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By J. Seifert, L. Hunter, P. W. Conrad, S. Rosenthal

"The goal of the protocol for reclaiming in-pit tailings ponds to exceed federal and state regulations was to develop a series of steps that can be followed to design, operate, and reclaim a tailings disposal pond that will develop into grazing land with a wetland for open pit sand mines in warm dry climates. By incorporating a wetland into the reclamation design, the post mining land use gives back to both the wildlife as a source of water as well as providing for a diverse range of post mining land use including but not limited to livestock grazing and ranch land use. An example design was completed using this protocol to demonstrate how the protocol can result in in a well-designed, reclaimed tailings disposal pond. BACKGROUND In an industry plagued with decaying historic mine sites, the public’s perception of mining appears to be poor. While modern mines are closely monitored and generally managed by ethical professionals, history still influences how the public perceives the mining industry. From collapsing abandoned underground workings to historic tailings dam failures, the failure to account for the environment in the past seems to affect public perspective on mining today. In a 2013 “Opinion Former Survey,” a survey conducted through interviews with a diverse range of stakeholders in various gold companies, it was noted that the most serious challenges facing the mining industry were environmental concerns and the permitting challenges associated with them (Council). In another article, this time focusing on Australian citizens and their perspectives of the mining industry, it was found that the majority of those surveyed had a big concern over the environmental impacts of mining especially when it comes to water quality and quantity (Scan). The statistics portrayed in these articles illustrate that today’s mining engineers needs to make more of an effort to change the public’s perspective of mining by being more environmentally aware. These engineers should be continuously asking themselves what they could be doing better from an environmental perspective to ensure that history is not repeated and that natural resources are used as efficiently as possible."

Jan 1, 2018

By Sean Hunter

Artificial Intelligence has a long history but is currently coming strongly into focus with new advancements. This leads to questions many people are asking: what exactly is AI, how can it be used effectively in mining operations, and what foundation is required to make AI implementations successful? In mining, many AI applications exist, from drill pattern optimization to predictive maintenance. However, many implementations struggle due to data integration challenges. Mining operations generate large amounts of data from many sources, such as fleet management systems, drill sensors, process control systems, and laboratory results. Unfortunately, this data often exists in silos where it’s difficult to get it out, making AI applications unable to leverage it. Worse still, tools that use AI don’t always provide their data back to the system, creating even further data silos. All these problems make it hard to take advantage of the data at the mine, slowing down and reducing the effectiveness of AI. This paper presents a comprehensive approach to organizing mining data using an AI-ready knowledge graph system. We will first explore the evolution of AI in mining, from early expert systems to modern machine learning applications. Then, we will detail how a knowledge graph can integrate business context, operational data, and AI models into a cohesive system that enables more effective AI implementations across mining operations. The proposed method has been developed considering both the unique data challenges faced by the mining industry, while also considering best practices learned from the AI field at large. By following this approach, it’s possible to better utilize existing data, getting higher quality and more complete results faster, and in a way that’s reusable and composable.

Feb 1, 2025

By L. Yuan, A. C. Smith

MFIRE, the mine-fire simulation program of the U.S. National Institute for Occupational Safety and Health (NIOSH), is widely accepted as a standard for assessing and predicting the impact of a fire on the mine ventilation system and the spread of fire contaminants in coal and metal/nonmetal mines. MFIRE has been used by U.S. and international companies to simulate fires for planning and response purposes. It is a dynamic, transient-state, mine ventilation network simulation program that performs normal planning calculations. It can also be used to analyze ventilation networks under thermal and mechanical influence, such as changes in ventilation parameters; external influences, such as changes in temperature; and internal influences, such as a fire. The program output can be used to analyze the effects of these influences on the ventilation system. Since its original development by Michigan Technological University for the former U.S. Bureau of Mines in the 1970s, several updates have been released. In 2012, NIOSH completed a major redesign and restructuring of the program with the release of MFIRE 3.0. MFIRE’s outdated Fortran programming language was replaced with an object-oriented C++ language and packaged into a dynamic-link library. However, the MFIRE 3.0 release included no change or improvement to the fire-modeling algorithms inherited from its previous version, MFIRE 2.20. This paper reports on improvements that have been made to the fire-modeling capabilities of MFIRE 3.0 since its release. These improvements include the addition of the t-squared fire as a new fire-source model and the ability to include available heat-release-rate versus time data, the addition of a moving fire source for conveyor-belt fire simulations, improvement of the fire location algorithm, and the identification and prediction of smoke-rollback phenomena. All of the improvements discussed in this paper will be included in MFIRE 3.1 and released by NIOSH in the near future.

