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By F. Nakhaei, M. Le Roux, Q. P. Campbell, S. Botlhoko

The results of coal sink and float tests are plotted as washability curves. Analysis of these curves indicates the most effective method by which the coal can be cleaned. Sink and float experiments are samplingdependent, destructive, and use toxic chemicals. The present research introduces an alternative method based on a 3D imaging system called RhoVol, in which the density of individual particles is determined from mass and volume measurements. A quantitative error analysis was conducted on coal sample density measurements obtained by RhoVol, and the main factors influencing the errors identified and investigated. The results show that the drawback of this technique is related to its not being able to detect hidden concavities in the particle, resulting in an overestimation of particle volume. Furthermore, it is difficult to capture the impact of porosity and cracks on the volume of coal particles obtained from 3D silhouette images. This mismatch between the RhoVol data and sink and float test results has led to attempts to apply neural network (NN) and linear regression techniques to produce a fully reliable model for correction and estimation of coal density. The NN approach offers superior predictive capability over linear regression, and the estimated density distribution is in line with the sink and float analysis. The root mean square error in estimation of density using the NN model was less than 0.05 g/cm³.

Aug 2, 2022

By K. Isaac, S. O. Bada

This research focuses on the co-firing of discard coal with refuse-derived fuel (RDF) to utilize this abundant resource in South Africa for energy generation and reduce the volume of waste disposed of at landfills. The potential of a coal with a high ash content (> 40%), which is a grade used in some power stations in South Africa, and its combustion compatibility with two different RDFs in terms of emission reductions has been established. Gaseous emissions and ash residues from the combustion and cocombustion of the coal, two different RDFs and coal/RDF blends of different proportion were analysed. One of the RDF samples contained mostly paper (PB) and the other mostly plastic (PL). Co-combustion ash from the discard coal and RDFs showed a decrease in chloride and alkali metal contents as the coal ratio in the blend increased. The slagging propensity of the co-fired blends was found to be very low, while the propensity for fouling decreased from high to medium for all the blends with < 75% RDF. Cocombustion of RDF with coal showed a decrease in SO2 emissions from 387 ppm (discard coal) to 50 ppm for the sample containing 25% coal discard plus 75% PL. A 15% PL to 85% coal blend also reduced NOx emissions from 145 ppm (100% PL) to 88 ppm. The lowest CO2 emission observed was 6000 ppm for the blend of 85% discard coal plus 15% PB. It was established that the most favourable fuel blend that can produce the lowest sulphur emissions if used for power generation is the 25% coal discard plus 75% PL sample.

Aug 2, 2022

By R. H. Matjie, J. R. Bunt, A. C. Collins, J. C. van Dyk, C. A. Strydom

South African discard coal fines and K₂CO₃ blends were heated in a laboratory-scale rotary kiln to produce ashes for H₂SO₄ leaching tests. The optimized H₂SO₄ leaching conditions of 6.12 mol.dm³ (M) H₂SO₄, solid to liquid ratios 1:5 and 1:10, and 80°C for 8 hours were used. K₂CO₃ was added to increase the dissolution efficiency of K. The objective was to determine if the Al present in metakaolinite (Al₂O₃.2SiO₂), the Al, K, and Ti in the alumino-silicate glasses, and the Ti in rutile (TiO₂) in the ashes could be selectively dissolved in H₂SO₄. XRF results show that the ashes formed at 700°C dissolved more efficiently (87% Al, 89% K and 23% Ti) compared to the ashes formed at 1050°C. This can be attributed to the presence of Al₂O₃.2SiO₂, K₂CO₃ melt, K₂CO₃ remnants, KAl(SO₄)₂, and K-aluminosilicate glass in these ashes. XRD results indicate that the ashes prepared at 1050°C contained anorthite (CaAl₂Si₂O₈), microcline (KAlSi₃O₈), pseudomullite (Al₂O₃.SiO₂), and silicon spinel (2Al₂O₃.3SiO₂), which are either insoluble or only sparingly soluble in H₂SO₄. These minerals resulted in the lower dissolution efficiencies of Al and K. Based on the high dissolution efficiencies of Al and K for the ashes produced at 700°C, coal fines blended with K₂CO₃ could possibly be utilized as feedstocks for the production of aluminium(III), potassium(I), and titanium(IV) and a sulphate-containing leach liquor. Furthermore, the environmental issues and costs associated with the handling and disposal of large volumes of coal fines will also be resolved.

