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By J. D. T. Steyl

"This paper presents a phenomenological model of the rate of iron(III) precipitation in batch and continuous autoclaves at medium temperature operating conditions. The rate expressions are based on information obtained from the literature and experimentation at low and high pulp densities. Special allowance is made for the formation of surface nuclei, which appears to be promoted at a higher iron(III) precipitate surface area, especially in suspensions of lower terminal acidity. This leads to the formation of secondary particulates and provides the required link to simulate high pulp density leaching-precipitation systems, using low pulp density batch precipitation data. In particular, the model allows direct application of the simulation to the autoclave oxidation of iron-containing copper sulfide concentrates and provides a good estimation of the relative precipitation rate of hematite, the preferred product, compared to hydronium jarosite. Some interesting mechanistic understandings of iron(III) precipitation in autoclaves are further elucidated.INTRODUCTIONThe objective of this work is to describe the rate of iron(III) precipitation and the relative amounts of hematite compared to hydronium jarosite precipitation during batch and continuous chalcopyrite oxidation under medium temperature (MT) (~130 to 160ºC) autoclave conditions. Published information has not yet revealed sufficient mechanistic insights about this sparingly soluble salt system under these conditions. The rate expressions in this paper are based in part on current literature information, supplemented by qualitative experimental observation at low pulp density conditions, in particular the high-resolution backscatter electron (BSE) images and particle size distributions (PSDs) of the precipitates. A summary of this work and insights from the literature are presented first, after which the behaviour of iron(III) in high pulp density leaching systems is used to derive a phenomenological expression of the effect of existing iron(III) precipitate surface area on the precipitation rate. The overall regression encapsulates all the experimental results, i.e., those obtained in both batch and continuous autoclave configurations (Steyl, 2012a)."

Jan 1, 2012

By J. A. Meech, G. R. Baiden

"A dynamic simulation of a mine-mill complex has been conducted using networked microcomputers (IBM PC/AT and IBM PC/XT). These models allow simultaneous operation of an open pit using shovels and trucks, a primary crusher, and a secondary crushing plant. Each process transmits information via the network, linking all operations together. The effects of blasting, ore quality, equipment utilization and configuration on productivity can be studied either interactively or from a report listing at the end of each shift. Programs are menu driven leading the user through the decisions required in day to day operations. The mine-mill simulator is currently being used as a teaching tool at Queen's University to provide senior mining and mineral processing engineering students with an experience and appreciation for the operating problems across the mine-mill interface. The need for coordination and close communication between the mine and mill can be aptly demonstrated using these models. The simulator could be used to contribute to the training of operating personnel in a real mining operation. INTRODUCTIONThis paper describes a computer simulator that is capable of showing the interactions and operating strategies between a mine and a secondary crushing plant. The simulator uses two models developed at Queen's University; one for open pit mining and the second for secondary crushing. PITSIM is a dynamic shovel/truck haulage model origin2lly developed by P.D.D. Chick (1) and K.G. Fytas (2) to solve shovel/truck scheduling problems. CRUSHSOFT is a dynamic secondary crushing plant model developed by R.J. Tucker (3) and C.A. Harris (4) to study alternative operating and control strategies in a crushing plant."

Jan 1, 1987

By Sudarshan Martins

The measurement of acoustic signals produced by a tumbling mill has been previously used to determine the operating state of the mill and correlate the variations of the sound intensity with the operating conditions of the mill. Separately, the discrete element model (DEM), a software simulation of the mill, was developed to provide insight into the operation of the mill. Presently, there has not been much work reconciling the DEM simulation of the mill with the acoustic signal. Working from basic principles of linear, time-invariant systems, agreement between an acoustic DEM simulation and the measured signal is sought. First, the impulse response function of the mill is measured. The DEM provides the forces applied to the mill shell as a function of time. A convolution of these simulated shell forces and the transfer function gives the simulated acoustic signal. This signal is compared to the measured acoustic signal, both in the time domain and the frequency domain. Finally, a discussion of the results is given.

