Search Documents

By A. R. Miller

A fuel cell locomotive incorporates the advantages of its competitors, namely catenary-electric and diesel-electric units, while avoiding their disadvantages. It possesses the environmental benefits, at the vehicle, of an electric locomotive but the higher overall energy efficiency and lower infrastructure costs of a diesel locomotive. The natural fuel for a fuel cell is hydrogen, which can be produced from many renewable sources or via nuclear energy, and thus a hydrogen-fuel cell locomotive will not depend on imported oil. Hydrogen produced from renewable primary energies or nuclear energy would provide a totally zero-emissions vehicle, that is, with zero carbon in the energy cycle. A project partnership among Vehicle Projects Inc of the USA, and South African partners Anglo American Platinum, Ltd, Trident South Africa, and Battery Electric, has designed and is launching a series of five prototype fuel cell-powered mine locomotives.

Jan 1, 2012

"Chairman: Professor J. C. Griffiths Rapporteur: Mr J. P. G. PRETORIUSPapers:Mine-mill production scheduling by dynamic programming by R. J. Roman Optimization of a large mining venture by J. C. Paynter, B. K. Loveday and C. G. Robinson Economic surface mining of multiple seams by T. V. Falkie and W. E. PorterIn introducing his paper, Mr Roman said that whereas in manufacturing plants the yearly production levels were usually chosen to produce the largest annual cash flow, in a mining operation, the raw materials (ore) were exhaustible so that the production had to be scheduled to maximize the total net present worth of the operation. This optimum production schedule could be determined by using dynamic programming. The required information was readily available to management at most mines. The 'possible operating range' of production rates lay between the rate with the highest profit per ton. and that with the highest profit per year. The optimum production rate started typically at the top of this range and decreased slowly as the deposit was depleted.Dynamic programming was used to determine several production schedules for a hypothetical mine-mill complex. The effects of changes in the ore grade estimates, size of deposit and acceptable rate of interest on the production schedule were taken into account. Apart from the fact that the net present worth of the overall profits was larger than that obtained by conventional methods, it appeared from the cases studied that the amount of metal recovered was also greater.Dr it P. King commented that this was a very interesting application of dynamic programming. He pointed out, however, that the market price of the metal was likely to vary significantly and randomly during the life of the mine, and he suggested that the problem should, therefore, be reformulated as a stochastic dynamic programming problem.If the price of the metal rose to abnormally high levels, a much higher than normal production rate could be expected. The results of analyses given in Table 5 showed that the production rate was a function of market price. In his view the stochastic problem could be solved just as easily as the deterministic problem.In reply to a question by Dr King as to whether the function relating recovery to production rate (Table I) was based on real data, the author replied that it was based on the results of an analysis conducted at the Union Carbide Corporation's Pine Creek tungsten mine in California.Dr D. M. Hawkins stated that costs were incurred when the production rate was altered, for example, in appointing or laying off staff, and that in practice it may be necessary to take these costs into account in finding the optimum production rate. Mr Roman replied that, while normal administrative costs were accounted for, the additional costs incurred in appointing and laying off staff were not taken into account."

Jan 1, 2014

By Y. Fu, C. Aldrich

This study investigates the use of dense convolutional neural networks to estimate bubble size distributions in flotation froths. 20 videographically captured images of froths from an industrial platinum flotation plant in South Africa were labelled semantically with an image annotation tool, LabelMe (https://github.com/wkentaro/labelme). As a result, pixels in the images could be categorized into three classes, namely ‘bubbles’ (class 0), ‘bubble boundaries’ (class 1) and ‘background’ (class 2). A U-net architecture with a ResNet34 backbone was trained to segment the images via classification of the pixels in the images. 5 of the 20 images were used to validate the performance of the neural network. Explicit inclusion of the bubble boundaries as a class proved to be significantly more effective than training the network with two classes only (i.e. bubbles and background). However, the thickness of the boundary layer regions were critical. If too thin, it was difficult to distinguish between some contiguous bubbles and if too thick, some fine bubbles may not be identified. The results were promising, although there is still significant scope for improvement, among other by making use of more images for training and validation. Keywords: Flotation Froths, Convolutional Neural Networks, Deep Learning, Bubble size Analysis

