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By Hakan Akcin, Pinar Eksert

The aim of this study was the safety risk assessment of accidents that occur because of production dynamics in deep coal mining, one of the highly dangerous business class, with spatiotemporal GIS. In this study, accidents that occur at certain times during production in underground mining workplaces are discussed based on evaluations of spatial and temporal dimensions. Accordingly, various analyses have been handled using criminology science tactics and strategies such as 80–20, kernel density, space–time cube, and hot spot, which have been adapted to GIS tools. Implementations have been realized on 3D underground cartographic models covering accident data from deep coal mine workplaces in the Zonguldak-Kozlu basin in Turkey between 2019 and 2021, at an average elevation of – 400 m. Space–time cube, kernel density, and time series analyses suggest that the Annual Bonus Incentives, which are repeated every year and given before the new year, increase the psychosocial risks for employees. It has been determined that this situation can lead to problems such as poor concentration among miners and loss of focus in some shifts. Additionally, significant relationships were found between the number of accidents and monthly production progress rates as a temporal parameter. The results demonstrate that applying a reactive approach with spatiotemporal GIS to accidents in deep coal mines is becoming increasingly important.

Apr 24, 2024

By Xiang He, Xinzhong Wang, Ning Li, Bao Cao, Hongyang Bai, Zhigang Du

Revealing the periodic fracture pattern of the main roof and the key influencing factors of the support resistance is crucial for strata control and support selection of the shallow buried working face with large mining height. Based on the cantilever beam theory, an improved step rock beam model, and the measured strata pressure data of the 12,401 working face in Shangwan Mine, the mine pressure behavior law of the shallow buried with a large mining height working face was analyzed. The results show that both ratio of maximum principal stress to load (σ1/q) and ratio of maximum shear stress to load (τmax/q) inside the main roof increase with increasing periodic advancing distance, while the ratio of maximum shear stress to maximum principal stress (K) is the opposite, indicating that the increase rate of σ1/q is higher than that of τmax/q. K is less than 1 when the periodic advancing distance exceeds 8 m, indicating that the periodic fracture of the main roof will be dominated by tensile failure. Support resistance increases with increasing immediate roof thickness, main roof thickness, periodic fracture step distance of the main roof, and mining height, and decreases nonlinearly with increasing friction coefficient of periodic fracture rock block hinge surface. The main roof thickness, the periodic fracture distance of main roof, and the friction coefficient of the hinge surface of the periodic fracture rock block are the key factors influencing the support resistance. The advance breaking of the main roof and increasing the friction coefficient of the hinged surface of the main roof can reduce the support resistance of the working face. The support resistance of the 12,401 working face in Shangwan Mine presents an arch distribution characteristic. The average periodic weighting step interval, average support resistance, and dynamic load coefficient are 15.6 m, 17,552 kN, and 1.3, respectively. Finally, the rationality and validity of the model are verified by comparing the measured and theoretical values of the support resistance in the 12,401 working face of Shangwan Mine and other shallow coal seams with large mining height.

Apr 22, 2024

By Jiaqi Jin, Jan D. Miller, Chen‑Luh Lin, Amanda N. Erskine, Shijie Wang

Recovery of metals from coarse ore particles is a great challenge for heap leaching operations of low-grade precious metal resources. Internal fractures of ore particles like micro-cracks can facilitate subsurface transportation of solution inside particles and leaching of valuable minerals. A plant-scale high-pressure grinding roll (HPGR) unit at Coeur Mining’s Rochester mine was operated at selected specific pressures to crush and prepare various products for crack analysis using high-resolution X-ray computed tomography (XCT). 3D shapes of cracks inside ore particles for selected size fractions reveal different damage mechanisms during HPGR crushing regarding particle size and crushing pressure. Close-to-surface cracks formed by abrasion were found in small 2.5 mm particles. Impact cracks with a high aspect ratio were found in particles of larger size and higher HPGR pressure. The volumetric percentage of internal fractures and the specific crack surface areas of selected ore particles are compared to give quantitative conclusions on particle damage by compression during HPGR crushing.

