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By R Kroukamp, G Rech

CRONIMET Australia in cooperation with Speciality Metals International, the mining lease holder of the Mt Carbine Tungsten mine, have demonstrated the preconcentration and processing of large (>12 million tonnes) tailings and mine waste dumps on site in far north Queensland. The first stage of this project has proven the economic viability of preconcentration using sensor-based particle sorting whilst ensuring high recovery of industry critical tungsten minerals – wolframite and scheelite. Sensor-based sorting technology have enabled the production of a sorter product to feed the existing wet gravity plant ensuring higher recoveries and increasing concentrate production. Processing of 1,000 tonne low grade samples using the TOMRA x-ray transmission (XRT) ore sorter installed on site, has reduced the volume of material entering the downstream wet processing plant by up to 60%. The sorted 10-25mm size range produced the highest upgrade ratio (product/feed) of 24:1 and achieved sorter concentrate grade of 1.52% WO3, sorter waste grades below 0.014% WO3 and metal recoveries of up to 93.4%. The appropriately sized, barren sorter waste material is also sold as aggregate and other quarrying products and thus adding to the overall economic benefit of the project. The utilisation of the sorting technology on site has produced an economically viable project, significantly reduced capital cost, and reduced the time to market of the final tungsten concentrate. The next phase of the project includes design and installation of a larger two sorter plant capable of over 150t/h feedrate.

Nov 10, 2020

The preconcentration of uranium ore by radiometric ore sorting at Mary Kathleen Uranium Ltd. is described. The operation of the ore sorting machines is discussed in detail and performance results obtained with the existing system are presented.

Jan 1, 1978

By T BoBo, D La Rosa, P Cameron

Efficient pre-concentration using natural and induced deportment starts with effective blast design. Leveraging these characteristics using Size-Based Grade Engineering® techniques requires detailed understanding and measurement of the particle size distribution (PSD) of the Run of Mine (ROM) ore. In turn, blasts must be designed to optimise fragmentation for the pre-concentration method. To be successful, fragmentation outcomes must be predicted and measured as part of the blast design process to account for the response ranking of the rock mass. The upgrade achieved using Size-Based Grade Engineering® methodologies will rely on the proportion of feed that reports to the screen undersize, so particle size distribution of the feed stock is of paramount importance if the potential benefits are to be achieved and maintained. Measuring actual fragmentation in the ROM ore and comparing with predictions allows the modification of subsequent blast designs to optimise fragmentation for pre-concentration scenarios. Automating this process can deliver significant increases in productivity and mine site profits. This paper discusses the importance fragmentation plays in Size-Based Grade Engineering® and explores technologies and methodologies used to measure it, consistently ensuring the best outcomes.

Nov 10, 2020

Ore sorting is a high capacity, low cost method of preconcentrating ores and in some cases of producing a marketable concentrate. In most cases it is applied to run of mine material, immediately after primary crushing and screening in sizes ranging from 10 mm to 150 mm. Recent developments in bulk sorting of friable uranium deposits have resulted in machines capable of handling fine materials with sensing and separation being achieved on a zone by zone basis. Modern ore sorting machines rely on the synchronous operation of four internal sub systems, feed presentation, sensing, data processing and separation. A variety of different sub systems is available which can be combined in various forms to produce sorters capable of handling a wide variety of mineral types. The benefits in using ore sorting cover a wide range of situations and are applicable to both established mines as well as new mining ventures. Reduced operating costs, increased productivity, capital savings, energy and resource conservation and environmental issues are all part of the reason why ore sorting is finding rapid acceptance in today's mining industry.

