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By B P. Voutharoj, R A. Dutch, M Paknezhad, T Ostersen

With the proliferation of new sensor technologies, acquiring multiple data sets over the same ground is becoming cheaper and easier than ever. This new, higher resolution multivariate data provides a significant resource for exploration and resource geologists but comes with the added complexity of effectively integrating the various data sets in useful and meaningful ways to elucidate new geological understanding. Both geophysical data sets and hyperspectral data are extensively used for exploration targeting, providing different information at different resolutions and crustal scales. One of the biggest challenges comes from trying to effectively integrate data sets that record very different physical properties, across the different scales these data are captured at, in a way which can allow for a data-driven analysis of these combined data sets.

Sep 1, 2024

By S Gulati, N Sarkar, T Vink, S Battersby, L Okada

This paper examines a successful project implemented by BHP Mitsubishi Alliance (BMA) and the Polymathian team at Deswik, aimed at enhancing short-term scheduling processes to reduce vessel turn times in the BMA Central Queensland coal value chain. The project’s objective was to digitalise the planning process to enable planners to make data-driven insights to improve the profitability of the value chain. The strategy involved developing a digital mining system that incorporates data storage, cloud computing, and the ability to meet the integration needs of both internal and external business systems. This was complemented by a sophisticated, optimisation-based, decision-support tool to enhance the planning teams’ ability to make timely and effective decisions.

Sep 1, 2024

By K Sherry, N Shahbazi

Scope 3 emissions are a set of often overlooked indirect greenhouse gas emissions within a company’s value chain and represent the majority of emissions for many sectors. These emissions arise from activities conducted by entities beyond the reporting organisation’s ownership or direct control and are often challenging to calculate. Scope 3 emissions typically encompass purchasing goods and services, transportation and distribution, managing operational waste, downstream processing and utilising sold products. Within the mining sector, scope 3 emissions often constitute a significant portion of the overall carbon footprint. Therefore, these emissions are a significant aspect of the future of sustainable mining. As the journey towards a world committed to achieving Net Zero Emissions has started, the time to spark a transformative conversation in the mining industry has arrived. Consequently, a better knowledge of scope 3 footprints allows organisations to assess their emission mitigation projects against the total carbon impact of their operations and products.

Sep 1, 2024

By J Coveney, A Rich, D Grimsey, J Wood, S Creedy

In 2021, BHP and Metso examined processing of high-MgO nickel sulfide concentrates using Metso’s Ausmelt Top-Submerged-Lance (TSL) technology. Test work was conducted in Metso’s pilot test work facility in Dandenong, Australia to explore operability of the SiO2-FeO-MgO-CaO-NiO slag system across a wide range of compositions, temperatures and bath oxygen potentials. Pilot-scale testing aimed to define slag ‘operability limits’, representing the lowest bath temperature at which stable process and equipment operation could be maintained. This work was supported by FactSage™, version 8.2 (by Thermfact/CRCT and GTT-Technologies) thermodynamic modelling, slag viscosity measurements, physical characterisation of quenched slag samples performed by the University of Queensland and benchmarking of commercial-scale TSL nickel smelting operations. A wide range of slag compositions were examined, with Fe/SiO2 ratios varying from 0.4–1.1, CaO content from 0.8–7.0 wt per cent and MgO content from 6–19 wt per cent. Slag SiO2/MgO ratio, wt per cent CaO and matte grade were found to have the greatest impacts on identified operability limits. Operability limits were found to be influenced by both the solids content in slag and viscosity of the remaining liquid slag phase, with the relative contribution of these parameters heavily influenced by the slag composition. In the majority of trials, limits were defined by a theoretical solids content of 40–50 per cent, however in trials with a low Fe/SiO2 ratio and/or low wt per cent CaO, limits were characterised by a much lower solids content due to the increased effect of the liquid slag viscosity in determining the behaviour of these slags. The test work highlighted inherent flexibility of the Ausmelt TSL process to operate across a wide slag range of slag compositions and recover from process disturbances without an interruption to feeding. The trials also demonstrated the possibility for Ausmelt TSL technology to process concentrates with an Fe/MgO ratio as low as 1.4, which has important implications to the commercial-scale processing of high MgO feeds. Arsenic rejection across the trials was very good, with only 30 per cent of arsenic in the feed inputs reporting to the matte phase. Such high levels of arsenic removal provide the Ausmelt TSL process with a notable advantage over alternative smelting technologies.