Apr 20, 2024

By Ashish Kumar Vishwakarma, Vivek Kumar Himanshu, Kaushik Dey

The accurate prediction of blast-induced ground vibration due to underground ring blasting is a prominent need for ensuring the safety of structures. Different site-specific empirical equations are available for the prediction of ground vibration. These empirical equations are best suited when the monitoring and blasting locations are present in the same medium. The change in the medium alters the behavior of wave propagation. Hence, existing empirical equations have limitations in peak particle velocity (PPV) prediction when the blasting location is an underground hard rock mine and the monitoring location is ground surface. This is because the underground metal mine comprises different levels having void in the form of excavated stope or paste-filled stope. It is very difficult to predict the magnitude of PPV on the surface in such instances. Therefore, this study has been carried out to predict the PPV at surface due to underground blasting. In this paper, PPV data was recorded at surface for 207-ring blasts. Furthermore, the PPV has also been measured at different underground locations for 47-ring blasts. Different empirical equations along with k-nearest neighbor (KNN) and random forest (RF) model of machine learning technique were developed for the prediction of PPV. Most of the empirical models have higher accuracy in the prediction of PPV at an underground location. This shows that scaled distance-based empirical predictors are best suited when the monitoring and blasting media are the same. However, the empirical models do not predict PPV accurately when the monitoring location is ground surface and the blast is conducted underground. The machine learning models are better suited for PPV prediction in such cases. Based on the analysis performed for the case study site, RF model predicts PPV at surface with the highest accuracy. The coefficient of determination and root mean square error for RF model used for predicting PPV at ground surface are 0.94 and 0.438 mm/s respectively. The RF-based model is also the best suited among all the models for predicting PPV at underground locations as well.

Apr 20, 2024

By Ismail Adeniyi Okewale, Hendrik Grobler

Significant factors believed to be responsible for tailings dam failure which can lead to loss of lives, destruction of properties and assets or damage to the environment are the mechanics of material characteristics and static liquefaction. It is therefore essential to understand the tendency for the likely occurrence of liquefaction in tailings dam as well as mechanics behind the behaviour of this tailing materials (inevitable products of ore mining, mineral and metallurgical processes). This study aims to present the mechanical behaviour and susceptibility to liquefaction of a gold tailings sample. Series of oedometer tests were conducted to determine the compression behaviour and the possibility of transitional behaviour or not. Index and physical tests were conducted to determine engineering grading descriptors which was directly linked to compression behaviour and comparisons made with other tailings. Microstructure was studied to understand the effects of fabric on the behaviour of samples and the chemical composition and mineralogy were also investigated. The compression paths slowly converge and the gold tailings might be said to be less transitional. The gold tailing is less dependent on initial state. The loosest gold tailing is more susceptible to liquefaction and compared to other gold tailings, this sample is less susceptible to liquefaction.

Apr 19, 2024

By V. K. Risinggård, M. Sparta

We report on the development of a finite-element method model for a pilot furnace for the production of manganese alloys. The model is a multiphysics model that addresses material flow, electrical conditions, heat transfer, and physical and chemical transformations. It is capable of studying both quasi-steady and transient states in time-dependent simulations. The model includes common charge materials and fluxes and can simulate production of both ferromanganese and silicomanganese alloys with acid and basic slags, as well as changing charge compositions. The model output provides access to the material distribution in the furnace during furnace runs, temperature profiles, current paths, energy balances, and alloy and slag production rates and compositions.

Apr 16, 2024

By S. T. Johansen, B. T. Løvfall, T. Rodriguez Duran

In this paper we develop a physics-based model for lining erosion in steel ladles. The model predicts the temperature evolution in the liquid slag, steel, refractory bricks, and outer steel shell of the ladle. The flow of slag and steel is due to forced convection induced by inert gas injection, vacuum treatment (extreme bubble expansion), natural convection, and waves caused by the gas stirring. The lining erosion takes place by dissolution of refractory elements into the steel or slag. The mass and heat transfer coefficients inside the ladle during gas stirring are modelled based on wall functions which take the distribution of wall shear velocities as a critical input. The wall shear velocities are obtained from computational fluid dynamics (CFD) simulations for a sample of scenarios, spanning out the operational space, and a model is developed using curve fitting. The model is capable of reproducing both thermal and erosion evolution well. Deviations between model predictions and industrial data are discussed. The model is fast and has been tested successfully in a ‘semi-online’ application. The model source code is available to the public at [https://github.com/SINTEF/refractorywear].

