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By G McCullough, J Bassan, d P. Knights, C T. Farrelly

By 2045, carbon-neutral mines will be economically producing products that are vital for the world’s transition to renewable energy. After overcoming significant technical challenges (and the investment of significant capital), leaders have successfully eliminated the use of diesel and other fossil fuels by introducing a wide range of new decarbonisation technologies. These leaders will be reaping the benefits of lower production costs (resulting from elimination of diesel), stable and predictable operations, and easier access to capital for their future projects. This paper describes a future scenario of how a net zero carbon and zero-entry mine could operate by taking maximum advantage of technologies in development or already proven in other industries. Some miners have been unsuccessful in their efforts to reach decarbonisation targets. Instead, they have been forced to close or offload their assets to be acquired by operators with better sustainability credentials, or, in some cases, to indigenous or community-based enterprises with vested interest in making operations viable and sustainable. Regardless of ownership structure, all successful mining operations will have fostered strong and positive community relations that bring education, health, security and economic development opportunities to the communities while respecting their traditions, land-uses and culture. As shallow, easy to mine deposits have become scarce, the majority of new mines are underground. Advancements in electric underground technology and the feasibility of ‘zero entry mining’ (with no personnel in active mining zones) has made it increasingly possible to economically operate underground mines, even at shallow depths. The newest mines have a near zero footprint on the surface, produce no harmful by-products, and are employing in-place or in situ methods of extraction that are efficient and low impact. Surface land-uses, such as agriculture and renewable energy generation, continue in the immediate vicinity of the mine, with no significant ground disturbance, community impact or environmental footprint.

Sep 1, 2024

By S Prakash, M Danish, D Kumar

The green energy transition is speculated to cause an increase in the demand for raw materials while recycling rates are improving; discoveries are required to maintain supply. Geological remote sensing offers a cost-effective way of exploring mineral resources. While satellite and airborne imaging are routinely used for exploration targeting, a gap remains at the outcrop scale. Hyperspectral imaging (HSI) is advantageous for large-scale regional mapping, typically performed from satellite or airborne platforms. Accurately mapping geological lithologies remains challenging in inaccessible areas, such as rough terrain or mine sites. Proximal sensing techniques can boost geological activities’ reliability, safety, and efficiency in exploration or during mining activities. It also generates objective, reproducible results and valuable raw data that can be archived, further processed, and re-interpreted. Ground-based hyperspectral imaging of outcrops has steadily increased during the last decade due to sensor development and better processing routines. There is often a big technology gap related to mineral mapping, integration of images and spectra (reduction in manual identification of minerals and types) and hyperspectral data visualisation through remote sensing. TEXMiN Foundation, in collaboration with its industry partner Dassault Systemes Foundation, carried out the project, ‘Developing Hyperspectral Image Processing and Analysis, build a rich library of Hyperspectral images of a vast range of minerals from India which will help in increasing prediction accuracy of mineral deposit for mining exploration’.

Sep 1, 2024

By J Leem, S Mehrishal, J Kim, A Fereshtenejad, J Song

Rock mass discontinuity mapping plays a crucial role in developing a reliable Discrete Fracture Network (DFN), providing insights into the distribution of geometrical and mechanical properties of discontinuities. This enables an accurate assessment of geotechnical infrastructure and mining excavations. Data obtained through conventional mapping approaches are substantially limited by factors such as accessibility and subjectivity. Moreover, these conventional methods may pose inherent risks due to manual techniques, exposing practitioners to potential dangers. Recent digital developments in remote surveying techniques offer opportunities for safer and more reliable rock mass discontinuity surveys. These technologies allow extensive three-dimensional surveying and the production of high-resolution 3D surface models, applicable at any time. This paper presents a workflow for digital discontinuity mapping employing drone technology and photogrammetry. Additionally, the capabilities and challenges of applying artificial intelligence (AI) algorithms in the rock mass discontinuity characterisation process are discussed.

