Optimization of dense medium cyclone plant for the beneficiation of low grade iron ore with associated high proportion of near-density material at Sishen Iron Ore Mine

A research report submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the Degree of Master of Science in Engineering (Metallurgy and Materials Engineering) July 2015The research report is premised on three aspects which are critical in the heavy mineral beneficiation. These aspects are classified as (i) understanding the densimetric profile of the available ore body, (ii) understanding the properties of the heavy medium utilised at the plant to beneficiate the ore, and (iii) the automation and modelling of the processing plant in order to maximise plant efficiency. Ore characterisation is mainly focused on understanding the densimetric profile of the ore body, in order to determine the probability of producing a saleable product as well as predicting the expected yields and quality. This is done to utilise the endowment entrusted upon the operating entity by the government and shareholders to treat the mineral resource to its full potential. Understanding of the beneficiation potential of the ore body will assist the mine planning and processing plant to optimise the product tons and quality. This will ensure the marketing plans are in accordance with the expected product as beneficiation will vary depending on the mining block reserves. The mining blocks have potential to produce varying product grades with different recoveries. Ore characterisation was conducted on the GR80 mining block, low-grade stockpiles (i.e. C-grade ore reserves & Jig discard and dense medium separation (DMS) run-of-mine (ROM) material. The GR80 material was characterised as having low proportion of near-density material and would be easy to beneficiate as well as produce high volumes of high grade product. Furthermore, it was revealed that the 2014 DMS ROM had an increased proportion of low-density material; however this material was also had low proportion of near-density material. The low-grade stockpiles was characterised by high proportion of near density material, which necessitate the beneficiation process to operate at high density in excess of 3.8 t/m3. Maintaining a higher operating density requires more dense medium which leads to viscosity problems and impact performance. The characterisation of the FeSi medium was imperative to understand its behaviour and potential influence on beneficiation of low-grade stockpiles and mining blocks with elevated proportion of near-density material. As the proportion of near-density waste material increases in the run-of-mine (ROM), it is necessary to beneficiate the material at elevated operating medium densities. However, when cyclones are operated at high densities, the negative influence of the medium viscosity becomes more apparent and thus influences the separation efficiency. Heavy medium, ferrosilicon (FeSi) characterisation looked at identifying the effects of viscosity on the FeSi stability and whether there would be a need for a viscosity modifier. Thus, the importance of controlling the stability, viscosity, and density of the medium cannot be under-estimated and can very often override the improvements attainable through better designs of cyclones. Furthermore, the slurry mixture of the heavy medium utilised for the purpose of dense medium separation should be non-detrimental to the effectiveness of separation in the DMS Fine cyclone plant. Medium characterisation showed that removal of ultra-fines leads to unstable media as indicated by faster settling rates. This would result in medium segregation in the beneficiation cyclone thereby leading to unacceptable high density differential which will negatively impact the cut-point shift and cause high yield losses to waste. The overall control of the metallurgical processes at Sishen’s Cyclone Plant is still done on manually and thus operation still varies from person-to-person and/or from shift-to-shift. This result in some of the process data and trends not being available online as well as being captured inaccurately. Furthermore, this negatively affects the traceability and reproducibility of the production metallurgical key performance indicators (KPI’s) as well as process stability and efficiency. It has been demonstrated that real-time online measurements are crucial to maintaining processing plant stability and efficiency thereby ensuring that the final product grade and its value is not eroded. Modelling and automation of the key metallurgical parameters for the cyclone plant circuit was achieved by installation of appropriate instrumentation and interlocking to the programmable logic control (PLC). This allowed for the control of the correct medium sump level, cyclone inlet pressure, medium-to-ore ratio as well as online monitoring of density differential as “proxy” for medium rheological characteristics. The benefit of modelling and simulation allows the virtual investigation and optimisation of the processing plant efficiency as well as analysis of the impact of varying ore characteristics, throughput variations and changing operating parameters. Therefore it is imperative that all cyclone operating modules are operated at the same efficiency which can be achieved by optimized process through proper automation and monitoring, thereby improving the total plant profitability. Keywords: dense medium separation; densimetric profile; dynamic modelling; FeSi rheology; iron-ore beneficiation; process automation; process control

