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By G Senanayake, K Hazarika

The demand for iron-ore is ever increasing with the industry directly employing 60 500 people in a range of highly skilled roles in Australia. In the year 2019, the global iron-ore production was 2.85 billion tonnes. It is estimated that each tonne of beneficiated iron ore produces 400 kg of tailings. The IOTs are fine, dense and stable crystalline material mainly composed of iron oxides, alumina and silica. The current and most applied method of iron-ore tailings (IOTs) disposal is using subaqueous disposal of tailings in dams. The footprint generated by a tailings dam is massive and requires constant monitoring due to the possibility of a failure making the operation and maintenance of tailings dam extremely expensive. This review briefly discusses the known causes of tailings dam failures, their impact to the environment and day-to-day human life and potential applications of IOTs. The increase in water content enhances the pressure on dam walls. This in turn increases the liquefaction potential of the tailings and reduces the overall strength of the dam making it more vulnerable to failure. Potential applications of IOTs are in paints, aggregates in construction materials and bricks. The reuse of IOTs reduce waste and generates further revenue facilitating a path towards a sustainable future for the industry.

Nov 8, 2021

By S Hapugoda, H Han, L Lu

Sinter quality depends heavily on the mineral phases, textures and physical structure of the sinter, which are formed upon solidification of the sinter melt. The interaction of sinter initial melt with its surrounding materials will impact the properties of the sinter melt and consequently the solidified structure and quality of resultant sinter. Spreading and penetration are two important phenomena dictating the interaction of the initial melt with its surrounding materials, such as nuclei and adhering fines. In the present study, the penetration behaviour of an initial melt into various natural iron ore substrates of different ore types during sintering was studied using a laboratory scale penetration testing procedure. The penetration depth and width were found to increase with temperature and vary with the type of iron ore due to their unique pore structure and mineralogical texture.

Nov 8, 2021

By P Dean, M Elmouttie

Radar monitors are now widely used in surface mining for monitoring slope deformations and predicting failure events. Their introduction has facilitated better management of risk associated with slope failure during mining and therefore protection of personnel and equipment. However, a wellrecognised problem is that radar monitors only measure deformation directed towards the detector (line-of-sight bias). This bias can lead to misinterpretation of deformation size, rate and failure mechanism, and therefore miscalculation of failure volume, which can significantly impact safety and productivity. This paper presents recently completed research and field trials into the feasibility of using low cost vision systems to mitigate this issue. It has been demonstrated that by integrating a computer vision system with an existing slope monitor, high precision tracking of features in the field of view can be performed. Combined with assumptions on the deformation characteristics, the true 3D deformation vector can be estimated. The applicability of using this technique for monitoring iron ore mine slopes is discussed.

Nov 8, 2021

By B Zhou

Geophysical borehole logging, which measures various in situ petrophysical parameters, can be used not only for qualitative interpretation such as strata correlation, but also for geotechnical assessment through quantitative data analysis. It can play an important role for safe and productive mining operations. Here we provide various applications of geophysical logs such as the estimation of the strength of intact rock or unconfined (or uniaxial) compressive strength (UCS), automated lithological/geotechnical interpretation, geophysical strata rating and orebody delineation and grade estimation. These derived parameters could provide input to control of geological and geotechnical models. This could assist site geologists and planning and production geotechnical engineers to predict and manage mining conditions on an ongoing basis. Both conventional logs such as density, natural gamma and sonic, and less common logging data such as full waveform sonic and televiewer data are examined for different applications. Although the examples used here are mainly for coal mining applications, but they can be equally applied to hard rock metalliferous mining such as iron ore mining.