Sep 1, 2024

By J Johansson, J Lööw

There are many reports about how the new technology will affect our work, sometimes they are utopian but often dystopian. Most of the visions describe the industrial work, while the work of the managers does not seem to be affected. In this article, the authors will discuss how the new technology within the concept of Mining 4.0 changes the conditions for leadership and the work of managers in a modern mining industry.

Sep 1, 2024

By B P. Banerjee. S Raval, P M. Ranasinghe

Simultaneous Localisation and Mapping (SLAM) is an important technology that enables autonomous robots to navigate independently and create detailed, real-time maps of their surroundings. This capability is crucial in underground mining settings, where it enhances operational efficiency and significantly strengthens safety in these subterranean environments. SLAM algorithms typically rely on identifying and using distinct geometric features, such as plane and edge features, to understand the spatial layout of the environment and to track how it evolves as the sensor moves through it. In underground roadways, the scarcity of noticeable edge features, coupled with the repetitive nature of walls and corridors, poses a significant challenge, making it difficult for these systems to distinguish one area from another. Furthermore, the absence of global navigation satellite system (GNSS) signals in underground adds more challenges, leading to the accumulation of errors in both the mapping and localisation.

Sep 1, 2024

By B P. Banerjee, D Patra, S Raval

Roof bolts are an essential component of roof support systems in underground mines. They are used to provide structural support to the roof of the mine and prevent it from collapsing. Therefore, it is imperative to perform regular assessments of these roof bolts to avert any hazards. Manual investigations of roof bolts are done by surveyors in underground mines, which is extremely timeconsuming and challenging due to the low-light conditions in underground mines accompanied by stringent mine access rules. To this end, automated recognition of roof bolts in 3D point cloud data obtained through laser scanning in underground mines serves as a potential solution to aid roof bolt monitoring. With the continuous advancements in laser scanning-based 3D data acquisition systems, the feasibility of making such surface estimations from 3D point cloud data has increased severalfold.

Sep 1, 2024

By T Hicks

Designers of mining facilities play a significant role in defining the overall mine greenhouse gas emissions performance. This demands an appreciation of all the greenhouse gas emissions sources, including Scope 3 emissions, which will form an increasing fraction of the emissions as we transition our generation sources to renewable energy. Traditionally overland conveyors are designed to operate as fast as practical, and through this approach, achieve relative minimisation of: conveyor belt tensions; belt width; mechanical equipment masses; structural steel quantities; and concrete quantities. It is well understood that higher belt speeds reduce capital cost and improve project economics. Operating at higher speeds introduces operating costs through system energy losses and increased wear rates. This paper assesses the life cycle greenhouse gas emissions for a typical iron ore overland conveyor to demonstrate how the design criteria and engineering decisions impact greenhouse gas emissions and project economics. An analysis of the decarbonisation potential and project economics using a range of operational parameters has been completed, developing a marginal abatement cost for each system configuration, creating a basis for integration of low emission overland conveyor designs as part of the broader facility decarbonisation strategy.

Sep 1, 2024

By B Murphy

Seeking to reduce the likelihood of uncontrolled personnel entry into the operating footprint of a dragline, Coronado Global Resources initiated a review of proximity detection systems currently available and equipment interactions in and around dragline operational areas. At the time of the assessment, there were no established personnel proximity detection systems in compliance with functional safety standards for large machinery in Australia. Our primary objective was to guarantee a functionally safe outcome, particularly by implementing a performance-level-rated system in accordance with AS4024 (Safety of Machinery series of Australian Standards). Applying appropriate detection technologies, the goal was to reduce the residual operating risk for machine-to-machine and machine-to-personnel interactions. A comprehensive analysis of available or in-development technologies was conducted, and a layered approach (demonstrated in Figure 1) was adopted to achieve the desired risk reduction by segregating the sensing zones into distinct areas using diverse and disparate technologies consisting of radar (short); light detection and ranging (LiDAR) (medium); and optical (long). To address the potential limitations of each technology, overlapping layered sensing zones were designed. With LIDAR and optical using two distinct artificial intelligence (AI) systems to classify detections, these were specifically trained to handle the unique environments of a mining operation.