Jan 1, 2020

By O. A. Bascur

Ores are becoming extremely variable with mineralogy and hardness disturbing the grinding and flotation circuits. The current grinding and flotation sensors provide large amounts of data for process optimisation. Adding the right context and operational events augments operational knowledge for proactive actions to improve the performance of the grinding and flotation circuits. A data-driven strategy is needed to enable operations, maintenance, and business personnel to quickly and easily take corrective action when abnormal conditions occur. A digital plant template transforms data into operational insights in real-time. It uncovers the hidden, idle and downtime losses. By measuring and managing these unproductive times, people find new ways of avoiding them, improving the profitability of the plant. The information created by the real time analytics enables the calculation of recovery in real time and develops predictive analytics models to find the best operating condition based on the type of ore currently mined. The creation of new workflows and collaboration between mining and concentrator plant and the enterprise, including services providers, are enabled. A grade recovery model is used to identify the best operating conditions in real-time. An optimal Gaudin size distribution shape is used to find the grinding operating conditions that optimise the metal recovery in the rougher sections of the mineral processing plant. Sensors in the flotation circuits enable estimation of metal recovery and determine the optimal froth depth and aeration profiles, using an industrial air holdup flotation model. The implementation of a recovery/grind strategy with industrial examples in non-ferrous metal concentrator is presented in the paper. Keywords: Digital transformation, soft sensors, predictive analytics, grinding flotation optimisation, flotation bubbles, particle size, particle size distribution shape, froth aeration profiles, flotation air hold up model, recovery predictive analytics

Jan 1, 2020

[Consider the situation where we wish to estimate the value of a block of ore W from the values of n samples wt (i = 1, 2.... n). The samples can be located anywhere inside or outside W. The blocks and the samples can have any size or shape (Fig. 8.1). We define ws as the set of all the samples wi: WS = Iw1; W2; W3.. . wn and we wish to estimate the block W using the samples ws. Let xi be the value of the ith sample and µw the unknown average value of the block. We can estimate µw from the average value of all the samples. Let µw be the estimator of µw. As the samples need not be of equal size, the sample average is: µw = wi xi/~ wi. (8.1) The mean squared error made when estimating µw by µw is known as the variance of estimation of W by ws. It is the error made when giving the value of the sample set ws to the block W and is written o2E (WS to W). By definition: o2E (ws to W) = E [(µw - µw)2]. (8.2) If n = 1, this error is known as the extension variance. Since the sum of the weights given to the sample values is equal to 1,0, the estimator µw is unbiased (the question of the absence of bias is studied in more detail in Chapter 9): E [( µw - µw)1 = 0. (8.3) The error (µw - µw) has zero mean and a variance o2E = E (W8 to W). If we assume that this error is normally distributed, we can define confidence limits for µw. Let tP be the value of the standardized normal variance t such that the probability that t is less than tP is p: (t,) = .\/27T f exp (- t2/2) dt = p (8.4) The probability that µw is larger than µw + t1-P oE is p. The probability that µw is smaller than µw- t1-P oE is p. The following approximation formulae are often used to calculate 2p central confidence limits for the block value: 68% central confidence limits (p = 16%): µw - o2E, and µw + o2E. 95 % central confidence limits (p = 2,5 %): µw - 2 oE, and µw + 2 oE. Tables of the function 0 can be found in any textbook on statistics (for example, Fraser, 1958, p. 388) (see Table 7.2). [ ] The last line of Table 2.2, corresponding to f = 00, also contains the value of tP for p = 80, 90, 95 and 97,5 %.]

Jan 1, 1978

By G. L. Smith, B. Genc, V. Morar, U. Govender

This paper presents a novel holistic healthy human framework for C-suite executives and senior leaders in the minerals industry. The value-add of the framework centres around the integration of inner holistic health and interpersonal holistic health to support and enhance environment, social, and governance transformation, with a focus on the social enterprise. The framework unpacks key components of holistic health and their interlinkages to environment, social, governance, and stakeholder engagement. Insights were gleaned from interviews with 10 C-suite executives, each with over twenty years of experience in mining or business leadership. By applying the holistic healthy human framework, industry leaders can strengthen the social licence to operate and positively transform the industry's public image. Broader application to other sectors is underway.

