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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 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

By Xin Wang, He Shao, Wenpu Li, Yiyi Zheng, Xi Chen, Yurong Gao

This study utilized experimental and numerical simulation methods to investigate and analyze the atomization characteristics of three internal air–water mixed atomizers under different operating conditions. By comparing the research results, the effective dust control working parameters for the application of the selected atomizer in the engineering field were determined. Firstly, the atomization characteristics of the three atomizers were studied using a customized experimental system. The results indicated that nozzle 2 had a wide atomization range, a small atomization distance, and small droplet size; nozzle 3 had a narrow atomization range, large droplet size, and fast atomization speed; and nozzle 1 not only had a large atomization range but also could produce droplets of dry mist size with fast atomization speed, meeting the dust reduction requirements of the Majiliang Coal Preparation Plant. Secondly, Fluent software was used to simulate the atomization process and particle size distribution of the three internal mixed atomizers, determining the working conditions of the atomizers, the required number of atomizers, and the application angle of the atomizers in the internal mixed dust removal system. Finally, the atomized dust control system was applied on-site, achieving a total dust removal efficiency of 90.72% and a respirable dust removal efficiency of 89.75%.

Mar 9, 2024

By Lingyun Zou, Xinghai Lei, Tiezheng Li, Yifei Song, Nan Wang, Yang Li

The stability of key strata is of utmost importance in ensuring safe and effective coal seam mining operations. To minimize disturbance impacts on these strata and ensure their stability, it is crucial to assess the degree of disturbance caused by mining activities. This study proposes the evaluation index “disturbance degree of key stratum (KSDD)” and establishes a quantitative KSDD criterion to measure the degree of disturbance on key strata. To facilitate the assessment process, an intelligent calculation system for KSDD is developed. The classification criteria are derived by combining the measured three-zone heights from multiple mines. The reliability and accuracy of the KSDD quantitative criterion are validated using field measurement data. Furthermore, the KSDD quantitative criterion is applied to the Meihuajing mining area No. 23, and the distribution characteristics of KSDD are analyzed. The findings of this study can serve as a valuable reference for reducing disturbance and enhancing the stability of key strata during subsequent mining operations. Overall, this work contributes to the field of ground control in coal seam mining by providing a comprehensive approach to assess and mitigate the disturbance caused by mining activities on key strata.

Mar 8, 2024

By Dayu Long, Changhong Li, Yu Wang, Juzhou Li, Yongyue Hu

To address the problem of seepage failure that affects the stability of the fine-grained tailings dam, two kinds of prevention and treatment measures were proposed involving composite flocculants and composite curing agents. The orthogonal test was conducted to determine the optimal ratio flocculant (ORF) and the optimal ratio curing agent (ORCG). Then, numerical models were established to evaluate the effects of the prevention and treatment measures on the seepage and stability of the tailings dam. The results show that the mechanical properties and microstructure of the tailings are significantly improved by adding the ORF and ORCG. Furthermore, numerical studies suggest that the addition of the ORF and the ORCG to the tailings improves the factor of safety of the tailings dam, but the addition of the ORCG also increases the height of the phreatic line. It is also speculated that the addition of the ORF can prevent the formation of through failure zone in the tailings dam. Therefore, the optimal measure to prevent seepage failure in the tailings dam is adding an appropriate amount of the ORF, as it reduces the height of the dam’s phreatic line and lowers the risk of seepage failure. The typical area susceptible to seepage failure can be treated by adding the ORCG. However, it is important to ensure adequate drainage of the area and to maintain the phreatic line at a reasonable buried depth.

Mar 4, 2024

By Shakuntala Tudu, Indrajit Paul, Surajit Sinha, Pulibandla Basaveswara Rao, Shaik Mahaboob Basha, Srinivas Dwarapudi

The iron and steel manufacturing sector directly accounts for 7–9% of global CO2 emissions. Raw material preparation, such as iron ore sintering, pelletizing, and cock making, is the major CO2 emitter. As climate change becomes a bigger concern, steel manufacturers need to lower CO2 emissions without hindering efficiency or increasing costs. In recent years, the percentage of iron ore pellets in blast furnaces has increased due to its uniform size, good reducibility, and high tumbler index. Pelletizing is energy-intensive and emits considerable CO2. Around 20% of CO2 emissions during pellet making come from fluxes. In the present work, the authors established a novel CO2- free flux called wollastonite (CaO.SiO2) for sustainable palletization. Pellets with varying percentages of wollastonite (0–6%) are prepared and tested for chemical, physical, and metallurgical properties. Image analysis through an optical microscope is carried out to quantify the phases of fired pellets. SEM–EDS is performed to evaluate the chemical composition of the melt and slag phases. The results showed that the reducibility index (RI) and swelling index (SI) of pellets decreased with an increase in wollastonite dosage. Pellet strength increases with an increase in wollastonite addition up to 1.2% CaO (2.27% wollastonite), and a decrease in strength is observed thereafter. The increase in strength is attributed to the increase in slag bonds. The decrease in strength beyond 1.2% CaO is mainly because of an increase in low melting eutectics and more magnetite content. Pellets with 2.27% wollastonite to get 1.2% CaO showed good physical and metallurgical properties.