Jun 1, 2016

By Yonghong Qin, Songbo Ma, Qi Zhang, Peng Gao, Jianwen Yu

Herein, the coal-based reduction was proposed to utilize the ferronickel slag of Jingchuan company. An excellent index with metallization rate of 99.22%, iron grade of 77.91%, and iron recovery of 92.79% was obtained at carbon addition coefficient 2.0, reduction temperature 1573 K, reduction time 60 min, the particle size of coal and ferronickel slag − 2.0 mm, and CaO content 15%. The 2FeO·SiO2 was reduced to Fe and SiO2 with the increase of temperature. The CaO could promote the reduction of iron oxide. Most of the sulfides (Fe, Cu, Co, and Ni) in the sulfonium were reduced to metal. The reduction degree increased with the reduction time and reduction temperature. The higher reduction temperature represented the higher peak value of reduction rate and the shorter time of reaching the peak value. The isothermal reduction process included three stages: early stage, middle stage, and late stage. The mechanism function were f(α) = 1/2(1 − α)3, f(α) = 3/2(1 − α)4/3[(1 − α)−1/3 − 1]− 1, and f(α) = 4(1 − α)[− ln(1 − α)]3/4, respectively. The activation energy of three stages was 183.498 kJ·mol−1, 420.077 kJ·mol−1, and 656.619 kJ·mol−1, respectively.

May 24, 2022

By Wang Xuewen, Bao Qingbao, Xie Jiacheng, Yan Zewen

This study puts forward a virtual memory cutting method based on the prediction of AFC shape. The integrated key technologies include the generation of virtual teaching cutting curve, the height adjustment strategy of front and rear drum, cutting height adjustment strategy, the reciprocating cycle of cutting technology and so on. Through the two algorithms, SVM and ELM, the form of the next working cycle can be obtained by rolling prediction using the form information of AFC in the first several circulations. Based on the obtained dynamic fluctuation of the form in the vertical and horizontal working faces, the position and cutting information of the shearer during its operation can be controlled and predicted in advance, the memory cutting template can be adjusted and modified in time. Employing this method, the more stable, accurate and timely memory cutting of the shearer under the uneven coal seam could be realized.

Aug 16, 2021

By Jiayao Wang, Jian Chen, Leiting Shen, Hongyang Wang, Zeping Cao, Ziru Wang

Large amounts of by-products, including coal gangue, circulating fluidized bed (CFB) slag, and coal fly ash (CFA), are generated during mining, washing and burning of high alumina coal (HAC). The stockpile of these by-products of HAC will cause the pollution of air, water and soil. Meanwhile, the unbalanced regional distribution of bauxite and alumina production has been a critical challenge for the sustainability of world alumina refineries, especially for China. Therefore, economical extraction of alumina from by-products of HAC not only resolves the environmental pollution problems caused by stockpile but also decreases the dependence degree of import bauxite in China. Considering the fact that powder alumina can only be produced by alkali methods, the alkali extraction of alumina from by-products of HAC is summarized in this paper. Based on the formation process of by-products of HAC, the principle, research status, and problem of existing methods were analyzed and discussed, as well as the forecast of research trend. The analyses indicate that simplex recovery of alumina from byproducts of HAC generates large amounts of leaching residue (red mud) with difficulty for disposing, while comprehensive extraction of alumina and silica meets the research trend for clean and high-value utilization.

