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By Wei Victor Liu, Omer Faruk Ugurlu, Chengkai Fan, Bei Jiang

Accurate prediction of truck productivity plays a pivotal role in improving the efficiency and profitability of openpit mining operations. This paper proposes a deep neural network (DNN) model to overcome the challenge of predicting truck productivity in openpit mines. The prediction model was built using eight variables and was optimized by considering different train-test split ratios, numbers of hidden layers and neurons, and activation functions. The proposed model’s performance was evaluated using various metrics and compared with other commonly used machine learning algorithms. The results showed that the proposed model outperformed traditional machine learning models by achieving higher prediction accuracy. Moreover, a single-variable sensitivity analysis showed that haul distance is the most influential variable for predicting truck productivity. This study marks a pioneering effort in employing DNN to predict truck productivity in openpit mining, signifying a notable advancement in the field.

Jul 1, 2024

By G. Akdogan, S. M. Bradshaw, A. P. Van Wyk, T. Punt

This study investigated the performance of citric acid as lixiviant for cathode material from end-of-life lithium-ion batteries (LIBs). Black mass containing 84.2 weight percent MNC (LiNi0.45Mn0.4Co0.15O2) and 15.8 weight percent LCO (LiCoO2) material was leached at solid-to-liquid ratios of 20, 50 and 100 g/L. Leaching with 1.5 M citric acid, 2 volume percent H2O2 and a solid-to-liquid ratio of 20 g/L at 95 °C extracted 90 percent Co, 95 percent Li, 94 percent Mn and 94 percent Ni within 20 min. At the highest solid-to-liquid ratio of 100 g/L with 1.5 M citric acid, 10 volume percent H2O2 and 95 °C, 84 percent Al, 84 percent Co, 87 percent Li, 86 percent Mn and 96 percent Ni were leached after 40 min, producing a leach solution containing 0.68 g/L Al, 20.0 g/L Co, 6.0 g/L Li, 13.6 g/L Mn and 19.3 g/L Ni. Using stepwise addition of H2O2, instead of initial bulk addition, did not significantly improve the leaching efficiency but did reduce the required leaching time. Temperature control of the reactor was also more manageable with stepwise addition of H2O2, and evolution of gas was less vigorous. It was observed that the leaching efficiencies of Co, Li and Mn decreased slightly at solid-to-liquid ratios of 50 and 100 g/L, while the leaching of Ni increased slightly. The solution leached at 20 g/L could be stored for six weeks without any spontaneous precipitation. However, solutions leached at 50 and 100 g/L showed changes in concentration after one month of storage, suggesting that processes that have a large material throughput and use high solid-to-liquid ratios around 100 g/L must ensure that the solutions are not stored for extended periods of time.

Apr 1, 2025

By C. Allen, H. Zhang, L. Falk

Shock loss occurs when there is a change in the area of a drift or airflow direction. These shock losses accumulate throughout the ventilation system and will increase the mine resistance as underground development deepens or becomes more complex. Hence, shock losses should be carefully considered when establishing the resistance through a series of branches as they can be a significant contributor to the estimated mine resistance. Using computer software to simulate a ventilation system is common but applying reasonable shock loss factors in the software is not a simple or direct process. Determining shock loss values includes the consideration of historical measurements, application of factors and formulas from literature based on the geometry and complexity of junctions, and the geometry variation at different locations. For example, the shock loss at the bottom of a ventilation raise can consist of a 90° bend and a sudden area change. This paper presents an approach for estimating shock loss factors near raise junctions using computational fluid dynamics (CFD). Current and future work will also be compared with field measurements. Results from this approach are compared with software defaults as well as classical techniques in published literature and standards.

Sep 1, 2024

By Jodie Robertson, Isabel Barton, Cristian Caro

Prior to mining, all rocks contained in a mineral deposit must be placed in one of several categories known as ore types. Each ore type describes a different way that the rock will behave in processing. The ore type determines which process stream a particular mined unit will be sent to, sets expectations for process engineers and metallurgists, and forms the basis for recovery predictions and production estimates. At first, ore types are assigned mainly by geologists based on visible geological criteria (dominant ore mineralogy, estimated grade, rock type, alteration type). As metallurgical tests are carried out and process data accumulate, the resulting criteria may be factored into the ore typing process, typically as assays and recoverable metal using the relevant process(es). Other variables may also be incorporated into ore typing at operations if they are particularly important, such as grindability, preg-robbing, gangue reagent consumption, and the presence of especially deleterious minerals such as talc or smectite. The mine operation department may also redefine ore types and/or process destinations based on economic criteria. A “best” ore type is designated that (in theory) best describes how the rock will behave in processing. Codes representing this ore type are entered into the drill-hole database, then interpreted on cross sections and level plans, and finally added to the block model. Ore types are iteratively reexamined and adjusted over the life of a project. Major difficulties in effective ore typing are (1) lack of communication between geologists and metallurgists, (2) the imprecision inherent in imposing clean categories on messy natural systems without discrete divisions, (3) the need for ore types to provide useful information for a wide range of processes, (4) difficulties in scaling up laboratory test results to mine production, and (5) conflict among geological, metallurgical, and economic criteria for ore typing.

