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By S. K. Samal, B. Mishra, M. K. Mohanty, S. C. Mishra

Steelmaking industries consume the majority of chromium and manganese ferroalloys to impart several properties in steel and also for other purposes. The quality of ore governs the process kinetics as well as the process economy of the ferroalloy industry. The present study demonstrates the thermal transformation behavior of chromite and manganese ores with varying compositions. Simultaneous thermal analysis (DTA/TG) is employed for such ore samples where the transformation of mineral phases is correlated with the thermogram characteristics and quantified. Phase, microstructure, and compositional analysis results of individual ores corroborated with thermal analysis are in good agreement. Chromite samples are ferruginous with goethite and gibbsite contents, whereas manganese ores vary in composition and also exhibit multiple and/or overlapping transformations.

Jan 21, 2021

By Göksel Hızlı, Selim Ertürk, Ayşegül Bilen, Raşit Sezer, Cüneyt Arslan

The carbothermic reduction of celestite is the first step in producing many strontium products. The way materials move in the rotary kiln has an essential effect on the carbothermic reduction efficiency as well as the temperature. In this study, the reduction of celestite ore and excess carbon blend in a laboratory-scale rotary kiln was investigated. In the experiments carried out at three different temperatures, the rotational speed and slope of the furnace tube were altered, and their effects on the reaction efficiency were examined. The leachability of the reduced powders and the content of the unburned coke indicated the optimal parameters for the reaction.When the speed was increased to 10 rpm, the powders weremoremobile in the stack and could react more easily with the furnace atmosphere. According to the results, celestite can be reduced by carbon at temperatures of 1000–1200 °C, at rates of between 5% and 75%. The maximumreaction yield (75%) was obtained with a slope of 2° and a rotational speed of 6 rpm at 1100 °C.

May 7, 2020

By Jianping Zuo, Chunlei Zhang, Yong Zhang, Shouyang Gao

To study the fracture evolution of overlying strata for ascending mining in a short-distance coal seam group, a two-dimensional physical simulation model was designed based on a specific geological condition. The fracture development zone was divided into the compaction zone and active zone by monitoring and analyzing the macro fracture evolution of the surrounding rock mass during the excavation of multiple coal seams. The secondary fracture development process of the overlying strata was demonstrated with a physical model. The quantity, length, and inclination of the fracture were calculated with MATLAB software, and the results were verified by geological radar. The total number of fractures between two coal seams increased with a “parabola” shape during the excavation of the lower coal seam, the crack angle was mainly vertical and horizontal, and the number of horizontal cracks first increased and subsequently decreased; the excavation of the upper coal seam caused the secondary fracture development process of the overlying strata, and the relief range and its extent increased. The mining-induced cracks from the lower and upper coal seams connected with each other, especially the permanent vertical fracture in the cutting room side and face side. Finally, the three-dimensional gas fissure was formed.

Nov 24, 2020

By Mahmut Altiner

In the present study, the use of horse residue as an alternative reducing agent in the roasting of a low-grade goethite ore containing 17.60% Fe was investigated. Additional roasting experiments were carried out with corn starch and without reducing agent for comparison. Each roasted product was characterized using X-ray diffraction (XRD) and magnetic hysteresis (MH) loops analyses. The optimum roasting conditions (roasting temperature [400, 500, and 600 °C], reducing agent/ore ratio [0.04, 0.08, and 0.12], and roasting time [10, 20, and 30 min]) were investigated based on the Taguchi approach. The magnetic susceptibilities of the roasted sample with the addition of reducing agents were higher compared to that of the roasted sample in the absence of reducing agent. Experimental findings indicate that the horse residue can be used as the reducing agent. Finally, an iron ore concentrate assaying a Fe grade of 62.12% with a recovery of 56.93% was prepared using wet magnetic separation at a magnetic intensity of 0.5 T from the ore roasted under the following roasting conditions: roasting temperature of 500 °C, reducing agent/ sample ratio of 0.08, and roasting time of 30 min.