Oct 2, 2025

By M. Z. Naghadehi, E. Emami, J. Sattarvand, R. Battulwar

In this paper, a methodology for a computerised recognition of joint sets on 3D point cloud models of rock masses is presented. The process starts with classifying joints on a 3D rock mass surface through training a deep network architecture and validated using manually labeled datasets. Then, individual joint surfaces are identified using the Density-Based Scan with Noise (DBSCAN) clustering algorithm. Subsequently, the orientations of the identified joint surfaces are computed by fitting least-square planes using the Random Sample Consensus (RANSAC). Finally, the joint planes are classified into different joint sets, and the dip direction and dip angle for each set are calculated. The performance of the proposed methodology has been evaluated using a case study. The results show that the presented procedure is fast, accurate, and robust.

Sep 1, 2021

By J. Witley

"Narrow tabular platinum group element deposits in the Bushveld Complex of South Africa are typically evaluated by diamond core drilling from surface. Several short deflections are drilled from each mother hole in order to obtain multiple intersections at a close spacing (less than 1 m). Examination of the intersections from deflection drilling revealed the importance of these deflections in understanding the representivity of the borehole, obtaining an estimate of the nugget effect, and mitigating the undesirable effect of the high grade variability at the ultra-short range that is a characteristic of these deposits. The use of deflections in estimation was investigated by means of a number of techniques and scenarios in order to find the most appropriate way to use them in an estimate. A significantly improved level of confidence was gained from using multiple close-spaced intersections rather than a single borehole intersection. IntroductionThe Upper Group 2 chromitite layer (UG2 or UG2 Reef) is known for its remarkable geological continuity, being traced almost uninterrupted for tens of kilometres. However, what is often less well emphasized is the high variability in platinum group element (PGE) grade and thickness (and therefore PGE content) and internal reef stratigraphy over very short distances (several metres or even tens of centimetres).This paper examines the application of short drill-hole deflections in evaluating UG2 PGE mineral resources at Marikana in the western Bushveld Complex of South Africa."

Jan 1, 2017

By L. W. Palmer

Compositing or regularization of drillhole data is common practice in mineral resource estimation and is deemed a necessary step in producing unbiased estimates of mineral resources and reserves. Commonly, data are collected over irregular distances due to the varying relative thicknesses of lithologies drilled or sampling/assaying strategies. This necessitates data transformation to regular lengths of equal size to ensure that all data have the same sample support. However, there have been few detailed publications on the effect of this process on the composited data that are subsequently taken forward for the estimation process. In this paper, three currently available compositing methods are reviewed and the effects of inappropriate compositing methodologies presented. It is shown through a case study that compositing samples to different lengths leads to changes in the average and variance of the grades in the drillcores in the dataset, which will impact the final estimated value. These differences are exacerbated by breaks or gaps in data where, for a variety of reasons, there has been no data collection or data have been lost. The importance of appropriately treating blank and zero data is also presented. Globally, these differences might be minimal, but locally may be substantial, affecting the efficiency of the estimation and subsequent use of the results in, for example, mine planning and reconciliation. Further detailed investigation of compositing practices is required if the full implications of compositing are to be understood and any induced bias effectively defined.

Jul 10, 2024

By J. H. Zietsman, M. W. Erwee, Q. G. Reynolds

Pyrometallurgical furnaces, essential for metal extraction, operate at temperatures exceeding 1600°C and represent complex multiphase systems that challenge direct industrial research. Multiphysics models play a key role in shedding light on their intricate behaviours, supporting the refinement of design and operational strategies. Integral to the operation are the tap-holes, which facilitate the removal of molten products and are routinely opened by lancing, a process comparable to the use of a cutting torch, where high temperatures result from oxygen reacting with an iron lance. When the lance pierces the clay, oxygen gas enters the furnace, which could influence the behaviour of the molten material inside. In this work, a multiphase fluid flow model was used to investigate bulk flow dynamics, with a focus on the effects of the lancing process on the inside of the furnace, immediately behind the tap-hole. Incompressible and compressible multiphase fluid solvers were used and compared with respect their performance – the intention was to assess whether using a compressible solver would yield a different solution to the incompressible one. It was concluded that there are negligible disparities in bulk fluid flow behaviour between the solvers for the case studies examined, indicating that solver selection might be less consequential for certain aspects of oxygen lancing.