Aug 2, 2022

By G. R. Drennan, N. J. Wagner, M. J. T. Sebola

The Soutpansberg Coalfield hosts South Africa's hard coking coal reserves. However, coals in this region are understudied compared to other coalfields in the country. This study characterizes the properties of fine-float fraction samples extracted from a wide diameter borehole core in the Makhado Project, Tshipise sub-basin, Soutpansberg coalfield. Conventional analyses were used to determine the coal quality, petrographic composition, mineralogy, geochemistry (including trace element and rare earth element composition), and free swelling index of samples from six coal horizons and three partings from the economic No.6 Seam. The coal samples are classified as medium rank bituminous C coals (0.88 %RoVmr, 0.92 %Rmax) and are highly vitrinitic in composition (97 vol% mineral matter free (mmf)). The samples show strong caking potential (FSI of 9). The total rare earth concentrations range between 570 and 3193 ppm in the ash samples. Preliminary analysis show all but two samples are promising sources of rare earth elements as the total concentrations exceeded the 1000 ppm cut-off grade. Further research is required to confirm these preliminary findings.

Aug 2, 2022

By B. J. Coetzee, P. W. Sonnendecker

The quality control of a two-stage coal washing process involves several complex components that need to be modelled accurately, to enable autonomous control of the process. The first objective is to develop a method to track the material through the washing process, while ensuring accurate washing prediction models are used. This was achieved through a digital twin model of the Grootegeluk 1 coal processing plant. The model is the amalgamation of manipulating and combining of data-sets from the plant historian, geological wash tables, and mining dispatch servers. This information is then used to control and set the processing medium densities of all 15 modules on the plant, 10 modules in the primary wash and 5 modules in the secondary wash. This controller has been successfully implemented and controlled the plant for 10 days.

Aug 2, 2022

By BEN WANG, HAORAN LI, YALI FENG, JINRONG JU

Acidic wastewater is at present directly neutralized with lime or limestone, which wastes resources such as titanium, scandium and iron and generates a great deal of solid waste. This study proposes a novel approach for the separation and recovery of titanium, scandium and iron from acidic wastewater, and utilization of red gypsum. The proposed process not only recovers valuable metals from acidic wastewater but also treats the red gypsum that has previously been dumped.

Aug 1, 2022

By ERIK C. WESTMAN, JESSICA M. WEMPEN, DALLAN J. COONS, WILLIAM G. PARISEAU, MICHAEL K. MCCARTER

Safe, efficient underground mining is dependent upon proper pillar sizing. Pillar sizing is typically based on a combination of observation of prior behavior, point measurements, theory and numerical modeling. The actual stress redistribution within a pillar, while assumed for many years, has rarely been imaged. Such imaging can help confirm whether or not theoretical and numerical modeling methods agree with actual conditions within a pillar. This research presents a case study from a longwall mine in the western United States. A two-entry, gate-road yield pillar in the headgate of the mine was instrumented with seismometers and convergence monitoring stations, and was monitored over a period of about six months as the longwall face approached the pillar. In this paper, the stress distribution imaged using seismic tomography is compared to the stress distribution expected from theoretical models, geotechnical measurements and numerical models. The tomography results generally agree with those proposed by theory, convergence measurements and numerical modeling results. The agreement of the methods provides validation for the theorized stress redistribution, and this study provides further evidence that tomography can indicate the redistribution of induced stress within a mined rockmass and is another tool available to ensure that mining is conducted safely and efficiently.

Aug 1, 2022

By RICHARD A. THOMAS, Liming Yuan, Lihong Zhou, DAVOOD BAHRAMI

Mine ventilation simulation software has become an essential tool for the mining industry to design and manage mine ventilation operations. Building a well-calibrated mine ventilation network is time consuming, however, and requires great effort. In the last several decades, the mining industry has seen a steady increase in the use of air velocity sensors to monitor airflow and detect unexpected abnormal airflow in some key locations in underground mines. The present research work was carried out to explore the possibility and methodology of calibrating a ventilation network model using atmospheric monitoring system (AMS) data on a routine and ongoing basis.