Jan 1, 1980

By Lee M. F, Guilfoyle K

A large hard rock rib pillar was recently preconditioned at Mt Charlotte mine using a novel blasting technique. The motivation for trialling this procedure was a history of past pillar failures, with associated seismicity. Design studies had shown that a new proposed pillar would be at risk of violent failure, and preconditioning was used in an attempt to reduce this risk. Preconditioning by blasting involves physically modifying a selected zone of ground in advance of mining, then forming the pillar so that it incorporates that zone of ground. The modified rock in the zone is intended to allow extra closure (yield) of the pillar in response to mining-induced stress changes. The ground modification was done by tight firing a blasthole array to fracture the rock. The blast design comprised pairs of pre-split blastholes to create a series of short cracks across the target zone, followed by main blastholes to fracture the rockmass between each pair of cracks. A monitoring program was used to establish whether or not the preconditioning was effective. It included conventional extensometers, stress change cells and closure stations, plus a seismic monitoring system. To-date, stoping is complete on one side of the pillar and has just commenced on the other. Results show significant movements within the preconditioned zone and on geological structures in the pillar, as well as lower stress in the pillar compared to an adjacent non-preconditioned site. The preconditioning technique can be applied elsewhere, provided its purpose, mechanism and side effects are understood. Benefits are likely to include more assured production, and successful pillar recovery even in high stress situations.

Jan 1, 1995

By J Samosir, L Snyman

Northparkes was the first mine in Australia to use block cave mining method which relies on gravity and natural rock stresses to fragment and recover the ore. It was also the first hard rock mine to use hydraulic fracturing, in conjunction with CSIRO, to promote caving of E26 Lift 1. The technique was later used on E26 Lift 2 wedge and E48 prior to undercutting.Northparkes production is currently sourced from the E48 Lift 1 block cave mine and E26SLC. The E48 block cave contains economic ore to the north and south of the current cave footprint. To recover this ore the footprint has been extended on the north and south with two extraction drives and one extraction drive, respectively. Modelling of cavability above the additional drives indicated that the cave would not readily propagate to a sufficient height of draw to mobilise the ore and tended to arch over into the existing cave. To address the modelling results and to reduce the risk of the project, rock mass preconditioning was adopted.This fracturing campaign was performed from surface drill holes adjacent the subsidence zone angled to intersect the higher grade and higher elevation ore zones.Optical televiewer surveys, run prior to fracturing, picked intervals and fault zones to be avoided. Holes were resurveyed post-fracturing to detect newly created fractures and as a measure of success of the program.During fracturing operations water and gel fractures were run at varying depths and pumping pressure was logged for each fracture. The mine seismic system monitored significant events and dye in the fluids utilised for tracking water inflow locations during underground inspections.Towards the end of the project, guar fibres from gel were detected within the mill circuit and required treatment to resume optimum processing.CITATION:Webster, S, Snyman, L and Samosir, J, 2016. Preconditioning E48 cave extension adjacent to an active cave, in Proceedings Seventh International Conference and Exhibition on Mass Mining (MassMin 2016), pp 471–478 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2016

By P González, J Videla, E Córdova, I Gottreux

Currently, underground mining of deeper massive deposits with lower grades, harder rock conditions in high strength environments, entails difficulties in caving, fragmentation and seismicity of the orebody.So far, the use of preconditioning (PC) with hydraulic fracturing (HF) has shown positive results in terms of seismic response and caving performance, while PC combined with explosives aims to weaken the rock mass, causing an additional effect on fragmentation.In particular, mines commonly referred to as ‘supercaves’, operated by caving methods, have the need to integrate mine to plant processes, where rock fragmentation appears as a key tool. In fact, it implies making mining and comminution processes more efficient to the plant and for mines, it justifies the search of innovative solutions in drilling and blasting techniques to precondition the rock mass. The following paper aims to show the feasibility of numerical blast modelling to weaken the rock mass using explosives, mainly through sensitivity analysis applied to designs to minimise bias and uncertainty in the results. It is shown how the presence of structures, their geometry and in situ stresses influence or interfere with the PC method being used.From the work, it is concluded that better knowledge on the application of explosives weakening allows specialists to strengthen numerical models associated with every design and therefore previously validate their applicability, helping to understand complex phenomena such as the propagation of mechanical waves in non-elastic heterogeneous media. In this sense, it is understood that while there are studies (Sanchidrián, Segarra and López, 2006) showing that the transfer of energy in the rock mass could be even greater in a confined environment, the more competent rock mass and higher in situ stresses interfere mostly on the effectiveness of a technique using explosives.CITATION:Gottreux, I, Córdova, E, González, P and Videla, J, 2016. Preconditioning modelling and explosives effectiveness in block caving, in Proceedings Seventh International Conference and Exhibition on Mass Mining (MassMin 2016), pp 683–688 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2016