Nov 8, 2021

By K Li, C Zhang, i, J Oh, S Saydam, H L. Ram

Rock surface roughness plays an important role in excavation engineering projects and applications related to surface support structures, such as shotcrete and thin-sprayed liner (TSL). The morphology of the substrate affects the mechanical behaviour at the interface significantly. Therefore, it is necessary to quantify the roughness to investigate the relationship between roughness and mechanical properties. The joint roughness coefficient (JRC) proposed by Barton and Choubey (1977) is widely used in practice. It initially estimated the roughness by comparing it to 10 standard profiles visually. However, this method has lots of limitations, it is not only subjective but also a two-dimensional parameter with a small lab scale (Beer, 2002). The subsequent research on JRC, from visual comparison with Barton’s standard profiles to measuring the roughness with a profilometer (Weissbach, 1978; Alameda-Hernández et al, 2014). Then, 2D profiles or 3D surfaces by different technologies with higher resolution and accuracy, such as 3D laser or optical scanners (Fardin, 2004; Jiang, 2020, 2021). These 3D scanners are expensive and only suitable for laboratory scales. LiDAR scanners (Lato, 2009; Aubertin, 2022) have been applied in industrial size, but it is difficult to achieve a millimetre-level accuracy, which is mostly used to detect the thickness of shotcrete in practice. Thus, finding a cost-effective surface roughness measurement method with high accuracy is necessary. Photogrammetry is another method to digitalise the roughness of the surface. Similar to 3D scanners, photogrammetry also generates the point cloud of the objective surface and then reconstructs the 3D model of the objects. 3D reconstruction technology is a trendy technology in recent years. The structure from motion (SfM) algorithm (Westoby, 2012) to rebuild the 3D model with a flexible workflow, aligning photos, building dense point cloud, mesh and texture, which has been proved that can rebuild an accurate model in variable fields.

Nov 29, 2022

By I Canbulat, A Mcquillan

This paper presents a parametric analysis showing the impact of virgin in situ stresses on a shallow (less than 100 to 150 m) high slope in a jointed sedimentary rock environment. Slope stability is assessed at varying ratios of slope orientation and horizontal stresses. The results of this study indicate stress conditions should be included in stability assessments of excavated slopes, particularly where structure is orientated perpendicular to the direction of horizontal stress. Some consideration of stress state is applied in deep open cut pits (eg those with planned excavations of 400–1200 m) (Myrvang et al, 1993; Stacey et al, 2003; de Bruyn et al, 2014; Kozyrev et al, 2015). Dodd and Anderson (1972), Kalkani and Piteau (1976), Lee (1978), Coulthard et al (1992), Noorani et al (2011) have studied the effect or horizontal stress and its impact on slope stability, showing that tensile stresses tend to develop at the crest of the slope, with larger tensile zones for higher horizonal stresses and steeper slope angles (Stacey, 1970, 1973; Sjoberg, 2013). However, the consideration of virgin stresses on shallow slope stability is less frequent (Lynch et al, 2005; Dight, 2006; Lucas, 2006; Sjoberg, 2013). This has led many geotechnical engineers to believe the impact of virgin in situ stresses on open cut slope stability is minimal and not worth time or consideration in modelling, or their effects on slope stability are still poorly understood (Stacey et al, 2003; Sjoberg, 2013).

Nov 29, 2022

By J Ashford, Minniakhmetov

Geostatistical simulations are the best practice for uncertainty quantification in non-linear systems. Simulations are currently undertaken on an ad hoc basis in the mining industry due to high requirements in computing environments and advanced geostatistics. In contrast to the estimation process, multivariate simulations can be performed using different methods, tools, and computational environments, similar to data science. For large companies with multiple commodities it is important to have a standard framework to test, build, and run workflows using different methods, applications and computational environments. This work presents an auditable, modular and scalable framework to create geostatistical simulation workflows where the workflow is abstracted from the implementation. Key aspects: automation – workflows should be able to run automatically given updated data (if hands on modelling is not required); auditability – workflows should document key considerations and parameters; modularisation – workflows should permit swapping out components, for example substituting domaining in Leapfrog software with automated domaining using machine learning scripts; scalability – easy, repeatable, portable deployments on diverse infrastructure (for example, experimenting on a laptop, then moving to an on premise cluster or to the Cloud); reproducibility – parameters should be archived to permit re-running and reproduction of workflows in future years; and sensitivity analysis – any component of a workflow should be able to run with multiple scenarios of parameters and data to enable global uncertainty quantification and sensitivity analysis. The presented framework can be used to create different workflows for geostatistical simulations in multiple assets to quantify uncertainty in the value chain for resource categorisation, reserves uncertainty, value of information and robust mine planning amongst others.

