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By A. T. van Zyl, M. Mthenjane, M. J. Cole

Growing global concern over the impacts of climate change, attributable largely to fossil fuel energy sources, has led to the widely shared goal for a ‘just transition’ to cleaner energy and reduced dependence on carbon-based fuels. As the world’s 14th biggest CO2 emitter and being particularly vulnerable to the impacts of climate change, South Africa must embark on a just transition pathway. This paper reviews expected coal mine closures and associated community vulnerabilities and local governance challenges in South Africa. Decommissioning schedules for all coal-fired power stations and operating coal mines are plotted, and 69 mining host communities and 21 municipalities are mapped, classified, and described. Community socio-economic profiles are measured using a set of SDG indicators and census data and municipalities assessed through financial audits. Our research shows that five coal-fired power plants (8.9 GW) and 15 coal mines (29.5 Mt/a) will probably close by 2030, and a further four plants (14 GW) and 23 mines (106 Mt/a) by 2040. Thus, the shift to cleaner energy will likely occur without the premature closures implied by the just transition. The impact of mine closure on the 2.5 million residents of host communities will be significant, particularly as levels of income, employment, and education are already very low and many municipalities are in financial distress. The South African approach to the just transition needs to take local realities into account and the narrative must support an effective transition that does not undermine energy security and economic growth.

Jun 5, 2023

By K. Woodward, Y. Potvin, B. McFadyen, M. Grenon

Open stoping has become a popular mining method in hard rock mines, not only due to the safety of the method as a non-entry approach, but also because of the high extraction rate and low costs. At mine sites, stope performance is evaluated by calculating stope overbreak using the stability chart. However, limitations of the stability chart regarding the precision of the predictions, nonconsideration of factors such as the influence of blasting, and the exclusion of underbreak have led to non-optimal designs. The capabilities of today's computers have increased the amount of data being collected and the power of models being built. This article presents a step towards a new stope design approach where stope overbreak and underbreak are measured and georeferenced using octrees at an approximately cubic metre resolution and predicted using multivariate statistical models (partial least square, linear discriminant analysis, and random forest). Results show that overbreak and underbreak location along the design surface and their magnitude are predicted with good precision using a random forest model. These predictions are used to build the expected geometry of the open stope. The resolution of the data and the use of multivariate analysis has enabled the prediction of variation in stope performance along the design surface, going well beyond the simple qualitative per stope face prediction provided by a traditional stability chart approach.

Jun 5, 2023

By Yang Song, Li Shaokang, Wang Zhiqiang, Wang Jinjun, Li Guofeng, Su Meixuan

CaCO3, as a component widely existing in natural minerals, is a common impurity. In recent years, triboelectric separation has been applied to the separation of minerals containing CaCO3. However, the CaCO3’ s tribocharging mechanism is still unclear and the charging effect of CaCO3 is not obvious. In order to study the effect of triboelectric charging of CaCO3 particles under different conditions, according to the single particle frictional collision charge-mass ratio formula derived from the condenser model, an experimental platform for particle tribocharging was built in this paper. Then, the formula of charge-to-mass ratio (Q/m) was derived based on the analysis of the particle force. Particle image velocimetry (PIV) was used to record particle motion trajectories to calculate the Q/m of one particle by this formula. In the experiment, the airflow velocity, tribocharge material, and moving distance of the particles were varied to investigate the variation of the particle charge-mass ratio results. The results show that CaCO3 was negatively charged when tribocharging with mental. The particle’s Q/m is positively correlated with the airspeed. When the metal is triboelectrically charged with the insulator, the metal with a smaller work function leads to the insulator particle with a larger Q/m. As the moving distance of the particles increases beyond 230 mm, the particle charge ratio decreases. The particle charge-mass ratio is consistent with the trend of the charge-mass ratio deduced from the capacitance model.

Jun 3, 2023

By Juan J. Monsalve, AMAN SONI, Nino Ripepi, Richard Bishop

The design and strength of pillars are important parameters when implementing the room-and-pillar mining method in a limestone mine. The process becomes complex with the presence of karst voids, which are frequent phenomena in carbonate rock formations. This research continues a previous study aimed at studying the effect of karst voids on the strength of a particular limestone pillar. Using calculated pillar strength and estimated redistributed stresses, it was assessed that the pillar can counter more stress than currently imparted on it. Numerical modeling studies combining in situ stress determination and excavation sequencing were used to estimate the existing stresses on the pillar. Different possibilities of modification to existing pillar design were simulated using distinct element method (DEM) modeling to determine a better design.

