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By Ahmad Rahbar-Kelishami, Zahra Karimi

When alumina is extracted from bauxite ore, one of the environmental pollutants created is known as red mud (RM). This study clarifies that the RM obtained from the Iran Alumina Company has a significant proportion of iron oxides (24%), alumina (19%), silica (17%), and calcium (21%), as well as trace amounts of other minerals. The elements in the RM can be removed and utilized again to reduce environmental pollution. Acid leaching is one of the best ways to selectively exclude some minerals from the RM. In this research, the RM is exposed to different inorganic acids, including HCl, HNO3, H2SO4, and H3PO4, and their binary mixtures. By comparing the results obtained from XRD, EDX, and SEM, it was discovered that CaSO4 crystals are formed by exposing the RM to sulfuric acid. Besides, phosphoric acid was only able to destroy the surface of RM particles. The XRD analyses of acid-washed residues demonstrated that except for the residue of HCl 5 N, all residues contain hematite, showing that inorganic acids cannot easily extract hematite from the complex phases of red mud. While the dissolution of RM with HCl or HNO3 will remove most of the calcium content of RM texture, increasing its iron oxide percentage, which may subsequently be utilized to make colors and pigments.

Mar 29, 2024

By Juan L. Yarmuch, Gonzalo Sepulveda

This article presents a novel approach to address the mining width-constrained open pit mine production scheduling problem in the context of medium-term planning. A mathematical formulation is proposed to incorporate mining width constraints into the production scheduling process, aiming to maximize the NPV of the schedule while ensuring enough room for the operation of mining equipment. To tackle the computational challenges posed by large-scale instances of the problem, we propose a method based on variable fixing and horizontal precedence generation. In this study, we apply the developed model to real-world scenarios from Radomiro Tomic short-term mine planning problems such as optimizing the timing of major truck maintenance and the impact of external factors, like the delay in the production of the Chuquicamata underground project. Remarkable improvements are observed with the mining width-constrained model. Specifically, the mining width satisfiability is enhanced from 2 to 60% compared to the traditional open pit mine production scheduling model, underscoring the significance of incorporating these constraints. The proposed method showed good results reaching optimality gaps within 5%.

Mar 28, 2024

By L. C. de Kooker, K. Esmaeili, I. Musonda, M. Ferentinou

A numerical investigation of the effect of pore pressure regime on the safety factor and the critical failure mechanism is presented for fly ash storage facility. Pore pressures’ measurements from standpipe piezometers and pore pressure estimated from seepage analysis are used to compare the factor of safety for a fly ash slope. This was applied for considering static and seismic scenarios. A probabilistic approach was applied to account for the uncertainties resulting from the limited data available and support a qualitative risk assessment evaluation. Slope stability analysis is conducted in two and three dimensions, adopting the limit equilibrium analysis approach, and also a finite element seepage analysis, to assess the stability of the slope. The two-dimensional cross-sections were extruded to three-dimensional models to estimate the factor of safety and associated shear failure. The results from the performed analysis suggest an increase in safety factor values of 5%.

Mar 27, 2024

By Joel Lööw, Jan Johansson, Erik Lund

Digitalization and automation technology offer new possibilities to increase productivity and obtain higher levels of autonomy in mining operations. Introducing autonomous systems into mining is not only a technical problem in terms of effectiveness and efficiency, nor a problem of safety in human-automation interactions. The systems also need to be designed and developed so that they foster healthy and attractiveworking environments. The design and development phase of newmining technology has not been extensively studied previously. To fill this knowledge gap, we investigated technology developers’ basic assumptions about humans and their interactions with the technology they develop. We conducted five semi-structured workshops within an EU funded project concerned with developing digitalization and automation solutions for the mining industry. The data suggests that many critical functions will still be under human control in future mining systems. The results also indicate increased complexity in the interaction between autonomous systems and humans as the technology becomes more advanced. As a result, we suggest that a human perspective, based on sociotechnical principles, should not only be considered in implementing the technology at mines but also in the early conceptual phases of developing and designing the technology. This will ensure healthy and attractive work environments in the future mining industry.