Aug 21, 2024

By A Van den Bulck, K Verbeken, O Vergote, I Bellemans

Viscosity is one of the most important physicochemical properties during pyrometallurgical operations. In the sub-liquidus regime, an important factor is the presence of suspended solid particles, yet its influence is not well-described in earlier literature, despite the significance of this factor. This project aims to determine the influence of spinel particles (Zn(Al,Fe)2O4) on the rheology of a multiphase synthetic PbO-SiO2-ZnO-Fe2O3-CaO-Al2O3 slag system. Three data sets with a wellcontrolled methodology and three different spinel sizes (small (13 μm), medium (34 μm) and large particles (76 μm)) were published previously, using a custom-built high-temperature rheometer. This study presents an additional data set of slag viscosity measurements, performed using a different apparatus, the Anton Paar FRS 1800, to verify the consistency of the earlier determined viscosity behaviour. Within this data set, no consistent trend could be found between the predicted wt per cent spinel and the relative viscosity. Therefore, additional quenching experiments were conducted to identify the morphology and experimentally determined volume fraction of the spinel particles in the slag. These measurements revealed a difference in spinel size across the samples and corresponding viscosity behaviour, emphasizing the importance of spinel particle size on slag viscosity. Once the spinel size was taken into account, consistent viscosity results (relative apparent viscosity and flow index) were observed across the two devices. This study confirms that, once all parameters affecting slag viscosity are considered, the viscosity behaviour of a heterogeneous slag can be uniquely determined. The resulting optimised slag viscosity models can be used to predict viscosity before processing, addressing relevant phenomena such as slag tapping, slag foaming and copper droplet settlement.

Aug 21, 2024

By R E. Gerald II, B Zhang, T Sander, J D. Smith, J Huang, R J. O’Malley, H Tekle

In the steelmaking process, mold fluxes are essential for ensuring thermal insulation, refining, and the efficiency of continuous casting. Real-time understanding of the in-service composition of slags and fluxes are crucial for optimising the steel production process and improving the quality of the final product. An in situ fibre-optic Raman probe that enables the study of the structure, composition, and viscosity of molten slags and fluxes at steelmaking temperatures has been developed and demonstrated both in the lab and in foundry scale experiments. The focus of this study is on the structural, compositional, and property analysis of molten fluxes in a laboratory setting, with the aim of applying this technology for in situ monitoring during industrial production. Raman spectra were successfully collected at various temperatures from 1000°C to 1400°C in real-time and analysed using a deconvolution algorithm to isolate and quantify peaks in the spectra associated with the specific structures of molecular components in molten and solidifying flux. The research successfully combines in situ Raman spectroscopy with high-temperature viscosity data, specifically targeting CaO-CaF-SiO2-Al2O3 based mould flux systems. Specified ratios of the deconvoluted Raman peaks, such as Al-O-Al/Si-O-Si ratio, shows good correlation with the flux chemistry, while the Q3/Q0 peak ratio shows good correlation with viscosity. A ruggedised Raman probe system was also developed and demonstrated in an 80 kg induction furnace. Ultimately, the goal of this work is to demonstrate in situ slag and mould flux analysis in industrial processes, such as in the continuous caster or electric arc furnace (EAF).

Aug 21, 2024

By G M. Tranell, M Tangstad

The CO2 footprints in the production of Mn-ferroalloys and silicon/ferrosilicon are correlated with the fossil carbon consumption. The CO2 emissions may be reduced in the Mn-ferroalloy process by increasing the degree of prereduction and reduction of carbonate materials, while the silicon/ferrosilicon process is optimised based on silicon yield. By changing the fossil reductant into biogenic reductants, the global warming potential will be decreased even more. Even if the reductants are biogenic reductants, there will still be a global warming potential (GWP) in eg the electrode consumption and the CH4 emissions in the charcoal production. To reduce the use of fossil reductants there are also more disruptive technologies like the use of H2 that at least for the silicon production is on a very low technology readiness level (TRL). Using metallothermic processes will reduce the use of carbon but requires carbon neutral metal reductants. Electrowinning can have low CO2 emissions, and the electrowinning of pure Mn is a technology of high TRL. Salt and oxide electrolysis is under investigation for both Mn and Si production however the research is still on a low TRL. The use of CCS/CCU (carbon capture storage/utilisation) is a part of obtaining carbon neutral processes. Last, the energy mix used for these energy demanding processes is discussed.