Aug 1, 2022

By Agus Sasmito, SRIVATSAN JAYARAMAN SRIDHARAN, Akash Adhikari, Purushotham Tukkaraja

The amount of toxic fumes produced during blasting operation depends on the types of explosives used, product formulation, degree of confinement, conditions of use, and reactivity of the explosives with the host rock. Ammonium nitrate and fuel oil (ANFO) is still the explosive of choice due to its lower price and ease of use/loading. If not properly monitored and controlled, toxic fumes produced from blasting operations can have serious health hazards [1]. This paper presents a novel technique developed to track trapped fumes during a development blasting.

Aug 1, 2022

By Nasser Madani, SULTAN ABULKHAIR

The geological and geostatistical modeling of mineral deposits requires densely sampled drillholes that provide accurate and reliable hard data. Furthermore, quantifying orebody uncertainty through geostatistical simulation can allow mining engineers to assess long-term risk in mine planning. Nevertheless, ore deposits can sometimes lack dense drillhole information, reliable hard data with proper quality assurance/quality control (QA/QC), or sometimes both. This study is based on a coal mine located in the Republic of Kazakhstan, where an iron dataset is based on data from three newly drilled drillholes, and geological information comes from a massive collection of legacy drillhole data with no evidence of proper QA/QC. For this reason, a workflow was introduced to construct a representative training image from legacy data and stochastically model geological domains within these three drillholes using a multiple-point geostatistics technique. Once the geological model was obtained, a two-point geostatistics algorithm was applied to model the iron inside each geological domain. The direct sampling algorithm was chosen for modeling geological domains, and sequential Gaussian simulation for iron grade calculation. Both methods were extensively evaluated using different statistical tools and analyses.

Aug 1, 2022

By CLAIRE STREBINGER, ADITYA JUGANDA, JURGEN F. BRUNE, GREGORY E. BOGIN JR.

Methane gas explosions are a major risk in underground coal mining operations. The severity of such explosions can range from local area damage to massive loss of miners’ lives along with significant damage to mine infrastructure and ventilation controls that may lead to mine closure and loss of the entire operation. This study demonstrates the viability of integrating a computational fluid dynamics (CFD) combustion model into a longwall mine ventilation model to simulate methane gas explosions in the longwall face area. The resulting 3D methane gas explosion simulation can provide better understanding of the fundamental physics and the potential impact of an explosion in an underground longwall coal mine.

Aug 1, 2022

By Charles Kocsis, Pedro Nascimento, W. Patrick Arnott, Samuel J. Taylor

Respirable crystalline silica (RCS) is an inhalation health hazard for mining and industrial work environments and must be monitored. We provide theoretical analysis of real-time measurements for determining RCS mass concentration without the use of filters by using photoacoustic spectroscopy. The suspended dust in the mine air can be continuously sampled by the photoacoustic instrument. A tunable quantum cascade laser is the light source, allowing for determination of interferences such as kaolinite, coal dust, and water vapor. The most useful spectral region is found to be between 11 and 13 μm. Absorption by water vapor, and, to a lesser extent, carbon dioxide, in this spectral region has gaps that allow for quantification of the aforementioned dust species as well as a convenient check on the calibration of the instrument. This work brings photoacoustic measurement of aerosol to the mid infrared range where spectrally dependent light absorption can be used to quantify dust composition and mass concentration.

Jul 31, 2022

By Shuie Li, Taibai Li, Tao Hu, Zhongjie Wang, Xiang Ge

As one of the main power sources, lithium-ion batteries (LIBs) will continue to be applied on a large scale in the future market. Commercialized LIBs cathode materials contain various valuable metal elements including Li, Co, and Ni. The development of green and efficient recycling technology is essential. Deep eutectic solvents (DESs) have recently emerged as a new class of green solvents that could potentially be applied for the LIBs recycling industry due to their capability to leach the active materials without the introduction of environmentally hazardous reagents as used in conventional hydrometallurgy process. Considering the rapid progress, a critical review focusing on the progress and fundamentals about the overall efficiency has practical significance for the further advancement of this field. Herein, we briefly introduce the overall process of using DESs for LIBs recycling and specifically focus on the efficiency of each step. Current fundamental understandings and new experimental approaches to enhance the efficiency of the leaching process, the extraction process, and reusability are summarized. We expect this review article to inspire scientists to use DESs as powerful tools for advancing the frontiers of LIBs recycling.

