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By John Thella, Edward McNew, Christina Thella, Mends Emmanuel, Pengbo Chu

Ore sorting is an emerging technology in mineral processing that can produce a significant impact on the total mining and processing economics. The technology is capable of preconcentrating an ore based on differences in the mineralogical characteristics, which can include color, brightness, transparency, size, shape, density or near-infrared response. The current practice of conducting an ore sorting test typically requires large amounts of materials to be sent to a commercial testing facility, which is expensive and time-consuming. Here, we present a novel method to simulate commercial ore sorting on a laboratory scale using a rare earth ore.

Jan 1, 2025

By Alper Kirmaci, Taghi Sherizadeh, Gunnar Wurst, Paul Brooks, Dogukan Guner, Samuel Nowak, Mina Esmaeelpour, Kutay Karadeniz

As mines continue to deepen and become more expansive, active monitoring of larger volumes of rock mass will become more critical to calibrate numerical simulations and to ensure the safety of underground workers. Monitoring larger volumes of rock mass requires low-cost sensors that are simple in construction and installation. In this study, a novel hybrid optical fiber cable (HOFC) designed for use in distributed optical fiber sensing (DOFS) via grouted boreholes was deployed to monitor a bulk mining operation in an underground metal mine. The HOFC was successfully used to monitor approximately 2.7 × 10 m3 of rock mass above excavations surrounding a pillar removal area in which six large pillars were removed simultaneously. A total of six measurement boreholes (maximum depth of 22 m) were used to measure strain along the optical fiber during the pillar removal operation using the HOFC, allowing for 70 individual strain measurement points, which were constructed for under one U.S. dollar each. Monitoring of the excavation area took place over a 44-day period after pillar removal. Extensional strains were noted in the areas closest to the removed pillars, while areas of compression were noted directly above the remaining pillar in the area. The results of the case study demonstrate that a low-cost optical fiber strain sensing network can be rapidly installed in a large excavation area and can provide highly sensitive strain measurements in a manner that would be cost prohibitive using other methods.

Oct 1, 2024

By Brendan Donnelly, Jung-Hoon Sul, Lasitha Piyathilaka, Sanghyun Jeong, Benjamin Probyn

The chains of armored face conveyor (AFCs) are constantly in contact with water and wet coal, which results in a significant proportion of unplanned downtime experienced on longwall equipment due to corrosion. While reverse osmosis (RO) is one of the most prevalent water treatment methods for reducing salinity and dissolved solids in coal mining, its impact on the corrosion of the AFC chains has not been well studied. This work studies the direct effects of RO water on the corrosion of AFC chains. Immersion tests followed by surface micromorphology analysis and corrosion indices indicate that the RO water increased the corrosion rate of the AFC chains due to the reduced tendency of preventive films on the chains.

May 1, 2024

By Elif Emil-Kaya, Bernd Friedrich, Merve Papakci

Samarium (Sm), one of the rare earth elements (REEs), and cobalt (Co) are used in the production of SmCo permanent magnets, which have excellent temperature stability, corrosion resistance and oxidation resistance. Of the two types of SmCo magnets, one contains a high amount of iron, approximately 15.2 percent. This paper focuses on the recycling of iron (Fe)-bearing SmCo. In this study, an oxidative leaching process with nitric acid was developed to eliminate iron through in situ hydrolysis and to dissolve REEs and Co. The influence of experimental conditions on the formation of an amorphous iron compound through the hydrolysis of Fe3+ in a nitric acid environment was thoroughly examined based on a Taguchi orthogonal array. The optimal parameters for oxidative leaching were determined to be an acid concentration of 3 mol/L, a solid-to-liquid ratio of 1/10, and a process temperature of 60 °C.

Jul 1, 2024

By ERIK CHARRIER, ADITYA JUGANDA, Jürgen Brune, Gregory Bogin, Patrick Maier

Confined explosions are a major risk in underground coal mine operations. Depending on confinement, ignition location and obstacles in the flame path, methane explosions can transition to detonations. This research focuses on explosion experiments in a reactor with diameter of 71 cm and length of 30.5 m, along with developing the corresponding computational fluid dynamics (CFD) model that captures the observed flame behavior. The results show that the 2D and 3D CFD models are able predict the experimental flame front propagation velocity, but the 3D model shows more explicit conformity than the 2D model.