Apr 16, 2024

By C. T. O’Connor

Since the first IMPC took place in London in 1952 there have been many developments in our understanding of flotation, both in terms of chemical and physical factors influencing the process. Many of these developments have been captured in the proceedings of thirty congresses that have taken place since that first event, as well as in numerous journal papers and special volumes dedicated to flotation. This paper attempts to highlight the individual contributions which many eminent researchers and engineers have made over the past 70 years towards extending our understanding of, especially, the effects of chemical factors on flotation. Although the focus is mainly on more fundamental aspects, it seems that the ‘pull’ of practice has often preceded the ‘push’ from laboratory-based research. As the fundamental understanding of the role of chemical factors on flotation continues to be developed, the major challenge remains to transfer this knowledge effectively into the domain of operations of this profoundly complex process.

Jan 1, 2020

By L. Bam, R. Machaka, S. Chikosha, N. S. Muchavi

"Parts manufactured through power metallurgy (PM) typically contain pores that can be detrimental to the final mechanical properties. This paper explores the merits of 3D X-ray computed tomography over traditional microscopy for the characterization of the evolution of porosity in metal injection moulding (MIM) and direct powder rolling (DPR) products. 17-4 PH stainless steel (as-moulded, as-debound and sintered) dog-bone samples produced via MIM and Ti-HDH strips (as-rolled and sintered) produced via DPR and were analysed for porosity. 3D microfocus X-ray tomography (XCT) analysis on specimens from both processes revealed spatial variations in densities and the existence of characteristic moulding and roll compaction defects in agreement with traditional microscopic microstructural analysis. It was concluded that micro-focus XCT scanning can be used to study MIM and DPR parts for the characterization of the amount, position and distribution of porosity and other defects. However, the majority of the sub-micron sized pores could not be clearly resolved even at the highest possible instrument resolution. Higher-resolution scans such as nano-focus XCT could be utilized in order to fully study the porosity in MIM and DPR parts. IntroductionMetal injection moulding (MIM) is a novel process, which combines the advantages of powder metallurgy (PM) and plastic injection moulding. MIM has found widespread applications in the cost-effective production of high-sintered density small parts with complicated shapes and mechanical properties equivalent to those of wrought materials (German and Bose, 1977; Machaka and Chikwanda, 2015; German, 2013). There are four basic processing steps involved in MIM, namely; feedstock preparation, injection moulding, debinding and sintering. These steps are discussed in greater detail elsewhere (Machaka, Seerane and Chikwanda, 2014; German and Bose, 1977; Machaka and Chikwanda, 2015; German, 2013).Feedstock preparation involves mixing metal powder with a carefully selected composition of polymeric binder materials at a specific temperature. The feedstock is then granulated and injected into a predefined mould die with the desired shape. The part produced during the moulding step is referred to as a ‘green’ component. The green component typically contains no porosity since the spaces between adjacent powder particles are readily filled with the binder materials (German and Bose, 1977; Li, Li and Khalil, 2007). Debinding is the systemic removal of the binder components by chemical, catalytic, or/and thermal means while maintaining the shape of the component. The part produced after the debinding step is referred to as a ‘brown’ component. Debinding is known to be the source of porosity in brown components (Ji et al., 2001; Tsai and Cen, 1995). Finally, the brown debound part is sintered to full or nearfull density (Sotomayor, Varez and Levenfeld, 2010). The sintering step and associated densification closes up the majority of the pores. Sintered MIM parts are typically sintered to high density (95–99%) and retain an irreducible amount of residual porosity (Barriere, Liu and Gelin, 2003; German, 1990)."

