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By J. T. M. Amphlett, C. A. Sharrad, M. D. Ogden, R. I. Foster

"A renewed interest in nuclear power around the world in order to reduce greenhouse gas emissions is going to increase demand for uranium as fuel. This will result in more uranium being mined, which will in turn increase associated environmental pressures, such as fresh water use. A move to lower quality waters containing impurities such as chloride would help alleviate these pressures. In this work, we determined the uptake characteristics of weakly basic anion exchange resin Ps-EDA towards uranium from saline solutions in a dynamic flow column. Breakthrough curves were produced, with suppression of uptake being observed for chloride concentrations above 5 g L-1. Calculated resin saturation capacities at zero and 5 g L-1 chloride are comparable with literature values for strong-base anion exchange resins, and exceed those published for weak-base resins up to 20 g L-1 chloride. Data has been fitted to multiple breakthrough models, with the modified dose-response model most effectively predicting uranium recovery. The results show that the ethylenediamine functionality could be suitable for use in future uranium processing flow sheets where a high-saline lixiviant is used. IntroductionIon exchange (IX) is a key technology in the uranium mining industry and is well established for the extraction of uranium from both acidic and alkaline leach liquors (Edwards and Oliver, 2000). It was first employed in 1952 at the West Rand mine in South Africa (Ford, 1993; Taylor, 2016). H2SO4 and Na2CO3 are the most commonly employed lixiviants used to solubilize uranium in acidic and alkaline leach conditions respectively. The chemistry of these systems causes uranium to form anionic sulphate or carbonate complexes, which can be taken advantage of by anion exchange resins.Another major technology for the extraction and purification of uranium from leach liquors is solvent extraction (SX). This technique involves the extraction of uranium from the aqueous phase into an immiscible organic layer. Although this is a commonly used method, there are major drawbacks to it, including the use of large volumes of flammable solvents, solvent loss, phase disengagement, third phase formation, and the production of problematic degradation products (Veliscek-Carolan, 2016). These problems can be circumvented through the use of IX resins."

Dec 1, 2018

To determine the characteristics of a mineral deposit, the usual practice is to take samples, analyse the properties of those samples and infer the characteristics of the deposit from these properties. This analysis can be done using statistical methods. In the present work we are concerned with two types of statistical approaches, classical statistics and spatial statistics. If one uses classical statistics to represent the properties of the sample values, the assumption is made that the values are realizations of a random variable. The relative positions of the samples are ignored, and it is assumed that all sample values in the mineral deposit have an equal probability of being selected. The likely presence of trends, zones of enrichment, or pay shoots in the mineralization, is ignored. The fact that two samples taken close to each other are more likely to have similar values than if taken far apart is also not taken into consideration. In contrast, spatial statistics will be used if one chooses to consider that the sample values are realizations of random functions. On this hypothesis, the value of a sample is a function of its position in the mineralization of the deposit, and the relative position of the samples is taken into consideration. The similarity between sample values is quantified as a function of the distance between samples and this relationship represents the foundation of spatial statistics. There are few situations where classical statistics can be used. The assumption that all sample values in the mineral deposit have an equal likelihood of being represented will be satisfied only if the sample values are randomly distributed, or if the sample positions are random. Sample values are in fact never randomly distributed within a mineral deposit. Further- more, geologists usually avoid taking samples at random (random sampling), as it is correctly accepted that samples located on a regular grid, or approximately on a regular grid, give more information than randomly located samples. In practice, classical statistics should be used only in the early stages of exploration, when the number of samples available is relatively small and the distances between samples are large. In these circumstances, and whenever the information available is not sufficient to permit the use of spatial statistics, application of the methods described in this chapter is justified.

Jan 1, 1978

By E. J. Magri, A. Couble

Kriging estimates of geological resources are sometimes conditionally biased because the kriging plan contains too few samples. This may be done purposely in order to match the variance of the estimates to the true block dispersion variance. This work aims at evaluating the influence of conditional bias over the ultimate optimum pit design in relation to its shape, size and NPV (Net Present Value of profits). It has been restricted to two real case studies: a ‘carrot shaped’ gold porphyry in northern Greece and a manto-typeexotic copper deposit located in northern Chile. The methodology applied to each deposit consisted of generating a ‘real block model’ and four resource estimates by the use of conditional simulation and the application of four different kriging plans to the drillhole databases respectively. The estimation models vary in smoothness and conditional bias. Ultimate optimum pits were determined for the ‘real’ and the four different kriging models. Pit comparisons lead to the following conclusions: •In the worst case, conditional bias overestimated the project's NPV by 32% and 5% for the gold and copper deposits respectively. •The overestimation of high grades is more relevant than the underestimation of low grades. This resulted in a tonnage over-extraction of 148% and 1% for the gold and copper deposit respectively. This difference was attributable to the vastly different geometry of the deposits. •The smoothing effect of kriging, without or very little conditional bias, produced open pits that were different to the ‘true’ (ideal) ones and furthermore, underestimated the project's NPV by 10% and 6% for the gold and the copper deposits respectively. •Other factors that influence the optimum open pit design and to some extent control the effect of conditional bias are: the cut-off grade, the orebody geometry and distribution of grades within it and the amount of over-burden. Keywords: conditional bias, ultimate pit design