May 1, 2024

By Jaeheon Lee, Junmo Ahn, Jiajia Wu

To reduce the environmental footprint of hydrometallurgical processing of black mass from spent lithium-ion batteries (LIBs), a green leaching system based on glycine and sodium metabisulfite (Gly-SMS) was proposed. The leaching study demonstrated that the highest cobalt and lithium recoveries of 100 percent and 99.8 percent were achieved under optimal conditions. The leaching mechanism revealed that the dissolution of LiCoO2 in the Gly-SMS solution followed the shrinking core model. The apparent activation energies for cobalt and lithium were determined as 48.05 and 41.51 kJ/mol, respectively, indicating a surface chemical reaction controlling mechanism. The leachate was then processed by an acidification- precipitation technique with oxalic acid as the precipitant to remove cobalt. Glycine complexes with metal ions by zwitterionic ligand and recycles in the leaching-precipitation circuit, reducing the reagent cost. Compared to other studies, this leaching system has near-neutral operating conditions and is cost-effective, making it an economically viable alternative for treating cathode materials from spent LIBs.

Dec 1, 2024

By Arif Emre Dursun

The aim of this study is to present hazard classifications of location, type and causes of accidents in the Turkish coal-extracting industry using the analytic hierarchy process (AHP). In this study, fatal mine accidents were analyzed by pairwise comparison and weighting, and the most important hazards were identified by determining the effective main and sub-criteria among location, type and causes of accidents. For this purpose, first-, second- and third-level hazards consisting of location, type and causes of accident were determined by using the data of fatal mine accidents in underground and openpit coal mining in Turkey between 2010 and 2020.

May 1, 2024

By Isabel Barton

This article describes and analyzes the history of research into the origins of the uranium-vanadium(-radium) deposits of the Paradox Basin. For several decades after their discovery in 1881, research was desultory and almost entirely descriptive, fluctuating with demand for vanadium and radium. Systematic geologic descriptions, accumulated between 1910 and 1950, supported rapid progress during a government-backed surge of research in the 1950s, when uranium was the chief commodity of interest. Most of the major theoretical innovations date from this decade, including the use of concepts from solution chemistry to identify the conditions and constrain the processes of deposit formation and alteration. Research from this time was highly influential in geology at large, providing the model for sandstone-hosted uranium deposits worldwide and numerous new minerals and mineral structures. After about 1960, mine production remained high but research dwindled, and most new advances were to the details of the hydrothermal model of ore formation rather than its core concepts. By the end of the 1960s, the deposits were understood to have formed at the mixing interface of an oxidized, metal-bearing water with a reducing fluid of debated origin. Research was desultory over the ensuing decades; the source of the metals and the nature of the chemicals constituting the trap were not clearly established. They remain questions today, as do factors like the relationship between ore mineralization and the geologic history of the basin. (More in the full paper.)

Jan 1, 2025

By Firat Atalay

Estimating the spatial distribution of ore grade is one of the most critical steps to proceed with an investment decision on a deposit. Kriging is the most widely used method to estimate the ore grade, but alternative techniques are being developed. Machine learning algorithms can be used as alternative methods to classical kriging. In this paper, the iron (Fe) grade of a deposit is estimated with the XGBoost algorithm, and the results are compared with kriging estimation results. For the estimations, samples collected from drillholes were used. Due to the different natures of the estimation methods, different steps were taken to perform the estimations. The results show that XGBoost produced higher-range estimates, which is a desired result in ore grade estimation, and the minimum and maximum of the estimates were lower and higher than the kriging estimates, respectively. However, like kriging, the estimation results were smoother than composites, and the variance of the XGBoost estimates was lower than the variance of composites. This means that even though estimation with XGBoost mitigates the smoothing effect, the estimation results suffer from smoothing like kriging.

Dec 1, 2024

By Amy McBrayer, Vladislav Kecojevic, Juan David Valencia Quiceno, Dragan Bogunovic

The mining industry’s commitment to innovation reflects a history of adopting technological advancements to enhance workplace safety, environmental sustainability and vocational training. The objective of this research was to develop an augmented- reality (AR) system for heavy-equipment operators (HEOs) in surface mining. The developed system has the potential to enhance mine safety, training and data-driven decision- making, which presents a significant step toward a more sustainable, effective and technologically driven mining training, contributing to the industry’s evolution and growth. The AR training system leverages Microsoft’s Power Platform and HoloLens 2 capacities to provide operators with detailed and immersive training guides for three mining equipment, including bulldozers, motor graders and haul trucks. AR guides combine speech controls, 3D objects, informative images and explicative videos in the real working conditions to enhance the operator’s learning process. The system has the potential to modify the training structure based on user performance and provides an efficient approach to data collection during training. This project was developed and applied through a case study in a surface mine in the Southern United States.