Mar 26, 2024

By Pei‑liang Xu, Jun Wang, Xi Zhang, Deng‑pan Qiao, Tian‑yu Yang

The surface backfill, serving as the operational platform for continuing mining in upward slicing and filling stopes, is required to possess sufficient strength and thickness. Currently, there are limited model methods for determining the strength and thickness of the surface fill body. By analyzing the mechanical actions on the surface backfill, it is determined that its stability is mainly influenced by the combined effects of normal and tangential uniform loads under full-load conditions of trackless equipment. Assuming a circular contact surface between the tire of the trackless equipment and the surface backfill, and utilizing solutions from elastic mechanics theories such as the Boussinesq and Cerruti solution, the stress and displacement distribution of the surface fill body were obtained. Based on the maximum vertical stress condition, where the surface backfill body undergoes maximum deformation while still in an elastic state, and considering the stress–strain relationship, a model for the strength and thickness of the surface backfill has been established. According to the research findings, the design for the strength and structural parameters of the surface backfill has been developed to meet the full-load operation of the Atlas ST7 scooptram, with a compressive strength of 1.32 MPa and a thickness of 0.5 m. Numerical simulation analysis results indicate that the stress and displacement of the surface backfill align with theoretical analysis results. Practical results from industrial application in the western section of the Dahongshan Copper Mine demonstrate that the designed strength and thickness of the surface backfill meet the operational requirements for trackless equipment, resulting in significant engineering application effects and economic benefits. The research findings hold significant importance for advancing the theory of backfill mining and have high applicability and promotional value for similar mines.

Mar 24, 2024

By Brajendra Mishra, Himanshu Tanvar

Niobium and tantalum extraction industries heavily depend on fluoride chemistry for metal oxide production. This study concentrates on developing a fluoride-free approach utilizing alkali treatment for selective dissolution of niobium and tantalum phases. The application of microwave heating in the alkali treatment of columbite significantly reduced the processing time, providing a higher reaction rate and recovery than conventional heating. A short duration of microwave exposure (6 min) elevated the sample temperature to more than 900 °C, resulting in the rapid formation of water-soluble niobium and tantalum complex. Metal recovery from the solution was attempted through direct precipitation using guanidine carbonate as the precipitating agent, resulting in a mixed oxide product with > 90% purity. On the other hand, solvent extraction was also attempted using methyltrioctylammonium chloride as an extractant, providing a niobium oxide and tantalum-rich mixed oxide with > 98% purity as the final product.

Mar 23, 2024

By Shailendra Chawla, Ashok Jaiswal, Sonu

Side spalling/skin failure occurs due to the high-induced stress in underground structures. In such cases, rock bolting or other support systems are being used to control the skin failure or spalling of the pillar. The nature of these support systems is passive, which acts during the deformation. These support systems restrict the displacement considerably of the side/or roof surface of the excavation. Ultimately, it improves the stability of the structure because of the increment in residual strength of rock mass. It is noted that these passive support systems give very low confinement in the range of 0–0.015 MPa at the onset of failure. As the level of confinement will be very low and dependent with progress of failure, triaxial test was not found practically suitable. Thus, an alternative procedure of testing has been proposed. In the procedure, sides of sample have been restricted little bit by using adhesive tape. It provides the limited boundness on the lateral direction (LBLD) of rock specimen. The uniaxial compression strength (UCS) test has been performed on 30 numbers of cylindrical rock specimens using the servo-controlled stiff testing machine. Specifically, two rock types (medium-coarse–grained and coarse-grained rocks) were studied in terms of stress–strain behaviour so that a full residual strength envelope for each specimen was obtained. This study reveals that the residual strength of limited confined rock specimens has been significantly increased as compared to unconfined rock for both groups of rock types. The average residual strength of LBLD specimens of fine-grained rock and medium coarse-grained rock has been increased around 12 times, and five times as compared to unconfined rock, respectively. The average peak strength of LBLD rock specimens has been increased in the range of 30.5 to 48.6% for coarse-grained rock. The results of this study have been presented in terms of peak strength, residual strength and Young’s modulus of rock, and the post-peak failure behaviour of rock specimens was also critically analysed through a stress–strain curve.