Jun 1, 2023

By Irina Chernyshova, Erik Larsen, Hanumantha Rao Kota, Vladislav Slabov, Garima Jain

The mining industry faces pressure to provide metals for the green digital shift using sustainable technologies. This study evaluates biosurfactants as collectors for ultrafine and coarser particles of hematite and malachite, aiming to improve the flotation of ultrafine particles.

Jun 1, 2023

By Aixiang Wu, Minjie Zhang, Zhuen Ruan, Yiming Wang

This paper combines theoretical and experimental analysis to conduct relevant research to improve the accuracy of predicting paste yield stress by slump flow. The analytical model of slump flow for yield stress is derived based on a mini-cylindrical mold with a height-to-diameter ratio of 1. It shows that the dimensionless slump flow is a monotonic decreasing function of the dimensionless yield stress and is independent of the material type (specific gravity), which provides a theoretical basis for quantifying the rheological properties of paste with slump flow. Three different tailing-prepared pastes were tested for their slump flow and implemented rheological tests simultaneously. The yield stress is obtained based on the Bingham model fit, as the measured value of the yield stress is substituted into the derived theoretical model. The studied pastes yield stresses range from 34.78 to 524.08 Pa, with corresponding dimensionless slump flow of 3.43 to 1.09. The results showed that the calculated slump flows were generally greater than the measured values. The analysis showed that this was mainly due to the thixotropy of the paste, with minor deviations ranging from − 1.5 to 5.8% for the less thixotropic pasted prepared from tailing C. An approximate analytical solution for yield stress as a function of slump flow is obtained using Taylor’s formula. However, it is unsuitable for predicting the yield stress because the yield stress calculated by this function is much higher than the measured value. The empirical yield stress model was constructed and experimentally verified. The results show that the empirical formula has high accuracy and good generality. The deviation of the studied pastes is between − 15 and 5%, which provides a practical method for rapid and accurate prediction of paste yield stress in mine sites.

Jun 1, 2023

By Brendan Demich, Brendan Macdonald, Timothy J. Orr, Jonathan K. Hrica, CASSANDRA L. HOEBBEL, Jason Navoyski, Jennica L. Bellanca

Haul truck fatal accidents and injuries continue to be a significant concern for the mining industry. However, the availability of high-quality training materials continues to be limited. Near-miss incident accounts, if packaged well, could help fill this gap, because for every fatality, there are hundreds of reportable accidents and thousands of undocumented near misses. Researchers from the National Institute for Occupational Safety and Health (NIOSH) collected detailed accounts of 21 near-miss incidents in virtual interviews with mineworkers at surface mining operations across the country. From these interviews, researchers created four simulation videos using the Unity game engine. The simulation videos bring these events to life through first-person retelling and various visual perspectives of actual events. Each video exemplifies a critical safety message and a common haul truck hazard. This paper describes the process of taking narratives and turning them into impactful visual stories using graphic simulation. NIOSH plans to co-release these simulation videos with the Mine Safety and Health Administration (MSHA) to the mining industry to raise awareness and ultimately help reduce haul truck-related accidents and fatalities in mining.

Jun 1, 2023

By Bahaa Alyosif, Murat Erdemoğlu, Muhammet Kürşat Aydemir, Turan Uysal

The effect of intensive milling on the conversion of microcline ( KAlSi3O8) to potassium chloride (KCl) occurred during the chlorination roasting process for artificial KCl production was investigated. A feldspar ore with 10.89% K2O grade and containing microcline was dry milled by a planetary ball mill for mechanical activation. Milled ore mixed with calcium chloride was roasted at temperatures between 500 and 1000 °C to get the chlorination roasting process. The product was then leached in water to dissolve KCl occurring during the roasting, which will be precipitated from the pregnant leach solution by evaporation. Results showed that potassium recovery from the unmilled ore increased rapidly up to 800 °C, and dramatically decreased at higher temperatures due to the removal of KCl from the furnace by means of evaporation. A potassium recovery of 31.95% was achieved by the unmilled ore, whereas it was 88.43% when 15 min milled ore was roasted at 750 °C. It was concluded that intensive milling caused mechanical activation of microcline to reduce the roasting temperature of the chlorination roasting process.