Jun 3, 2020

By SANDEEP KUMAR JENA

This review work reports the recovery of potassiumfromdifferent rocks and mineral sources. The global demand for potassiumis rising consistently due to the growth of agricultural production. A major portion of the world potassium production is consumed in making of fertiliser; however, other uses include those in pharmaceutical, glass, ceramic, food and detergent industries. The availability of soluble potash minerals (sylvite, kainite and carnallite) in different countries like Canada, USA, Israel and Russia makes them as major potash producers, whereas agricultural-based countries like Liberia, Somalia, Central African Republic, Thailand, Indonesia and Malaysia including India meet their potassium requirement through import only. On the contrary, the availability of huge potassium-bearing rocks/minerals (like nepheline syenite, feldspar, mica, glauconitic sandstone) in these countries containing around 4–17% K2O would be a prospective for commercial production of potassium. The potassium recovery from minerals/rocks is very complicated due to the uniform distribution of potassium throughout the crystal structure. Different physico-chemical separation methods like bioleaching, chemical leaching, flotation and roast leaching have been discussed for the successful recovery of potash values from these rocks/minerals. However, the recovery of potassium from hugely available seawater using the chemical precipitation, solvent extraction,membrane separation and ionic exchangemethods is not cost-effective due to the low concentration of potassium.

Aug 31, 2020

By Ihsan Berk Tulu, Mark Alexander Van Dyke, Deniz Tuncay, Ted M. Klemetti

Bleeder entries are critically important to longwall mining for the moving of supplies, personnel, and the dilution of mine air contaminants. By design, these entries must stay open for many years for ventilation. Standing supports in moderate cover bleeder entries were observed, numerically modeled, and instrumented by researchers at the National Institute for Occupational Safety and Health (NIOSH). The measurements of the installed borehole pressure cells (BPCs), standing support load cells and convergence meters, and roof extensometers are presented in this paper in addition to the numerical modeling results and visual observations made by the NIOSH researchers in the bleeder entries. The results include the effects of multiple panels being extracted in close proximity to the instrumented site as well as over one and a half years of aging. As expected, standing supports closer to the longwall gob showed the greatest load and convergence. The roof sag appeared generally independent of the proximity to the longwall gob. The BPC readings were driven by both the proximity to the gob and the depth into the pillar. The results of this study demonstrated that the entry roof can respond independently of the pillar and standing support loading. In addition, the rear abutment stress experienced by this bleeder entry design was minimal. The closer the mine development, pillar, or supports are to the gob, the greater the applied load due to rear abutment stress.

Jan 7, 2021

By MOHAMED WAEL, ANASTASIA GOEVA, ABDULAZIZ TAWFEEQI, IHTISHAM TARIQ, S. M. ZAKIR HOSSAIN, NIAZ ALI KHAN, MUHAMMAD FAISAL IRFAN

Carbon capture and storage (CCS) is an attractive area of research in such fields as CO2 mineral carbonation, global warming and sustainable energy systems. In this study, carbonation efficiency for aqueous mineral carbonation (MC) was achieved through two steps,which include leaching of calciumfrom cement kiln dust (CKD) followed by the reaction of pure CO2 with the calcium hydroxide precipitates formed by the hydroxylation using NaOH. Response surface methodology (RSM) with a Box-Behnken design (BBD) was applied to optimize the calciumleaching yield,while the carbonation efficiency from CKD was assessed using RSMwith central composite design (CCD). Optimization of calcium leaching is highly important, as it is a rate-limiting reaction step in MC and also influences and enhances carbonation efficiency. Different parameters including acid concentration (HNO3), leaching temperature, leaching time, and dose of CKD sample were considered in order to optimize the maximum yield of Ca leaching from the CKD sample. In addition, different CO2 flow rates and temperatures were used as parameters for optimizing carbonation efficiency. Two quadratic regression models were developed for each process, i.e. calciumleaching and carbonation. For calcium leaching, a maximum of 98.55% calcium was extracted under the optimal set of acid concentration 4.13 M, 90 °C, 28 min leaching time, and 13.8 g of CKD sample. For carbonation, the maximum carbonation efficiency of 89.2% was achieved for a CO2 flow rate of 1163 cm3/min at 90 °C. Calcium leaching results indicate that the leaching yield was significantly affected by all the input parameters except leaching time. For carbonation, both factors affected the carbonation efficiency, with the effect temperature shown to be greater than that of the CO2 flow rate. Additionally, the predicted results agreed well with the experimental values for both calcium leaching and carbonation processes, with errors of less than 1% and 5%, respectively.