Jan 1, 2003

By E. Spicer

X-Ray diffraction (XRD) provides useful information about the composition of an ore sample in terms of quantification of crystalline phases and amorphous content. The use of new, fast detection systems in XRD creates the opportunity to use this technique in modern process control. In the analysis of heavy mineral sands, XRD can identify the main mineral phases, such as ilmenite FeTiO3, rutile TiO2, Zircon ZrSiO4and quartz SiO2, and any other minor components present, such as anatase TiO2, magnetite Fe3O4, haematite Fe2O3or monazite (Ce, REE)PO4. Quantitative analysis is possible by various classical methods such as straight line or polynomial calibration with standards, but modern quantification analysis techniques such as Rietveld analysis (Bish and Howard, 1988) are attractive alternatives, as they do not require any standards or monitors. These methods offer impressive accuracy and speed of analysis. The Rietveld method compares calculated versus experimentally derived X-ray powder diffraction patterns for the sum of all crystalline phases. Another analysis technique offering great benefit to mining industries is cluster analysis. Enormous amounts of XRD measurement data are generated during the process control and material evaluation. New ways of handling such vast amounts of data are required to produce meaningful information for the end users. Cluster analysis greatly simplifies the analysis of a large amount of data from different processes or different raw materials, and automatically sorts closely related scans of an experiment into clusters and marks the most representative scan of each cluster as well as outlying patterns. The use of cluster analysis to evaluate the XRD data allows fast and reliable tracking of the process. It is the most economical procedure to have automatic data evaluation without involving any dedicated personnel in the process. Details of the techniques used, sample optimization methodologies, results, data precision and limitations will be discussed. The approach has potential as a relatively inexpensive, reliable tool, useful in the characterization of heavy minerals sand materials.

Jan 1, 2007

By D. Moradkhani, S. M. Javad Koleini, M. Abdollahy, F. Soltani

"The objective of the study was to determine the type and distribution of rare earth elements (REEs) in the phosphate flotation concentrate from the Esfordi flotation plant in central Iran, in order to understand their leaching behaviour. Samples of the concentrate were prepared and analysed using XRF, XRD, ICP, and EMPA. The Ce, Nd, La, and Y contents were 5608, 2227, 1959, and 679.7 mg/kg, respectively. The main REEbearing minerals in the concentrate are fluorapatite, monazite, and xenotime. Apatite is the chief mineral of the concentrate and the ratio of apatite to monazite is greater than 60. From EMPA analysis, monazite contains a much higher proportion of REEs than apatite, but more than 50% of the REE content of the concentrate is in apatite, as this is the main mineral constituent of the concentrate. During the leaching of REEs in the phosphoric acid production process, more than 99% of the total rare earth values report to the large amounts of phosphogypsum (CaSO4·2H2O) formed during the dissolution reaction. Accordingly, two process options are suggested for treating the Esfordi concentrate. In the first option, the concentrate is treated with 98% H2SO4 at 200–300°C. After digestion and water leaching, phosphorus and REEs are precipitated out of solution. In the second option, the concentrate is treated in a pre-leach stage. The process residue from the pre-leach stage is then subjected to acid digestion at elevated temperature for phosphoric acid production.IntroductionThe rare earth elements (REEs) comprise a set of 17 chemical elements in the periodic table, specifically the 15 lanthanides plus scandium and yttrium. REEs and alloys that contain them are used in devices such as computer memory, rechargeable batteries, cell phones, catalytic converters, magnets, fluorescent lighting, and many more (Krishnamurthy and Gupta, 2004). China supplies about 94% of the REE demand, with the remaining 6% coming from Russia and Estonia, the USA, India, Malaysia, and Brazil (Zhanheng, 2011). Increased industrial development in China has prompted the Chinese government to limit annual export quotas to approximately 35 kt of rare earth oxides (REOs), while non-Chinese annual demand is expected to reach 80 kt by the year 2015. This constriction of supply is being met by the development of many new rare earth mining projects, each of which has its own unique mining and processing challenges (Jordens, Cheng, and Waters, 2013). One of these projects is the Esfordi phosphate project, which is located in Yazd Province in central Iran. The concentrate from the Esfordi flotation plant contains 1.2–1.5% REEs."