Jan 1, 2016

By M. S. Shishvan, J. R. van Duijvenbode

The results of dig limit delineation in open pit mining are never truly optimized due to gaps in the underlying data, such as insufficient sampling. Aside from the data uncertainty, there is also an influence on the final dig limit by either humans or by the heuristic character of an optimization method like simulated annealing. Several dig limit optimizers have been published, which can replace the manual dig-limits designing process. However, these dig limit designs are generally not adapted to account for this heuristic character. In this paper we present a stochastic analysis tool that can be used with the results of heuristic dig-limit optimization to increase confidence in the obtained results. First, an enhanced simulated annealing algorithm for dig limit optimization is presented. Then, this algorithm is tested on ten different blasts at the Marigold mine, Nevada, USA, as a case study. Finally, the results are analysed with a destination-based ensemble probability map and an analysis conducted of the final solution data distribution. The generated dig-limit designs of the algorithm include high revenue areas that are excluded in comparable manual designs and show improved objective and revenue values. The analysis tool provides block destination probabilities and box plots with the distribution of opportunity value for the dig limit. Furthermore, with the analysis tool, it is possible to make well-informed design decisions in areas of uncertainty.

Dec 13, 2022

By V. Maseko, C. Musingwini

"When considered collectively, Mineral Resources and Mineral Reserves are arguably a key asset for any mining company. Mineral Reserves are the economically mineable portions of Mineral Resources. They therefore provide a good indication of the economic prospects in the short to medium term and associated non-financial impairments for mining companies, hence a focus on Mineral Reserves. An assessment of modifying factors for converting Mineral Resources to Mineral Reserves revealed that Mineral Reserves were most sensitive to long-term commodity prices, hence the focus on long-term commodity prices. The justification for selecting gold and platinum mines is that they collectively make a significant contribution to South Africa’s earnings from mining.The introduction of the South African Code for the Reporting of Exploration Results, Mineral Resources and Mineral Reserves (SAMREC Code) in 2000 informed the basis for analysing long-term commodity price assumptions for major South African gold and platinum mining companies between 2000 and 2016. The analysis revealed that the least number of non-financial impairments occurred when long-term commodity prices were within ±5% of spot prices. This finding suggests that this range is the ideal range for long-term commodity price assumptions to improve confidence in Mineral Reserve declarations and minimize impairments. Introduction The South African Code for the Reporting of Exploration Results, Mineral Resources and Mineral Reserves (SAMREC Code) defines a Mineral Resource as ‘a concentration or occurrence of solid material of economic interest in or on the Earth’s crust in such form, grade or quality and quantity that there are reasonable prospects for eventual economic extraction’ (SAMREC, 2016, p. 18). Mineral Resources are categorized according to increasing levels of geoscientific confidence or knowledge, from Inferred to Indicated and lastly, Measured categories. The SAMREC Code defines a Mineral Reserve as ‘the economically mineable part of a Measured and/or Indicated Mineral Resource’ (SAMREC, 2016, p. 25). In some of the other reporting codes such as the Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves (the JORC Code), a Mineral Reserve is synonymous with an Ore Reserve. The conversion of Mineral Resources to Mineral Reserves involves applying modifying factors, which are non-resource considerations. The modifying factors used in the Mineral Reserve estimation process include mining, metallurgical, processing, infrastructure, economic, marketing, legal, environmental, social, and governmental factors. Each of these modifying factors consists of several components which require due consideration in the estimation of Mineral Reserves. Table I shows some of the components typically considered for each of the modifying factors."

Mar 1, 2019

By B. Ceki, A. Mabentsela

The BCL furnace is scheduled to restart operations after being placed on care and maintenance in 2016 due to depressed nickel prices. The decision to start operations after such a stoppage ought to be led by a techno-economic evaluation of process options to make operations more resilient. For BCL, the decision lies between using the existing flash-smelting furnace (FSF) or a top-submerged lance (TSL) furnace. Available studies show that the FSF combined with other converting technologies is cheaper to operate; however, such studies are based on flowsheet simulation results of single copper concentrates and therefore do not provide a full scope of practical capabilities based on smelter operator skills. Using a t-test on normalized prior operational data from three Cu FSF and two Cu TSL, it was found that the only statistical differences between the operating costs of the FSF and TSL technologies are in the coal use for heating the feed blow and number of rebuilds: the FSF consumes coal to heat the feed blow and the TSL requires 2.4 rebuilds during a course of a single FSF campaign. A summative operating cost comparison over the existing BCL FSF 11-year life shows that BCL can decrease operational costs by some BWP 55.5 million if the operation were to change to the newer TSL technology. The savings derive from reduced coal use, which is normally associated with heating the blow when using the FSF. Despite the TSL carrying added costs of 2.4 rebuilds during a life time of one FSF furnace campaign, the cost associated with the TSL rebuilds of approximately BWP 1.3 million is minimal compared with the overall operational expenditure decrease that BCL will incur on using the TSL technology. In terms of the technology, BCL can have higher Ni–Cu recoveries at lower operational costs by elimination of Ni–Cu losses and eliminating the slag-cleaning furnace by converting to a TSL furnace.