Apr 16, 2024

By E. Lutz, M. Momayez, K. W. Brown Requist

As real-time air quality monitoring becomes more prevalent in US underground mines, it is important to provide the highest data reliability with the fewest possible sensors. Real-time sensors remain costly, and these costs are not exclusively financial; the time required to install, calibrate, and maintain real-time sensors poses a large barrier to widespread implementation. Current atmospheric monitoring systems typically rely on displaying point-specific values. This requires operators to infer real-time airborne contamination distributions. Monitoring and control software utilizing mine ventilation network (MVN) solvers has been implemented in limited cases because of their ability to simulate ventilation systems quickly, but these solvers use a one-dimensional representation of the mine, limiting spatial resolution of estimated distributions. Computational fluid dynamics (CFD) has likewise been considered as a means to improve spatial resolution, but processing times prevent its use as a basis for monitoring and control. For the real-time monitoring of airborne contamination distributions, we propose a spatial interpolation method that can estimate the distribution of airborne contaminants in near-real time. This method provides a middle ground between fast processing times and increased spatial resolution. With the use of a pathfinding algorithm and optimization through absolute percentage error minimization, this method outperforms spatial interpolation with a Euclidean distance. By providing contamination distribution information to operators, this method and its derivatives stand to outperform current atmospheric monitoring systems.

Apr 16, 2024

By G. Akdogan, Q. G. Reynolds, S. J. Baumgartner

A computational model of a submerged arc furnace (SAF) used in the production of ferrochrome is presented. The model‘s intended use is to investigate the extent to which intrinsic and extrinsic properties of the raw materials affect burden distribution and electrical resistance within the furnace. The model is built on the discrete element method and calculates the mechanical interactions of particle distributions resulting from the flow motion of typical raw materials used in the smelting of chromium ore. This model excludes the effects of thermodynamics, furnace chemistry, and heat transfer. It illustrates how the consumption of materials (chromite pellets, flux, and reductant) is affected by changes in electrode length, reductant fractions, and reductant sizing and density during the formation of a reductant bed. The resistance calculation algorithm developed by Mintek was applied to construct networks developed from particle contacts, which can quantitatively generate estimates of the electrode-to-electrode and electrode-to-bath electrical conduction conditions.

Apr 16, 2024

By S. T. Johansen, B. T. Løvfall, T. Rodriguez Duran, J. Zoric

A methodology for building pragmatic physics-based models is here adapted to predict the erosion of ladle linings in the steel industry, in order to support operators when deciding whether the lining can be used safely for another heat. A defective lining may allow 140 t of molten steel to spill, with disastrous consequences for workers and plant. The adopted work flow for the development, challenges faced, and some model results are presented. One key learning outcome is that model development should allow time for maturing the process understanding, as well as for many iterations by ‘questions-responses and actions’ at various stages in the model development. Good interaction between the development team and industry case owner is an important success factor. Combining or extending the model with the use of machine learning and cognition-related methods, such as knowledge graphs and self-adaptive algorithms, is discussed.

Apr 16, 2024

By B. Yu, M-H. Cao, C. Zhou, X-Z. Zhang

The transient infiltration and lubrication behaviour of slag during continuous casting of steel is important for billet quality. A two-dimensional coupled mathematical mould model was developed to investigate these phenomena. The accuracy of the model was verified by comparing the calculated slag consumption with measurements by the plant. The results show that the liquid slag is consumed from the middle and late period of positive strip time to the next early period of positive strip time, including the entire negative strip time. The maximum downward infiltration velocity and positive pressure in the slag channel is at the middle of the negative strip time. Increasing the positive pressure of the slag channel is conducive to lubrication. The shear stresses acting on the shell surface and at the mould side were determined by the lubrication slag consumption and total slag consumption, respectively, and gradually decreased with increasing slag consumption. The negative strip time was lengthened to increase the slag consumption and prolong the time near the maximum downward shear stress, so as to be conducive to the demould.

Apr 16, 2024

By Y. Ren, B. Yang

The magnetic field characteristics due to electromagnetic stirring in the secondary cooling zone of an extra-thick slab during continuous casting are numerically determined using Maxwell's equations, with particular emphasis on the distribution of magnetic induction intensity and electromagnetic force, as well as the influence of process parameters on the magnetic field. The orientation of the electromagnetic force is the same when the electromagnetic stirrers at the 30° and 60° posistions of the arc-shaped slab are powered in the same direction; otherwise, the orientation is opposite. The magnetic induction at the centre of the section of the stirrer's central axis at the 30° positio, as well as the current, frequency, and fitting formulae, are as follows: B = {0.075I.(1/A)-0.3} mT and B = {-1.75f.(1/Hz)+22} mT. The electromagnetic force and current fitting formula at the central point of the B-B section is F = {0.03168I2.(1/A2)-03.762I.(1/A)+326.7} N/m3, and the fitting formula of electromagnetic force and frequency at the centre point is divided into two segments. The first takes the form of a parabola: = {-21((f-4.3).(1/Hz)2)+970} N/m3, and the second segment is negative linear: F = {-1.65f.(1/Hz)+51.5} N/m3.