By E Kunz

Decreasing the gas content in the worked seam by degassing before the start of winning has proven its worth in some areas of German hard coal mines. On the one hand, it removes the risk of gas/coal outbursts and on the other hand it reduces the gas inflow into the longwall. The underground experiences of the last 30 years have led to a æhit listÆ of coal seams with respect to their suitability to predegassing. Trials in the DMT laboratory and also results gained in the deposit show that the suitability of a seam for predegassing depends on its rank. In seams with volatile matter of 20 - 30 per cent, high efficiency ratings are achieved as a rule, with lower ratings both in seams with lower and with higher content of volatile matter.If the rock pressure is unusually high, the efficiency rating of the predegassing is lower, even in seams which would normally be suitable for this process. Under unfavourable conditions, for example below or above residual pillars, in-seam boreholes cannot be drilled successfully and the method is not practical. But if the worked seam was already stress relieved, the predegassing has an optimal efficiency. Latest investigations show that the distance between the in-seam boreholes can be extended. But in that case, the time necessary to reach the same reduction of the gas content increases considerably.

Jan 1, 2005

The dynamic response of holdup in a continuous ball mill has a direct influence on the rate function of grinding kinetics and is useful for predicting the variation in the size distribution of the finished product with time.A model was proposed involving three interacting, completely mixed chambers and this was used to derive analytically the transfer function of the system, from which the unit impulse response and the unit step response of the holdup with feed rate were obtained.The theory was confirmed by comparing it with previously published experimental data for the residence time distribution of particles passing through a ball mill.

Jan 1, 1975

By K Gardner, R Fraval, V Singh

Using new technology to create optimised infill drill programs in underground or open pit settings, it is possible to quantify the value of a drill program. The computer designed programs are optimised to uplift the most amount of resource possible into the specified resource classification, while honouring geological, spatial, equipment and budgetary constraints. When designing ‘by hand’ balancing all these factors is a time-consuming effort with no real way to determine metrics on ‘how good’ a program will be. The optimisation considers many factors allowing geologists to apply critical thinking and domain knowledge to constrain the optimisation, letting the computer do the heavy lifting of determining hole placement. Once programs have been created, they can be integrated into a production schedule. This is a critical step in determining the correct sequencing and balancing of resource availability and seeing how a program will interoperate with other tasks in the mine. For example, if drill drives are a requirement for part of the program, will they be developed in a time frame that is useful for the goals of the program? Do we risk drilling infill holes too late to add value? Do we put production at risk by not classifying parts of the model ahead of time, thus adding to uncertainty? Using software to assist with optimising and scheduling of drilling is a useful technique to save the geologists from the mundanity of manually designing drill programs and puts metrics around the effectiveness of a program and has the potential to add quantifiable value to a program. Examples will be presented that demonstrate the effective use of drill hole optimisation, comparing manual designs with optimised designs, as well as the examples that show the effective use of scheduling.

Mar 22, 2022

Carbonation of reinforced concrete is a potential durability issue for vehicular tunnels. This is particularly the case where elevated carbon dioxide concentrations exist and when the design life is 100 years or more. The process of carbonation can result in loss of passive protection to embedded steel reinforcement and initiation of corrosion. Therefore, tunnel design needs to consider the potential for carbonation on internal surfaces and how design life can be achieved in severe environments. This paper examines methods for predicting carbonation and how deterioration can be mitigated through appropriate concrete mix design and construction practices.