Mar 21, 2024

By Abhiram Kumar Verma, Soumya Ranjan Mallick

Generally, waste such as soil and sandstone is used in mines for road construction or haul roads. In many such mines, it is challenging to design haul road pavement to match the dumper capacity. This paper investigates overburden soil to find its utility as a pavement material. It is found that overburden soil is unsuitable pavement material without stabilization; hence, nine composite materials are developed using overburden soil and RBI. Physical, mechanical and microstructural properties of unstabilized and stabilized soil are determined. Statistical analysis is carried out to assess the effect of soil type, RBI and curing period of strength characteristics of unstabilized and stabilized soil. ANOVA tests assess the influence of RBI percentage on soil geotechnical properties, and regression relations are developed. Two-way ANOVA shows the effect of RBI and soil type on soil geotechnical properties, whereas one-way ANOVA shows that the influence of soil type is more than the RBI. The regression relation is developed for CBR, UCS, Poisson’s ratio and modulus of elasticity with a good correlation coefficient. The performance of RBI is more with the finer material and reduces with an increase in the size of soil grains. The performance of the developed composite is better than the earlier developed composite based on overburden with fly ash, lime kiln dust, lime or clinker.

Mar 19, 2024

By Hossein Ghaedi, Hadi Fattahi

Despite the significant role of coal in the economic progress of nations, the occupational and health risks associated with its mining pose a major concern for industry stakeholders. The occurrence of roof collapses in coal mines remains a critical factor leading to substantial loss of life and financial damages for miners. Therefore, accurately predicting the roof fall rate (RFR) holds paramount importance. However, the uncertainty surrounding rock parameters in mines hinders the application of conventional methods to assess roof collapse rates in coal mines. To tackle the challenges associated with predicting roof fall rates in underground coal mines, this study proposes a novel solution by leveraging the Rock Engineering System (RES) method. The investigation is grounded in a dataset comprising 109 data points, encompassing crucial input parameters like depth of cover (DOF), primary roof support (PRSUP), intersection diagonal span (IS), mining height (MH), and coal mine roof rating (CMRR). In the model construction phase, 80% of the data (87 points) were utilized to build the RES model. A critical aspect of this study involves the evaluation of the RES model’s performance against alternative regression techniques, namely linear, power, exponential, polynomial, and logarithmic regression. This comparison was executed using the remaining 24 data points (20% of the dataset) for rigorous evaluation. Employing key statistical metrics such as mean square error (MSE), root mean square error (RMSE), and squared correlation coefficient (R2), the study systematically demonstrated the superior accuracy of the RES-based method compared to other approaches. In conclusion, the outcomes strongly support the efficacy of the RES method in predicting roof fall rates, not only in the specific case studied but also indicating promise for its application in other underground coal projects. This underscores the potential of the RES method as a reliable and versatile tool for forecasting roof fall rates in the complex and critical context of underground coal mining.

Mar 19, 2024

By Xie Junjie, Li Shina, Ma Ruixin, Min Changli, Yin Zichen, Li Kang, Shi Zhuonan

Cesium and rubidium were effectively separated by zinc ferrocyanide coprecipitation method, and the effect of precipitant addition amount on the separation of cesium and rubidium was studied. Under the conditions of Zn/Cs molar ratio of 0.45 and Zn/Fe molar ratio of 1, the precipitation rate of cesium is 84.01% and the separation factor of Cs/Rb is 164.65. The thermogravimetric curves of the sediment were measured, and the effects of roasting temperature, roasting time, and leaching liquid/ solid ratio on the extraction of cesium were studied. Almost all of the cesium was extracted under optimal conditions: roasting temperature of 600 °C, roasting time of 3 h, leaching temperature of 25 °C, leaching time of 0.5 h, and liquid/solid ratio of 5:1 mL/g. After the leaching process, the leach liquor with high concentration of cesium of 80.17 g/L was obtained. Finally, the leach liquor was further purified by solvent extraction, and the purity of the cesium chloride product reached 99.66%.