Feb 1, 2025

By C. Nesbit, N. Duru

During the cyanide leaching process of gold and silver, ores that come from the transition zones which typically con-tains low levels of sulfide may produce one or more of the following reduced sulfur species: sulfide (HS ), polysulfides (Sn ), thiocyanate (SCN ), thiosulfate (S2O3 ), trithionate (S3O6 ), tetrathionate (S4O6 ), pentathionate (S5O6 ) and hexathionate (S6O6 ). The actual speciation of the reduced sulfur species in the circuits will primarily depend on the re-dox potential, pH, cyanide levels and existing sulfur species in recycled process water, as well as the presence of other reac-tive metal species. Development of an accurate analytical method for sul-fur species in cyanide leaching units of gold ores where sul-fur speciation occurs has an important role in explaining the metal recovery deviations. This study presents the speciation of sulfur species and development of an ion chromatography method to analyze the reduced sulfur species thiocyanate, thio-sulfate, trithionate and tetrathionate in cyanide leaching circuits for gold ores. The method developed has resulted in the precise quantification of target sulfur species in leach solutions.

Jun 1, 2024

By Andres Salazar, Carlos Delgado Robles, Richard K. Preece

Minera Escondida, located in the Antofagasta Region of northern Chile, is the world’s largest producer of copper as concentrate and SX-EW cathode. Projects to increase mill and flotation capacity began soon after start-up in 1990 to off-set decreasing copper grade. Subsequent projects had the objective to increase copper production through heap leach and SX-EW production and a second concentrator. The mine footprint concurrently expanded peripherally from the central high-grade enriched core of Escondida and then into the separate Escondida Norte deposit. Early in the mine life, metallurgical forecasting that was based on metallurgical composites of presumed ore types and historical plant production was adequate for operational planning, plant design, and project valuation. This approach became unreliable, however, as the increase in mine footprint was accompanied by an increased variability in key ore body characteristics such as hardness, copper-iron sulfide mineralogy, and sulfide liberation textures that were not reflected in the geological criteria used for ore type designation. The project study teams turned to small-scale physical and chemical tests to better characterize the spatial distribution of these key ore characteristics. Programs associated with capital growth projects were carried out through the mid-2000s to sample and construct a three-dimensional spatial model of hardness, copper sulfide mineralogy, and rougher flotation recovery from tests on 15-m drill core composites. Mathematical models were developed from the respective ore characteristic data to calculate throughput, flotation recovery, and concentrate copper grade. The spatial models were integrated with the concurrent mineral resource block model using standard geostatistical methods and the metallurgical process calculations were applied to the block estimates. The geometallurgical model, originally constructed on a project basis, is now managed by a dedicated team reporting to the manager of Geosciences & Resources Definition in the Escondida organization. The model has evolved with increasing complexity of the mine and processing plants and currently includes seven forecasting areas for three concentrators and four areas for two leach plants. Metallurgical forecasts of mill throughput, final flotation recovery, and concentrate copper grade still have the highest relevance to mine planning and optimization. Sample preparation, test procedures, and quality control methods are summarized for the ore characteristic tests important to these forecasts. Analytical results from recent annual sampling programs are presented for the hardness indices, rougher flotation recovery, and partial extraction copper analyses. Geostatistical analysis of the SAG mill hardness index is summarized as an example for the spatial estimation process. Mathematic models are presented for throughput (based on hardness indices), final flotation recovery (based on rougher recovery and plant calibration studies), and concentrate copper grade (based on sulfide mineralogy and empirical pyrite rejection studies).

Aug 31, 2023

By Ping Li, Baokun Zhou, Lei Yang, Changfeng Li, Erhui Zhang

A uniaxial compression experiment was conducted on standard sandstone specimens to explore the sandstone’s mutation characteristics and early warning interval during deformation and failure. Meanwhile, acoustic emission (AE) and digital image correlation (DIC) techniques were introduced to realize multi-field analysis and cross-validation from the stress field, deformation field, and elastic wave field. The mutation characteristics of rock failure were investigated based on the cusp catastrophe theory. The results showed four mutation points in the destabilization process of sandstone: compressional density, yielding, destruction, and residual retention. As an internal activity characteristic of the sandstone failure process, AE directly reflected the dynamic failure process of sandstone. The stress variation was closely related to the evolution of AE characteristics. Sandstone loading failure was a process of the mutations of releasable elastic strain energy, dissipative energy, and releasable elastic strain energy. The mutation of dissipative energy was used as the starting mark of the sandstone warning state, and the second mutation of releasable elastic strain energy was used as the end mark of the sandstone warning state. Besides, the warning range corresponded to the loading time of 178 to 208 s. Finally, the sandstone instability warning interval was re-determined from deformation field evolution characteristics in the sandstone damage process, with a loading time of 180–204 s. This was consistent with the warning interval specified using the cusp catastrophe theory. The combination of AE, DIC, and cusp catastrophe theory revealed the mutation characteristics and early warning interval of sandstone failure. Hence, the results provide significant importance to predicting rock failure.