Jan 1, 2017

The influence of Harold Hotelling?s work in the field of mineral economics is both unusual and outstanding. In the 66 years since its development, theory surrounding the economics of exhaustible resources has only been significantly researched since the early 1970s. At that time a wave of research into the economics of exhaustible resources arose from the threat of global resource scarcity and continued into the late 1990s. Current East Asian and global demand for natural resources as well as mineral and metal commodities, has stimulated interest in the optimal and sustainable exploitation of exhaustible resources to the point that the subject is worthy of review. Hotelling?s theory and the assumptions that he made in establishing a model for the optimal exploitation of mineral resources at the industry level and at the level of the individual mine owner, are examined. He showed that the rate of increase inexhaustible resource prices should be equivalent to the market rate of interest and that in a market with rising prices the rate of extraction should be constant. In markets where demand is stable optimal exploitation requires that the rate of extraction should decline over time, while in a monopoly market he showed that the rate of extraction is retarded. In addition, the effects of cumulative production on costs and prices, the uncertainty associated with estimates of the resource stock, the impact of exploration and issues of intergenerational equity are examined. An analysis of the optimal price path, extraction costs and mineral rents at an industry level is presented as a model. An analysis of the rates of production and optimal benefits at the individual mine level including total, average and marginal costs on the optimal rate of production, is considered. Optimal extraction rates for a mine with a clearly defined concave positive cost equation vary according to the position on the marginal cost curve. The influence of discount rates and the size of the ore reserves on the rates of mineral extraction are also examined and could define the frontier of usefulness for the ?economics of exhaustible resources?.

Jan 1, 2007

By S. Kauchali, J. van Dyk, J. Feris, S. Pershad, M. van der Riet, D. Love, J. Brand, C. A. Strydom

"This paper offers an introduction to and strategic context for the other papers included in this special UCG edition of the Journal of the Southern African Institute of Mining and Metallurgy. South Africa is facing long-term energy security challenges, brought about by a myriad of factors that are somewhat unique or exacerbated in the global context. Underground coal gasification (UCG) is a process used to produce synthesis gas from coal in situ, that is, in the coal seam. UCG is an emerging, advanced clean coal technology that offers a potential solution for these challenges, as it can cost-effectively and cleanly liberate vast coal resources in the country that currently cannot be economically exploited using traditional mining technologies. One of the tasks of the South African Underground Coal Gasification Association (SAUCGA) is to advance the development of UCG in South Africa by compiling a technology roadmap. This paper presents the initial findings of the SAUCGA Roadmap (Draft), and contextualizes the technology opportunities and challenges, stakeholders, and provides a basis from which to progress further plans for technology development. Firm development plans and deadlines are not yet possible due to the reliance of the UCG Roadmap on the higher level South African energy policy and regulatory framework. However, the draft roadmap has taken the first step of identifying these policies and stakeholders, and should be seen as the seed from which this embryonic technology and industry can be further developed. IntroductionSouth Africa’s long-term energy security challenges include energy access and affordability, dwindling reserves of accessible bulk primary energy, mounting environmental concerns with all forms of energy generation (especially coal and nuclear), balancing the electricity grid by incorporating an increasing proportion of non-despatchable renewable energy sources, mounting environmental liabilities regarding defunct mining operations, and lastly but by no means less important, fluctuating exchange rates and energy commodity prices.Correctly managed underground coal gasification (UCG) is an emerging, advanced clean coal technology that offers a potential solution for these challenges, as it has been shown to have the potential to cost-effectively and cleanly liberate vast coal resources in the country that currently cannot be economically exploited using traditional mining technologies."