May 31, 2023

By Anup Tiwari, Khanindra Pathak, BIBHUTI BHUSAN MANDAL

Failure of in-pit overburden dumps in open-pit coal mines causes debris to flow toward the active working face, threatening the safety of people and equipment. The evaluation of the potential mobility of failing mass will aid in hazard mitigation associated with unwarranted dump failure. The potential mobility is shown by mobility ratio (ratio of total drop between debris flow's initial and final deposition points to total travel distance) and runout characteristics. In light of above, a laboratoryscale debris flow flume was developed to investigate the effect of material gradation and slope angle on runout characteristics and mobility ratio. The total mass of experimental debris mix (Q) is fixed at 30 kg with 20% water content. Experiments at three different slope angles (30°, 35°, and 40°) demonstrate that increasing the proportion of fines in the experimental mix increases runout characteristics while decreasing the mobility ratio. The length and area of the runout decrease as the slope angle increases, while the mobility ratio increases. There is a positive correlation between d50 and runout characteristics at a fines content of 0.1Q, but a negative correlation at a fines content of 0.2Q and 0.3Q. Conversely, there is a negative correlation between d50 and mobility ratio for fines content of 0.1Q, but a positive correlation exists for fines content of 0.2Q and 0.3Q. A new index called the fine-to-coarse (F/C) ratio is used to identify the critical value of fines and coarse proportion that causes a transition from dry granular flow to fluidized debris flow.

May 29, 2023

By Amar Prakash, V. M. S. R. Murthy, VIVEK KUMAR HIMANSHU, Sufal Mehrotra, Ashish Kumar Vishwakarma

Raises are vertical or inclined openings made to connect two levels of an underground metalliferous mine. They are developed using drilling and blasting-based technique or by mechanical means. Raise boring machines (RBM) have evolved in recent years, which provide quicker and safer raise excavation. The penetration rate using RBM has influenced applied thrust. The required thrust to enhance penetration rate with optimal use of energy would be different under varying geological and geotechnical conditions. In this study, the influence of applied thrust on penetration rate using RBM has been investigated. The investigation has been made for two different rock types, amphibolite (AMP) and garnet-biotite-sillimanite-gneiss (GBSG). The numerical simulation model was developed for this purpose using Ansys-Explicit Dynamics. The induced tensile stress under different conditions of applied thrust has been analysed in the calibrated numerical model. The model output shows the power trend between the parameters. The experimental data on penetration rate was also collected along with the respective operational parameters. A statistical analysis has been carried out for the gathered data. The analysis of data also shows a power trend between thrust per cutter and penetration rate in both rock types and hence validates the numerical simulation-based output. Based on the outputs of the numerical simulation and empirical study of the experimental data, the optimum thrust per cutter for excavation in both rock types is in the range of 12–14 tons. The approach used in this study can be helpful for predicting the optimal operational parameters of raise boring machines under different geological/geotechnical conditions.

May 29, 2023

By M J. Nimmo

extremely powerful tools for building predictive and generative models. ML can be used for building highly accurate regression and classification models. But without careful data science and statistical analysis, a regression or classification model could be highly biased and completely wrong – and we may not even realise. An example rock density estimation task will be used to illustrate the potential gains and possible pitfalls in using ML and AI in Mineral Resource estimation. What could possibly go wrong? Nothing! For most simple regression or classification problems, very little. For density estimation, using the global mean may be all that is possible, but the resource classification would need to reflect the uncertainty in global estimation of tonnage. Everything! From data collection and measurement, from selecting ML and AI techniques and designing the analysis workflow to our own cognitive bias. The things that could go wrong are vast and may include but not limited to asking the wrong question, not asking questions, data bias, measurement errors, insufficient data coverage, not collecting the right variables, not collecting enough observations, collecting clustered samples, unbalanced data, filtering out data without reason (outliers), clipping data (outliers), relying on automatic feature selection, including irrelevant variables, excluding relevant variables, geological interpretation, changing context, blindly following best practice, splitting small data sets, subsetting large data sets, using the wrong tool for the task, insufficient budget to complete the analysis, not allowing enough time for testing and experimentation (the science), focusing too much on building the model (the engineering), not learning from the data, our assumptions, our preconceptions, and our skill. This paper will explore the question of how training regression models to predict rock density are affected by gaps in the data (missing observations and missing variables). What could possibly go wrong?