Affected Relative Pair Linkage Statistics That Model Relationship Uncertainty

Most of the complex diseases have major public health concern in United States. Linkage analysis helps to map disease genes, and we have proposed linkage statistics that give higher power in real data scenario where the true family structure might not be known. In linkage analysis with affected related pairs (ARP), stated familial relationships are usually assumed to be correct, thus misspecified relationships can lead to either reduced power or false-positive evidence for linkage. In practice, studies either discard individuals with erroneous relationships or use the best possible alternative pedigree structure. We have developed several linkage statistics that model the relationship uncertainty by properly weighting over possible true relationships. We consider ARP data for a genome-wide linkage scan. Simulation study is performed to assess the proposed statistics, and compare them to maximum likelihood statistic (MLS) and Sall LOD score using true and discarded structures. We have simulated small and large pedigree datasets with different underlying true and apparent relationships, and typed for 367 microsatellite markers. The results show that two of our relationship uncertainty linkage statistics (RULS) have power as high as MLS and Sall using the true structure. Also, these two RULS have greater power to detect linkage than MLS and Sall using the discarded structure. Thus, our RULS provide a statistically sound and powerful approach for dealing with the commonly encountered problem of relationship errors.To apply RULS on a real data, we have used Otitis Media with effusion (OME) data from Caucasian families. OME is an infection causing fluid in the middle ear, and is the most common cause of hearing loss among young children. We have recruited subjects (with history of tympanostomy tube insertion) and their families (parents and affected/unaffected siblings). Genotyping was done using Affymetrix 10K SNP chip technology, and out of 1584 enrolled individuals (322 families), 1191 (305 families) are genotyped at this date. We performed nonparametric multipoint linkage analysis using conservative dataset. The preliminary results show suggestive linkage peaks on chromosomes 2, 7 and 10, the highest being on chromosome 7 (rs2014450, 153cM) with Sall LOD score of 2.08 (p-value 0.001)

XVIII International Coal Preparation Congress

Changes in economic and market conditions of mineral raw materials in recent years have greatly increased demands on the ef fi ciency of mining production. This is certainly true of the coal industry. World coal consumption is growing faster than other types of fuel and in the past year it exceeded 7.6 billion tons. Coal extraction and processing technology are continuously evolving, becoming more economical and environmentally friendly. “ Clean coal ” technology is becoming increasingly popular. Coal chemistry, production of new materials and pharmacology are now added to the traditional use areas — power industry and metallurgy. The leading role in the development of new areas of coal use belongs to preparation technology and advanced coal processing. Hi-tech modern technology and the increasing interna- tional demand for its effectiveness and ef fi ciency put completely new goals for the University. Our main task is to develop a new generation of workforce capacity and research in line with global trends in the development of science and technology to address critical industry issues. Today Russia, like the rest of the world faces rapid and profound changes affecting all spheres of life. The de fi ning feature of modern era has been a rapid development of high technology, intellectual capital being its main asset and resource. The dynamics of scienti fi c and technological development requires acti- vation of University research activities. The University must be a generator of ideas to meet the needs of the economy and national development. Due to the high intellectual potential, University expert mission becomes more and more called for and is capable of providing professional assessment and building science-based predictions in various fi elds. Coal industry, as well as the whole fuel and energy sector of the global economy is growing fast. Global multinational energy companies are less likely to be under state in fl uence and will soon become the main mechanism for the rapid spread of technologies based on new knowledge. Mineral resources will have an even greater impact on the stability of the economies of many countries. Current progress in the technology of coal-based gas synthesis is not just a change in the traditional energy markets, but the emergence of new products of direct consumption, obtained from coal, such as synthetic fuels, chemicals and agrochemical products. All this requires a revision of the value of coal in the modern world economy