Jan 1, 2008

By J T. Sharp, M A. Styler, D McGowan, P W. Mayne

Static liquefaction is a geotechnical hazard in mine tailings facilities. Soils that are contractive in shear are susceptible to static liquefaction. Tailings facilities are dynamic structures, typically growing in height each year. Dilative tailings may become contractive under increased effective stress. In this paper we show that Cone Penetration Test (CPT) data can be used to estimate the future state of in-place tailings under changes in effective stress. Susceptibility to static liquefaction is typically evaluated with the CPT by using a clean-sand equivalent normalized cone tip resistance (Qtn,cs) or by estimating the state parameter (?). An alternative approach is to evaluate the soil-state using the yield-stress-ratio (YSR = ?’y/?’v0). If the YSR equals one it is on the normal consolidation line and the soil-state is contractive. YSR values greater than three are typically dense of the critical state line (CSL) and the soil-state is dilative. In this paper we review how to calculate Qtn,cs, ?, and ?’y; and how the YSR can be used to screen for contractive soil behaviour. Unlike Qtn,cs and ?, it is very simple to estimate how the YSR will change due to an increase in overburden stress. This YSR approach was evaluated at three locations that saw increases in overburden of 10 m, 20 m, and 25 m. We show that the ?’y calculations are consistent and the increase in effective stress moves the soil state towards looser soil states. CITATION:Styler, M A, Mayne, P W, McGowan, D and Sharp, J T, 2018. Predicting changes in static liquefaction susceptibility using cone penetration test results, in Proceedings Mine Waste and Tailings Stewardship Conference 2018, pp 317–332 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 23, 2018

By S L. Barbour

Measurement of the net percolation from the base of a cover system into the underlying waste material is a key component of a cover system monitoring program. The units of measure (ie a percentage of precipitation or rainfall) are simple to understand for all stakeholders, which increases the importance of obtaining representative net percolation values. In general, lysimeters are used to measure net percolation across the cover material-waste material interface; however, the design of lysimeters for cover system monitoring programs in the mining industry have typically not considered fundamental aspects of lysimeter design. Lysimeter design is typically thought of as being conceptually simple, when in reality the design, installation, and operation of lysimeters is often counter-intuitive, due to the complexities of flow through unsaturated soil systems. This paper puts forward a methodology for lysimeter design while also presenting the fundamental design variables that should be considered. Lysimeter design for differing climates, cover materials, and waste materials is discussed. Finally, the performance of lysimeter designs previously installed in the field at sites in Australia, Canada, and the United States are subjected to numerical modelling to determine whether net percolation is being measured properly.

Jan 1, 2003

By J E. Everett

An essential requirement of product quality control in the mining industry is to be able to reliably predict key quality properties of finished product from the data available before the extraction of the ore. From a production viewpoint, the unit of data collection is generally the input and output data set for each shift of crusher production, but could be any period where mine precrusher data can be reliably matched with product data.This paper demonstrates that linear regression models can be used to predict crush grades from blast grades, even where the crush material is blended from multiple sources or pits for each of which differing regression models might apply. The advantage of using increasingly complex regressions models to match the available data to give increasingly more powerful models is examined. The best model for any application will be a balance between required predictability, available data and the business’ tolerance for complex models.The regression modelling approach has several advantages over the more classic method of run-of-mine (ROM) crusher trials, which will be discussed.The models can use any predictor variable such as grade, geotype and in situ density provided the preextraction data set can be reliably matched with post-crusher data and is significant as a predictor. The models have been used extensively in the generation of the daily crusher plan with the aim of maintaining finished product grade. This approach has also been used associated with exploration drilling and long-term planning.It is acknowledged that there are inherent problems in fitting lump and fines grade to a linear model. However, these problems are minor when they are used for interpolation within the window spanned by the shift blend records used to produce the model. This paper discusses some of the issues limiting linear regression models in this application, and suggests methods enabling consistent models to be formulated