Aug 25, 2023

By Milka Madahana, John Ekoru

For efficient management of operations, mining companies are required to be able to predict potential scenarios for main market factors. Competitive advantage and value creation are established through managing the value chain well. The mining value chain is usually faced with challenges from various shifts in commodity markets as well as ongoing uncertainties. Therefore, there is a need for accurate analysis of data from the markets, for the prediction of commodities, for instance, Precious Group Metals (PGM). The main objective of this research work is to apply machine learning methodologies with the aim to identify patterns and trends in the Precious Group Metals, and thereafter analyze and predict the future trends of these markets. Numerous machine learning models are applied to a dataset consisting of 15 years of daily price for eight precious metals namely Platinum, Palladium, Rhodium, Ruthenium, Osmium, Indium, Silver, and Gold. The results reveal the patterns and trends within the data sets and that different machine learning methods could be suited for the prediction of market prices for each of the PGMs. The application of an amalgamation of various machine learning methods may result in more accurate predictions of the PGM markets. Accurate prediction of market prices for PGMs will possibly result in unlocking untapped sources of value in the mining industry.

Jun 25, 2023

By Nate Ober, Heath Rushing

"Mining companies want to be in a position to move quickly and seize a favorable market or to keep their key staff productively busy. One of the problems for these companies is the time required to compensate for unavoidable impacts that the mine will have on the natural environment and to gain environmental permits. All too often, circumstances that were favorable when the project was proposed have become less favorable by the time all the hurdles have been cleared.Accordingly, many mining companies are interested in ways they can inject more predictability into their timelines for gaining environmental permits, shorten those timelines, and be more certain of getting the permits they need to carry out their next project.One increasingly popular way to do this is through a relatively new kind of service — the mitigation bank.Mitigation banks purchase property or easements through property that has been impacted by agricultural, industrial or resource activity. They then turn it around from an environmental point of view. This might include restoring streams and wetlands so that fish and aquatic organisms can survive, and animals have habitat and food to flourish.Appropriate native species of plants including trees and shrubs are planted, and steps may be taken to introduce wildlife to the new habitat. In some cases, a special focus is placed on creating habitat for rare and endangered species of plants or animals.The property is inspected by regulatory authorities, coordinated through an interagency review team (IRT). If the property is determined to be effective as natural habitat, the mitigation bank is then issued credits that it can then sell to development projects that are creating an unavoidable permitted environmental impact elsewhere. A mining company, for example, would buy credits to offset the aquatic impacts due to construction of a mine, access roads and other infrastructure — as required by the Section 404 Clean Water Act permit that governs those unavoidable aquatic impacts. The mitigation bank used for offset must have an IRT-approved service area that includes the location of the impacts."

Jan 11, 2017

By Noel Jarrett

Energy consumption and distribution in aluminum production, conservation accomplishments, and future goals are presented. Electrolysis and electrode manufacture show the greatest promise for major improvements. Means are proposed for reducing waste heat generation in smelting and for conserving energy in anode manufacture by furnace design and substitution of other materials for petroleum coke. Hall-Heroult Process modifications, alternative designs, and the Alcoa Smelting Process are discussed as energy savers. Scrap recycling, more use of aluminum in transportation, and the installation of offshore smelters in less developed countries are shown to be additional means of coping with possible energy dislocations.

Jan 1, 1981

By LINDSAY BOTTOMER, Tassos Grammatikopoulos, Massoud Aghamirian, MARK FEDIKOW

A master composite (Master Comp) sample was prepared from three pegmatite zones from the Zoro Dyke D1 for mineralogical analysis and heavy liquid separation (HLS). The mineralogical examination was conducted on a subsample that was crushed to approximately P80 = 600 μm. The sample consists of spodumene (10.5 percent), quartz (29.3 percent), plagioclase (29.0 percent), K-feldspars (21.3 percent), micas (5.1 percent), tourmaline (2.9 percent) and Fe-Mn-phosphates (0.1 percent). Liberation of spodumene (88 percent) and gangue minerals, including quartz (89 percent), feldspars (94 percent) and micas (83 percent), is very good at this P80 . The average lithium (Li) concentration is 3.7 percent in spodumene, 2,196 ppm in micas, 1,001 ppm in tourmaline and 115 ppm in K-feldspars. Spodumene accounts for 96 percent of the total Li in the sample. The mineralogical data indicate the potential to recover spodumene by flotation with minimal Li losses due to other Li carriers. The HLS was conducted on a subsample that was crushed to smaller than 6.4 mm, with the smaller than 600 µm fraction removed from this test. The HLS results indicate it is possible to produce a high-grade lithium concentrate, with close to 6 percent Li2O, after the rejection of iron silicates with magnetic separation.

