Mining, Metallurgy & Exploration最新文献

Abstract

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.

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.

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.

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.

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%.

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.

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%.

Graphical Abstract

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.

Graphical Abstract

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.

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 (S_n²⁻), thiocyanate (SCN⁻), thiosulfate (S₂O₃²⁻), trithionate (S₃O₆²⁻), tetrathionate (S₄O₆²⁻), pentathionate (S₅O₆²⁻), hexathionate (S₆O₆²⁻). 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 (S₂O₃²⁻), trithionate (S₃O₆²⁻), tetrathionate (S₄O₆²⁻) 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.