Jan 1, 2012

By Arnaud Faucher, Amar Sabih, Sudarshan Martins, Tristan Martin, Sami Makni, Peter Radziszewski, Poorya Hosseini, Francois-Raymond Boyer

The measurement of acoustic signals produced by a tumbling mill has been previously used to determine the operating state of the mill and correlate the variations of the sound intensity with the operating conditions of the mill. Separately, the discrete element model (DEM), a software simulation of the mill, was developed to provide insight into the operation of the mill. Presently, there has not been much work reconciling the DEM simulation of the mill with the acoustic signal. Working from basic principles of linear, time-invariant systems, agreement between an acoustic DEM simulation and the measured signal is sought. First, the impulse response function of the mill is measured. The DEM provides the forces applied to the mill shell as a function of time. A convolution of these simulated shell forces and the transfer function gives the simulated acoustic signal. This signal is compared to the measured acoustic signal, both in the time domain and the frequency domain. Finally, a discussion of the results is given.

Jan 1, 2012

By João Felipe Costa, Jair Carlos Koppe, André C. Zingano

Abstract - Traditional mine planning based on block models built with interpolation techniques such as kriging does not take into account the uncertainty associated with the estimates. These models are inadequate for short-range mine planning. In contrast, conditionally simulated models reproduce the actual variability (histogram) and spatial continuity (variogram) of the attributes of interest. Conditional simulation can be used to address the problem of measuring the uncertainty associated with an estimate. This paper outlines how the sequential Gaussian conditional simulation algorithm can be used to assess uncertainty of grade estimates and also illustrates how simulated models can be incorporated into mine planning and scheduling. A case study demonstrates the efficiency of the method in assessing risk associated with geological and engineering variables.

Jan 1, 2000

By S. Sundararajan, Z. Lin

ABSTRACT Fierce market competition and demand have made it imperative for mining companies to achieve higher productivity and operational efficiency. The selection of the best mining method and equipment combinations will enable companies to meet production and efficiency targets. Continuous mining is increasingly preferred by companies for its high efficiency and low unit costs. We developed simulation models for two continuous mining systems: the continuous surface miner (CSM) system and the at-face slurrying (AFS) system. Considering two different case studies, the paper discusses application of developed models to determine the optimal number of trucks and equipment capacities for the two systems.

Jan 1, 2013

By J. T. Chen, S. Winkler, M. J. Worswick, O. Orlov

This paper presents a review of research conducted at the University of Waterloo concerned with the application of aluminum alloy sheet and tube in automotive structures and body panels. The research has focussed on formability prediction and results using a range of damage-based formulations. These models include continuum-level damage approaches and, more recently, a so-called percolation damage approach intended to capture microstructural heterogeneity effects on damage development. This paper presents applications of these damage approaches to simulate formability of experiments considering stretch flange panels. The experiments consider drawbead effects associated with the bend/unbend deformation as the material flows through the drawbead. Recent work on simulating in situ X-ray tomography experiments that capture damage evolution during tensile deformation will also be reviewed.

Jan 1, 2006

By S. Razavialavi

In the planning phase of every construction project, layout of temporary facilities is a crucial task; site layout can affect safety, travel cost and time, construction productivity, and space utilization. However, site layout planning can be a complicated problem, due to the interdependency of influencing factors. Although interaction among activities is one of the major drivers of site layout planning, it has not been properly addressed in past research. In this study, simulation is presented as a promising tool to address this gap. The capability of simulation technology to model complex processes in construction projects makes use of simulation tools in site layout optimization problems effective, while existing methods are unable to perfectly model these problems, in some cases. Additionally, the advantages and challenges of implementing simulation are assessed and a generic framework for simulation application in site layout planning is proposed.

Aug 1, 2013

By D. W. Ginsberg, D. Cieplinski

"The lifetime cost of a material handling system, or any mine system, can be reduced through the application of quality engineering. Dynamic simulation is a powerful tool that can be used to enhance the experience and ingenuity of the design team. It cannot only de-bottleneck the system to improve system productivity, but also define critical design criteria to eliminate over-design and reduce capital cost. Eliminating over-design also reduces operating costs by lowering component replacement costs and by ensuring all parts of the system operate at a higher utilization and efficiency. IntroductionA mine owner’s profitability is improved when a mine is developed at the lowest lifetime cost. This cost relates not only to capital and operating costs, but also, to a great extent, on the efficiency and reliability of the operation. These factors are tied directly to the quality of the engineering which depends on the experience of the engineers involved, and their ability to apply known system information in a rational and constructive manner.It is becoming apparent that it is increasingly more difficult to deliver the quality of engineering expected and needed to provide attractive lifetime costs using traditional design methods. Historically, system information has been evaluated based on a limited amount of information to which global rules-of-thumb and the engineer’s personal experience were applied to develop design criteria. However, market forces are dictating that more system parameters be defined and that they be defined more accurately so that the most economical system can be developed. This increase in the volume of information and the need for more accurate predictions is straining, if not already exceeding, the ability of engineers to apply simple global rules of- thumb and to combine all the information in a rational, comprehensive and representative set of design criteria. Furthermore, as proposed system production rates increase beyond established industry practice, the extrapolation of the engineer’s experience becomes more difficult and increases the risk in the proposed design."