Aug 23, 2023

By Mustafa Kumral, Yu Cheng Yang, Zhixuan Shao, Young Bin Moon

Since the discoveries of favorable deposits are becoming increasingly difficult, mining operations shift to lower grade and deeper deposits. The viability of these operations is sensitive to many factors, such as commodity prices and operating costs. Given that a mining corporation has no power to set prices, the focus is directed on minimizing the operating costs. Underground mining operations require a network infrastructure, including shaft, ramps, declines, levels, cross-cuts, raises, winzes, and adit. The design of this network is a costly process. As such, it has a significant potential to reduce development and haulage costs. Furthermore, network design is a continuous process along with development, production, and maintenance throughout mine life. Under the constraints of the turning radius, the gradient, and the obstacle avoidance for haulage network of underground mines, this paper first demonstrates network design and optimization approaches using Dubins path combined with the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithm. A threshold-based model is developed, providing viable solutions to the network design when the number of declines is high. Furthermore, a three-dimensional Rapid-exploring Random Tree (RRT) algorithm combined with Dubins path is employed as a heuristic solver for obstacle avoidance purposes in the network. Various case studies are conducted to show the applicability of the proposed methods.

May 24, 2023

By Konstantinos Komnitsas, Evangelos Petrakis, Emmanouil Varouchakis

During the modeling of grinding systems, population balance modeling (PBM) which considers a constant breakage rate has been widely used over the past years. However, in some cases, PBM exhibited some limitations, and time-dependent approaches have been developed. Recently, a non-linear framework which considers the traditional linear theory of the PBM as a partial case was introduced, thus allowing the estimation of product particle size distribution in relation to grinding time or the specific energy input to the mill. In the proposed model the simplified form of the fundamental batch grinding equation was transformed into the well-known Rosin–Rammler (RR) distribution. Besides, the adaptability and reliability of the prediction model are among others dependent upon the operating conditions of the mill and the adjustment of the RR distribution to the experimental data. In this study, a series of grinding tests were performed using marble as test material, and the adaptability of the non-linear model was investigated using three loads of single size media, i.e., 40, 25.4, and 12.7 mm. The results indicate that the proposed model enables a more accurate analysis of grinding, compared to PBM, for different operating conditions.

Jun 24, 2023

By Amar Prakash, V. M. S. R. Murthy, VIVEK KUMAR HIMANSHU, Sufal Mehrotra, Ashish Kumar Vishwakarma

Raises are vertical or inclined openings made to connect two levels of an underground metalliferous mine. They are developed using drilling and blasting-based technique or by mechanical means. Raise boring machines (RBM) have evolved in recent years, which provide quicker and safer raise excavation. The penetration rate using RBM has influenced applied thrust. The required thrust to enhance penetration rate with optimal use of energy would be different under varying geological and geotechnical conditions. In this study, the influence of applied thrust on penetration rate using RBM has been investigated. The investigation has been made for two different rock types, amphibolite (AMP) and garnet-biotite-sillimanite-gneiss (GBSG). The numerical simulation model was developed for this purpose using Ansys-Explicit Dynamics. The induced tensile stress under different conditions of applied thrust has been analysed in the calibrated numerical model. The model output shows the power trend between the parameters. The experimental data on penetration rate was also collected along with the respective operational parameters. A statistical analysis has been carried out for the gathered data. The analysis of data also shows a power trend between thrust per cutter and penetration rate in both rock types and hence validates the numerical simulation-based output. Based on the outputs of the numerical simulation and empirical study of the experimental data, the optimum thrust per cutter for excavation in both rock types is in the range of 12–14 tons. The approach used in this study can be helpful for predicting the optimal operational parameters of raise boring machines under different geological/geotechnical conditions.

May 29, 2023

By Ankit Jha, Javad Sattarvand, Aaron Young

Blockchains are 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 for 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 manuscript. This paper 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 spare parts, contract management, regulatory compliance, and cyber security.