Jul 10, 2024

By R. K. W. Merkle, F. A. S. Reyneke, Z. Harris, P. W. J. Delport

The technological advancements in computing power in the last 30 years have enabled the practical visualization of complex geological environments in three-dimensional (3D) space. 3D models and their application in the mining industry are becoming increasingly important, for example, to identify future exploration areas and targets, for mineral assessment and evaluation, and prediction and planning of future drill-holes. However, acquiring borehole data is an expensive practice, with drilling programmes costing mining companies up to billions of dollars each year. Tighter financial constraints on exploration budgets result in more pressure being put on three-dimensional models to accurately identify future target areas. This article aims to evaluate the potential drilling success of simulated greenfield and brownfield exploration using a 3D geological model created of Leeuwpoort tin mine. These simulations investigate the probability of intersecting a mineralized zone of economic interest and evaluate how the probability is affected when the number of drill-holes and distance from a known intersection changes. Furthermore, these simulations attempt to obtain an indication for the minimum number of drill-holes required for a successful exploration campaign at the mine. The investigation also aims to establish a first-pass attempt towards developing a ‘favoured procedure’ for identifying potential exploration targets for tin deposits with geological and geochemical characteristics similar to Leeuwpoort. The results for the ‘favoured procedure’ established are statistically tested using the ‘bootstrapping’ method. By simulating various exploration scenarios, the study also emphasises the importance of predicting successful drilling, which aids in budgeting for drilling programmes as the minimum number of drillholes needed for a specific exploration project can be determined.

Feb 2, 2022

By T. Khumalo, L. Musenwa, S. Masemola, M. Kgaphola

"In 2017, Petra Diamonds completed the construction and commissioning of a modern, fit-for-purpose diamond processing plant at Cullinan Diamond Mine (CDM). The design of CDM’s milling circuit is unconventional in that it comprises an autogenous (AG) mill with a grate discharge with large ports, low-revolution jaw crushers, and high-pressure grinding roll crushers with large operating gaps. In this paper we review the design to provide guidance on what is expected from the milling circuit and to demonstrate how the design aims to address challenges experienced in the old plant, which was based on staged crushing technology. We assessed the performance of the CDM AG milling circuit from commissioning and early production stages to examine its impact along multiple dimensions. In the assessment we sought to understand the lessons from our milling circuit regarding diamond liberation, energy consumption, and the future of diamond processing as a whole. IntroductionCullinan Diamond Mine (CDM), previously known as Premier Mine, is an underground diamond mine owned by Petra Diamonds. Petra Diamonds is a leading independent diamond mining group and a growing supplier of rough diamonds to the international market. Petra Diamonds is listed on the Main Market of the London Stock Exchange under the ticker ‘PDL’. Petra’s total resource of 305 million carats ranks third by size after De Beers and ALROSA (Petra Diamonds, 2018).CDM was established in 1902. The mine rose to prominence in 1905, when the 3106 carat Cullinan Diamond — the largest rough diamond of gem quality ever found — was discovered there. The mine has produced over 750 stones that are larger than 100 carats and more than a quarter of all the world's diamonds that are larger than 400 carats. Cullinan is renowned as a source of large, high-quality gem diamonds, including Type II stones, as well as being the world’s most important source of very rare blue diamonds (Petra Diamonds, 2018)."