Jan 1, 2019

By R. C. W. Webber-Youngman

The mining industry in South Africa faces real challenges with regard to the reduction of safety-related incidents. The purpose of this paper is to highlight the need for alternative interventions in addition to other safety improvement strategies already employed on mines. It furthermore supports an existing paradigm: incident investigations. An investigation into fatalities in the South African mining industry shows that although great progress has been achieved through the reduction in fatalities in all sectors of the industry over the last few years, more can and should be done to achieve status of ?zero harm?. Fatalities and lost time injuries on mines result not only in large financial losses, but also in disruptions of mining operations in general through Section 54 stoppages to resolve the situation. The approach of the paper is therefore not to try and prove whether there is high fatality rate and/or lost time injuries, but in what way incident reconstruction simulations (IRS) can have an impact in the future prevention of such incidents. The challenge therefore lies in the utilization of pro-active systems that would show employees the possible outcomes of being exposed to certain hazards. In real life, these incidents cannot be re-enacted and in most cases we can only learn through the previous mistakes of others. A virtual reality (VR) education and training system will enable employees to be ?exposed? to different hazards in a safe environment, and simulation, in a ?forgiving? environment, of the possible consequences of unsafe acts. According to the Occupational Safety and Health Act (OSHA), unsafe acts and unsafe conditions are indirect causes of safety-related incidents, but there are also direct causes; for example, unplanned release of energy and/or hazardous material, and basic causes, for example, management safety policies, personal factors, and environmental factors. The administrative workload associated with any incident investigation places a large burden on the investigation team, and in most cases other employees are informed through vague administrative processes what the ?real cause? for the incident/accident was. New preventative strategies are often put in place without showing the employees what the real causes of the incident/accident were. This can be mitigated through the use of interactive VR simulations/animations of the hazards that they are exposed to and how to deal with them. If VR interventions are not used as proposed by this paper, the real causes and consequences of almost all fatalities and lost time injuries may never be fully understood. This paper also emphasizes what potential impact IRS could have on the prevention of future mine incidents as part and parcel of a pro-active risk prevention strategy. The intention is therefore not to replace any other risk prevention strategies, but to visually enhance the reality of the incident. Keywords virtual reality, risk management, incident reconstruction simulations, interactive safety training, usability context analysis, mine safety.

Jun 1, 2013

By J. N. Van der Merwe

Following the Coalbrook disaster in 1960, research into coal pillar strength resulted in the adoption of the concept of a safety factor for the design of stable pillars in South African coal mining. At the time when the original statistical analysis was performed by Salamon and Munro in the early 1960s, 27 cases of failed pillar workings were considered suitable for inclusion in the database of failed pillars. Pillar failure did not stop after the introduction of the safety factor formula by Salamon and Munro (1967). In the ensuing years, pillars that were created before the application of the formula deteriorated and later failed, as did ones that were created after the introduction of the formula. This means that over time, the database of failed pillar cases increased in size, allowing ever more reliable analyses to be performed. The number of failed cases in the database had grown from the original 27 in the 1960s to 86 by 2011. All the failed cases are contained in the updated database. The database of stable pillars, which is also used in the derivation of strength formulae, has now been extended from 125 to 337 cases. The new database of intact pillar cases is more complete as it bridges the time gap between the Salamon and Munro (1967) and the Van der Merwe (2006) databases. The original requirements for inclusion into the database were satisfied in the compilation of this latest collection. The characteristics of the original database of intact pillars did not change in a meaningful way. The mining depth and pillar dimensions of the new database are largely as they were in the original database. Time-related trends with regard to pillar dimensions and depth of mining could not be found, indicating that the geometrical parameters of coal mining in South Africa have not changed meaningfully in approximately a century of mining. The characteristics of cases in the updated database of failed pillars does not differ substantially from the one published by Van der Merwe (2006). The same difference between that database and the original Salamon and Munro database, namely that the average safety factor of the failed cases had increased dramatically, from 1.0 to 1.5, is still apparent. This may be due to the inclusion of more failures from specific areas that exhibit a disproportionate number of failures at higher safety factors. These areas are the Vaal Basin, Klip River, and Free State coalfields. The new database confirms yet again that there is no correlation between the safety factors of failed pillars and their time of failure. The safety factor on its own is thus not a reliable predictor of longterm stability of pillars. Keywords coal pillar, stable pillar cases, pillar collapse, pillar data base.

Nov 1, 2013

By M. Arnesen

Mining professionals recognize the need to continuously evaluate and refine mine planning standards and scheduling. We must examine our current reality, and evaluate the following: •How well do our planning standards represent the actual mining process? •To what extent do they support the requirements of the downstream mining activities? •How we apply them to operational management and control? In most operations, mine-planning standards are global averages. Little differentiation is madein quantifying key planning variables. Often standards used in the long-term, are applied to the short-term, and the standards and scheduling precedents are only reviewed occasionally. Mine-planning standards applied to production schedules are often only focused on the management of functional mining performance, and play no role in managing the requirements of down stream processing. Many mining operations are characterized by high levels of fluctuation, and typically incorporate a wide range of factors and adjustments to compensate for deviations from performance targets, in mining operations as well as for the other business areas. The reason for using global averages is because of a lack of understanding of the causes of deviations that occur through the process, and the impact that they may have on the performance of the business as a whole. Average standards and factors are often used to quantify the variability in a system. From these average values, measurement standards and performance targets are derived for the planning and execution environments. During the execution of a plan/schedule there will be deviation in actual performance and the planned ‘average’ standards. In reality the ‘average’ conditions seldom occur and the impact of variability and interdependency are seldom constant or predictable. The predictability of variability and interdependency is further complicated by the fact that mining conditions have a role to play in the actual production performance, and they too are variable. By developing the throughput knowledge of our production systems, we can better understand the nature of variability and the interdependency within the systems as well as the impact of interdependency between the links in our production chains. With this knowledge, planning standards and scheduling precedents can be better defined and sensibly differentiated. This will improve planning and management of ore utilization, mining production and the effectiveness of processing. As a result the business will be more stable and predictable and business performance will be improved. The purpose of this paper is to describe: •At a high level, the scope for refining and differentiation in mine planning standards, and incorporating geological and plant parameters into mine scheduling. This will improve planning and scheduling and the overall performance of the mine. Given our current level of scientific knowledge and the technological tools at our disposal we should be able to plan and schedule production so that we can manage pro-actively and improve business performance. In doing so we can also improve reconciliation and value tracking through mining and processing •The flexibility and functionality of the XPAC planning and scheduling tool that will enable a throughput management approach.