Sep 5, 2011

Predicting Flotation Response from Liberation Information

Sep 13, 2010

By J E. Everett, D Linden, P Maney

In response to the implementation of a new schedule for iron ore fines in the International Maritime OrganizationÆs (IMO) International Maritime Solid Bulk Cargoes (IMSBC) Code, improved measures for the management of moisture have been developed. In particular, prediction of cargo moisture allows management of iron ore fines within the supply?chain to facilitate the safe?shipping of iron ore fines.An ARIMA model, augmented to allow for shipment tonnage, has been developed to predict the moisture level from previous shipments of the same product. The model explains about 60 per cent of the moisture variance. It was found that inclusion of other available information, such as ore composition, train/rake assays and recent rainfall at port and mine, did not add to the predictive power of the model.CITATION:Everett, J E, Linden, D and Maney, P, 2013. Predicting iron ore fines shipment moisture, in Proceedings Iron Ore 2013 , pp 17-26 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 12, 2013

By D Roldpo, M Vidigal, J F. C L Costa

The local cumulative distribution function (lcdf) of a selective mine unit (SMU) can be estimated by conditional simulations using the statistics derived from the sample points, generating multiple equally probable scenarios. Conditional simulations permit the evaluation of the lcdf at any support, taking into account the spatial variability, ie the variogram, and the two statistical moments, mean and variance, of the conditioning samples. The SMU ore losses and dilution depend on the mining method and mining equipment selectiveness that, in its turn, depends on the predicted block size. A new approach to predict ore loss and dilution was developed in this study. Monte Carlo simulation is used to randomly generate a grade value derived from the lcdf at the mining stage (Zs_mc(t)) in order to make a decision about the SMU destination, ie processing plant (ORE) or waste dump (WASTE). If Zs_mc(t) is lower or equal to the cut-off (Z_cut-off) the block is ORE and, conversely, if Zs_mc(t) is higher than the cut-off (Z_cut-off) the block is WASTE. Considering these binary destinations ORE/WASTE, at the mining time t, and combining each realisation of the simulated random function Zcs_i (X), there are four possibilities for each SMU simulated value: 1. the block was simulated as ore and is actually ore (OO), 2. the block was simulated as ore and is actually waste (OW),3. the block was simulated as waste and is actually ore (WO), and 4. the block was simulated as waste and is actually waste (WW).The dilution factor is given by possibility 3 (WO), while the ore loss factor is represented by possibility 2 (OW). These results comprise the classical classification and reconciliation plots used in the mining industry. The new procedure proposed in this paper is based on the use of all the equally probable simulations to define the ore loss and dilution factors. An application of this methodology was carried out at Vale's iron mine in Brazil. The grade of silica was simulated and 50 multiple equally probable 3D models were generated. The mean and the standard deviation of the ore tonnage (OO + WO) for the 50 realisations, was 233 Mt and 0.5 Mt, respectively. The mean grade increased for the diluted ore (OO + WO) as well as their respective coefficient of variation (CV). The CV increases from 62 per cent in the undiluted ore (OO), to 101 per cent in the ore, considering the dilution factor (OO + WO). The mean ore loss (OW) was 10 Mt and the waste tonnage dilution (WO) was 9 Mt.

