual platform, defining the interaction between our new Q-learning adaptation and Lamghari’s VND, and potentially other hierarchically controlled components of an artificially intelligent mine, having various degrees of automation. Sample computations involving Q-learning and VND are presented.

Dec 1, 2021

By Sabine Verryn, Johan de Villiers

"Through the application of the Rietveld method, X-ray diffraction analysis has developed into a fully quantitative method for phase analysis. The Rietveld method itself has progressed from an unstable method that required constant operator intervention to a stable and robust method suited even for routine analysis. The method however, requires a good initial calibration and periodic checks on its precision and accuracy.Several examples from minerals processing, pyrometallurgy, and materials science show the strengths and applicability of the method. The limitations and sources of error are also discussed.1. IntroductionDiffraction of X-rays by matter has been used for more than 80 years, initially to elucidate the structure of crystalline matter, and to investigate the bonding between atoms. The first development of powder diffraction cameras and the later development of X-ray diffractometers saw the development of methods to identify phases and to try to quantify them in mixtures. A comprehensive database and search-match techniques have been developed over the ensuing years. Effective and accurate quantification had to wait for the so-called Rietveld' analysis where the total diffraction pattern is used and where the crystal structure data for the constituent phases are needed as input. Overlapping of diffraction peaks of different phases is handled without difficulty and reliable results can be obtained in spite of this occurrence.The development of methods for structure analysis from powder data has also progressed rapidly and more and more complex structures are being solved from first principles, i.e. without knowledge of unit cell or space group data. Because of the ease of use of the Rietveld method, it is finding increased application in metallurgy, especially in the quantification of phases of importance in minerals processing, in pyrometallurgical processes, and in materials characterization. This study will examine the principles of the Rietveld method, its application in metallurgy, and finally also the common pitfalls that need to be avoided.2. Rietve1d AnalysisAs the Rietveld method compares the experimental diffraction pattern with one calculated from known crystal structure data, the following data are needed:•,An XRD Pattern with as Iowa background as possible. This should have good resolution and high diffraction peak intensities. With modem X-ray detectors, this can be achieved in minutes rather than hours.•,Instrumental parameters such as goniometer radii and slit sizes are needed. These are the so-called ""Fundamental parameters"". They are used to calculate the shapes of the resultant diffraction peak profiles that are caused by the instrument. The parameters are used to correctly separate the instrumental effects on the diffraction pattern from the sample effects."

Jan 1, 2014

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 K. B. Owusu, W. Skinner, R. K. Asamoah, J. Karageorgos, M. Zanin, C. Greet

High Pressure Grinding Rolls (HPGR) are mostly used prior to pelletising processes to increase the specific surface area (SSA) of iron ore concentrate. For expressing SSA, the Blaine index is utilised as one of the most important dimensional properties of iron ore pellet feed. ISO 21283 is a standard test method that explains the manual of Blaine air-permeability apparatus for determination of this parameter. In this standard, the disaggregation method is based on passing the minus of 1 mm samples from the 0.150 mm sieve. The disaggregation process has an effective role on the results of Blaine airpermeability test especially for regrinding HPGR products. In this research, firstly the Blaine index of samples was measured without disaggregation. Following this, disaggregation was done by passing the minus of 1 mm samples through three sieves with different dimensions, 0.150, 0.090 and 0.045 mm, separately, and the Blaine index was calculated for each one. Finally, lab-mill with rubber balls, called Jar mill, was investigated as another option. Screen analysis and image analysis with SEM were performed to evaluate the effects of the sample's disaggregation on the size distribution and agglomeration of samples. The results showed that the disaggregation method with sieve size 0.150 mm, according to ISO 21283, was not applicable for HPGR products because the particles were still stuck together. In addition, the disaggregation method with the sieve size 0.045 mm or with Jar mill offered reasonable results. Keywords: Disaggregation, Blaine index, specific surface area, regrinding HPGR, ISO 21283, Jar mill