Jan 1, 2003

By C. Klutke

This paper outlines a simple methodology for mineral characterization, developed as part of the Australian Mineral Industry Research Association (AMIRA) managed research project P777 ?The Development of Heavy Suspension Techniques for High Density Separations (Replacement of Clerici?s Solution)?. The project was sponsored by De Beers, Rio Tinto and Iluka Resources. Heavy mineral characterization of samples arising from exploration, mining or metallurgical processes is frequently conducted using laboratory heavy liquid analysis. Unfortunately, there are only a limited number of high density (?heavy?) liquids and these tend to be more toxic as their density increases. Low-toxicity inorganic solutions, based on tungsten compounds, have been developed that can be utilized at relative densities (RD) up to 3.0. Beyond this value organic liquids can be used; however, this presents significant health and safety hazards. Diiodomethane (methylene iodide) having a relative density of 3.31 is commonly used. Mixtures of thallium formate and thallium malonate were found in the early 1900s by Clerici to provide liquids having specific gravities between 4.0 and 5.0. For the characterization of the heavy components of mineral sand deposits (e.g. anatase RD 3.9, rutile RD 4.2, ilmenite RD 4.4?4.7 and zircon RD4.6?4.8) there is currently no heavy liquid alternative to Clerici?s solution. Clerici?s solution is highly toxic and testing is now conducted by few laboratories worldwide, with costs reflecting the chemical costs, infrastructure costs and health and safety regimes (e.g. blood testing of exposed staff). A simple laboratory technique of density fractionation has been developed, employing suspensions of fine tungsten carbide particles in lithium heteropolytungstates solutions, that can replace Clerici?s solution in the evaluation of fine mineral sands samples (e.g. -250 +150microns). The developing methodology that can achieve low-cost, low-toxic separations at relative densities above 4.0 is outlined and the comparison of results with Clerici?s solution presented. In addition, preliminary work on density fractionation of zircon samples is presented. Zircon fractionation relates to their inclusion, radionuclide content and metamictization.

Jan 1, 2007

By J. W. Neale

Mintek was a leading participant in the BioMinE project between 2004 and 2008. This project, which was funded in part by the European Commission, was aimed at the development of biotechnology for the minerals industry in Europe. Mintek?s research programme focused mainly on the development of integrated bioleach-based processes for the recovery of base metals from complex, low-grade sulphide concentrates. Specific European mineral resources were targeted and used in integrated piloting campaigns involving bioleaching, solution purification, and metals recovery. This paper describes the use of thermophilic bioleaching for the recovery of nickel and copper from a low-grade nickel-copper concentrate produced at the Aguablanca Mine in southern Spain. Currently, the Aguablanca Mine produces a bulk nickel-copper concentrate for sale to a smelter, and the proposition is to increase the profitability of the operation by the on-site production of metal or metal intermediate. Initially, bench-scale bioleach tests were conducted to determine the bioleach operating conditions. These tests included an evaluation of mesophilic, moderately thermophilic and thermophilic microorganisms. In order to achieve sufficiently high levels of both copper and nickel extraction, a thermophilic process was selected?this was necessary for leaching of the refractory chalcopyrite that occurs in this concentrate. Additional bench-scale test work was carried out to derive a conceptual process flowsheet for the solution purification and metals recovery circuit. The results of the bench-scale tests were used to design, construct and commission an integrated pilot plant, which was subsequently operated at Mintek for over seven months. During this time, the solution purification and metals recovery processes were optimized, and all recycle loops were closed. The final process flowsheet included the following unit operations: concentrate regrinding, thermophilic bioleaching at 70°C, primary iron removal using limestone, copper solvent extraction and electrowinning, secondary iron removal, nickel hydroxide precipitation using magnesia, and final solution purification using lime. Where applicable, process solutions were recycled to preserve water. The process design data derived from this pilot-plant campaign formed the basis for a conceptual engineering study for the developed process. In the study, mass and energy balances were derived, and a process flowsheet was developed and used as the basis for estimating the capital and operating costs of the process. This enabled a preliminary economic analysis of the process to be undertaken. The findings of this study are discussed.