Jan 1, 1998

By Peter Rubie

For many years, optimising the relining of hard rock grinding mills has been complicated by: ?? the large number of variables; ?? the low frequency of relines (slow feedback loop); ?? the potential economic risk associated with some changes. A technology that has its roots in the automotive manufacturing industry is being utilised to construct a statistically accurate, configurable, and dynamic simulation of the mill relining process. The effects of various mechanisation and process changes can be rapidly modelled and compared. This technology will provide mill maintenance managers and contract relining companies with the opportunity to benchmark current performance against world?s best practice. It will also provide an opportunity for concentrator plant designers and mill manufacturers to plan for maximum plant efficiency, by designing an infrastructure and equipment combination that maximises annual plant availability. This simulation tool and its associated data set, has been developed using recent grinding mill performance data from mills of varying dimensions, liner configurations, mill relining equipment, operator and tool variables. The simulation will provide an output that the various stakeholders can utilise to make optimal decisions within the given financial, physical and technological constraints of the individual concentrator plant.

Jan 1, 2012

By Peter Rubie

"For many years, optimising the relining of hard rock grinding mills has been complicated by:?? the large number of variables;?? the low frequency of relines (slow feedback loop);?? the potential economic risk associated with some changesA technology that has its roots in the automotive manufacturing industry is being utilised to construct a statistically accurate, configurable, and dynamic simulation of the mill relining process. The effects of various mechanisation and process changes can be rapidly modelled and compared.This technology will provide mill maintenance managers and contract relining companies with the opportunity to benchmark current performance against world’s best practice. It will also provide an opportunity for concentrator plant designers and mill manufacturers to plan for maximum plant efficiency, by designing an infrastructure and equipment combination that maximises annual plant availability.This simulation tool and its associated data set, has been developed using recent grinding mill performance data from mills of varying dimensions, liner configurations, mill relining equipment, operator and tool variables.The simulation will provide an output that the various stakeholders can utilise to make optimal decisions within the given financial, physical and technological constraints of the individual concentrator plant."

Jan 1, 2012

By A. Rousselet, H. Gilbert-Tremblay, A. Berton

"Robex Resources interrupted production at the Nampala Mine in September 2014 following throughput and gold recovery results which were below expectations during the first months of operation. After a thorough plant audit, an important brainstorming took place in order to identify an economical path to resume production. It was clearly identified that a significant investment was necessary at the concentrator prior to restarting the plant, namely the addition of a ball mill and a new elution system.The mineral processing simulation software USIM PAC was used in order to simulate the grinding circuit in design. The simulations’ outputs allowed the ball mill characteristics and the surrounding classification devices to be designed with more accuracy. Many ball mills available from second hand retailers were therefore studied in the simulated circuit. The chosen ball mill, which was in perfect condition, had the advantage of being available for rapid delivery on site.The paper first describes the ball mill sizing method in comparison with the conventional Allis Chalmers method. It then describes the phase 2 concentrator start-up (that took place in 2016) with the commissioning of the ball mill, the classification circuit, the gravity concentration, the four (4) new carbon-in-leach (CIL) tanks, and the Zadra elution system (The phase 1 start-up took place in 2014). It finally provides production data compared to expected simulation data, as commercial production was reached in January 2017.IntroductionDesigning a new concentrator or new equipment within an existing concentrator requires significant efforts to identify possible bottlenecks and their causes (i.e. limiting equipment or sectors) and accurate sizing of major equipment can have a tremendous impact on the economy of the whole project. In the presented case study, the ball mill was the critical equipment and oversizing it could have brought the Capex to a level where the project would not have gone through. Inversely, undersizing the mill could have resulted in lower production and therefore no economic viability for the project once it is in operation.During engineering studies, equipment sizing often relies on a static mass balance and one-by-one sizing of all pieces of equipment. The sizing is then left to the equipment manufacturer or in the case of mills, evaluated with empirical models mostly relying on the Bond equations (Allis Chalmers method) [Rowland and Kjos, 1978]. This methodology shows the disadvantage of not considering interaction between equipment in a mineral processing circuit, especially when recirculation occurs. Also, it has the disadvantage of not using the more advanced grinding models that include the use of the whole particle size distribution as well as phenomenological components by only using limited parameters in the ore particle size distribution (i.e. the P80). This can be explained by the lack of data that sometimes needs to be gathered in order to tune the more advanced models but also by the conservative mindset in mineral concentration engineering which does not always favor the use of process simulation. In many aspects of process engineering, Soutex has demonstrated its affinity to using simulation in order to size equipment with more accuracy, consider process variability, simulate complex systems, and study supply chain management (Berton et al., 2015)."