Sep 1, 2024

By H S. Shin, H Jin, B H. Ryu, J Lee

Prospecting ice on the Moon necessitates drilling systems to obtain subsurface samples and measure the composition of ice deposits. Landers and rovers equipped with drilling equipment are essential for analysing ice and subsurface resources located at the Moon’s poles. These devices must be small, lightweight, low-power, highly efficient, and high-performance units to function properly in the extreme conditions of the lunar environment. Researchers have developed a prototype drilling apparatus capable of operating in atmospheric and cold environments. A newly developed drilling system in Korea, capable of performing not only sampling but also subsurface investigation, is introduced.

Sep 1, 2024

By C Xu, B Li

Multi-sensor fusion visual perception technology significantly enhances visual perception capabilities in complex and harsh environments by combining visual data from different sensors. This technology is especially useful for scenarios where traditional single visible light sensors, such as standard cameras, struggle due to poor lighting, adverse visual conditions, or other visual obstructions. In environments with low light, smoke, or dust, the performance of conventional visible light sensors degrades, limiting their application. By integrating data from various sensors like radar, infrared thermal imaging, and others, multi-sensor fusion technology provides a more comprehensive and complementary visual solution. This fusion not only enhances the robustness of visual systems but also greatly expands their potential applications in fields like visual surveillance. In recent years, deep learning methods have become the mainstream technology for addressing multi-sensor fusion issues, demonstrating significant advantages in adaptive feature selection compared to traditional machine learning methods. However, deep learning-based multi-sensor fusion algorithms still face several challenges. The design of network structures is often redundant, lacking effective screening of useful components within multimodal information. Mainstream fusion algorithms focus excessively on improving display effects without adequately considering the needs of downstream applications and tasks. Existing fusion perception algorithms are generally designed for open visual scenes and lack targeted design for complex visual degradation factors present in tunnel environments of mines. Current deep learning methods for designing multi-sensor fusion networks heavily rely on manual experience to create fusion modules. This reliance increases the complexity of network design and can lead to redundancy. Redundant network modules are difficult to identify in end-to-end learning tasks at this stage, significantly slowing down network inference and potentially interfering with the output of fusion perception. Additionally, training these fusion modules typically requires large amounts of well-annotated multimodal data, further increasing implementation difficulty and cost. For instance, the fusion network design proposed by Li and Wu (2018) focuses on extracting multimodal fusion features, while Zhao et al (2020) introduced a feature decomposition mechanism in the feature fusion and extraction modules. Researchers like Zhang and Ma (2021), Xu et al (2020), and Liu et al (2017) have attempted to improve network structures through dense cascades and the introduction of residual connections. Although these methods have improved the handling of multimodal information to some extent, they still face limitations in distinguishing between useful and redundant information, with redundancy persisting in network designs. Ideally, the design of fusion networks should be more intelligent, guiding network structure design heuristically based on the importance of different modal information for the current task. This would reduce information redundancy and network weights, requiring the development of new algorithms or frameworks capable of automatically identifying and optimising fusion strategies, thereby reducing dependence on manual experience while improving fusion efficiency and network performance. Current deep learning designs for multi-sensor fusion algorithms often overlook the

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 C. Allen, H. Zhang, L. Falk

Shock loss occurs when there is a change in the area of a drift or airflow direction. These shock losses accumulate throughout the ventilation system and will increase the mine resistance as underground development deepens or becomes more complex. Hence, shock losses should be carefully considered when establishing the resistance through a series of branches as they can be a significant contributor to the estimated mine resistance. Using computer software to simulate a ventilation system is common but applying reasonable shock loss factors in the software is not a simple or direct process. Determining shock loss values includes the consideration of historical measurements, application of factors and formulas from literature based on the geometry and complexity of junctions, and the geometry variation at different locations. For example, the shock loss at the bottom of a ventilation raise can consist of a 90° bend and a sudden area change. This paper presents an approach for estimating shock loss factors near raise junctions using computational fluid dynamics (CFD). Current and future work will also be compared with field measurements. Results from this approach are compared with software defaults as well as classical techniques in published literature and standards.