Jan 1, 2009

By D. G. Almond

Low-grade, complex mineral deposits have resulted in the need for complicated large-throughput processing plants delivering increased productivity, reliability, and utilization, together with reducing operational costs. Complex mineralogy has resulted in complicated process flow sheets designed to recover minerals as efficiently as possible. In addition, the remote location of many minerals¬-processing plants, continuously rising energy costs, and fierce competition pose significant challenges to the modern mine, compounded by a global scarcity of qualified and experienced operational personnel. Over the last decade the Internet and automation technologies have undergone major advancements. Automation technologies, solutions, and concepts that existed, but were considered risky or unreliable prior to the year 2000, have now gained acceptance and matured. Furthermore, new technologies and different collaboration schemes have appeared, offering innovative solutions to the mining industry to address many of the challenges described. These advancements in reliable remote systems that access technology through the Internet provide significant opportunity to support mining operations, enhance process performance, provide engineering services, and proactively anticipate and execute maintenance services. This paper references a global survey of automation trends in the mining industry and the potential for an intelligent collaborative environment using automation technologies to exploit opportunities in operating the plant of the future, increasing effectiveness, and reducing operational costs. A variety of possibilities are described, including asset management solutions, remote access capabilities, performance monitoring solutions, advanced process control technologies, and the formation of an intelligent collaborative environment. A real example where this technology is used to support the operation and maintenance at a cement plant in Egypt is given to underpin the concepts described in this paper.

Jan 1, 2013

The peak in Sulphur price late 2008 caused again intensified investigation into the decomposition of sulphates and spend acid. One option is the recycling of sulphur from spend acid, which already started more than 40 years ago in the field of spend acid from organic processes in refineries and acrylic glass manufacturing. Since this acid couldn't be neutralized and discarded due to high organic contents, another source of SO2 to produce sulfuric acid is the decomposition of metal sulfates. The decomposition of metal sulfates was investigated at the next peak in Sulphur price in the 80?s. The first major scale pilot tests and studies of gypsum decomposition were carried out for clients in Florida. The decomposition of gypsum was quite often mainly influenced by the strategic decision of some countries to get own and independent acid production. In other cases the industry doesn?t have enough space to dump the gypsum. Therefore the company was also forced to convert the gypsum into ?saleable? products to avoid these residues. Other projects were made for the recycling of iron-sulfates from the pigment industry. The motivations for these projects were not only given by acid price. For the German pigment industry it was no longer permitted in the 80?s to dump the iron sulphate residues into the sea. These regulations forced the industry to develop new technology, which allows converting of the FeSO4-residues into iron oxide and acid. Therefore economical and mainly environmental factors influenced the decision of the companies to develop and to build these plants. Beside the above mention iron- and calcium-sulphates many other process exist, which produce metal sulphates as an intermediate product. These cases are not forced by environmental or strategic factors. In cases like Ni, Co or Mn-decomposition the main product of the plant is treated in the decomposition plant and later on used as ferrous-alloys. These final products are higher in price compared to e.g. CaO, which exclude the high-energy consumption for the endothermic chemical decomposition reaction. The reaction of SO2 generation based on acid or sulfate decomposition takes place in the range of 1000°C. The energy demand of the endothermic reaction is considerable and leads due to the high fuel-combustion off-gas stream to a diluted SO2 gas. Energy prices are usually increasing at the same time like sulphur. Sulphuric Acid based on decomposition is therefore more expensive than as acid based on sulphur combustion. The paper describes fluid bed technology and possible process concepts for decomposition plants. Additionally the thermodynamic background of the decomposition process and the main influence factors are provided to receive a better understanding of this technology.