Aug 21, 2024

By E Jak, M Shevchenko, E Nekhoroshev, D Shishin

In the field of pyrometallurgy, the presence of multiple molten phases with distinct chemical compositions, such as slags, mattes, speiss liquids, metals and molten salts, is a well-known phenomenon. These phases exhibit strongly non-ideal solution behaviour and are mutually miscible to varying degrees. To describe these complex molten liquids, the Modified Quasichemical Model (MQM) has proven effective and has been applied to numerous binary, ternary and several higher-order multicomponent systems related to pyrometallurgy. In recent decades, the complexity of high-temperature processes has escalated due to increased impurity concentrations in primary ores, the incorporation of recycled consumer products and the integration of metallurgical plants through by-product and waste exchanges. To address these issues, PYROSEARCH laboratory has been developing large 20-component thermodynamic database using a generalised CALPHAD (CALculation of PHAse Diagrams) methodology integrated with experimental investigations. Over the past decade, strategic decisions were made balancing the ability to generate experimental data, prediction power, accuracy, stability of calculations, as well as computational time, which are discussed in the paper. Examples provided for issues of >3 liquid immiscibility, non-ionic behaviour and exaggerated ‘sharp’ enthalpies of mixing in silicate slags, dealing with multiple oxidation states, as well as comparative analysis of pair and quadruplet approximation in MQM.

Aug 21, 2024

By P Taskinen, D Lindberg

The increase in metals demand in the electrifying globe means significant growth in the smelting of copper, nickel, zinc, and lead, produced from primary sulfide sources or using sulfide mattes as the intermediates of the process chains. This means that leaner and complex mineral deposits will be evaluated as ores and are in the future traded in the commodity market for smelting and refining to pure metals. An important issue in the trend is the technology metals, like antimony, tellurium, and gallium, which exist as trace elements in sulfide ores and form no ores of their own. Their recovery becomes important in the coming decades as will be the case with growing slag amounts without use in other industries. The key is to produce environmentally acceptable slags in the smelting operations. It sets new boundary conditions to the treatment of flue dusts. This means that all material streams of smelting and refining must be re-evaluated for the deportments of the main and minority metals. In copper smelting, the recoveries of precious metals are today important for the feasibility of the custom smelters but due to low prices of many minority metals they are discarded in slag landfills. It is one of the emerging issues also in the secondary copper smelting today and once the demand grows, the same question will be faced also in the mining-beneficiation-smelting-refining chain of the primary production of nickel, zinc, and lead. The distributions of many technology metals in the copper and nickel smelting have been recently studied using methods where the chemically bound trace elements in the slag and its phases at the smelting conditions have been studied. Thus, the key data about options for process modifications and additional processing steps are piling up. Short processing routes in the metals smelting and refining are attractive due to their simplicity. At the same time, complexity of many raw materials challenges the fluxing at high oxygen partial pressures in low silica slags with high metal concentrations. The compromise between high primary recovery and safe operation is a demanding task in conditions where slag foaming outside the processing window is evident. The increase in the demand of pure nickel is challenging the raw material basis where low-grade sulfide ores are soon smelted along with nickel laterites to matte. It is a demanding task at high MgO concentrations. The low solubility of MgO in iron silicate slags requires new fluxing strategies and new smelting end points for the operation at reasonable temperatures; the direct nickel matte smelting in one-matte mode may be an option.

Aug 21, 2024

By M K. Nahian, R G. Reddy

The thermodynamic model for species distribution in aluminium chloride (AlCl3) and 1-butyl-3- methylimidazolium chloride (BMIC) system was developed. The experimental thermodynamic data, considering a range of aluminium chloride species, such as AlCl4-, Al2Cl7-, Al3Cl10-, Al4Cl13-, and Al2Cl6 were used in developing the model. When the XAlCl3 was in the range of 0 to 0.50, only anion species Cl- and AlCl4- were existing in the solution. As the XAlCl3 value increased more than 0.50, the available anions were Al2Cl7-, Al3Cl10-, Al4Cl13-, and Al2Cl6. Specifically, the concentration of Al2Cl7- increased in the composition range from 0.50 to 0.67 XAlCl3, after which it decreased. This change in the concentration of Al2Cl7- was due to its reaction with excess AlCl3, leading to the formation of Al3Cl10-. The average cathode current density was determined by the electrochemical experiments varying XAlCl3 from 0.50 to 0.71 in the AlCl3:BMIC solutions. The average cathode current density increased as the XAlCl3 increased from 0.50 to 0.67. However, it decreased when the XAlCl3 > 0.67. This trend can be attributed to the electroactive species Al2Cl7-. The Al2Cl7- promotes the reduction rate at the cathode, resulting in an increase in the average cathode current density.