Jan 1, 2018

By J. W. Merks

"Simulation is the process of designing a computerized model, of a system or procedure, for the purpose of understanding its behaviour and developing strategies to control its operation. Simulation models are rapidly becoming an effective tool for mineral processing plants. Powerful software and fast hardware are more readily available than a basic understanding of the theory of mathematical probability and applied statistics that process simulation models demand.Simple spreadsheet software can be used to develop simulation models that take into account any set of conditions at a mineral processing plant. In addition to an unbiased estimate for each variable in the set on which two-and three-product formulas are based, reliable variance estimates for all variables are required. How to estimate variances, effectively and at the lowest possible cost, and how to compute variances for simple functions such as the metal content of a quantity of ore or concentrate, or more complex functions such as the percentage recovery at a mineral processing plant, are the key to useful simulation models.IntroductionSimulation models for systems and procedures have become one of the most powerful and effective applications for computers( 2.6). Simulations are applied to a wide range of scientific and engineering disciplines. Generally, a model is designed to investigate the effects of changes in and interactions between a set of variables before a system is in operation or a procedure is implemented, by simulating weeks, months, and even years of operation, in a few minutes of computer time. Along with practical and useful applications always comeabuse and misuse. For a simulation process cannot be more reliable than the methodology that was applied to design the model, to estimate variables and variances, to check performance, and to verify validity. A mineral processing plant is a dynamic system that changes continuously as a function of time but within probabilistic constraints that can be estimated by applying statistical tools and techniques to the variables and variances that interact in the system.A model should be designed to simulate not only the set of variables but also the variance for each variable. Models in which constant variances are used to generate normally distributed random numbers, are less realistic than models in which the variances are simulated first, and then used to simulate the variables."

Jan 1, 1991

By René Lefebvre

Numerical simulations of the physicochemical processes related to acid rock drainage (ARD) in the Sugar Shack South rock pile of the Questa Mine were performed with the TOUGH AMD simulator. The objectives were to 1) identify the main processes responsible for observed present-day conditions, 2) provide an estimate of gas phase humidity transfer, and 3) give a preliminary indication of the potential impact of closure involving the installation of an alluvial soil cover. Modeling results indicated that the mine rock geometry (thin layers placed along steep mountain slopes) favors the onset of strong thermal air convection. Simulations also indicate that resloping the piles would not significantly reduce convection and oxidation. For simulation purposes, a potential cover with the permeability range of a local alluvium was investigated and found to be of questionable effectiveness since its permeability can exceed the value of 3x10-13 m2 required to prevent thermal air convection and reduce ARD.

Nov 1, 2002

By R. V. Ramani

"A computer simulation model of a dragline has beer developed for the study of alternative dragline deployment schemes for varying geological and mining conditions. In this paper, the mathematical aspects of the model, the input data and output results are discussed. An application of the model to a coal mine in eastern Kentucky is presented.IntroductionDraglines are very productive machines. To extend their operating ranges, they are operated in several modes such as advance benching, key cut, extended benching and pullback. Unfortunately, these variations result in low machine productivities. Appropriate methods to operate these machines must be developed on the basis of detailed analyses of dragline performance under varying geological and mining conditions. There are several standard engineering procedures for the selection of dragline, and design of a dragline pit (Ramani, Iroegbu and Manula, 1976). However, the complex interrelationship which exists among equipment, methods and natural conditions can be quantified only through orderly and systematic experiments.Computer simulation is well suited to studying these types of equipment selection and method layout problems. Several alternatives can be analyzed in a relatively short time by the modification of input variables. Also, the application of computer simulation models can significantly reduce the manpower and cost required for such analysis."