Jan 1, 2009

By S. Tu, Y. Yuan, H. Wei, Z. Chen, M. Jia

"To reduce production costs and increase efficiency in ageing coal mines, a system that utilizes two shearers in a fully mechanized longwall working face is proposed. Using theoretical and engineering experience, three issues pertaining to the system were determined: (a) the two-shearer mining technique; (b) matching and modifying the equipment; (c) and coal-cutting task allocation for each shearer. Two mining processes are proposed, with the two shearers travelling in either the same or opposing directions. To avoid breakage of chains and pan extrusion of the armoured face conveyor (AFC), the length of the AFC ‘snake’ was controlled. To ensure continuous cutting and transporting of coal, the cross-sectional dimensions of the AFC were checked and the shearer closer to the head drive was modified. Based on the assumption of equal cutting times for each shearer, the meeting position of the two shearers was obtained by using a theoretical model of mining task allocation. Application of this technique at No. 2 Jining Mine, China, has shown remarkable benefits: daily production capacity was increased by 54% and personnel efficiency was improved by 33 t/d per person. IntroductionAll coal mines aim to increase the unit output of the working face to reduce mining costs and improve the economic efficiency of the operation. To achieve this goal, a production model known as one mining face of the mining area has been adopted by most Chinese coal mines (Hu, Meng, and Zhu, 2008; Zhang, Zhang, and Wang, 2000). Under these conditions, the main technical approaches to maximize the output are increasing the width of the working face (Qu, Xu, and Xue, 2009) and accelerating the advancing speed (Robbins, 2000). In coalfields with shallow seams, the width of a fully mechanized face exceeds 300 m (Ju and Zhu, 2015; Fu, Song, and Xing, 2010); in coalfields with deep seams, the width of the face is usually greater than 240 m (Liu et al., 2016; Li et al., 2013). The term ‘super-long working face’ was proposed to describe working faces with a width of over 240 m (Zhao and Song, 2016; Xu et al, 2007) in China. To support these long working faces with rapid advancing speeds, high-powered mining equipment is required (Kulshreshtha and Parikh, 2001, 2002; Tu et al., 2009; Mishra, Sugla,and Singha, 2013). This is easily achieved in newly built mines, but is not a good choice for ageing mines because of the low return on a high investment on account of the limited remaining resources. It is therefore difficult for ageing mines to significantly increase their unit output with the existing mining equipment. This study focused on this problem: two shearers were applied to a longwall fully mechanized working face (LFMWF) to achieve increased unit output."

Oct 1, 2018

[The following notations will be used: O an ore body. z a point in O. z' another point in O. w0 (z) a point support of infinitely small dimensions w0 centred in z. w (z) a sample (or block) of finite dimensions kv centred in z. W (z) a block of size W greater than or equal to w. W'(z) a block of size W' greater than or equal to W. W" (z) a block of size W" greater than or equal to W'. x (z) value of the regionalized variable x with support wO at point z. p (z) average value of x in w (z). pw WZ) = E[x(z')l zt in w(z) pw (z) average value of x in W (z). pwl (z) average value of x in W' (z). pwU (z) average value of x in W" (z). Note that pW (z), pw (z), pwf (z) and pw,, (z) are (regular- ized) regionalized variables with support w, W, W' and W" respectively. The relative sizes of wO, w, W', W" and O are represented schematically in Fig. 7.1. The variance of pw (z) when w (z) takes all possible positions in O is known as the dispersion variance of w in O and is denoted by a? (w in O) or a\: 0; = a2(w in a = Ew,z, inn {[p~ (z) - p121. (7.1) For convenience, the following simpler notation will be used: a> Ew in n [(p w - pl21. Consider now a large block W (z) in O with average value p~(z), and all the possible smaller blocks (or samples) w (z') of size w in W (z). We can calculate the variance of the blocks w (z') in the block W(z), which is the dispersion vaciance of w in W (z), from the relationship a2 [w in W(z)l = Ewcz,, in W(Z) {[PW (z') -pw (z)l21. (7.2) Provided the intrinsic hypothesis is satisfied (§3.4.4), this variance is a function only of the dimensions of the supports w and W, and is independent of the position z of the block W (z). We can therefore define the dispersion variance of w in W, as follows: u2 (win W) = Ew in w [(ptti - PW)~]. (7.3) In cases where the intrinsic hypothesis is not satisfied, the variance of samples w in blocks W may vary only slightly from block to block, so that the average dispersion variance of w in W (z) for all possible W (z) in O can be used: ayw in W) = Ew(,, ~n n {a2 [W in W (z)]}. (7.4) The following example will help to illustrate the importance of the variance of dispersion. Assume that we plan to develop a bedded coal deposit Q. We consider mining the ore body with only one giant dragline, which will extract each day a block of coal of size W'. The total area mined in a year will have a size W". We want to know whether this scheme is acceptable, given that the daily variation in ash content must not exceed a given percentage specified in the sales contract, which is renewable on a yearly basis. On a given day, if we mine the block W' (z), the ash content will average pwT (z). In a period of one year, the expected daily variation in ash content is measured by the expected variance of pwf (z) in W", i.e. by a2 (W'in W"). An alternative mining method might be to use two smaller draglines, each one mining W'/2 of ore per day, and Wn/2 per year. If the draglines are used to mine two distinct sections of the deposit, the expected daily variation in ash content will be u2 (W'/2 in Wj1/2)/2 Other situations, where economic decisions cannot be made without knowledge of the dispersion variance, are illustrated in § 7.4 and 7.5 below. Remark: The notation a2 (w in W) is used in this publication because of its clarity. An alternative notation, which is increasingly accepted in the literature, is s2w/W. ]