Apr 16, 2024

By J. H. Zietsman, M. W. Erwee, Q. G. Reynolds

Pyrometallurgical furnaces, essential for metal extraction, operate at temperatures exceeding 1600°C and represent complex multiphase systems that challenge direct industrial research. Multiphysics models play a key role in shedding light on their intricate behaviours, supporting the refinement of design and operational strategies. Integral to the operation are the tap-holes, which facilitate the removal of molten products and are routinely opened by lancing, a process comparable to the use of a cutting torch, where high temperatures result from oxygen reacting with an iron lance. When the lance pierces the clay, oxygen gas enters the furnace, which could influence the behaviour of the molten material inside. In this work, a multiphase fluid flow model was used to investigate bulk flow dynamics, with a focus on the effects of the lancing process on the inside of the furnace, immediately behind the tap-hole. Incompressible and compressible multiphase fluid solvers were used and compared with respect their performance – the intention was to assess whether using a compressible solver would yield a different solution to the incompressible one. It was concluded that there are negligible disparities in bulk fluid flow behaviour between the solvers for the case studies examined, indicating that solver selection might be less consequential for certain aspects of oxygen lancing.

Apr 16, 2024

By M S. Tuohy

Poorly judged or under-appreciated change plays a role in many major accidents. In particular, operational changes related to continuous improvement, maintenance and introduction of new technology can lead to unintended safety (and other) consequences. This paper provides an overview of the role of management of change in preventing unwanted impacts on safety, community relationships and the environment. It draws on a range of incidents covering mining, minerals processing, refining and smelting where inadequately assessed or ineffectively implemented change led to significant safety, environmental or community consequences. The paper will also highlight cases of well-managed complex change and the underlying model of decision-making in place to make those decisions. All these examples are drawn from Atturra’s experience in response to accidents or working with sites to improve their management systems. The paper will report on the challenges of applying conventional risk assessment approaches to complex or technically significant change. These typically result in either onerous and lengthy change procedures that are prone to workarounds or poor implementation. Conversely, ‘light touch’ or efficiency driven change processes present the risk of intended consequences by failing to bring appropriate expertise to bear in decision-making. Such balances can be resolved by considering the designation of ‘technical authority’ with appropriate expertise to consider the change and deconflict any production, cost or schedule trade-offs. Finally, the paper will reflect on the key components of management of change systems in the context of major accidents, highlighting good practice in how they are implemented. This will consider the integration of existing corporate processes, risk management and organisational structures into management of change systems, not just the content of change forms and procedures.

Apr 16, 2024

By Y Lin, B J. Seligmann, M Hassall, S Micklethwaite

For multi-site mining companies, checking the quality and consistency of the data recorded in risk registers is important for confirming how well mine safety management systems have been implemented. However, this task is complicated by the differences in scope of the site, their particular nature, the complexity of the operations and many other factors that can introduce nuances to the characteristics of the risk registers. We present here an application of a technique called Causal Network Topology Analysis for comparing the quality and consistency of risk registers. By quality we refer to, for example: - missing causal relationships between risks - location of missing controls - focus of risk treatment strategies: prevention versus mitigation controls. By consistency we refer to how causally interdependent are the risk events. There are often causal interactions between the lines of a risk register that mean that the likelihood and consequence scores that are applied to each risk event are not independent. We measure this degree of interactions by: - proportion of independent scenarios per register - efficiency of risk treatment strategy comparison. This approach can indicate quality and consistency differences between registers irrespective of the actual details of the site or operation. This occurs by comparing aspects of the structure of a causal network extracted from how the risk events, causes, controls and consequences causally interact. In this work we compare pairs of registers to demonstrate the approach.

Apr 16, 2024

By D I. Cliff

The loss of 11 miners in the 7 August 1994 Moura No.2 Underground Mine Disaster was the catalyst for major change in the way safety was managed in the Australian Mining Industry. The impact was felt across all sectors not just underground coal. It was the catalyst for the overhaul of the regulatory frameworks, moving away from prescription to management systems and risk management. This had a substantial impact on the way not only the industry operated but also on how the regulator functioned. It heralded the introduction of competency-based training across all levels of the mining workforce. Since that time major improvements in safety performance have occurred. However, hiding within the statistics are some disturbing trends. This paper aims to analyse the progress made in the past 30 years and identify the current and emerging issues. Automation is bringing major production and safety benefits, but at the same time other factors such as the reduction in workforce numbers and ever-increasing production pressures are leading to high turnover rates. This in turn causes to a loss of experience and expertise. In addition, and of particular importance, is the recognition of psychosocial wellness on workforce safety. Many of these factors are not unique to the mining industry however they may be exacerbated by the scale of mining, the remoteness of the mines and family unfriendly mining rosters.