Mar 22, 2022

By E J. Hancock, K H. B Chu

Failures within hard rock underground excavations have historically been defined by a depth of failure, estimated in the field or through individual measurements, with a simplified failure geometry; such as 1/3 span, cubic or paraboloid. This simplified shape, volume and mass of failure is typically used to estimate in situ demand as a simplified discrete point. However, the highly variable failure geometry indicates simplified methods to estimate the mass can be erroneous in comparison to high precision LiDAR scans. Advances in technology have enabled the accurate capture of failure geometry and allow a far more accurate analysis of failures to be completed. This case study investigates a number of real-life failures to accurately define the failure geometry, the distribution of the failure parameters and compares this to traditional methodologies. This paper also outlines a suggested means of standardising failure geometry parameters whilst accounting for their variability.

Nov 29, 2022

By M I. Pownceby, M A. Rhamdhani, S Purohit, G Brooks

The current practice of magnetite ore agglomeration involves high temperature oxidation roasting (typically at 1200–1350°C) of magnetite to hematite phase in order to improve the strength and reducibility of pellets. The requirement to pre-oxidise the magnetite before introduction to an ironmaking plant increases the CO2 emissions generated during the ironmaking process. In our previous papers, a novel, alternative agglomeration route for magnetite ores was presented where magnetite was converted to a reducible CaFe3O5 (CWF) phase through the addition of lime to produce a Lime-Magnetite Pellet (LMP) feedstock that can be directly charged to ironmaking units. The LMP process eliminates the magnetite oxidation stage, thereby reducing the CO2 emission during ironmaking. The concept was tested by thermodynamic calculations, high temperature experiments and scaled-down pilot scale test work. In this paper, larger scale synthesis of halfstoichiometric LMPs (1 mole of Fe3O4 and ½ mole of CaCO3) were prepared using a balling drum, followed by overnight drying at 110°C and induration at 1050°C for two hours. The LMPs were analysed using X-Ray Diffraction and Scanning Electron Microscope techniques for phase and microstructure characterisation. The LMPs were found to have 14–15 wt. per cent of CWF phase when indurated under a CO2/CO ratio of 8.5:1. Pilot scale testing of the LMPs was conducted following ISO standard test procedures. The test results indicated the LMP’s had a Reducibility Index (RI) of over 91 per cent, a Tumbler Index (TI) of 87 per cent and a Reduction Degradation Index (RDI) of 4.6 per cent. The results indicate LMPs may be useful as an alternative feedstock to ironmaking processes that would result in lower overall CO2 emissions.

Nov 8, 2021

By B Haase, R Saha

Conditional simulation (CS) has been extensively used in metal industry to assess uncertainty of geo metallurgical variables to build robust distributions around grade tonnages across different time horizons. Coal’s entry to nonlinear stochastic modelling is relatively new and this paper summarises the work done at BHP to enable its practical usage from production time frames to Life of Asset planning. CS in coal using Sequential Gaussian Simulation (SGS) is used to understand resource confidence around specific variables within pre-defined boundaries of spatially continuous domains for each coal seam. The variation between simulations for a given parameter reflects uncertainty. This paper demonstrates the use of CS to profile resource based upon agreed seam/parameter uncertainty thresholds which affect planning, forecasting, extraction and inform identification of key production risks and defining mitigation strategies. The end goal is to de-risk long-term plans by optimising infill data collection and improve stability in short-term planning through increased understanding of confidences locally rather than at global resource definition stages. The paper also briefly discusses the use of automated workflows and systems to minimise the time spent on the process to enable use in decision-making.