Mar 17, 2024

By Christos Roumpos, Philip‑Mark Spanidis, Francis Pavloudakis

Coal mining operations are large-scale, long-term frameworks of high complexity. Mining organizations accumulate, develop, and leverage knowledge from diverse scientific and technological fields as a result of these operations. Both practical experience and existing literature indicate that knowledge management (KM) methods within the mining industry primarily target solving immediate technical challenges and operational requirements. However, they are not commonly regarded as strategic tools to enhance the performance and competitiveness of mining companies. Empirical evidence from the Greek mining industry suggests that the management of available knowledge is intricate, less effective, and dysfunctional. This paper presents a methodology based on the principles of quantitative research (QNR), collaboratively conducted with a group of mining experts, to assess the KM landscape in the Greek mining industry. The methodology involves a structured data collection framework using questionnaires, subsequent statistical analysis, a discussion on critical methodological aspects, and an interpretation of results focusing on key aspects useful for planners and designers of KM systems in the mining industry. Finally, the paper concludes by summarizing the methodology’s outcomes and proposing further perspectives for research.

Mar 16, 2024

By Mary Nelima Ondiaka, Kayode Henry Talabi, Oladunni Oyelola Alabi, Fatai Olufemi Aramide, Francis Gitau

Iron ore is essential in steel making; however, high-grade ores have diminished, making low-grade ores inevitable. These lowgrade iron ores need further beneficiation to upgrade the iron content. Currently, traditional physical and chemical methods are utilized and are not environmentally friendly. Bio-beneficiation techniques have emerged as a sustainable alternative for mineral recovery. This review delves into recent bio-beneficiation advancements for enhanced low-grade iron ore recovery using microbes. Research has revealed that bio-beneficiation methods such as bio-leaching, bio-flotation, and bio-flocculation have proven successful in iron recovery from ores. The bio-beneficiation process occurs in mild conditions using bio-reagents derived from microbes and offers a reduction of chemicals used in processing. Bio-beneficiation of iron ore potentially offers a relatively energy-efficient, cost-effective, and environmentally friendly method of maximum iron ore recovery. However, this review has identified a scaling-up difficulty in which a future approach for industrial-use applications is offered following a thorough sustainability assessment. Bio-beneficiation, using microbial processes, provides a viable avenue for maximizing iron ore recovery while tackling the constraints of dwindling high-grade iron ore resources and environmental sustainability.

Mar 16, 2024

By Kyeong Woo Chung, Rina Kim, Ho‑Seok Jeon, Yeongjin Ahn, Byunghun Go, Min‑seuk Kim, Hong‑In Kim, Sujeong Lee, Yuik Eom

The study focused on the recovery of vanadium from a Korean vanadium-bearing titaniferous magnetite (VTM) ore, examining the behaviors of magnetic separation and Na2CO3 roasting-water leaching. Two concentrates were prepared using single-stage dry magnetic separation and three-step wet magnetic separation, resulting in V2O5 grades of 0.8% and 1.0% and major gangue mineral SiO2 contents of 6.5% and 1.7%, respectively. These concentrates were subsequently roasted at 1050 °C with the addition of Na2CO3 and then water-leached at 25 °C. Various stoichiometric ratios of V2O5 to Na2CO3 were tested, ranging from 1:1 to 1:40 of the theoretically required amount. As the amount of Na2CO3 increased, the vanadium leaching efficiency showed fluctuations between 4 and 35% for ratios of 1:1 to 1:10, while it linearly increased from 4 to 82% for ratios of 1:10 to 1:40 in the leaching of the low-grade concentrate. In contrast, the leaching efficiency increased from 47 to 74% for ratios of 1:1 to 1:8 and then sharply rose to 84% at a ratio of 1:10 in the leaching of the high-grade concentrate. Subsequently, it reached a plateau of 92 to 94% for ratios of 1:20 to 1:40. The difference in leaching efficiency was primarily due to the reaction of gangue minerals with Na2CO3, which hindered vanadium leaching from the VTM concentrates. This hindrance was notably more pronounced in the low-grade concentrate with the lower salt ratio, as the gangue minerals exhibited a preference for consuming Na2CO3 over vanadium. The mineral formation was analyzed in detail using XRD and MLA to shed light on the mechanism of different vanadium leaching behavior depending on the concentrate grade and vanadium to salt ratio. Based on the results of this study, it is evident that applying a proper magnetic separation procedure is significant to achieving satisfactory vanadium recovery with less salt amount by removing gangue minerals ahead.