Jan 1, 2020

By D. C. Krige

The estimation of the tonnage and grade of payable ore in a mine and the correct policy of selective mining based on such estimates, is of vital importance to the mining engineer it is surprising, therefore, that more attention has not been devoted on the Witwatersrand to the scientific improvement of mine valuation methods. At present these methods consist almost entirely of the application of simple arithmetic and empirical formulae guided by practical experience, and ignore the many advantages to be gained from a careful statistical analysis of the behaviour of the gold values. The science of statistics has expanded rapidly during the last two decades and its value as a powerful and indispensable tool is now recognized not only by research workers and scientists but also, ever-increasingly, by the commercial and industrial world. This being the case it is noteworthy that in a mining field such as the Rand with its highly developed and advanced mining methods, singularly little attention has been paid to the analysis of mine valuation problems on a modern statistical basis. This omission is even more striking when cognizance is taken of the wealth of sampling data concerning the gold ore which is available and of the far-reaching decisions and deductions constantly being based on such data. Some contributions have however been made from time to time towards the application of statistics to mine valuation on the Rand (References Nos. 7, 8, 9, 11, and 12), but none of these have been generally applied in practice and a systematic practical approach based on clearly deemed fundamental concepts still appears to be lacking. The object of this paper is, therefore, to define these statistical concepts and to indicate briefly the lines along which statistical methods can be applied profitability in solving some of the existing problems and in improving the general standard of mine valuation on the Rand For this purpose a knowledge of mathematical statistics is essential, but as this paper is primarily intended to provide the mine valuator with a practical introduction to statistical application in his field, the mathematics is confined to a short annexure, together with references from which details can be obtained.

Jan 1, 1994

By R Linares

For centuries, diamond's superlative properties have earned it a reputation as the 'dream' material for mankind in its search to create advanced applications. Until recently, this dream has been realized only in the use of diamond for gemstones and abrasive applications where several tons of diamonds are now used on an annual basis. The vision of having large, high quality diamond as part of a broad engineering tool-kit for many diverse high tech industries is now becoming a reality however, with the advent of early stage commercial availability of single crystal and poly crystalline CVD diamond.

Jan 1, 2010

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 D. Wines

"Slope stability analyses have traditionally been undertaken in two dimensions assuming plane strain conditions. Although three-dimensional analysis techniques are widely available and used routinely for open pits, two-dimensional analyses are still more common due to the relative ease of model construction and the relatively rapid simulation times.Two-dimensional analyses will often produce different results to three-dimensional analyses for the same slope. It is generally thought that two-dimensional analyses will produce more conservative results. The main reason for the differences is the ability of three-dimensional analyses to account for the three-dimensional nature of the various model inputs, including the slope geometry, the distribution of soil and rock mass domains, the orientation of geological structures with respect to the excavation face, the orientation of the in situ stresses, and the distribution of pore pressure. In some cases, for a long, straight slope in basic geological conditions, two-dimensional analyses can provide a reasonable representation of the problem. However, in many cases, the inability of a two-dimensional analysis to represent the true three-dimensional nature of the problem will lead to unrealistic analysis results.This paper discusses the reasons, as detailed above, for the differences in two-dimensional and three-dimensional analysis results. Work by others is summarized, and additional numerical analyses are performed to provide an improved understanding of the effects of slope geometry, structural orientations, and in situ stresses on predicted stability. Case studies are presented for both stable and unstable slopes, and the behaviour of these slopes is related to the three-dimensional nature of the slope geometry and geology.The previous work, the new analyses performed here, and the case studies show that it is often important to provide a realistic representation of the slope in three dimensions in order to obtain reasonable stability analysis results. This is particularly true for hard rock environments where structurally controlled failure mechanisms are most likely. The paper also highlights the fact that back-analysed properties obtained from one analysis technique are not necessarily applicable to forward analyses using another technique."

Jan 1, 2016

By M. Dworzanowski

The difference in the magnetic properties of minerals is the basis for magnetic separation. All minerals can be generally classified as ferromagnetic (strongly magnetic), paramagnetic (weakly magnetic) or diamagnetic (non-magnetic). Magnetic separation can be conducted dry or wet. The majority of the applications of wet magnetic separation in the mining industry are based on the wet drum magnetic separator. The wet drum magnetic separator has been in use for over 50 years and its design is based on a rotating drum installed inside a tank. Inside the drum are stationary, permanent magnets arranged in an arc to provide the magnetic field. These magnets can be of the ceramic ferrite type providing a low intensity magnetic field or of the rare earth type providing a high intensity magnetic field.

Jan 1, 2010

By G. R. Marchant, B. K. Loveday

"A mathematical model has been developed for flotation circuit simulation. This model was designed to investigate the effect of varying the circulating loads and to determine whether an improvement in overall efficiency could be gained by a size separation prior to flotation.Model parameters were obtained by regression to plant data. Highly correlated parameters in the model were combined to reduce the number of parameters so that the need for excessive data gathering was eliminated. Mass balance smoothing was used to obtain a consistent data set for regression.The results of the simulation indicate that for the same grade of concentrate, an increase in copper recovery of 0.6 per cent may be Possible by increasing the circulating loads. The results of the simulation also indicated that recleaning of the plus 200-mesh material may be beneficiaL."

Jan 1, 2014