Apr 16, 2024

By B Beale

Bow-tie analysis is a commonly used tool to identify and display risks that have the potential for an undesired hazardous event. The output of the analysis are bow-tie diagrams, which are an effective and versatile communication format that can be applied to any type of risk. Contrary to their simplicity, a proper bow-tie diagram that maintains its usefulness and clear communication is difficult to build. Over two decades assisting Major Hazard Facilities with bow-tie analysis for Safety Cases, several common mistakes have been identified. This paper aims to highlight those issues with examples and provide improvement strategies. A sample of the most common mistakes are: - overly complicated risk analysis - poorly scoped and defined terms - poor descriptions and justifications - identifying too many dependent controls. Overly complicated risk analysis leads to wasted time in obtaining data for little gain. The bow-tie diagram is only a model. Effort should be redirected into identifying and managing controls that will make a tangible difference to site risk. Broad scopes lead to enormous and confusing bow-tie diagrams for both the user and the workshop team. Defining the scope of the study, the consequence severity of interest and critical control characteristics creates focused workshops and targeted analysis. With more definitive scope, there may be more bow-tie diagrams, however, they are succinct and specific. Well described causes are imperative for clear communication to users, regulators and future bowtie review workshop groups. It is best to use common wording structures and explain the event stepby- step. Also, clearly document any likelihood calculations and use data references where applicable. Identifying all possible controls creates a false sense of security that there are many layers of protection. In reality, most controls are dependent on a single system or person and could all be compromised from a single failure. A definition of a ‘bow-tie’ control is required whereby it must be independent from other controls. Improving the bow-tie analysis process will assist operators in developing meaningful and ‘operational’ bow-tie diagrams to support risk management systems and practices.

Apr 16, 2024

By M Hassall, E Humphries

Personal risk assessment processes, also known as Take 5 or SLAM (Stop, Look, Assess, Manage) have been utilised in high hazard industries for over 30 years. However, there is limited research to understand if a personal risk assessment process improves safety and health outcomes. The author’s learnings during discussions with training participants in G3/G-MIRM (Risk Management Systems) and G2 (Risk Assessment for Supervisors) courses have provided them with significant insight into understanding if a personal risk assessment process is valued across a number of mining industry organisations. These discussions arise when the four-layer model is presented (Figure 1) where ‘Layer 4’ represents the last resort risk checking activity. In this context, training participants agree that this process has value. However, the consistent opinion is that the personal risk assessment process is not effective, that it is a ‘tick and flick exercise’ and is not achieving the desired outcomes.

Apr 16, 2024

By M Jara, R Nuñez

As the global interest in sustainable energy sources has increased, lithium has emerged as a vital resource, playing a crucial role in the transition towards a cleaner and more efficient economy, but with this comes important challenges, especially associated to health, safety, and environmental matters. So, it is imperative for the lithium industry to prioritise HSE measures to protect workers, environment and surrounding communities. Implementing robust safety protocols and technology helps ensure the sustainability of mining operations and contributes to the overall responsible development of the industry. In this work we present how the Chilean lithium mining industry becomes a safer and more compliant industry using digital transformation (Cochilco, 2018; Bradley et al, 2013; Cabello, 2022).

Apr 16, 2024

By M Alston

Organisations’ incident classification processes are plagued by the overclassification of events, often leading to excessive workloads and suboptimal outcomes. This presentation addresses the pressing need to rethink how incidents are classified to maximise organisational learning and minimise systemic risk. A major issue in the current incident classification landscape is the tendency to classify events at high levels, overwhelming organisations with investigations they cannot efficiently handle. This results in inadequate risk reduction and learning opportunities. The link between injury classification and investigation methods further compounds these problems, creating unnecessary administrative clutter. Challenging the misconception that every event, no matter how minor, requires a comprehensive investigation, this presentation advocates for a shift in perspective. The key recommendation is to decouple injury classification and risk matrices from the decision-making process regarding what and how to investigate. Instead, the emphasis should be placed on identifying opportunities for organisational learning and risk reduction. Organisations can streamline their incident management processes by adopting a more pragmatic approach that aligns incident classification with the organisation’s investigation capacity. This transformation focuses on achieving meaningful outcomes, enhancing safety and improving performance. This presentation provides an innovative process for organisations to revamp their incident classification practices, enabling them to harness the full potential of incident data for learning and risk mitigation. It highlights the importance of aligning incident classification with the opportunity for organisational learning, ultimately leading to more effective incident management and enhanced safety outcomes.

Apr 16, 2024