Feb 1, 2019

By A. M. Garbers-Craig, T. Coetsee, T. M. Nemavhola

Accretions often form in furnaces when slag and charge materials attach to the refractory wall and build up over time. Accretion formation is usually unwanted because it reduces the working volume of the reactor and hinders material flow through the reactor. However, in some instances a thin, stable accretion layer may be desirable to protect the underlying refractory material. In order to prevent and/or manage accretion formation, it is important to understand the underlying principles of this phenomenon in the particular reactor. Excessive accretion formation hampered production at the Exxaro FerroAlloys ferrosilicon melting and atomization plant. This plant uses induction furnaces in which a 15% silicon-iron alloy is produced by batch smelting a mixture of ferrosilicon of 75%Si grade and low-carbon steel. The molten ferrosilicon alloy is then gas-atomized to a powdered product for use as a dense medium in mineral processing plants. The objective of this study was to investigate the effect of different impurity levels in the ferrosilicon feed material on the extent of accretion formation as well as the effect on the accretion properties, which influence the ease of accretion removal upon furnace shut-down. Refractory and accretion samples were collected after a furnace shut-down and characterized using X-ray diffraction and scanning electron microscopy–energy dispersive spectroscopy. It was concluded that the trace elements in the FeSi-75 feed material (Al, Ca, Mn) were mostly responsible for accretion formation, but that rust on the low-carbon steel and oxidation of the steel contributed to accretion attachment to the lining. The total contaminant content, calcium to aluminium ratio in the FeSi-75 feed material, and thereby the liquid to solids ratio in the accretion at temperature determine the strength of attachment as well as growth of the accretion.

Feb 2, 2021

By Y. Suzuki, H. Yoshida, K. Sakaguchi, K. Matsuki, M. Minami

To estimate three dimensional in-situ stress at great depth, Downward Compact Conical-ended Borehole Overcoring (DCCBO) technique, which is one of stress relief methods, was developed. DCCBO technique can be applied to a water-filled vertical/sub-vertical borehole. In in-situ tests, the bonding device and the cleaning system were verified to work well in a water-filled borehole with cuttings on the bottom. Um dreidimensionale in-situ Beanspruchungen in großen Tiefen abzuschätzen, wurde das Downward Compact Conical-ended Borhole Overcoring (DCCBO) Verfahren entwickelt, wobei es sich um ein diese Beanspruchungen entlastendes Verfahren handelt. Die DCCBO Technik kann auf wassergefüllte vertikale und subvertikale Bohrlöcher angewandt werden. Bei den in-situ Tests wurde die Einsatzfähigkeit der Verbindungsvorrichtung und des Reinigungssystems für wassergefüllte Bohrlöcher mit Einschnitten am Boden bestätigt. La technique de Downward Compact Conical-ended Borehole Overcoring (DCCBO) ou ‘Surcarottage par sondage à extrémité conique compact dirigé vers le bas’, qui est une méthode de détente des tensions, a été développée pour calculer les tensions in-situ à trois dimensions à grande profondeur. Cette technique peut s’appliquer à des sondages verticaux/sub-verticaux remplis d’eau. Au cours des essais in-situ il a pu être vérifié que le dispositif de liaison et le système de nettoyage fonctionnaient bien dans un trou de forage rempli d’eau avec saignées au fond.

Jan 1, 2003

By C. Musingwini

The South African mining industry continues to be a major source of employment at a time when at least 25 per cent of the working age population is unemployed. At the same time the industry faces a skills shortage in many of the disciplines necessary for its future health. The University of the Witwatersrand, University of Pretoria, University of Johannesburg, and University of South Africa have historically produced mining graduates for the South African industry, with any shortfall being met by the recruitment of overseas graduates. More recently the global shortage of engineers and other mining industry professionals has seen a reversal of this trend and a very significant emigration of well-educated and highly skilled personnel. The traditional career path for mining graduates is in production and mine management. However, there is the parallel and possibly more pressing need for specialized skills in such fields as ventilation, rock engineering, mine planning, mineral resource evaluation, and mineral asset valuation. It is in these essential areas that chronic shortages continue to hamper the development of the industry and may well frustrate its ambitions to be safe, healthy, and profitable into the future. The permeability of skills across sectorial boundaries within the mining industry requires that skills shortages in the platinum sector are not looked at in isolation, but within the context of the entire industry. This paper reviews the efforts being made by the universities at both undergraduate and postgraduate levels to meet the needs of the South African mining industry, in terms of the required numbers and the range of specialized skills.

Jan 1, 2012