By W. C. Morgan

The Federal Surface Mining Law enacted in 1978 is now being translated into regulations which must be followed in future coal mining. Substantial change to mining procedures is required to maintain stricter air and water control while mining and to return the mined out land to equal or better use than before. These changes do not come easy; and in most cases, they create a substantial additional cost. Based on field observations and mining studies, Caterpillar has been making suggestions on the use of their types of equipment to conform to the new standards at the least cost. This paper will be a brief review of some of the overburden stripping and reclamation methods suggested by Caterpillar. A production and cost comparison of dragline, scraper/dozer and truck, loader systems in 20 to 150 ft. Overburden conditions illustrates potential cost savings using mobile equipment.

Jan 1, 1980

By Louis H. Meece

The romance of the River lives on in the tales of Mark Twain; and many Americans still think of the Mississippi River in terms of the steamboats loaded with passengers, gamblers and cotton. Yet for many years, coal has been a major cargo on the American waterways. Currently, about 100 million tons a year of coal is handled in some part of its journey from mine to destination by barge. The bulk of this traffic has been on the Ohio River System and the Upper Mississippi River System in years past. Now we have a new entry. Over the past 10 years various movements of coal have developed down the Mississippi River to power plants at Memphis and along the Gulf Coast, and a small amount of metallurgical coal has moved down the Mississippi River for export to Japan since 1970. But in 1980 a brand new player came on the scene. 1980 was a momentous year for the American coal business. Historically, we have exported about 50 million tons a year of metallurgical coal to the world's steel mills. Just before and after World War I, we also had a fairly healthy export trade in steam coal; and again in the late forties, we supplied large amounts of coal to Europe until domestic production could recover from the ravages of World War II. But since the early fifties, the name of the export game has been metallurgical coal. Starting in the mid seventies, something began that was almost totally missed by the American coal industry; and that was the growth in the use of coal first in Europe and now in the Far East as a steam product and as an alternative to petroleum products. As these world coal markets began increasing, the U.S. at first was thought to be noncompetitive because ocean rates were still very low. For example, as recently as 1977, Australian coal could be moved all the way from Australia to the Gulf Coast for $12.50 per metric ton. Coal exporting countries were Poland, Australia and South Africa, except for the continuing exports of U.S. high quality metallurgical coal. But then came the second oil shock, and all of the sudden that $12.50 rate from Australia to the U.S. Gulf became $25.00. And then suddenly and almost unrecognized by the American industry, American coal was in fact competitive at overseas destinations because of the drastic change in trade patterns brought on by the doubling and tripling and quadrupling of bunker fuel prices for ships.

Jan 1, 1982

By Yi Luo

Subsurface strata movements and deformations caused by longwall mining operations in underground coal mines could affect many important coal mining activities, such as gob well degasification, ground water protection and multiple seam mining. The stratifications in the overburden have significant influence on the subsurface and surface movements and deformations in the ground subsidence process. An enhanced subsurface subsidence prediction model considering overburden stratifications has been introduced in this paper. In this method, the entire overburden strata are equally divided into a finite number of layers and the percent of the hard rocks in each layer is an additional input. The proven influence function method is applied to predict the subsidence on each of the predefined layers progressively upward using the predicted subsidence on the previous layer as the subsidence cause for the current layer. A computer program is developed to facilitate the calculations. A case demonstration is used to show the applicability of the proposed subsurface subsidence prediction model.

Jan 1, 2012

By Peter Hall

The need for large volume covered storage has increased drastically in the last ten years. Increased world demand for such products as thermal coal, potash, metallic concentrates, etc., availability of land for large open storage and environmental issues have brought about this need. This paper discusses briefly demand, environment, types of covered storage and the Alternative Storage System "Eurosilo", a proven system for storage of dry bulk mateials in units up to 100,000 m3.