Jun 5, 2020

By Serdar Aktaş, Burcu Nilgün Çetiner

According to critical statistical studies, antimony is one of the rarest elements in the world, and global resources could be exhausted by 2050. In light of these observations, its extraction will be costly due to poor-quality ore, deep mining, remote locations, and high energy consumption. In the present study, an alkaline leaching process was carried out on stibnite concentrate to evaluate the effect of reaction parameters on the percentage of antimony extraction. The leaching efficiencies of different sulfur and hydroxide sources were studied and compared to one another to create a better understanding of the reaction process. Kinetic models were investigated to identify the reaction pathway and calculate the activation energy. The activation energy of the stibnite dissolution was assessed as 19.13 kJ/mol using a two-dimensional diffusion-reaction model. The value of activation energy indicates the quantity of energy necessary for a reaction to proceed. As expected, potassium hydroxide leaching was significantly more successful than was sodium hydroxide; however, in terms of economics, the use of sodium hydroxide was found to be more cost-efficient. Interestingly, this finding indicated that caustic leaching is still the most effective method for stibnite extraction.

Jul 23, 2020

By Ana Chiquini, Clayton V. Deutsch

The most common approach used in the mining industry for mineral resources modeling is to estimate the grades using ordinary kriging and report the recoverable resources based on this deterministic estimated model. Mineral resources calculated with kriging are a smooth representation of the actual distribution of grades and do not provide an assessment of uncertainty. Unlike kriging, simulation reproduces the variability of the grades in the mineral deposit and provides an assessment of uncertainty. Reporting mineral resources directly on high-resolution simulation results would assume perfect knowledge of the grade at the time of mining and selectivity at the scale of the data. There will always be uncertainty left at the time of mining, so assuming perfect knowledge of the grade in the future is incorrect. There are two concerns when geostatistical simulation is used for resources modeling: the information and the mining selectivity effects. A new framework for resource estimation is proposed with two separate modules to address those concerns. The information effect is accounted for by anticipating the additional production data that will be available at the time mining to guide the destination for the mined material. The mining selectivity effect is addressed by mimicking the grade control procedure to get mineable dig limits at a chosen selectivity, represented by a minimum mineable unit size. In addition to a prediction of recoverable resources that will be closer to the material mined in the future, the framework proposed provides an assessment of local and global uncertainty for risk management.

May 26, 2020

By Mingfei He, Jianhua Chen, Yingchao Liu, Yuqiong Li

Pyrite is one of the most common sulfide minerals on earth, which is usually grown with chalcopyrite and other sulfide minerals. In flotation practice, pyrite from different mines or different sections in a same mine may have different flotation behaviors. This is because the pyrite crystal contains lattice defect, including ionic vacancy and lattice impurity. The present work investigates the effects of three typical 3d transition metal (Co, Ni, and Fe) on the adsorption of CH3OCS2 −, OH−, and CN− on pyrite surface by density functional theory (DFT) calculations. Calculated results show that Co impurity reduces the adsorption energies of CH3OCS2 − and CN− on the surface of pyrite, while Ni and Cu impurities significantly increase the adsorption energies of CH3OCS2 − and CN− on the surface of pyrite. Co impurity has small influence on the adsorption of OH−, but Ni and Cu impurities significantly increase the adsorption energies. Calculations on Mulliken charge population of Co2+, Ni2+, and Cu2+ indicate that the Mulliken charges of Co2+, Ni2+, and Cu2+ after OH− adsorption are more than those after CN− adsorption. This suggests that the ionic property of the M-OH- coordination bond is greater than that of M-CN- coordination bond, while covalent bonding of M-CN- coordination bond is greater than that of M-OH- coordination bond. The adsorption results are discussed based on coordination field theory (CFT).