Sep 1, 2024

By K Saito, M Hasegawa

In steelmaking processes, it is known that P2O5 in dephosphorisation slags often exists in solid solutions between Ca2SiO4 and Ca3P2O8, <C2S-C3P>SS, and thus the solid solutions play an important role in the dephosphorisation reaction. Hence, the knowledge of thermochemical properties, ie phase relations and activities of components, in slags containing <C2S-C3P>SS are necessary for the effective removal of phosphorus from hot metal. In this study, the P2O5 activities in <C2S-C3P>SS were measured through the gas equilibrium method. In the present experiment, oxide samples were equilibrated with Cu-P liquid alloys at 1573 K under a stream of Ar + H2 + H2O or Ar + H2 + CO2 gas mixture in which oxygen potential was fixed and then equilibrium phosphorus concentrations in the Cu-P alloys, [mass%P]Cu, were analysed with ICP-OES.

Aug 21, 2024

By D Stepanenko, G Stovpchenko, L Lisova, D Togobitskaya, L Medovar

Classical electroslag remelting of consumable electrodes is a drop-by-drop melt feeding through a slag layer into a renewing molten metal bath, slowly solidifying into a homogeneous, dense, defectfree ingot in a copper water-cooled mould. The new look at the additive nature of the electroslag remelting (ESR) process in a protective atmosphere allowed us to formulate the principles of a comprehensive thermodynamic-based model that can predict dynamic changes in slag and metal composition at certain ingot remelting. The model considers drastically different slag-to-metal mass ratios at the beginning and end of remelting and predicts gas, slag and metal composition in a chain of thermodynamic subsystems. Despite consisting of calcium fluoride and stable oxides, the ESR slag can oxidise main and active elements from steel and alloys (primarily aluminium, titanium and silicon) due to chemical reactions between slag and metal. ESR is not an electrochemical process in its nature. However, slags are ionic melts and deviation in their composition causes a change in their properties, affecting both operation mode and ingot quality. Another important understanding derived from the modern metallurgy technological route is that the ability to refine metal from impurities is not a priority for the ESR because consumable electrode has already passed all stages of refining and deep degassing at ladle treatment that changes ESR slags engineering principles. The critical importance became slag’s ability to generate process heat and keep the melting composition in the metal bath unchanged (except for non-metallic inclusions assimilation). Slag engineering for ESR required a compromise between chemical inertness to a metal composition and desired physical properties deriving from technological reasons. The Directed Chemical Bonds Concept (DCBC) in a multicomponent oxide system was used to build predictive models of electric conductivity and the melting temperature of fluoride-oxide slag based on their chemical composition. Both models help to design a customised composition of effective slags for steel and alloy groups or individual grades, and they are significant steps in the development of a comprehensive model of electroslag remelting.

Aug 21, 2024

By G M. Zhomin, A S. Arkhipin, A Kondratiev

Viscosity of multicomponent slags is one of the crucial physicochemical properties for many industrial processes and technologies. While the viscosity-temperature relationship of completely molten slags can well be described by an Arrhenian-type law, the compositional dependence of viscosity is still not fully understood, especially in compositional regions with the lack of experimental data (eg at the glass-former concentration of 90 molar per cent or higher). In the present work major compositional relationships of the activation energy of viscous flow have been revised for numerous binary and ternary slag systems on the basis of experimental data collected and stored in the viscosity database OxiVis. For example, it has been found that the activation energy relevant to the polymerisation effect in binary systems of the MO-GFO type, where MO is the modifier oxide (ie monovalent K2O, Na2O, Li2O and bivalent CaO, MgO, BaO, MnO, PbO etc) and GFO is the glass-forming oxide (SiO2 or B2O3) is not always proportional to the third power of XGFO (contrary to the Urbain formalism) and can vary significantly dependent on the slag system. Also, the activation energy of the charge compensation effect has been revised for ternary systems of the AO-MO-GFO and AO-MO type, where AO is the amphoteric oxide (Al2O3, Fe2O3 or other). A simple polynomial model has been proposed on the basis of the carried-out analysis for estimation of viscosities of multicomponent slag systems. The model has been optimised against the experimental viscosities in the selected binary, ternary, and higher-order oxide systems and has been shown reasonable agreement with the experimental data.