Jan 1, 2009

By M I. Pownceby, N A. S Webster, R Pattel, N Ware

The decrease in quality of Australian iron ore, coupled with the demand for more efficient energy use, necessitates closer monitoring and optimisation of process conditions for iron ore sinter production. Sinter properties are correlated with the mineralogical content and traditionally, quality control has relied on methods such as Fe2+ determination, point counting via optical microscopy and automated electron beam techniques such as QEMSCAN; these can have a typical turnaround time of several days between sampling and reporting of results. As well, there is additional uncertainty around quantifying some of the complex mineralogical phases in sinter such as silico-ferrite of calcium and aluminium (SFCA) and SFCA-I, which are key phases influencing sinter quality. There is a clear need for the implementation of alternative analytical methodologies that offer a turnaround in hours or even minutes to provide information to accurately maintain production conditions.X-ray diffraction (XRD) is a technique widely used for the quantitative mineralogical phase analysis (QPA) of ores and processed materials in the iron ore industry. Partial least squares regression (PLSR) analysis methods have recently been suggested as an indicator of sinter Fe2+ content from powder XRD data without the need for rigorous and often time-consuming mineralogical analysis by the operator. In this study we provide results from the implementation of PLSR to predict the strength of iron ore sinter. Results are sourced from a well-constrained data set comprising strength properties (as quantified by a tumble index (TI)) from a series of compact laboratory test samples. Using this data set it was determined that PLSR has potential to be used as a method for calculation of sinter TI from powder XRD data and, therefore, process control.CITATION:Webster, N A S, Pownceby, M I, Ware, N and Pattel, R, 2017. Predicting iron ore sinter strength through X-ray diffraction analysis, in Proceedings Iron Ore 2017, pp 331–334 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 24, 2017

By K Jupp, T J. Howard

Cliffs Natural Resources Pty Ltd (CNR) operates iron ore mines in the Koolyanobbing region of Western Australia. Ore is mined from three locations, separated by many kilometres. The ore is stockpiled at these locations, according to an in-house ore classification system (based on grade and source) and then trucked to the crushing and screening plant at Koolyanobbing. Lump and fines products are railed to Esperance for ship loading and export to Asian customers. CNR prides itself on the relatively low inter-shipment grade variability of the products. The Koolyanobbing crusher is fed using a daily blend plan, generated to maintain lump and fines product grades within acceptable tolerance ranges around targets. Achieving low variability requires predicting lump and fines grades as accurately as practical from the estimated head grades of the ROM ores potentially going into the blend. The grade prediction model may be either a direct prediction of crushed lump and fines grades and lump percentage, or be split into two stages: the bias between blasthole estimated head grade and crusher head grade and then the lump-fines algorithm for splitting the head grade between lump and fines products. The lump-fines algorithm comprises the percentage of lump and the difference between the lump and fines grades. We describe a weighted least squares (WLS) regression model for predicting crusher grades and lump proportion from the estimated head grade for Fe, P, SiO2, Al2O3, Mn and S. The method is applied to CNR production data, where the regression model explains approximately 60 per cent of the variance in the crushed ore grade, for both lump and fines. A further small but significant improvement in prediction can be achieved by including the ore classification data in the model. The regression errors exhibit strong positive serial correlation, indicating trends in grade error across multiple blend records. To compensate for the longer-term error, an exponentially smoothed model was developed and applied to the daily grade blend errors. This gave an increase in the longer-term variance explained and therefore an improvement in grade prediction.

Jan 1, 2009

By Trueman R

If continuous mining systems are to be successfully applied in metalliferous mines then reliable models will be needed to predict rock cutting machine advance and tool wear rates for effective machine selection before mining commences. Many of the predictive models developed to assess cuttability in situ are over-simplistic. As a result they tend to be both site and/or machine specific. Nevertheless very detailed models have been developed for full face machines which are capable of accurate cuttability predictions in a variety of rock mass conditions and for a variety of machine and tool configurations. However, models to predict productivity and tool consumption for partial face machines are not as well advanced. There is a need to develop reliable models for partial face machines such as Roadheaders, the Robbins Mobile Miner and the HDRK-Wirth CMM, as these types of machine are likely to predominate in a mining environment. The paper outlines the current state-of-the-art for predicting cutting machine performance and the work being carried out within the Centre for Mining Technology and Equipment (CMTE), in collaboration with the Australian mining industry, to advance our capability in this area.

Jan 1, 1995