Aug 21, 2024

By K. G. Philo, R. C. W. Webber-Youngman

mining, where data-driven decision making optimizes resource extraction, enhances safety, and ensures sustainability. The adoption of digital technologies like artificial intelligence (AI) and the Internet of Things has amplified the importance of digital information. However, the integrity and security of this information are paramount, leading to the exploration of blockchain technology as a potential solution for secure digital value exchange in mining. This research examines blockchain's capabilities, drawing insights from its applications in sectors like banking, government, healthcare, and entertainment, and evaluates their relevance to mining's core value chain processes. The study identifies blockchain's distributed ledger technology, cryptographic security, and decentralization as unique advantages that can revolutionize mining by enhancing transaction speed, reducing costs, and improving supply chain transparency and compliance with sustainability standards. Blockchain's transparent and auditable records can enhance business transparency, fostering trust among stakeholders, including investors and regulatory bodies. The technology's consensus mechanisms and smart contracts further promote trust in collaborative ventures. This research provides a foundational understanding for decision-makers in the mining industry to evaluate blockchain's feasibility and potential return on investment, guiding strategic planning and resource allocation for blockchain applications. By leveraging blockchain, mining companies can optimize operations, improve sustainability practices, and establish a robust foundation for future growth, positioning blockchain as a transformative technology in the sector

Jul 10, 2024

By Scott Burchmore, Jason Emery, Michael Melville

This paper presents best practice data management for monitoring of extensometers in Australian underground coal mines. This work is based on the combined experience of the authors and the available literature. The information and ideas presented herein are a culmination of many years of database development founded from mine site-based ground support design, underground inspections, extensometer data management and data analysis. Each author has more than ten years’ experience as a practicing geotechnical engineer at several operating industry wide research project focused on utilizing mechanical extensometer data for data analytics and machine learning. Principal hazard ground control management plans, stipulated in Australian coal mining legislation, outline the mandatory installation of ground monitoring devices during routine mining activities. After 20+ years of data gathering the barrier to implementing modern data analytics remains the challenges imposed by inconsistent data structure and data quality. This inconsistency is still routinely found between sites, companies and mining regions. Through the relatively simple application of a standardized database structure, the potential to shift from simplistic tracking of trigger levels, siloed at individual sites, to an industry standard method for compilation & comparison of monitoring data is enabled.

Jun 25, 2024

By T. M. Barczak, Zach Agioutantis

The Support Technology Optimization Program (STOP) has been developed by the National Institute of Occupational Safety and Health (NIOSH) to provide a comprehensive tool for evaluating the performance of available secondary roof support systems and designs based on support strength, convergence, cost, installation time and material handling considerations. This program uses engineering models developed from full-scale testing of numerous supports under controlled loading conditions in the unique NIOSH Mine Roof Simulator load frame to determine the support load-displacement performance as a function of the various sup- port design parameters. Both standing supports, such as wood cribs installed within the entry, and intrinsic supports such as cable bolts, can be evaluated. Support systems can be designed and compared for use in a new mining section or to evaluate potential replacements for an existing design. The support design requirements are defined from 1) estimating the failure height in the immediate roof, 2) in-mine measure- ments of support and strata interaction or development of ground reaction curves from numerical modeling, 3) the performance of an existing support system, or 4) from any arbitrary load and convergence criteria. All settings can be saved to permit resuming an evaluation in progress at a later time. This paper presents the updated MS Windows version of this tool, which can be easily installed and run on a personal computer. This Windows implementation will feature a project and application scenario setup where multiple scenarios can be assigned to one project. Scenarios can then be compared on support parameters and cost. Cost parameters can be provided either as individual cost items or using a price grouping feature. Additional support performance curves and/or additional ground reaction curves will be distributed with program updates as new information is developed. Users can also provide their own support and/or ground reaction curves.