Jul 1, 2024

By Carter Brown, Kate Brown Requist, Eric Lutz, Moe Momayez, Athira Satheesh

New mining health and safety training modalities are becoming increasingly prevalent in the underground mining industry. Various digital training tools have been developed over the past several years, but the extent of their use remains unclear. Advances in gamified training by way of computerbased video games and virtual reality (VR) have opened a new avenue for mine rescue and self-escape training, but these methods have not been widely adopted across the mining industry. Mine rescue and self-escape situations require a mix of in-classroom training as well as live drills, but it is important to assess the extent of and effectiveness of new training modalities. The Mine Rescue and Self-Escape Survey (MRSES) was distributed to underground mining operations to collect perceptions of current training effectiveness as well as willingness to adopt new training methods as a complement to live rescue drills. Responses from the MRSES indicate that adoption of digital training technologies has been slow-going despite an interest in their use. Further, there appears to be no meaningful connection between more frequent escape and rescue training and feelings of emergency preparedness. With relatively little use of already developed digital training tools but an interest in their adoption, it may be time to reassess current emergency preparedness training philosophies.

May 1, 2025

By Kadri Dagdelen, Lee J. Zamalloa

Truck-shovel dispatch systems based on linear or nonlinear programming algorithms have been in operation since the mid-1980s, with different levels of success depending on the correct arrangement of operational resources and the complexity of the mine. These systems are known for shortcomings related to the logic behind the decision-making of the operational objectives. This makes it necessary to have a human agent (dispatcher) to guide the system when the operational parameters change, creating the possibility of suboptimal decisions due to the human factor. To address this issue, the present work discusses the implementation of a methodology based on artificial intelligence (AI) techniques to assist in the decision-making of the best optimization goals arrangement when operating a fleet management system. The focus of the analysis is on the evaluation of variable goal weights in a nonpreemptive, multigoal optimization model for multiple uncertain scenarios based on regions of optimal feasibility.

Apr 1, 2025

By Iga Trisnawati, Fitria Puspita, Himawan Tri Bayu Murti Petrus, Gyan Prameswara, Idi Amin, Andi Nurfaadhilah Ulfah

Laterite ores, rich in essential metals like nickel, iron and cobalt, are a crucial resource for modern technology. However, the extraction of nickel from laterite ores is a complex process due to their intricate mineral compositions and low nickel concentrations. This paper presents the results of a study to understand the leaching behavior of preroasted laterite ore and the impact of roasting on leaching kinetics. The ore was subjected to roasting at 280 and 610 °C for a duration of three hours, followed by leaching in sulfuric acid (H2SO4) under atmospheric conditions. The results show that preroasting the ore at 610 °C significantly improved the recovery of nickel during leaching, with recovery rate of up to 93 percent, and the leaching process of the preroasted ore was primarily controlled by diffusion through the ash layer. The activation energy values were found to be 20.97 kJ/mol for the ore roasted at 280 °C, and 18.97 kJ/mol for the ore roasted at 610°C. These findings suggest that preroasting can enhance the leaching performance of laterite ore, potentially paving the way for more efficient and sustainable nickel extraction processes.

Aug 1, 2024

By Michael Forbes, Rick Jeuken

The challenge of managing geological uncertainty in mine planning is central to optimizing resource extraction while minimizing risks and costs. This paper introduces a novel approach to coal mine planning by integrating chance-constrained programming to address the uncertainty inherent in mining operations. The main takeaway from this work is the demonstration that focusing on reducing the variance of high-quality coal blocks, rather than low-quality ones, can lead to better blending outcomes, higher profitability and more efficient resource utilization. The study presents a case study of a coal mining operation, using chance-constrained programming to manage the uncertainty surrounding coal property predictions, specifically the predicted coke strength after reaction (CSR).

Jan 1, 2025

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