May 24, 2023

By W Patton

Investment decisions in the mineral resources sector are made on the basis of an assessment of the economic potential for a mineral deposit. Given the supporting information for the location, scale, and quantity of the commodity of interest, miners and investors aim to make risk-informed decisions when considering further investment. The objective of resource classification is the synthesis of various types and quantities of geologic information used in resource model construction to assign confidence categories to the estimated mineral resources, which can then be used to support informed economic decisions. In this paper a risk-based classification scheme for iron ore mineral resources using conditional simulations is presented. The method involves categorisation of each block according to a confidence level, considering expected recoveries from a kriging model over mining production volumes. The realisations of the simulated model are used to assign risk-based confidence categories to zones of the ore deposit. One motivation for this work is to assess the sensitivity of the scheme to geologic uncertainties. Specifically, that which uncertainty in the layout of mineralising alterations and weathering overprints influence variabilities of associated rock properties and the likelihood of obtaining expected ore recoveries. It is shown these risks have material implications for a project’s economic potential. How the scheme can be extended to the grade control context and the value subsequent grade control activities is also quantified.

May 24, 2023

By I Sucholutsky, D M. First, D Mogilny, F Yusufali

Machine learning is creating value in all facets of the mining industry, from exploration to production. The authors provide an accessible, high-level introduction to artificial intelligence (AI), machine learning (ML), and deep learning (DL); the latter being widely recognised as one of the most powerful forms of ML. In particular, the authors will introduce deep learning models known as convolutional neural networks (CNNs), how they are applied, and the economic considerations necessary for determining when DL may be the right solution to de-risking complex block modelling problems. The authors present preliminary results from the mineral resource modelling study of the Jundee orogenic gold deposit, Yandal belt/gold province, Western Australia. The primary goal was to identify the direction and location of the narrow gold veins more accurately and demonstrate how non-linearly correlated elements are used as direct inputs to the resource model to assist with the target element’s grade prediction. This demonstrates that: (1) existing techniques for finding correlations between assayed elements do not adequately reflect the complex geology of the asset, (2) nonlinear correlations that are difficult to model as simple mathematical functions are representative of geological patterns in a deposit, and (3) non-linearly correlated assayed data, fed as inputs, increase the performance of the resource model as reconciled through blind tests. To conclude, the authors hypothesise that the patterns represented by the DL block models may be revealing the results of overprinting geological processes that generated mineral deposits. For example, the primary hydrothermal processes that deposited metals created depositional patterns that become particularly complex as a result of being overprinted, in part or in whole, by secondary physicochemical processes. This may explain why non-linear geochemical relationships have the capacity to generate more accurate block models of mineral deposits.

May 24, 2023

By A A. Latscha, D O’Connor

Increasing orebody complexity, restrictions in ground access, and longer lead times for disturbance approvals, have generated the need for the Resource Development Team within Rio Tinto Iron Ore (RTIO), to explore optimised drill design techniques that deliver resource conversion value while maximising program outcomes. In response to this challenge, the Team initiated a case study to produce an AI assisted/designed drill program using a non-machine learning AI. The case study involved the assessment and implementation of an AI generated drill program at one of RTIO’s Pilbara iron ore deposits, located in the Hamersley Province of Western Australia. The Mineral Resource is currently classified as 100 per cent Inferred. Access constraints inherent to topography, and the presence of exclusions zones have prevented adequate drilling coverage, resulting in lower resource confidence and a poor definition of the orebody extents and geometry. The drill campaign, planned in Q1 2023, needs to consider access constraints, complex topology and the limitations related to additional ground clearance, while addressing the requirement of improving orebody knowledge. The drill plan had to address two objectives. The first and main aim of drilling was to upgrade the Resource Classification to allow for possible conversion to Ore Reserve. The input for this objective was a volumetric representation of the areas currently not meeting pre-defined quantitative Resource Classification upgrade criteria. The second objective was to better define the orebody extents and geometry. For the second objective, the input to the drilling optimiser was a volumetric representation (blocks) of the areas of high uncertainty in the mineralisation/waste boundary, which were defined using an indicator conditional simulation technique. The drilling optimiser output was a range of compliant drill plans. A set of KPIs based on economic and orebody knowledge criteria were used to assess the plans and to select the most optimal drill design to be drilled in 2023. The geology and management teams were able to make better informed, objective decisions using the trade-off between cost and orebody knowledge gained. As part of the assessment, the AI generated plans were compared to our current planning practises. The AI assisted plans, when gauged against the project KPIs, showed clear and measurable improvements in both meeting project objectives and in managing operational risk.