Jun 25, 2024

By SME SME

NORTH AMERICAN TUNNELING 2024 PROCEEDINGS

Jun 23, 2024

By Elnaz Saminfar, Jae Bateman, Eric Westergren, Mark Trim

This paper presents a case study of two major Australian infrastructure projects that used digital engineering to facilitate design delivery: WestConnex Project (Rozelle Interchange), and Sydney Metro West (Eastern Tunnelling Package). The paper presents project overviews and building information modeling (BIM) execution and focuses on modeling techniques, software utilization, data management strategies and how the digital models helped the design-build team mitigate impacts to schedule by identifying clashes between disciplines before the execution of work. Finally, it demonstrates the positive and transformative impact of digital engineering on the design and construction of large underground infrastructure projects and highlights its role in asset management throughout the project lifecycle.

Jun 23, 2024

By Jamal Rostami, Tom Iseley, Saleh Behbahani

Tunnels and underground infrastructures assets, like all assets, deteriorate with time. At some point, they reach the end of their useful life. Therefore, frequent inspections, higher levels of maintenance, and rehabilitation are needed to address loss of life and safety concerns. The repair cost of tunnels will increase if maintenance of tunnels is not satisfactory and timely. Historically, tunnel inspections have primarily relied on visual and manual procedures. Due to their time-consuming nature and susceptibility to human error, there is a demand for alternative automated techniques that can enhance efficiency and reliability in tunnel inspection. By utilizing a tunnel scanning system, such as laser scanner and thermography, or photogrammetry system, tunnel inspection cost, time, and personnel can be reduced. The goal of this study is to utilize deep convolutional neural networks (CNNs) for automated identification of defects in tunnel lining inspection. This paper presents a framework to classify two types of defects in tunnel lining (water leakages and cracks) using CNNs. The CNNs were trained and tested using 4,608 images. The Precision, Recall, and F1 Score were each 99.6%, confirming the viability of this approach in the automated defect identification in tunnel lining.

Jun 23, 2024

By Matt Bilson, Ritesh Mahajan, Antoni Kuras, Wataru Okada

The Waterview Tunnel comprises twin 2.4 km long 13.1 m internal diameter three lane road tunnels in Auckland, New Zealand. The City Rail Link (CRL) is a 3.45 km long, 6.24 m internal diameter twin rail tunnel underneath Auckland’s city center. This paper presents an overview of the tunnel geometry, segmental lining congurations, geometric constraints, performance criteria and functional reuirements for the large diameter Waterview Tunnels and smaller diameter CRL tunnels. Other key aspects, which include sustainability, innovations, construction performance and practical aspects are discussed and compared. Lessons learnt from these mega tunnelling projects are also presented.

Jun 23, 2024

By Tom Michaud, Rob Albinger, Ian Turner, Michael Rispin

Data transmission, communication, tracking, and the connection of equipment such as gas detectors, cameras, and collision avoidance systems in today's tunnel industry are critical pieces of the constructor's infrastructure. Reliability, flexibility, redundancy, and cost-effectiveness are key in selecting and implementing inte- grated systems. Both wired and wireless components are used to deliver custom solutions and can involve interconnectivity between backbones. Systems integration is important as industry adopts proven technologies from other industries. Case stud- ies are given showing how tailor-made approaches deliver needed functionality, with varying degrees of com- plexity, in various classifications of environment, in order to meet a project need.

Jun 23, 2024

By S. Klein, M. McLeod, S. Gambino, K. Johnson, E. O’Hara

The Mokelumne Aqueducts Resiliency Project (MARP) involves construction of a 16.5-mile tunnel across the Sacramento-San Joaquin Delta (Delta) to replace the existing surface aqueduct pipelines with more resilient conveyance. The tunnel will be bored in Pleistocene-age alluvium at elevations between 100 to 10 feet below mean sea level. At this depth ground conditions are signicantly stiffer and denser than surcial soils and will mitigate potential seismic harards related to liquefaction ground shaking and cooding that could arise from potentially damaged levees. The heterogeneous soil deposits at tunnel depth consist of interbedded layers of stiff to very stiff clay and silt, and dense to very dense clean sand and silty sand.

Jun 23, 2024

By Gunjan R. Bhattarai, K. Bhattarai

Applications of machine learning and robotics in the tunneling industry are still nascent. Research and development are ongoing in TBM guidance; prediction of TBM cutter wear and tunneling induced ground deformations; and robotic arms for segment installation, inspection, cleaning, and maintenance of TBM cutting tools. This paper presents a case study of geological profile reconstruction using multimodal machine learning. The results from this study can aid the development and application of multimodal AI technologies to generate data reports and geological profiles in real time, taking voice recordings, photos, or videos obtained directly from the field as inputs.

Jun 23, 2024