Oct 6, 2020

By Jafar Safarian, Leiv Kolbeinsen, Stian Seim, Hossein Salehi

The present work aims to investigate the link between the oxidation and reduction of a weathered ilmenite concentrate in terms of phase transitions, microstructural changes, and element distribution. An ilmenite concentrate sample was pelletized and fired at 1000 °C in air, and as a result, the pellets were oxidized. The oxidized pellets were reduced by hydrogen gas at 1000 °C, which yielded almost complete metallization of the iron content of the pellets. The ore and the pellets were characterized in each step by XRD and SEM techniques, and distribution of elements and phases were investigated. Ilmenite, pseudorutile, and rutile were the main phases detected in the ilmenite concentrate sample, and depending on the weathering degree of the particles, different fractions of the phases were identified in their microstructure. It was found that irregular rutile grains dispersed in a pseudobrookite matrix is the morphology of the oxidized ilmenite phase. However, increasing microcracks and porosities were the only microstructural changes in the pseudorutile phase after oxidation in air. Studying the specific types of the ore particles and their oxidized and reduced forms indicated that the phase distribution in the ilmenite ore particles dictates the phase distribution in the oxidized and reduced ones. Results show that the morphology of the reduced particles includes a titanium (III) oxide matrix in which reduced iron globules are dispersed.

Feb 8, 2021

By Brenton Fletcher, Yongjun Peng, Wonder Chimonyo

As a cheap, renewable and non-toxic material, starch can contribute to the sustainability of the flotation process, albeit in a minor way as one type of reagent in systems involving materials with far greater impact. But the physical and chemical versatility of starch can help address another issue, namely, that of processing complex ores with decreasing grades of valuable minerals and increasing mixtures of gangue. This paper compares the results of two lab scale flotation studies where starches (native wheat starch (NWS), dextrin and two oxidised wheat starches) were used to depress two common gangue minerals, copper-activated pyrite and carbon (graphite), over a range of dosages. The oxidised starch with the larger molecular weight structures depressed copper-activated pyrite best, and the oxidised starch with lower molecular weight structures was better at depressing graphite. In both cases, the oxidised starches allowed greater recovery of chalcopyrite, pointing to selectivity potential. The extent to which the carbonyl and carboxyl moieties of the oxidised starches contribute to depressant performance is difficult to quantify, but it should not be discounted. Importantly, the results demonstrate relatively simple modifications of native starch by oxidation can yield structures suitable for depressing gangue minerals with diverse surface properties. The challenge remaining for greater application of modified starch depressants is being able to replicate the desired structures at scale in cold-water-soluble form.

Jan 18, 2021

By Sebastian Avalos, Julian M. Ortiz, Willy Kracht

Semi-autogenous grinding mills play a critical role in the processing stage of many mining operations. They are also one of the most intensive energy consumers of the entire process. Current forecasting techniques of energy consumption base their inferences on feeding ore mineralogical features, SAG dimensions, and operational variables. Experts recognize their capabilities to provide adequate guidelines but also their lack of accuracy when real-time forecasting is desired. As an alternative, we propose the use of real-time operational variables (feed tonnage, bearing pressure, and spindle speed) to forecast the upcoming energy consumption via machine learning and deep learning techniques. Several predictive methods were studied: polynomial regression, k-nearest neighbor, support vector machine, multilayer perceptron, long short-term memory, and gated recurrent units. A step-by-step workflow on how to deal with real datasets, and how to find optimum models and final model selection is presented. In particular, recurrent neural networks achieved the best forecasting metrics in the energy consumption prediction task. The workflow has the potential of being extended to any other temporal and multivariate mineral processing datasets.