Mar 22, 2022

By M Khanal, J Qin, B Shen, Y Duan, X Luo

Gaining confidence in interpreting rock and strata properties of the coalmine roof is necessary for design, maintenance, modelling and optimisation of roadways supports. One of the key causes of roadway instabilities experienced in underground coalmines is an extreme variable nature (thickness, competence, discontinuities etc) of the coalmine roof. Normally, the thickness and strength of the roof are characterised with the geotechnical and geological data gathered from exploration boreholes, which are drilled often at considerable distances apart. This limited data cannot capture localised geological variations in the coalmine roof. With this background, this paper explores feasibility of using measurement while drilling concept to perform geotechnical characterisation of the coalmine roof. The parameters, for example, penetration rate, rotary speed, torque, sound, vibration, obtained during the drilling process can provide valuable insights into geotechnical properties. The paper describes the progress of the experimental work conducted at the laboratory on synthesized concrete samples representing various rock strata using a field-scale drilling machine. The samples with and without interfaces have been tested to replicate various underground roof strata. The signals returned from the drill machine, as the drill bit passes through the layers, have been analysed and interpreted to characterise whether the drill response data can differentiate various strengths associated with the rock layers. The initial laboratory results are promising as they show distinct responses of the various sample blocks in a controlled environment. The drilling data can differentiate the synthesized rock samples and detect ‘signatures’ of the roof strength variability and delineation of lithological interfaces (transitions). The weight and torque on the bit vary and show dependency on the strength of the blocks.

Nov 29, 2022

By J Lyons, M Hasan, D Pepper, C Vadeikis

Processing of large volumes of ultrafine ores has long challenged mineral processing operators because of lower recoveries and increased tailings. This has led to many deposits, or parts of existing deposits, being viewed as uneconomic. As the mining industry can no longer afford to overlook resources that require finer sizes to achieve liberation or result in high tailings losses, the need for technologies to address these issues has increased. Mineral Technologies (MT) worked with a prominent Australian iron ore producer over five years to implement an innovative gravity separation technology for the beneficiation of ultrafine magnetite. The magnetite mineralisation requires a liberation size of <40 μm and selective rejection of ultrafine silica prior to magnetic separation. Through collaboration with the client, MT applied their Lyons Feed Control Unit (LFCU) technology for the beneficiation of finely grained magnetite. LFCUs are widely used in the mineral sands and iron ore gravity plants, and in tailings applications, to recover water and provide constant high density process streams. This project was an extension of knowledge gained from these applications. Test work was conducted on-site, using 1 t/h pilot and 300 kg/hr laboratory scale units. This test work showed that the LFCUs could reject 20 per cent of feed mass to tails whilst recovering >94 per cent of Fe to product. This upgraded the feed from 53.7 per cent Fe and 19.7 per cent SiO2 to 63.8 per cent Fe and 8.8 per cent SiO2. Recovery by size data showed a minimum 88 per cent Fe recovery to product for <8 μm material and up to 98 per cent Fe recovery for the -38+25 μm fraction. The LFCU rejected 70 per cent of <25 μm SiO2. The information obtained from the test work was utilised in the design of the full-scale units which are due for installation at the project site in 2021. This paper outlines the results of this laboratory and pilot scale test work and how the data obtained was used to design the full-sized units.

Nov 8, 2021

By E Kasai, D Maruoka, Y Konno, T Murakami

The iron ore sintering process produces approximately three per cent of carbon dioxide emission in Japan because a large amount of coke breeze is used as the main agglomeration agent. Therefore, its suppression has been required. A promising method is to replace the coke breeze with biomass char and iron-bearing materials. In this study, the effect of the utilisation of metallic iron with coke or palm kernel shell char (PKS char) as an agglomeration agent on its oxidation behaviour was examined by a series of experiments using a sintering simulator. The use of PKS char leads to a larger decrease in the pressure drop difference of the sintering bed compared to the case using coke. Furthermore, the oxidation rate of metallic iron was larger in the case using PKS char together than that using coke. It was considered that the oxidation of metallic iron was promoted because the bed-temperature increased at a faster rate and achieved a higher temperature.