Design and development of an on-line sedimentation analyser

This thesis describes the design and development of a multiple vibrating reed analyser for the routine on-line procurement of sedimentation kinetic data in two phase media. Briefly, each reed system comprises a stainless steel rod pinned at an intermediate point along its length. One end is exposed to the settling suspension whilst the other is driven into transverse vibration at resonance using an alternating current electromagnet. The principle of operation of the device relies on the fact that the resonance frequency of a stiff reed performing simple harmonic motion in a fluid medium is directly related to the fluid bulk density. In the case of a settling solid/liquid suspension, or a two-phase liquid dispersion containing a heavier phase, the fluid bulk density and hence the hydrodynamic head decreases with time as the heavier phase settles. Sedimentation kinetic data including settling velocities and flux profiles are in turn obtained by continuous monitoring of the resonance frequencies of a number of reeds positioned at set levels along a settling tank. The feasibility of operation of the analyser has been successfully verified in conjunction with a variety of model and industrially relevant systems. The former include mono and polydisperse glass ballotini / water mixtures with solids particle size and concentration ranges 55 - 200 μ and 1.75 - 2.81 % v/v respectively. Measured settling velocities are in excellent accord (ca. ± 0.1 %) with those obtained from direct visual observation of suspension-clear liquid interfaces. The industrially relevant systems include kaolin/water suspensions with solids concentrations as high as 20 % v/v and oil / water emulsions with light phase concentrations in the range 30 - 50 % v/v. The performance of a number of empirical models including those proposed by Richardson and Zaki (1954), Garside and Al-Dibouni (1977), Bamea and Mizrahi (1973), Reed and Anderson (1980), Batchelor (1972) and Happel (1958) has been evaluated by comparing predicted settling velocities with those obtained using the analyser. We find that the model proposed by Richardson and Zaki produces the best agreement (ca ± 1.3 %) whilst Happel's model (1958) produces the worst results (ca ± 24 %). For polydisperse systems we observe that measured interface velocities correspond to Stokes (1851) particle sizes which are in reasonable agreement (ca. ± 6 %) with the experimentally determined smallest significant particle size in the sample distribution. Also, as the initial solids concentration increases, the Stokes diameter decreases indicating a greater tendency for particles to segregate resulting in more diffuse interfaces. Therefore, the behaviour of such systems is characterised by differential rather than hindered settling. By measuring the time delay between the onset of sedimentation and that resulting in a change in reed resonance frequencies at various locations along the settling tank we have been able to obtain estimates of propagation wave velocities marking the transition between steady and unsteady state behaviour. For the systems tested we find that the wave propagation velocity is, in general, independent of solids concentration but increases with the mean particle size

Äänisisällön automaattisen luokittelun menetelmiä

This study presents an overview of different methods of digital signal processing and pattern recognition that are frequently applicable to automatic recognition, classification and description of audio content. Moreover, strategies for the combination of the said methods are discussed. Some of the published practical applications from different areas are cited to illustrate the use of the basic methods and the combined recognition strategies. A brief overview of human auditory perception is also given, with emphasis on the aspects that are important for audio recognition.Tässä työssä esitetään yleiskatsaus sellaisiin signaalinkäsittelyn ja hahmontunnistuksen menetelmiin, jotka ovat usein sovellettavissa äänisisällön automaattiseen tunnistamiseen, luokitteluun ja kuvaamiseen. Lisäksi työssä esitetään strategioita mainittujen menetelmien yhdistelyyn ja annetaan näihin ratkaisuihin liittyviä esimerkinomaisia viitteitä kirjallisuudesta löytyviin käytännön sovelluksiin eri sovellusalueilta. Työ sisältää myös suppean esityksen ihmisen kuulon toiminnan pääpiirteistä äänitunnistuksen kannalta

Characterising the acid mine drainage potential of fine coal wastes

Includes bibliographical references.Acid mine drainage (AMD) is one of the major environmental challenges facing the South African mining sector. Acid mine drainage has received significant public attention in recent years. South Africa's long mining history has led to a growing concern that coal-related AMD from these mines (both operational and defunct) will continue for centuries to come. Pyrite bearing fine waste, generated during coal preparation and beneficiation, is thought to carry a significant amount of AMD pollution risk. Coal-related AMD generation has not been afforded the same exposure as AMD generation from high sulphide minerals such as gold and copper ores. This is exacerbated by the growing concern over water quality degradation in the Mpumalanga region of South Africa. The development of integrated solutions to address the management of coal-related AMD requires an understanding of the principle causes behind coal-related AMD. To date, most of the prediction methods described in literature have been derived for the prediction of AMD in metal bearing ores. Furthermore, some of these methods are based on assumptions and do not take into consideration the various sulphur species present. Additionally, some of these methods have limited applicability to coal due to the high total organic carbon content (TOC) of the material. This research project attempts to address these short comings and uncertainties by developing a systematic and meaningful framework for the characterisation of South African coal and coal waste. The research project contributes to the knowledge of coal-related AMD with particular emphasis on the characterisation methods responsible for sulphur speciation and mineralogy for coal. The approach entails carrying out a case study assessment aimed at empirically assessing a coal tailings sample according to: particle size distribution, textural reference, mineralogical characteristics, and how the aforementioned factors influence the acid potential in coal. The approach intends to address key factors which include: identifying the sulphur bearing organic and inorganic constituents related AMD generation in coal, assessing how the mineralogy, texture and particle size distribution contribute to AMD potential in coal tailings, and then identifying suitable analytical techniques and test methods which can provide data. The combination of these key outcomes will seek to provide a systematic and meaningful framework for the characterisation of coal and coal waste streams. The characterisation methods used in this case study outlined a framework focusing on four main areas of acid mine drainage characterisation for coal wastes, these included: chemical characterisation, mineralogical characterisation, sulphur speciation and AMD prediction. This comprehensive approach employed a suite of techniques, including: petrography, quantitative x-ray diffraction (QXRD) and quantitative evaluation of minerals by scanning electron spectrometry (QEMSCAN)