Jan 1, 1978

"Sampling error and bias, especially the Increment Preparation Error (IPE), are introduced when the tool allocated to do the job fails to extract a representative sample. This is the case with chip sampling; the tool can only extract haphazard shapes of loose or fractured material and not always from within the demarcated sample area. Increment Extraction Error (IEE) and Increment Delimitation Error (IDE) could be severe, but are found to be relatively unbiased. The uncontrolled action of the sampler in discarding excess sample material after sample collection has a significant impact on the error and bias introduced with each and every extraction. A new type of bias, referred to as the ‘waste discard bias’, arises when samplers select what portion of the excess sample material to discard at the sample site. Material visually identified as waste is discarded in preference to mineralized broken ore if there is an excess of sample material. This results in a considerable error in the analytical results. The bias is proportional to the reef-waste ratio in the demarcated sample. IntroductionTwo types of ‘sampling’ are distinguished, namely sampling of particulate materials (broken ores) and sampling of solid, unbroken in situ mineralized reef. This study considers only chip- or face-sampling of in situ, goldbearing, carbon-rich conglomerates typical of the Upper Witwatersrand Supergroup and examines where components of sampling error and bias, clearly specified in the Theory of Sampling, may arise during the practice of ‘face sampling’. Many millions of face samples have been extracted from Witwatersrand-type mines using a hammer and chisel, and detailed descriptions (standard operating procedures) of how the samples should be taken have been developed by many mining companies. There is, however, no taxonomy or nomenclature for managing or reporting the different types of errors associated with chip sampling. The Theory of Sampling compiled by Pierre Gy in the early 1950s provides, comprehensive nomenclature of sampling errors that is applied to particulate sampling of ore in a lot, a stockpile, or a moving stream on a conveyor belt. The taxonomy and characteristics of sampling errors, grouped according to the sources from which they arise, and identified by Gy (1973, 1979, 1982, 1992, 1995, and 1998) are shown in Figure 1. This classification of errors is used extensively in regard to the sampling of particulate materials in the mining and minerals industry, but not in regard to chip sampling. A relatively small mass (hundreds of grams) of representative particulate material for estimating the average grade of a much larger mass (thousands of tons – the ‘lot’ in the Theory of Sampling) is extracted by the chipping or cutting of a representative rock ‘sample’ from the stope face."

Jan 1, 2016

By J. J. Cilliers, I. K. Craig, J. D. le Roux, K. Hadler

An analysis of the state-observability characteristics of a dynamic tank-to-tank model of a flotation bank indicates that the concentrate-flow rate of each tank can be estimated from accurate measurements of the pulp height in each tank and the final tailings flow-rate exiting the final tank. Therefore, there is an opportunity to construct an observer (model-based soft-sensor) which can estimate the concentrate flow-rate of tanks in a flotation bank. The concentrate flow-rate, i.e. mass pull, is generally measured by means of froth image analysers on industrial plants. A model-based soft-sensor will not only provide a means to validate froth image analyser results, but could potentially substitute them as they are less expensive to implement and maintain. Keywords: Concentrate flow-rate, estimation, flotation, modelling, observability, soft-sensor

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 N. Naude, W. P. Roux, O. Kaba

Ceramic filtration plates are used for dewatering slurries with high solid concentrations and particles in the size range of 30 μm to 150 μm. After extensive operating times, the ceramic filter plates at Minas Rio in Brazil begin to blind due to the precipitation of barium sulphate on the surface of the ceramic filter plate, which reduces the overall efficiency of the filtration process. Further research is needed to identify the barium precipitate phases on the blocked filter plates and its thermodynamic and kinetic behaviour in the system. A crystallography analysis was performed on the sample and the results showed that there are two different sets of precipitates formed on the filter plate: grey crystals which were large and scatted on the filter plate and red micro crystals that covered the entire surface of the filter plate. The red microcrystals on the sample were identified with XRD, which indicated that the sample contained barium sulphate in the mineral form barite. Experiments were conducted to determine the optimum conditions under which barium precipitation will occur. The conditions tested as a possible driving force for barium sulphate precipitation were the effect of temperature, pH and concentration. The pH and temperature ranges were pushed to both the lower and higher boundaries. The effect of temperatures as low as 15oC was studied and pH levels of 7 and upwards. The first nuclei started appearing at a pH of 7 but significant growth is promoted at higher pH levels. The X-Ray diffraction analysis confirmed the phase of the precipitates formed, and the orthorhombic crystallographic structure formed is a characteristic of barium sulphate. Keywords: Iron ore, barium sulphate, temperature, pH, concentration, morphology, and ceramic filter plate

Jan 1, 2020