Jul 30, 2022

By M. P. Roy, P. K. Singh, A. K. Mishra, Ashish K. Vishwakarma, Vivek K. Himanshu

Ground vibration is one of the major hazards produced by rock-blasting operation. The accurate prediction of vibration is necessary for designing controlled blasting parameters. The existing vibration predictors consider maximum explosive charge weight per delay and distance as the parameters responsible for ground vibration. These predictors are based on the assumption that the geometrical parameters of the blast will be constant for a site. However, the mining sites with bigger production targets have varying geometrical parameters to suit the excavator utility. Accordingly, the other blast design parameters will also have an impact on ground vibration intensity. A principal component analysis is a dimension reduction technique. This technique along with multivariate logarithmic regression has been used in this paper to predict the ground vibration. The technique has classified the blast design parameters into four principal components. The regression with the scores from these principal components has been carried out. The evaluation of the model performance of predictors along with the existing empirical predictors has been carried out using R2 and RMSE values. The evaluation suggests that the predictor with logarithmic regression followed by principal component analysis gives better performance with respect to the existing empirical predictors.

Jul 30, 2022

By Michael Murphy, Gamal Rashed, Brent Slaker

Pillar stability continues to be a significant concern in multiple-level mining conditions, particularly for deep mines when pillars are not stacked or the thickness of interburden between mining levels is thin. The National Institute for Occupational Safety and Health (NIOSH) is currently conducting research to investigate the stability of pillars in multiple-level limestone mines. In this study, FLAC3D models were created to investigate the effect of interburden thickness, the degree of pillar offset between mining levels, and in situ stress conditions on pillar stability at various depths of cover. The FLAC3D models were validated through in situ monitoring that was conducted at a multiple-level stone mine. The critical interburden thickness required to minimize the interaction between the mining levels on top-level pillar stability was explored, where the top level mine was developed first followed by the bottom level mine. The model results showed that there is an interaction between numerous factors that control the stability of pillars in multiple- level conditions. A combination of these factors may lead to various degrees of pillar instabilities. The highest degree of local pillar instability occurred when pillar overlap ranges between 10 and 70%. On the contrary, the highest degree of stability occurs when the pillars are stacked, the underlying assumption is that the interburden between mining levels is elastic (never fails). Generally, for depths of cover investigated in this study, the stability of top-level pillars shallower than 100 m (328 ft) or with interburden thicknesses greater than 1.33 times the roof span—16 m (52.4 ft) in this study—does not appear significantly impacted by pillar offset. The results of this study improve understanding of multiple-level interactions and advances the ultimate goal of reducing the risk of pillar instability in underground stone mines.

Jul 27, 2022

By VIVEK KASHYAP, Evody Tshijik Karumb, PATRICK TAYLOR

The partial reduction of zinc ferrite to zinc oxide and iron (II, III) oxide can enhance the leaching rate of zinc. Zinc ferrite has often been found as a major component of zinc residues and electric arc furnace dust. The Waelz process is an existing process for zinc ferrite processing, which requires a temperature of more than about 1200 °C to produce Waelz oxide containing ZnO. Since zinc residues have been deemed as a potential way for the extraction of zinc and other critical metals, it is important to analyze the reaction kinetics in the temperature range of interest. This manuscript discusses the chemical kinetics of zinc ferrite reduction by hydrogen gas. Several researchers studied the reduction of zinc ferrite with CO; however, unlike CO, the use of H2 gas as a reductant allows partial reduction of zinc ferrite even at low-temperature range (400–600 °C). Thermogravimetric analyses (TGA) experiments were performed in the temperature range of 300–700 °C with 10% and 30% H2, and the data obtained was analyzed using the isoconversional method of kinetic analyses. The standard models used for isoconversional kinetic analysis were chosen from literature and experimental data were fitted to determine the controlling mechanism and calculation of kinetic parameters of reduction of zinc ferrite. The rate of reaction was found to be increasing with an increase in temperature and partial pressure of H2 gas. The reaction could be divided into three stages, where reaction interface contraction was found to be the controlling mechanism at the initial stage of reaction. As the reaction proceeds, product layer thickness increases, and thus, diffusion was found to be the controlling mechanism. Roasting products obtained from TGA experiments were also characterized using a scanning electron microscope (SEM) to verify critical morphological details.