Methods and Applications for Collection, Contamination Estimation, and Linkage Analysis of Large-scale Human Genotype Data

In recent decades statistical genetics has contributed substantially to our knowledge of human health and biology. This research has many facets: from collecting data, to cleaning, to analyzing. As the scope of the scientific questions considered and the scale of the data continue to increase, these bring additional challenges to every step of the process. In this dissertation, I describe novel approaches for each of these three steps, focused on the specific problems of participant recruitment and engagement, DNA contamination estimation, and linkage analysis with large data sets. In Chapter 1, we introduce the subject of this dissertation and how it fits with other developments in the generation, analysis and interpretation of human genetic data. In Chapter 2, we describe Genes for Good, a new platform for engaging a large, diverse participant pool in genetics research through social media. We developed a Facebook application where participants can sign up, take surveys related to their health, and easily invite interested friends to join. After completing a required number of these surveys, we send participants a spit kit to collect their DNA. In a statistical analysis of 27,000 individuals from all over the United States genotyped in our study, we replicated health trends and genetic associations, showing the utility of our approach and accuracy of self-reported phenotypes we collected. In Chapter 3, we introduce VICES (Verify Intensity Contamination from Estimated Sources), a statistical method for joint estimation of DNA contamination and its sources in genotyping arrays. Genotyping array data are typically highly accurate but sensitive to mixing of DNA samples from multiple individuals before or during genotyping. VICES jointly estimates the total proportion of contaminating DNA and identify which samples it came from by regressing deviations in probe intensity for a sample being tested on the genotypes of another sample. Through analysis of array intensity and genotype data from HapMap samples and the Michigan Genomics Initiative, we show that our method reliably estimates contamination more accurately than existing methods and implicates problematic steps to guide process improvements. In Chapter 4, we propose Population Linkage, a novel approach to perform linkage analysis on genome-wide genotype data from tens of thousands of arbitrarily related individuals. Our method estimates kinship and identical-by-descent segments (IBD) between all pairs of individuals, fits them as variance components using Haseman-Elston regression, and tests for linkage. This chapter addresses how to iteratively assess evidence of linkage in large numbers of individuals across the genome, reduce repeated calculations, model relationships without pedigrees, and determine segregation of genomic segments between relatives using single-nucleotide polymorphism (SNP) genotypes. After applying our method to 6,602 individuals from the National Institute on Aging (NIA) SardiNIA study and 69,716 individuals from the Trøndelag Health Study (HUNT), we show that most of our signals overlapped with known GWAS loci and many of these could explain a greater proportion of the trait variance than the top GWAS SNP. In Chapter 5, we discuss the impact and future directions for the work presented in this dissertation. We have proposed novel approaches for gathering useful research data, checking its quality, and detecting associations in the investigation of human genetics. Also, this work serves as an example for thinking about the process of human genetic discovery from beginning to end as a whole and understanding the role of each part.PHDBiostatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162998/1/gzajac_1.pd

Explicit-Duration Hidden Markov Model Inference of UP-DOWN States from Continuous Signals

Neocortical neurons show UP-DOWN state (UDS) oscillations under a variety of conditions. These UDS have been extensively studied because of the insight they can yield into the functioning of cortical networks, and their proposed role in putative memory formation. A key element in these studies is determining the precise duration and timing of the UDS. These states are typically determined from the membrane potential of one or a small number of cells, which is often not sufficient to reliably estimate the state of an ensemble of neocortical neurons. The local field potential (LFP) provides an attractive method for determining the state of a patch of cortex with high spatio-temporal resolution; however current methods for inferring UDS from LFP signals lack the robustness and flexibility to be applicable when UDS properties may vary substantially within and across experiments. Here we present an explicit-duration hidden Markov model (EDHMM) framework that is sufficiently general to allow statistically principled inference of UDS from different types of signals (membrane potential, LFP, EEG), combinations of signals (e.g., multichannel LFP recordings) and signal features over long recordings where substantial non-stationarities are present. Using cortical LFPs recorded from urethane-anesthetized mice, we demonstrate that the proposed method allows robust inference of UDS. To illustrate the flexibility of the algorithm we show that it performs well on EEG recordings as well. We then validate these results using simultaneous recordings of the LFP and membrane potential (MP) of nearby cortical neurons, showing that our method offers significant improvements over standard methods. These results could be useful for determining functional connectivity of different brain regions, as well as understanding network dynamics