Jun 16, 2020

By FELIPE SÁNCHEZ, PHILIPP HARTLIEB

Innovation plays a critical role in the mining industry as a tool to improve the efficiency of its processes, to reduce costs, but also to meet the increasing social and environmental concerns among communities and authorities. Technological progress has also been crucial to allow the exploitation of new deposits in more complex scenarios: lower ore grades, extreme weather conditions, deeper deposits, harder rock mass, and high-stress environments. This paper discusses the importance of innovation for the mining industry and describes the mechanisms by which it is carried out. It includes a review of the drivers and actors involved and current trends. The digital transformation process that the industry is going through is analyzed, along with other relevant trends that are likely to shape the mining of the future. Additionally, a case study is presented to illustrate the technical and economic implications of developing a disruptive innovation project.

Jul 23, 2020

By Timothy J. Orr, Robin J. Burgess-Limerick, Jennica L. Bellanca, MARGARET E. RYAN

Powered haulage continues to be a large safety concern for the mining industry, accounting for approximately 50%of the mining fatal accidents every year. Among these fatal accidents, haul-truck-related accidents are the most common, with 6 of 28 and 6 of 27 fatal accidents occurring in 2017 and 2018, respectively. To better understand why these accidents continue to occur and what can be done to prevent them, researchers reviewed the 91 haul-truck-related fatal accidents that occurred in the USA from 2005 to 2018 and performed bow-tie analyses using the final reports published by the Mine Safety and Health Administration. The analyses explore the context of the accidents with a focus on the initiating event, event outcome, hazards present, and possible preventative and mitigative controls. Overall, the vast majority of the accidents resulted in a haul truck colliding with the environment, and the majority of these events were initiated by loss of situational awareness or loss of control. The majority of the hazards were related to design and organizational controls. The results of this study suggest a need to investigate operator decision-making and organizational controls and to focus on improving design and operation controls such as mine design and operational procedures.

Feb 22, 2021

By Mei Long, Tawum Juvert Mbah, Jianhua Zhang, Haiwang Ye

There have been many improvements and advancements in the application of neural networks in the mining industry. In this study, two advanced deep learning neural networks called recurrent neural network (RNN) and autoregressive integrated moving average (ARIMA) were implemented in the simulation and prediction of limestone price variation. The RNN uses long shortterm memory layers (LSTM), dropout regularization, activation functions, mean square error (MSE), and the Adam optimizer to simulate the predictions. The LSTM stores previous data over time and uses it in simulating future prices based on defined parameters and algorithms. The ARIMA model is a statistical method that captures different time series based on the level, trend, and seasonality of the data. The auto ARIMA function searches for the best parameters that fit the model. Different layers and parameters are added to the model to simulate the price prediction. The performance of both network models is remarkable in terms of trend variability and factors affecting limestone price. The ARIMA model has an accuracy of 95.7% while RNN has an accuracy of 91.8%. This shows that the ARIMA model outperforms the RNN model. In addition, the time required to train the ARIMA is than that of the RNN. Predicting limestone prices may help both investors and industries in making economical and technical decisions, for example, when to invest, buy, sell, increase, and decrease production.