May 24, 2023

By M Bond, R R. Hargreaves, G W. Booth

There are numerous causes of speculative mineral resource and reserve inflation. Traditionally, these are linked to issues of data accuracy or misinterpretation, the use of overly optimistic estimation parameters or assumptions, an absence of independent expert verification, or the simple pressure to increase company value, covert or otherwise. Owing to its subjective nature, classification of resources and reserves remains an opaque process. Of necessity, Competent Persons rely on personal heuristic interpretations, ideally underpinned by appropriate estimation and classification experience across commodity and deposit types. Whereas independent verification of individual resource and reserve statements remains impractical, publicly available data can be interrogated for potential category inflation, particularly when viewed with exploration expenditure statistics included in annual company reports. Abrupt changes in category tonnages and market capitalisation without concomitant expenditure can aid in outlier detection. Consequently, a comparison of common exploration and resource reporting parameters offers a basis for risk assessing classification robustness, over time. In this introductory study, an analysis of globally listed companies was undertaken over a multi-year period, examining base and precious metal projects in both preproduction and operational asset classes. From these, a series of exploratory decision tree trigger points were generated against which target companies were anonymously identified and risk-ranked.

May 24, 2023

By D Clarke, I Minniakhmetov

The Olympic Dam deposit is truly a world-class IOCG-Ag deposit, the world’s fourth largest deposit of copper and the world’s largest known single uranium deposit. Traditional and non-traditional methods have been used to accurately model the geology and mineralisation of the Olympic Dam deposit. Conditional simulation models have long been used as the most robust method for estimating risk and uncertainty in mine planning decisions at other mines around Australia and the world. There are many challenges associated with simulating the Olympic Dam deposit at a selective mining unit size sufficient for underground mine planning purposes. These include the size of the deposit, resulting in hundreds of millions of grid blocks; the disseminated nature of the zoned sulfide mineralisation. And lastly the direct relationship of the relative abundances of the sulfide mineral species that are crucial to the Olympic Dam smelter performance. Several geostatistical techniques have been utilised in the workflow for the Olympic Dam Conditional Simulation model to address these challenges. The key techniques are: • Projection Pursuit Multivariate Transform to de-correlate the main elements before simulation. • Pluri-Gaussian implicit boundary simulation method to simulate the mineralisation domains. • Spectral simulation method of de-trended and de-correlated attributes with account of local varying variance. The resulting conditional simulation models have been validated against histograms, grade-tonnage curves, cross-plots and assessed for variogram reproduction. This paper presents how the final conditional simulation models compare to benchmarking models created using alternate estimation techniques of ordinary kriging and local uniform conditioning. It also presents a validation process using historical samples to test final estimate accuracy of the simulation models.

May 24, 2023

By Mustafa Kumral, Yu Cheng Yang, Zhixuan Shao, Young Bin Moon

Since the discoveries of favorable deposits are becoming increasingly difficult, mining operations shift to lower grade and deeper deposits. The viability of these operations is sensitive to many factors, such as commodity prices and operating costs. Given that a mining corporation has no power to set prices, the focus is directed on minimizing the operating costs. Underground mining operations require a network infrastructure, including shaft, ramps, declines, levels, cross-cuts, raises, winzes, and adit. The design of this network is a costly process. As such, it has a significant potential to reduce development and haulage costs. Furthermore, network design is a continuous process along with development, production, and maintenance throughout mine life. Under the constraints of the turning radius, the gradient, and the obstacle avoidance for haulage network of underground mines, this paper first demonstrates network design and optimization approaches using Dubins path combined with the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithm. A threshold-based model is developed, providing viable solutions to the network design when the number of declines is high. Furthermore, a three-dimensional Rapid-exploring Random Tree (RRT) algorithm combined with Dubins path is employed as a heuristic solver for obstacle avoidance purposes in the network. Various case studies are conducted to show the applicability of the proposed methods.