Mar 15, 2024

By R. J. Quevedo, Y. A. Sari, S. D. McKinnon

The large scale of cave mines leads to many challenges, including operational logistics and geomechanics design. In current practice, pillar stability assessment relies almost exclusively on stress analysis. However, stability is also affected by other factors including those related to operational aspects of the mining method, the effects of which are difficult to account for during the design stages. In this paper we present a case study of the application of a machine learning approach to evaluate the influence of these operational factors on pillar stability at the Chuquicamata underground cave mine in northern Chile. Due to the likely multi-factorial damage process leading to collapses and considering the different pillar conditions, a tree-based machine learning method was used and analysed to improve the understanding of the relative importance of the various contributing factors. Unlike stress analysis methods, it does not require any a priori knowledge of failure mechanisms, nor the calibration of associated controlling parameters. The proposed random forest model predicted pillar collapses with 80% accuracy despite limited samples to model from. The main contributing factors to collapses were found to be related to available pillar volume, cave front geometry, and time under abutment stress conditions. The effects and interactions of such factors were also studied, showing that careful and improved control over operational conditions can significantly reduce the likelihood of pillar collapses. These conclusions could not have been obtained from stress analysis alone, illustrating the complementary nature of conventional stress analysis and machine learning approaches.

Mar 14, 2024

By J. P. Gouvea

Back-analysis of two mining-induced tremors in 2011 was used to determine a modelling criterion for the entire Klerksdorp Goldfield (i.e., Vaal Reefs region). At that time, most mining operations in the region were owned by AngloGold Ashanti (AGA) and shared many geotechnical similarities. By 2018 AGA had sold off all its Klerksdorp operations to different mining companies, which continued applying the 2011 modelling criterion. As mining activities became more remote, scattered, and isolated, the extraction of isolated blocks of ground and remnants became increasingly necessary. However, the inherited criterion allowed only minimal or no mining activities at these areas. Keeping in mind that safety is the overriding consideration, an innovative numerical modelling approach, which includes the application of peak particle velocity designs, was developed to provide practitioners in the Klerksdorp Goldfield with a suitable criterion to justifiably and safely mine isolated blocks of ground and remnants. This would not always be possible if a conformist approach was used.

Mar 14, 2024

By W. Bendaikha, S. Larbi, A. Ramdane

An oolitic iron ore from Gara Djebilet, Algeria was characterized by X-ray diffraction, scanning electron microscopy, and energy dispersive spectrosopy and the phosphorus distribution between various phases studied. Two ore types were identified – a haematite-dominated, oolitic type and a more massive, magnetite-dominated type. The haematite-dominated ore had a higher phosphorus content, up to 0.6% in the iron oxide minerals, than the magnetite-dominated type (0.3% P). Owing to the very fine-grained texture of the gangue minerals, reducing the phosphorus content to levels suitable for steelmaking (below 0.05% P) by conventiobal means would entail an energyintensive process with a high carbon footprint. Preliminary leaching test work using a sulphurous geothermal water as lixiviant, assisted by solar thermal acceleration, gave very promising results, removing 0.13% of the residual P (or 21.7% removal of total P) from the high-phosphorus oolitic ore.

Mar 14, 2024

By S. Swanepoel, A. V. Cherkaev, Q. G. Reynolds, M. Erwee

Ferrochrome (FeCr) is a vital ingredient in stainless steel production and is commonly produced by smelting chromite ores in submerged arc furnaces. Silicon (Si) is a componrnt of the FeCr alloy from the smelting process. Being both a contaminant and an indicator of the state of the process, its content needs to be kept within a narrow range. The complex chemistry of the smelting process and interactions between various factors make Si prediction by fundamental models infeasible. A data-driven approach offers an alternative by formulating the model based on historical data. This paper presents a systematic development of a data-driven model for predicting Si content. The model includes dimensionality reduction, regularized linear regression, and a boosting method to reduce the variability of the linear model residuals. It shows a good performance on testing data (R2 = 0.63). The most significant predictors, as determined by linear model analysis and permutation testing, are previous Si content, carbon and titanium in the alloy, calcium oxide in the slag, resistance between electrodes, and electrode slips. Further analysis using thermodynamic data and models, links these predictors to electrode control and slag chemistry. This analysis lays the foundation for implementing Si content control on a ferrochrome smelter.