Nov 23, 2023

By Jian Wang, Kun Li, Hao Wu, Juan Nan

In this paper, in order to solve the problems of low accuracy and slow speed of fire flame recognition, an extreme learning machine (ELM) method based on improved Harris hawks optimization (IHHO) is proposed for fire flame recognition. A novel Harris hawks optimization (HHO) is used to solve the problem of parameter selection of ELM. In order to solve the problem that the original HHO is prone to fall into local optimum, firstly circle mapping is used to initialize the population to solve the problem of uneven distribution and small range of the initial population. Then the formula of escaping energy of HHO is modified to make the population have a large range in the middle and late iterations while gradually decreasing in the whole iteration process. Thus, the exploitation stage in HHO is improved to make the search range smaller near the optimal solution to accelerate the convergence process. Finally, at the end of each iteration, a certain number of individuals are selected to perform Gaussian and Cauchy hybrid mutation to prevent the IHHO from falling into local optimization. Through three groups of experiments, the effectiveness of the proposed IHHO and IHHO-ELM is verified. In experiment 1, the convergence performance of IHHO is significantly better than that of the other remaining algorithms in the test results of six benchmark functions. In experiments 2 and 3 of real fire flame recognition case, IHHO-ELM outperforms other remaining algorithms on the whole and has significant advantages in some indexes.

Jan 17, 2023

By Shenghua Yin, Xun Chen, Rongfu Yan, Zepeng Yan, Wei Chen

The application of cemented paste backfill (CPB) with alkali-activated slag and phosphogypsum (ASP) can contribute to the sustainable development of the mining industry. The effects of PG content, NaOH content, solid content, and waste rock-rod milling sand (W/R) ratio on workability, unconfined compressive strength (UCS), and setting time of ASP-CPB were investigated in this paper. The results showed that the workability of ASP-CPB decreased with PG content and NaOH content. Compared to OPC-CPB, ASP-CPB exhibited better workability and higher long-term (7 days and 28 days) strength at predetermined backfill formulations and curing times. The mid-term strength of ASP-CPB first increased and then decreased with PG content, while the short-term strength (3 days) decreased gradually due to the influence of soluble acidic impurities. Excessive NaOH will harm the strength of ASP-CPB, possibly due to the swelling effect of the reaction products (ettringite and sulfate). Strength and setting time increased and decreased with solid contents, respectively. Moreover, the compactness of the mixture has an important effect on strength and workability. The workability and strength of ASP-CPB reached the minimum and maximum values at a W/R ratio of 5:5, respectively. Pollutant index detection indicated that most of the pollutants in ASP-CPB leachate met the discharge standard, which proved that ASP-CPB is an effective method to recover PG. The results of the research will provide theoretical guidance for the efficient recovery of PG resources and support the achievement of safe, clean, and efficient mining.

Nov 17, 2023

By Zhenzhong Bian, Ruiyang Zhang, Xiaofeng Zhong, Zhangxuan Ning, Yuanping Zhang, Jie Lu, Airan Zhang

This study addressed the separation and recovery of vanadium(IV), iron, and titanium from synthetic and real leach solutions of vanadium-bearing titanomagnetite using extractant P204 (di-(2-ethylhexyl) phosphate) and P507 (2-ethylhexyl hydrogen- 2-ethylhexyl phosphonate). Based on the speciation analysis of vanadium in sulfuric acid medium, the single-stage extraction efficiency of vanadium, iron, and titanium was 94.21%, 3.45%, and 5.32%, respectively, under the optimal extraction condition of P204-P507 concentration of 15% (v/v), P204 to P507 ratio of 3:1 (v/v), TBP (Tributyl phosphate) concentration of 5%, sulfonated kerosene concentration of 80%, initial pH of 1.8, contact time of 8 min, and phase ratio (O/A) of 2:1. By confirming the predictions of the McCabe-Thiele diagram, a five-stage countercurrent extraction was carried out and the desirable extraction efficiency for vanadium reached 98.13%. The maximum co-extraction coefficient and distribution ratio of vanadium were 2.58 and 26.23, respectively. The stripping efficiencies and concentrations of a vanadium-rich solution by three stages of countercurrent experiments with 20 vol.% sulfuric acid reached 99.14% and 0.58 g/L, respectively, while almost all of the titanium remained in the organic phase. The mechanism of synergistic extraction between hydrogen ions of P–O–H and VO2+ in acidic conditions was confirmed by ATR-FTIR spectroscopy and molecular structure derivation. Besides, the separated impurity ions ( Fe2+) after oxidation, precipitation, and roasting process form a qualified iron oxide pigment with a total iron content of 97.2%.

Apr 25, 2023