Mar 4, 2024

By Cheng Xie, Zhihu Li, Xiaoming Sun, Linsen He, Jiaxu Ding, Jinkun Yang, Yong Zhang, Zhenmin Qi

To solve the problem of large deformation of deep soft rock roadway, taking the soft rock roadway of no. 1 coal mine in New Shanghai as an engineering example, the deformation mechanism of surrounding rock of deep soft rock roadway is analyzed by combining theoretical analysis, numerical simulation and field test, and the control countermeasures centering on deep and shallow dense drilling are put forward. Through theoretical derivation, based on the masonry beam theory, surrounding rock structure S-R stability principle and composite beam principle, the length, angle, and spacing of deep and shallow dense drilling are determined. Through numerical simulation, the deformation evolution process of soft rock roadway surrounding rock after dense drilling pressure relief is reproduced, and the influence of drilling parameters (drilling spacing, dip angle) on pressure relief effect is analyzed and compared. The field application test and monitoring verify that the deformation control measures of deep and shallow dense drilling broken roof surrounding rock have a good effect of large deformation control of soft rock roadway, and provide a new support means for the safety and stability control of soft rock roadway.

Mar 2, 2024

By N. Duru, C. Nesbitt

During the cyanide leaching process, gold and silver ores that come from the transition zones, which typically contains low levels of sulfide, may produce one or more of the following reduced sulfur species: sulfide ( HS−), polysulfides ( Sn 2−), thiocyanate ( SCN−), thiosulfate ( S2O3 2−), trithionate ( S3O6 2−), tetrathionate ( S4O6 2−), pentathionate ( S5O6 2−), hexathionate ( S6O6 2−). The actual speciation of the reduced sulfur species in the circuits will primarily depend on the redox potential, pH, cyanide levels, and existing sulfur species in recycled process water, as well as the presence of other reactive metal species. The development of an accurate analytical method for sulfur species in cyanide leaching units of gold ores where sulfur speciation occurs has an important role in explaining the metal recovery deviations. This study presents the speciation of sulfur species and the development of ion chromatography method to analyze reduced sulfur species thiocyanate ( SCN−), thiosulfate ( S2O3 2−), trithionate ( S3O6 2−), tetrathionate ( S4O6 2−) in cyanide leaching circuits for gold ores. The method developed has resulted in precise quantification of target sulfur species in leach solutions. Method development and validation results were illustrated on analytical graphs containing each species’ peak number, retention time (min), type, width (min), area (mAU*s), height (mAU), and area distribution (%) of the peak.

Mar 2, 2024

By Laura Suarez, Jörgen Kajberg, Pär Jonsén

How does an investigation into the breakage characterization of electric arc furnace (EAF) manganese slags contribute to a more responsible usage of resources throughout the life cycle of steel products and reduction of carbon emissions? The main goal of this study is to increase the knowledge on the mechanical response of manganese slag to open the potential of pyrometallurgical residues to become secondary material in industrial applications such as infrastructure construction, fillers, binders and soil stabilization, among others.

Mar 1, 2024

By Kasimcan Koruk, Julian M. Ortiz

A geological model accounting for uncertainties possesses important advantages for resource estimation. Machine learning algorithms (MLAs) employed on multivariate geochemical datasets open up ways to new methodologies for such geological models with ease in comparison to traditional geostatistical methods. This article proposes a two-step MLA with an ensemble implementation to define geological domains and their uncertainties based on geochemical data. The proposed workflow is applied hierarchically on a dataset from a porphyry copper deposit to perform binary classification that can be attributed to alteration domains.

Mar 1, 2024

By Ankit Jha, Javad Sattarvand, Aaron Young

Blockchain technology is one of the prominent disruptive technologies that are being implemented in several disciplines. The application of blockchains in the mining and mineral industry can provide utility to several processes especially when the industry is undertaking digital transformation. The governing principles of blockchain technology are applicable in undertaking transformation in several processes within the mining industry. This study investigates the applications of blockchain technology within the realms of the mining industry and identifies key areas of implementation. A systematic review of publications on academic platforms relating to blockchain technology in the mining industry did not retrieve a considerable number of articles. Consequently, a thorough review of white papers and articles authored by individuals on use cases within the mining industry is compiled and presented in this review article. This review article identifies all the potential areas within the mining industry where blockchains could provide value and improve processes through their implementation. The broad area of implementation of blockchains includes supply chain, traceability in spares parts, contract management, regulatory compliance and cybersecurity.