Jan 6, 2021

By Andrea Brickey, JUDITH BUABA, RICHARD AMOAKO

The global mining industry has recorded significant declines in accident and injury rates attributed to the advancement in technology, increased enforcement, and safety consciousness. A goal of the mining industry is to achieve zero injury and occupational illness on all mine sites, prompting increased research into ways to further reduce mine accidents. A machine learning technique known as multiclass logistic regression is applied on a 10-year injury dataset from the Mine Safety and Health Administration (MSHA) to determine a miner’s susceptibility to a class of injury and to help identify significant risk factors associated with different classes of injury. The data is aggregated based on injury classification to provide statistically relevant results. The analysis identifies specific risk factors that influence a mine worker’s susceptibility to a given class of injury, i.e., non-fatal with no days lost or restricted activity, non-fatal with days lost and/or days of restricted work activity, and fatal and total permanent or partial permanent disability. These factors include miner’s age, mine type (coal vs. non-coal), experience on the current job (years), shift start time, employment type (operator vs. contractor), mining district, and type of accident. The results of the analysis indicate that a miner’s experience on the job, i.e., the number of years worked in a current job, is a significant risk to injury occurrence, even for those with decades of total mining experience. We further show the differences and similarities between the surface and underground mine incidents.

Nov 3, 2020

By Diler Katircioglu-Bayel

This manuscript aimed to examine the impact of operating parameters on the wet grinding of talc in a vertical-type stirred media mill. Within the scope of the research, the effects of operating parameters including media filling ratio, solid mass fraction, grinding media size, and grinding time were studied. The findings were assessed based on the product particle size (d50, d10), surface area (Sw), and energy consumption (Em). As a result of the present research, the following optimum grinding test conditions were determined: 65% media filling ratio, 40% solid mass fraction, 1 mm grinding media size, and 120 min grinding time. After determining the optimum grinding conditions, the Box–Behnken statistical design was used to determine the effect of parameter interactions on the d50 size. The media filling ratio was found to significantly affect the decrease in d50 compared to the other two parameters. Furthermore, the minimum d50 size was also achieved under optimum grinding conditions.

Aug 12, 2020

By İsmail İnce

The existence of water is one of the most effective factors in deterioration of natural building stones. In the process of deterioration, capillary water absorption is the most significant procedure of water penetration into the building stones. Pyroclastic rocks have been widely utilized as building stone especially in historical buildings and monuments since ancient times in the Central Anatolia in Turkey. Nowadays, this type of rocks is used in the restoration of historical buildings as well as in the construction of modern buildings. Pyroclastic rocks are highly susceptible to deterioration process. Capillary rise has a significant influence on water penetration into building stones. Therefore, it is quite important to identify the factors affecting the values of capillarity, capillary rising speed, and capillary rise that define capillary water absorption in these rocks. To this end, pyroclastic rock samples in different textures were compiled from the Cappadocia region, in Central Anatolia. First, petrographic, mineralogical, geochemical, physical, and pore diameter distribution properties of the samples were determined in the laboratory. Then, capillarity values with capillary rise and capillary rise speeds dependent on time were established. Based on the data obtained, correlation coefficients between matrix percentage and capillary water absorption rate and capillary rise values of pyroclastic rocks were calculated and found to be as 0.850 and 0.891, respectively. Thus, the article proposes a new empirical equation to practically calculate the capillary rise value depending on the matrix percentage (MP) and median pore diameter (MPD) values.

Nov 30, 2020

By K. V. Raj, R. Jacksha

Conveyor systems persist in being a source of injuries and fatalities in the mining industry. To reduce these incidents, better methods are needed to enhance the monitoring of probable hazards and improve situational awareness during the normal operation and maintenance of conveyor systems. To address these issues, researchers from the National Institute for Occupational Safety and Health (NIOSH) continue to investigate emerging technologies that show the potential to improve miner safety around conveyors. This paper presents a feasibility assessment by NIOSH researchers of a fully integrated, commercially available wireless Internet of Things (IoT) system to improve situational awareness around conveyor systems. Included are discussions of a full-scale laboratory test bed that was designed to simulate a working conveyor system as well as the challenges and successes of integrating the IoT system with the test bed.

Oct 6, 2020