Mar 14, 2024

By I. Ince, S. Kahraman, M. Rostami, B. Dibavar

The density, porosity, and strength of rocks are fundamental in the design of geo-engineering projects. Determining these properties requires the preparation of smooth core samples, which is usually impossible for soft rocks. Besides, only fragmented samples may be available in some projects. A method for predicting rock properties from rock particles such as drilling debris would therefore be useful. This study was undertaken to develop prediction equations for compressive strength (UCS), tensile strength (BTS), density, and porosity values from the crushability index (CI) obtained from rock fragments. The results showed that UCS, BTS, density, and porosity were strongly correlated with the CI. The physical characteristics and strength of rocks may be predicted with the help of the derived equations. The CI test is a valuable tool for estimating rock properties in drilling projects and in situations where core specimens are not available.

Mar 14, 2024

By Christopher Mark

Six decades ago, the most dangerous job in the USA was mining coal underground. Roof falls were responsible for half of the deaths, killing about 100 miners every year. Fast forward to 2016 and zero roof fall fatalities. Just three miners were killed by roof falls during the following 6 years. How did the mining community achieve this historic goal? This paper starts by analyzing the roof fall fatalities in 1968, categorizing them by their fundamental cause. Then, it shows how each type of roof fall was reduced over time, using snapshots of the fatalities occurring in subsequent decades. Along the way, it evaluates the influence of the regulatory environment, changing mining methods, and better ground control technology. The study found that in 1968 more than half of roof fall fatalities at large mines were attributable to an inadequate safety culture. The immediate effect of the 1969 Coal Mine Health and Safety Act was to reduce the riskiest activities, like needlessly going under unsupported roof. Other hazards, like large roof falls, required technological developments before they were brought under control. Roof Control Plans, which the US Bureau of Mines had been advocating since the 1920s, played a significant role throughout the process.

Mar 12, 2024

By Yao Yevenyo Ziggah, Victor Amoako Temeng, Solomon Evans Kweku Koomson

Tyre hours/life deficit is a major operational challenge facing the mining industry which adversely affects materials production and costs. An accurate forecast of the tyre life is key in addressing this menace. This study for the first time employed the hybrid intelligent technique by utilising three metaheuristic optimisation algorithms, including particle swarm optimisation (PSO), genetic algorithm (GA), and whale optimisation algorithm (WOA), as trainers for the parametric weights and biases to optimise multilayer perceptron neural network (MLPNN) for enhancing prediction of on-site dump truck tyre life in the mine. Four hybrid models known as PSO-MLPNN, WOA-MLPNN, GA-MLPNN, and BP-MLPNN were developed using a total of 157 tyre dataset records obtained from a surface mine in Ghana. In assessing the prediction performances for the models developed, five statistical performance metrics of variance accounted for (VAF), Nash–Sutcliffe efficiency index (NASH), coefficient of determination (r2), mean absolute percentage error (MAPE), and correlation coefficient (r) were utilised. Moreover, ranking, uncertainty analysis and Bayesian information criterion (BIC) techniques were utilised to establish the most effective hybrid model, whereas sensitivity analysis was conducted on the input parameters. Results achieved showed that PSO-MLPNN was the best for prediction because it had the least MAPE value of 1.196% and relatively high values of VAF (99.642%), NASH (0.996), r2 (0.996), and r (0.998). Besides, PSO-MLPNN had the best selection criteria values of 6, 7.1725, and 444.834 for the ranking, uncertainty analysis and BIC respectively. Hence, PSO-MLPNN is recommended for the prediction of on-site dump truck tyre life for the studied mine.

Mar 11, 2024