Mar 1, 2024

By S. Afrouz, C. Keles, W. R. Reed, E. Sarver, T. Akinseye, A. Greth, L. Pan, F. Animah

The resurgence of severe lung disease among U.S. coal miners has not only highlighted the need for improved dust controls, but also the need for an improved understanding of dust characteristics and monitoring strategies [1]. Following up on prior work by the National Institute of Occupational Safety and Health (NIOSH) to demonstrate a novel wet dust collection system on a roof bolter [2], the current study explores the effect of that system on dust characteristics and uses interlaboratory comparisons to comment on analytical methods. Results indicate the wet system did not appreciably affect the composition or size of respirable dust in the vicinity of the operating roof bolter. However, the system does appear to have substantial benefits for the operator. NIOSH has already shown it can reduce the respirable dust mass concentration to which the operator is exposed during dustbox cleanout [2,3], which is a frequent maintenance activity that can re-aerosolize dust, and new results here indicate the silica and silicates content in this dust may also be reduced, thereby reducing the overall hazard. Moreover, regarding analytical methods, excellent correlation was demonstrated between measurements of quartz mass, taken first by NIOSH and then by a university laboratory, using direct-on-filter Fourier transform infrared (FTIR) analysis. This method is the basis for envisioned “end of shift” silica monitoring (quartz is the predominant form of crystalline silica in coal mines) [4]. For particle-level analysis by scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), there was more variability in results generated by two independent university laboratories.

Mar 1, 2024

By JIAQI JIN, Chen-Luh Lin, Amanda N. Erskine, Jan D. Miller, Shijie Wang

The liberation and exposure of valuable mineral grains in ore particles are of significant importance in understanding the efficiency of flotation separations. A flotation feed sample from the Kensington concentrator was scanned by micro Xray computed tomography (micro-XCT), to determine the liberation and exposure of auriferous pyrite grains. The analysis results suggest a satisfying extent of liberation for particle sizes smaller than 212 μm. Theoretical flotation recovery of pyrite for selected particle size fractions was predicted from the three-dimensional liberation and exposure analysis. The plant flotation tail was also characterized by micro-XCT to identify liberated and partially liberated pyrite particles that might not be collected into the concentrate. However, liberation analysis of the tail sample revealed that the majority of liberated pyrite was recovered in the plant flotation circuit. Trainable Weka, a machine learning segmentation approach, was compared with the Watershed thresholding segmentation for the 106 × 45 μm particle size fraction scanned at a voxel size of 1.85 μm. Improved segmentation of small particles was found using the machine learning method.

Mar 1, 2024

By Quanjun Liu, Rongping Lin, Rongdong Deng

Arsenic contamination significantly affects the quality of copper concentrates, presenting challenges during smelting processes. Considering that covellite and enargite have similar surface properties, they are difficult to separate by flotation, resulting in copper concentrates with excessive levels of arsenic. To address this issue, this study systematically investigated the flotation separation of covellite and enargite in microflotation and bench-scale flotation tests using calcium lignosulfonate as a depressant, with the results indicating that calcium lignosulfonate can be used to separate covellite and enargite because it enables the separation of arsenic-bearing copper minerals into high- and low-arsenic (As 0.57%) copper concentrates. According to contact angle and adsorption tests, scanning electron microscopy–energy dispersive spectroscopy, and X-ray photoelectron spectroscopy, the differential adsorption of calcium lignosulfonate onto covellite and enargite is the primary reason for their distinct flotation behaviors in the presence of calcium lignosulfonate. The selective depressive effect of calcium lignosulfonate provides a novel approach for improving the flotation separation of arsenic-bearing minerals from copper sulfide minerals.

Feb 28, 2024

By Tuanhui Wang, Qiwei Wang, Quanrui Liu, Jianhui Xu, Chao Wang, Yu Liu, Yuefeng Li

Rockburst is a highly destructive geological hazard that can cause casualties and equipment damage. To achieve highaccuracy discrimination of rockburst intensity, this article proposes an improved model that addresses the inefficient maximum membership principle used in traditional rockburst fuzzy evaluation models. The stress coefficient σθ/σc, brittleness coefficient σc/σt, and elastic deformation energy index Wet are selected as evaluation indicators for rockburst classification. Subjective and objective weights are obtained using the Delphi method and entropy weight method (EWM). Three types of membership function distribution forms are then used to obtain the membership degrees of each indicator to rockburst grades: trapezoidal membership function (TMF), normal membership function (NMF), and quadratic parabolic membership function (QPMF). Finally, six traditional models and six improved models are established using the maximum membership principle (MMP) and weighted average-maximum membership principle combination evaluation principle (WMP), respectively. Based on the analysis of 100 sets of rockburst field data, the accuracy, precision, recall, and F1-score of the improved evaluation model are increased by 11.3%, 0.097, 0.068, and 0.089, respectively, compared to the traditional model. The Delphi-NMF-WMP model is selected as the best model, with four performance indices reaching 97.0%, 0.979, 0.979, and 0.978. The best model is applied to evaluate the rockburst intensity of the Cangling Tunnel, Dongguashan Copper Mine, and Jiangbian Hydropower Station Diversion Tunnel, with evaluation results consistent with the actual situation, demonstrating the reliability and scientificity of the model.

Feb 28, 2024