Nov 8, 2021

By S Sullivan

A recent review of resource reports lodged to statutory bodies found geological models with oversmoothed or unrealistic lithological boundaries, many of which do not represent geological appearance in the field, pit or underground drive. The underlying data is often too complex or messy to be incorporated into the resource model and is thus a simplification of reality, to the detriment of the mining operation and its shareholders. Volumes can be over- or underestimated and subsequent grade predictions can be misplaced, combining to cause over- or understatement in resource reporting to stakeholders and statutory authorities. Domain models can be improved with new modelling techniques such as machine learning. However, with poor data or improper use of machine learning techniques, the conclusions can be just as misleading as with current techniques. Machine learning rarely offers a single ‘right’ outcome, rather a range of possible outcomes from the data provided. But importantly it can take advantage of the full richness of data for more informed models. Machine learning also provides confidence in its predictions so that uncertainty in the resultant models can be quantified and passed through for risk assessment during mine planning and operation. This paper will discuss the factors accentuating complexity in deposit modelling: data diversity, structural controls, chemistry, data volumes, process workflows and external non-geological constraints. A case study illustrates the risk of reducing or ignoring complexity, which can result in an overly simplified geological model.

Mar 22, 2022

By J H. Wood, I Gray

This paper examines the occurrence of outbursts, coal bursts and rock bursts in underground mining. It then examines them from the viewpoint of the failure mechanism and velocity of particles. The presence of gas is extremely important as it can both act as the fluid pressure component of effective stress leading to failure, and as a substantial energy source in projecting material during a burst. For gas to drive a dynamic event it must be present as free gas held in voids within the rock or coal mass. This can pre-exist the burst event or be released from desorbing gas during it. The latter is typically part of a multi-stage outburst event which can reach very large proportions. Rock and coal bursts are driven by strain energy release and can vary in form. These tend to be single events associated with failure and strain energy release. It is also possible to conceptually have hybrid events where the failure of the mass and the energy release are due to both stress and expanding gas.

Nov 29, 2022

By I Auranen, J Raatikainen

IMA Engineering (IMA) and Mine On-Line Service (MOLS) companies have used on-line sensors for analysing ore and waste rock in mining for more than 25 years. Today IMA on-line sensors are used in various stages of the mining process including on-line analysis of drill cores, drill chips, ore and waste in loader bucket, ROM ore analysis on belt conveyor belt and in bulk ore sorting and in slurry analysis in concentrators. During years of extensive field experience and testing we have found that the waste rock dilution and ore losses create much larger economic and environmental losses than has been previously recognized. According to our studies the main reason is limited number of analysis already in exploration when drill cores or drill cuttings are used in block modelling. The same happens in production because too few and biased samples from benches are used to estimate the ore grade. Much more than today estimated amount of waste enters the mill and considerable volumes of ore losses happen at the same time. The ore grade on the benches and in muck piles is averaged and “homogenized” with averaged and biased samples. These are the main root causes of waste rock dilution and ore losses. Sensor based preconcentration can be the remedy to waste rock dilution and ore losses. This presentation will show examples of the use of on-line sensors in preconcentration when analysing ore and waste rock in drill cores, drill cuttings, on conveyor belt and in bulk ore sorting. Waste rock removal in preconcentration has direct effect on energy consumption in crushing and grinding and chemicals in concentrator. In concentrator waste is separated and goes to tailings pond, however, preconcentration directly reduces the volume of the tailings. In our presentation we will cover cases in base metals and in gold mines.