Jul 26, 2022

By Kwame Awuah-Ofei, Sisi Que, Shaochun Yuan, Yumin Wang, Ziwei Ding

This research sought to facilitate improved stakeholder analysis in mining by providing further insights into the preferences of local community members using discrete choice theory. While recent research has demonstrated the usefulness of discrete choice theory in mining stakeholder analysis, no previous work has examined which discrete choice model (DCM) is most suitable. This paper provides a research note on a case study in a mining community that was performed to compare three DCMs. After a thorough examination of the benefits and deficiencies of all models, this study concludes that the conditional logit model stratified by questions is the most useful DCM for mining stakeholder analysis. The recommendation is based on the usefulness and accuracy (ability to match the survey data) of this model.

Jul 25, 2022

By Ihsan Berk Tulu, Haochen Zhao, Deniz Tuncay

This paper proposes a new method to estimate the percentage of load carried by the gob in underground coal mines using a new parameter that introduces the site-specific overburden geology. The new parameter was defined as the total strong layer thickness (tstr) that represents the strength and stiffness of the overburden with a single value. Twelve field measurement case studies from 11 different U.S. longwall mines with different overburden geologies were used to develop the new methodology. 2D numerical models of these case studies (and additional parametric runs with different panel widths) were verified against field measurements such as surface subsidence and stress. Statistical analyses using the model results were conducted for a loading model with the new tstr parameter as one of the variables. The new methodology was found to have a coefficient of determination (R2) of 85% when compared to the field measurements and the parametric models. The method was then tested for practical implementation for pillar design. The percentages of load carried by the gob as estimated by the new method were implemented into the LaModel program, that is commonly used in the coal industry. The results obtained from LaModel were compared to the available field stress measurements, and the new method implemented into LaModel was found to give successful results.

Jul 18, 2022

By Alen Shibu Joseph, Arvind Rajnarayan Singh, Mudila Dhanunjaya Rao, Kamalesh K. Singh

In this article, the cementation of major impurities from zinc sulphate leach solution by the addition of zinc dust was studied by considering different parameters including time, mesh size, and percentage of excess zinc dust. The output obtained from various experiments was utilized for the design of experiments. A multi-level categorical factorial design with a quadratic model was employed during this study. Results were predicted to minimize the concentration of impurity metals in the solution by altering the parameters. Furthermore, these predicted results were validated by performing another experiment. Successfully, it showed that the predicted and experimental data values were close to each other. The predicted optimized values were 40 min, 100% excess zinc dust, and 300 mesh size for copper; 42 min, 100% excess zinc dust, and 300 mesh size for cobalt; 37 min, 100% excess zinc dust, and 300 mesh size for cadmium; and 34 min, 100% excess zinc dust, and 300 mesh size zinc dust for nickel. At these optimized values, the experimental results showed 99.99%, 55.7%, 99.6%, and 76.6% cementation efficiencies for copper, cobalt, cadmium, and nickel respectively. The statistical design of experiments for the effective cementation of impurities corroborates the economic feasibility of optimizing parameters for the proposed process.

Jul 18, 2022

By Kanhaiya Mishra, Phanil. K. Mandal, S. K. Behera, P. S. Paul, Prashant Singh, C. N. Ghosh

The techno-economic and social benefits of cemented paste backfill (CPB) resulted in its wide acceptance by the mining industry. The Ordinary Portland Cement (OPC) remains the key binder but to diminish its economical constraints, suitability of alternate binders has been examined worldwide. The present study aimed to investigate the effect of partial replacement of OPC with fly ash on the CPB’s strength and to determine the most optimal mix to achieve the required strength (1 MPa at 28 days of curing) at the most cost-effective way using the Bayesian network (BN). The CPB mixes were prepared at 72 wt.% solid concentration with mill tailings (87–91%), OPC (6–13%), and fly ash (0–4%), and instantly after mixing, fresh (slump, bleeding, density) CPB properties were measured. The strength was tested at 7, 14, 28, and 56 days of curing and initially analysed through traditional model. The traditional models follow the aleatory principle and are considered not appropriate for geotechnical engineering. Hence, the BN model was developed and tested. The reliability of two classifiers in learning model structure was compared which gives Naïve Bayes as the highest reliable tool. The CPB’s strength is most sensitive to the OPC content. The most consistent mix(s) is mill tailings: 87–88%, OPC: 9–11%, fly ash: 1–4%. Adding fly ash at 89–91wt% mill tailings possesses high failure probability of the CPB. The collinearity test indicates that the fines percentage and chemical composition of CPB’s ingredients are highly correlated with its slump, bleeding, and strength development.

Jul 14, 2022