May 24, 2023

By Guodong Li, Chenlin Wang, Zibiao Yu, Bo Xu

Abandoned coal mines have many underground space resources, such as roadways, shafts, and gobs. Among them, abandoned roadways are the best gas storage space for underground compressed air energy storage (CAES). However, CAES caverns have high air pressure and strict sealing requirements. Therefore, the stability and sealing of abandoned roadways under high internal pressure must be analyzed. Afterward, the suitability of abandoned roadways used for CAES caverns should be evaluated. In this study, the numerical simulation software FLAC3D was used to calculate the stress, deformation, plastic zone volume, and pore pressure of surrounding rock in an abandoned roadway under 10 MPa internal pressure. The influence of buried depth, surrounding rock grade, and in situ stress state on roadway stability and the effect of surrounding rock permeability on roadway sealing were analyzed. Results showed that the stress, displacement, and plastic zone volume of surrounding rock were affected by high internal pressure when the buried depth was less than 300 m, but high internal pressure had little effect on them when the buried depth was more than 300 m. The suitable range of buried depth was more than 300 m. The optimal choice of surrounding rock grade was I and II, followed by grades III, IV, and V. The optimal choice of in situ stress state was σH > σh > σv, followed by σH > σv > σh and σv > σH > σh. The sensitivity of the stability evaluation parameters was ranked in descending order as follows: buried depth, surrounding rock grade, and in situ stress state. When the surrounding rock permeability was less than 1 × 10− 14m2, the 24-h air leakage rate of the roadway was less than 1%. The suitable range of surrounding rock permeability was less than 1 × 10− 14m2.

May 23, 2023

By Muhammad Hashim Rasa, Ali Aras

Recovering valuable metals from tailings not only provides a source of income but also helps conserve natural resources, thus reducing the environmental impact of mining activities. This study aimed to recover cobalt using tailings of the Küre flotation plant, which were determined to contain 0.17% Co. Flotation tests were conducted on samples taken from the tailings to investigate the effects of pH and pH conditioning time, as well as types and amounts of depressant, collector, and frother on the grade and recovery of Co in rougher flotation tests. Optimal flotation conditions were determined to be pH 6, a pH conditioning time of 7 min, and dosages of 50 g/t, 100 g/t, and 20 g/t of sodium hexametaphosphate, X-231, and DF250, respectively. According to the rougher flotation test results, a concentrate with a Co grade of 0.46% and a Co recovery of 84.15% was obtained. In the concentrate obtained using cleaner flotation tests, the Co grade increased to 0.49% and Co recovery increased to 90.56%. These results show that froth flotation, carried out with the appropriate reagents, is a successful method for recovering Co by enriching the flotation plant tailings.

May 17, 2023

By Abhishek Kumar, T. G. Sitharam, Surender Singh

The height of tailings pond (TP) embankments is frequently raised to accommodate the ever-increasing volume of tailings released by the mining industries. Excess pore water pressure (EPWP) may develop during the height-raising operations, which can affect the overall stability of TP. This article presents a detailed stability analysis for the embankments of an existing TP, the height of which was increased twice utilizing downstream (D/S) and upstream (U/S) construction techniques. A rigorous two-dimensional transient fully coupled-stress-pore pressure analysis is performed in the finite element-based package RS2 to examine the build-up of EPWP during different stages of construction. Furthermore, an attempt is made to investigate the feasibility of future height raising, with due consideration given to the influence of embankment raising rates. Results from the analysis show a development of higher EPWP within the tailings deposit in comparison to the embankments of TP, indicating the development of an undrained-like condition. The study further reveals that the development of EPWP is highly affected by the rate at which embankments of TP are being raised. A higher rate of embankment-raising results in the development of greater EPWP in comparison to a lower embankment-raising rate, which may lead to the ultimate collapse of TP. Furthermore, based on the stability analysis, the height of existing TP can be further raised by 4 m (two lifts of 2 m height) utilizing the U/S construction technique. A thorough cost and benefit analyses are however required before implementing the results of the current analysis since the storage capacity of TP is reduced while raising by the U/S method.

May 16, 2023