Jan 1, 1985

By J. Ramirez-Castro, J. A. Finch

"Galena is the finest component of the product of a closed-circuit grind treating a lead-zinc ore, largely due to preferential recycling of this high-density mineral by the cyclone. For example, at the Pine Point Mines concentrator, for ~ 55% -200 mesh over-all, the galena will be close to 95% -200 mesh. This sliming of the lead can limit recovery, selectivity and dewatering. A proposed circuit modification to reduce the sliming is to incorporate a unit cell. A simulator was constructed to study the No. 3 grinding circuit at Pine Point modified by a unit cell on ball mill discharge (BMD).The simulator used a cumulative size basis rate-of-breakage with plug flow ball mill model, the parameters being obtained by laboratory grinding tests. Flotation and the cyclone models used a cumulative recovery/size matrix. The behaviour of each mineral, galena, sphalerite, pyrite and calcite/dolomite, was simulated. Simulation was adapted to a programmable calculator. A close fit to the existing circuit performance at two tonnages and mineral mixes was established.The simulator showed that the modified circuit could significantly coarsen the Pb grind, from 95% to —50% -200 mesh, depending on recovery, without substantially altering the size of the other minerals. The other principal findings were: compared to laboratory flotation tests on existing circuit BMD, the unit cell concentrate (CONC) will be coarser and markedly lower in grade; relatively low unit cell stage recoveries are desirable, because the cyclone scavenges the tail to give a circuit recovery which is higher than the unit cell stage recovery; unit cell stage recovery should not exceed the cyclone stage recovery, as the latter is the maximum circuit recovery; low unit cell stage recovery helps offset the disadvantage of the high flow at BMD; other high-density minerals will also be scavenged into the CONC, as illustrated by pyrite, making CONC quality difficult to maintain; density control of BMD flotation does not greatly alter feed density to the cyclone or ball mill.Possible plant metallurgy is forecast for a CONC diverted to final lead concentrate."

Jan 1, 1980

By Sukumar Bandopadhyay, Arunapuram Sundararajan

"For the last three decades, the application of network planning has provided a basis for a formal and general approach to the discipline of project management. For fixed activity duration, a very simple algorithm commonly known as critical path method (CPM), gives the length of time required for the total project as well as indicates the activities which are vital to the completion of a project. Project Evaluation Review Techniques (PER T) on the other hand, generalize the above approach to recognize uncertainty in the activity durations by allowing them to be random variables. One of the misleading aspects of current "" PER T"" solution method is, however, the implication that there is a unique critical path. In general, any number of paths could be critical, depending on the particular realization of the random activity durations that actually occur. In this case, simulation can be utilized to estimate completion time of a project.In this paper, the concept of criticality indexing is discussed, and a simulation model application which defines the critical path based on the criticality indexing concept, to a longwall development - extraction network, is presented. The model also provides suitable scheduling of resources based on the resource constraints and smooth s out period-t o-period assignments. IntroductionThe successful management of large-scale projects require careful planning, scheduling , and coordinating numerous interrelated activities. To aid in these task s, formal procedures based on the networks and network techniques (variously called PERT or CPM) were developed. In its original form the completion time for individual activities of a project was assumed fixed and known in advance: this in turn led to the familiar algorithms for computing the critical path, earliest start time, slack, and so forth. The unreality of such an assumption is, of course , apparent in many contexts. Consequently, attempts were made to introduce probalistic activity completion times, allowing representation of the stochastic nature of most projects."

Jan 1, 1987

By Sukumar Bandopadhyay, Arunapuram Sundararajan

"Unique production and environmental problems are associated with multiple seam mining where dragfines are used for overburden and interburden removal. On the production side, the problems are decreased dragfine efficiency in chopdown operations, the general need for spoil rehandle, complications in sequencing stripping and coal handling operations, and potential stability problems in highly stacked spoil. Many variations of dragline methods have been reported in the literature to encounter these problems. Because of the physical properties and peculiar hydrology of sub-arctic region mining of multiple seams in such areas probably could not be done with the methods used in temperate regions.The properties of thawed material would make spoil hard to place in a stable manner and thus would influence the mini sequence. For instance, multiple seam mining which requires some rehandling of spoil and prolonged exposure of overburden and interburden material might be precluded by the instability of thawed spoil and therefore mining techniques have to be modified. Since the deployment and operation of a dragline in modes different from conventional schemes will affect productivity, it will be necessary to study the effects on production of changing the dragfine operational schemes. This paper presents a heuristic simulation model of multi-seam dragline operation of a sub-arctic mine that can be used to analyze the handling of overburden and detailed study of the dragfine performance."