Nov 10, 2020

By O Kirtel, A A. Faizan

With the rapid increase and development of high-speed trains (HSTs), the problems such as train-induced ground vibration and its dynamic effects on nearby structures have become a major environmental concern in urban areas. Ground-born vibrations produced by high-speed trains pose a great challenge for engineers to build structures in such areas that is applicable for residents. In order to study the effect of train-induced ground vibration on nearby buildings, an advanced three-dimensional finite element model for train-induced ground vibrations has been developed using PLAXIS 3D Ultimate. The results of the in situ measurements which was previously carried out by the authors were used to validate the numerical model. The field test for ground vibration due to the passage of a high-speed train was carried out on the Istanbul-Ankara high-speed railway in Turkey with a train speed of 250 km/h. An in-depth analysis was achieved to investigate the effect of different soil properties on the train-induced ground vibrations by using the verified model. According to the result of the vibration analysis, the relative vibration response curves in all directions (x, y, z) for different soil conditions were obtained comparatively. The obtained results of the vibration analysis are discussed in order to figure out some useful conclusions.

Nov 29, 2022

By M Pyle, R Ch, T Vizcarra, ramohan, G Lane, G Ballantyne

Preconcentration, through gravity separation (Wallace et al, 2015), magnetic separation and particle size (Clout, 2013), has been used in many historical projects to convert low grade material into ore. More recently, pre-concentration technologies such as bulk sorting (Kurth, 2017), screening (Bearman, 2014) and coarse particle flotation (Vollert et al, 2019) have also demonstrated their ability to progressively reject waste through the value chain. These technologies can not only deliver stepchange improvements to the economics of mining operations, but can transform the environmental and social aspects by minimising water and energy consumption and significantly reduce the quantity of fine tailings produced. However, implementing progressive waste rejection requires technologies and approaches to be combined and applied in the right way to capture the value. From a technical perspective, progressive waste rejection introduces challenges related to the orebody, equipment performance, engineering and understanding the value chain from the resource through to final product. From a management perspective, the key issues are related to people and processes, in particular; motivating the business, challenging the paradigms, and introducing new ways of operating within the constraint of existing management structures to manage risks and minimise lost opportunity costs. This combination of technical and management issues means that progressive waste rejection is a complex undertaking for mining companies, yet the reward for the business and other stakeholders is potentially high and should not be ignored. This paper presents how progressive waste rejection can offer step-change improvements to the business case for high and low grade greenfield and brownfield projects based on case studies completed by Ausenco. The paper then outlines different implementation approaches from concept studies to execution to address the various technical and management challenges outlined above.

Nov 10, 2020

By J Rutter, D La Rosa, P Walters, M Scott, L Keeney

Bulk ore sorting technologies, whether surfaced based or penetrative, have seen an increased uptake by the mining industry for preconcentration application. As with all technologies, going through the technology validation process is key to de-risking the operationalisation of the technologies and to demonstrate and confirm predicted value propositions. The ability to laboratory calibrate cross-belt bulk sensors is standard practise for sensor vendors, however transitioning the technology from laboratory to real-world application is a non-trivial process. The industry has taken two main approaches to trialling and validating bulk sensing technologies in operational environments, namely:  Construct an off-line pilot facility at scale, or  Install bulk sensing systems on production conveyors Each of these two approaches have significant advantages and disadvantages and require different experimental design programs and analysis methodologies. Consideration of material movement, heterogeneity degradation, logistical requirements, and financial investment all factor into which approach is most suitable for an evaluation scenario. CRC ORE in partnership with mining companies, have conducted several bulk sensor pilot trials utilising different sensor technologies employing each of the two main approaches outlined above. This paper describes the challenges faced, learnings obtained and outlines a position on how to transition bulk sensing technologies from the laboratory into the operating environment. The case studies presented cover a range of commodity types in both open pit and underground operations.

Nov 10, 2020

By M Revell, B Sainsbury, D Sainsbury

This paper extends the existing knowledge associated with the design and placement of prefabricated pastefill barricades through a consideration of asymmetric drive geometry and conditions. The load capacity of prefabricated barricades and their failure modes are considered in relation to abutment geology and barricade geometry that includes curvature and span and drive geometry that includes abutment angles, haunch angles and misalignment. Design charts are provided for typical barricade sizes to provide general guidance for design capacities and optimising location placement based on asymmetric drive geometry. A recent barricade failure is considered in relation to the drive geometry and the potential impact it had on the installed capacity.

Nov 29, 2022