Aug 21, 2024

By S L. Nicol, B J. Hogg, O J. Mendoza, S Nikolic, A Burrows

The top submerged lance (TSL) technology, developed in the 1970s, is now widely used for the processing of a range of materials. The key advantage the ISASMELT™ TSL technology provided was the ability to process feed materials in a highly turbulent bath, reaching close to equilibrium conditions, uniquely allowing for operation below the liquidus of the molten slag phase. The details on what happened below the liquidus line in the phase diagram became critical for the successful operation of the technology. During the development of the ISASMELT™ technology this led to a collaboration between the Process Technology group of Mount Isa Mines, now part of Glencore Technology, and the Pyrometallurgy Research Centre (PYROSEARCH) at The University of Queensland. The fusion of the phase equilibria research into the technology development allowed for understanding of the behaviour of molten splash, reliable tapping of the furnace, and the ability to operate the furnace with a refractory lining and achieve a year campaign life in excess of four years. The outcome has allowed for the highly successful adaption of the ISASMELT™ technology to recycling of complex feed streams necessary to drive circularity in our modern global economy.

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 G Sartor, A Rich, D Grimsey, R Forzatti, M White

An in-depth process model was developed for the pyrometallurgical, off-gas systems and water balance of the Kalgoorlie Nickel Smelter. This model was used to assess plant capacity with changing concentrate grades, increased throughput and tighter environmental emissions under a range of potential future operating conditions. Comparison of modelled results allowed for flow sheet optimisation across a range of metrics including sustainability, processing capacity and costs. Process modelling software, METSIM® (ver 2020.06 by METSIM International), was used to simulate the flash furnace, integrated electric slag cleaning furnace, Pierce-Smith converters, matte granulation, waste heat boiler, hot gas handling equipment, wet gas cleaning plant and acid plant. The METSIM® model was divided into three separate, yet interconnected models: metals, off-gas and water balancing. This allowed for improved modelling efficiency and traceability while minimising manual error. The METSIM® model was supported by inputs from other specialised software. Chemical thermodynamics software, FactSage™ (ver 8.2 by GTT Technologies), was used to establish relationships for the flash furnace fluxing strategy and determine the operating temperature. Arena® (ver 16.0 by Rockwell Automation), a discrete event modelling software, was used to simulate material movements within the aisle as well as Pierce-Smith converter operation, allowing for integration with upstream and downstream systems. A dynamic data exchange (DDE) was used to connect the results of each software package, interfacing through Excel® (version 4203 by Microsoft). The integration between models provided a streamlined approach to test capacity, bottlenecks, water consumption and emissions under a range of operating conditions, enabling a more robust process. Further downstream modelling techniques were used to assess mechanical equipment. METSIM® outputs provided key parameters for combustion assessments using computational fluid dynamics and finite element analysis for the furnace mechanical design.

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 M-A Van Ende, N Kumar, I-H Jung

In order to utilise the powerful thermodynamic databases for process simulations, a concept called Effective Equilibrium Reaction Zone (EERZ) was introduced to couple thermodynamic database calculations and reaction kinetics. Using the EERZ concept, many process simulation models for steelmaking processes have been developed within the FactSage steelmaking consortium. After validation of the simulation results by comparing with plant data, the simulation models have been applied to improve plant operations. Several success stories of the improvement of real steelmaking operations are shared. A new user-friendly FactProSim software developed for building process simulations is introduced.

Aug 21, 2024