Jan 1, 1986

By G. G. Li

"A dynamic ventilation-modeling package, VREX, was used to simulate the mine activities through tracking the equipment movements in underground workings and determine the airflow demand for a new production scenario in a ventilation-on-demand (VOD) system. It incorporates the mine development data from a discrete event simulation and balances the ventilation network using the CANVENT ventilation solver. A case study was performed to demonstrate the capabilities of the software, evaluate the performance of the network and determine the potential energy savings for implementing VOD in a deep mine operation.INTRODUCTIONThe ventilation cost of an underground mine can be significant—up to 50% of the mine’s energy consumption could be used to run fans and provide heat/refrigeration to meet the specified production environment for workers and equipment. The VOD system has proven to be more efficient in operating the fans and supplying the amount of air corresponding to the mine activities taking place in underground workings (Hardcastle, Kocsis, & O’Connor, 2006). In order to properly solve and evaluate the VOD system, a dynamic ventilation modeling software VREX—the ventilation rules engine has been developed to simulate the mine activities and determine the airflow demand for each production scenario within an operation period (Dasys & Cameron, 2011).VREX is a decision support tool, backed by the CANVENT mine ventilation solver (Li, Kocsis, & Hardcastle, 2009), for determining the outcomes of network configuration changes over time. The software incorporates the mine development data with ventilation modeling through the discrete event simulation (DES) performed by SimMineTM. As it simulates the air requirements for different vehicles and activities, VREX can evaluate both the performance of the ventilation system and the potential economic benefits of making operational or technological changes (Pritchard, 2010). For example, the model can be used to assess the economic and environmental impacts arising from modifying regulations to support the use of electric or lower emission vehicles. The combination of DES and ventilation modeling provides a new technology to generate the production scenarios according to mine schedules and activities and to determine the potential benefits for various levels of ventilation control, such as time interval and work shift change."

Jan 1, 2019

By Pierre Roy, Claude Gosselin, Maryam Sadeghi, Michel Bourassa, Christian Rochefort, Claude Bazin, Gautier Mahieu, François Lavoie, Marilène Renaud, David Cataford

"Spirals are gravity concentrators used for the concentration of iron oxide minerals from ores. This paper presents the mineral size recovery curves observed for spirals operating in two Canadian iron ore processing plants. The size recovery curves are presented for rougher, cleaner and re-cleaner spirals. The partition curves observed for the spirals are significantly different than those observed for typical gravity concentration devices such as hydrocyclones or hydraulic classifiers. The size recovery curves show the complex behaviour of the minerals as they flow down a spiral and are analysed with a view toward process modelling and simulation. Initial simulation results show that gains in the iron recovery can be achieved by increasing the recovery of coarse iron oxide particles in the rougher spirals.INTRODUCTION Spiral concentrators are gravity based separation devices used for the preparation of coal, iron and different heavy minerals ores (Wills, 1992). The classification of the particles in spirals is based on the combination of gravity, centrifuge, drag, lift and Bagnold forces (Atasoy and Spottiswood, 1995; Burt, 1984; Bouchard, 2001). Several papers are dedicated to the analysis of the forces acting on the particles flowing down a spiral (Das and al., 2007; Sivamohan and Forssberg, 1985; Holland-Batt and Holtham, 1991; Holtham , 1992). Most of these papers aim at the development of a general model for the simulation of the classification of the particles for coal ore processing. Few papers deal with the operation of spirals for processing iron ores (Hyma and Meech, 1989; Srivastava, 2001; Dallaire et al., 1978) and fewer papers present results for spirals used as cleaners following a rougher stage. Since the classification in spiral classifiers is dependent on the particle size and specific gravity a partition or performance curve commonly applied to classifiers (Mai Manga et al., 2012) is used here to analyse spiral operation. Few papers were found to describe the operation of spirals in terms of partition curves (Atasoy and Spottiswood, 1995; Holland-Batt and Holtham, 1991; Richards et al., 2000). Most of the investigations presented the application of a model to simulate the position of coal particles of various sizes and specific gravities along the trough of a spiral (Kapur et al., 1996; Holland-Batt and Holtham, 1991). In addition most of the available literature on spirals deals with one stage of concentration by spirals (Dallaire et al., 1978; Das and al., 2007; Sivamohan and Forssberg, 1985) while industrial circuits usually consist of rougher and cleaner spirals."

Jan 1, 2014