Jan 1, 1982

By B. Samanta

This paper highlights the use of an innovative mine production scheduling scheme for grade-control planning tasks that take into consideration grade-model uncertainty. The scheduling exercise has been carried out with the help of a multiobjective genetic algorithm (MOGa) for the production scheduling operations. The underlying motive behind the use of MOGa has been the generation of a set of pareto optimal solutions to meet the goals of the target-grade specifications for the considered multiple grade attributes. Several new concepts related to MOGa formulation, in particular the mutation operation and the convergence criteria of this algorithm, are proposed in this paper. The modeling of grade uncertainty into the scheduling outputs has also been incorporated through a set of conditional simulated grade maps. The proposed scheme of production scheduling operations has been applied for the grade-control planning operations in an iron ore mine to meet the targeted grade specifications of iron, silica and alumina, and a risk analysis has been performed to this end.

Jan 1, 2013

By David De Lemos Pires

Mining is essentially a materials management process where materials are classified, excavated, moved to a desired location, processed at a cost and sold for a price hopefully to generate a profit. ?How much is that cost and can it be reduced?? is the age-old question. The requirement for a paradigm shift with regard to materials movement in search of low-cost production has not just happened by chance but, rather, has been driven by agents of change that include mining companies, consultants, governments and equipment suppliers. During the past 100 years of mining, surface mining technology has involved humans with hand tools, humans with machinery and unmanned automated equipment. In the past 50 years, surface mining technology has evolved and now takes the form of trucks and loaders (TL), in-pit-crushing conveying (IPCC) and autonomous haulage equipment (AHS).

Dec 1, 2013

By James Humphrey

There is a natural resistance to change in any form. When it comes to implementing a game-changing technology like autonomous haulage on an operating mine site, the resistance can at times appear insurmountable. Whether based on real information or misguided preconceptions, it?s essential that we don?t underestimate the effort it will take to overcome this resistance, while clearly recognizing when it?s worth the effort. These realizations did not happen overnight for sites where autonomous haulage has been implemented. Nor did they happen overnight for manufacturers of autonomous mining equipment. Caterpillar, for example, began building toward autonomy more than 30 years ago and had a truck operating in the mid-1990s. Lessons learned during those early years led to the realization that there was much more to be learned ? not just about the machines themselves, but about the systems and knowledge that must be in place for a successful implementation. Working closely with customers, initiating real-life demonstrations on mine sites, having discussions with regulatory agencies and other stakeholders ? these and many other activities were necessary before autonomy could be fully and successfully launched. After decades of effort, Caterpillar?s first official commercial autonomous mine site went to work in 2011 in Farmington, NM.

By J. Reyher, R. Bratton, G. Luttrell, B. Li

"Flotation is regarded as the best available method of upgrading minerals and coal fines. However, its efficiency deteriorates rapidly with decreasing particle size. Further, ultrafine concentrates are difficult to be dewatered economically, forcing companies to discard part of the ultrafine materials to impoundments. To overcome these problems, a new method of separating and simultaneously dewatering ultrafine particles has been developed. Following extensive laboratory-scale test work, the process, known as hydrophobic-hydrophilic separation (HHS), has been tested successfully in continuous operations at proof-of-concept (POC)- and pilot-scale tests. The results show that the HHS process is capable of producing high quality clean coal with high recoveries and low moistures. INTRODUCTION Coal preparation plants are designed with up to four parallel processing circuits for treating coarse (> 12 mm), intermediate (12x1 mm) small (1x0.15 mm), and fine (<0.15 mm) particles. The plus 0.15 mm fractions can be effectively cleaned efficiently with gravity separation methods (Wills, 2006). At present, the only commercially viable option for cleaning the finest fraction is froth flotation (Yoon et al., 1999). In flotation, air is dispersed in the form of small air bubbles in a tank in which coal fines are suspended. The small air bubbles selectively collect the hydrophobic coal particles and float to the surface, forming a froth phase which overflows into a launder. As is well known, ultrafine coal particles of less than 30-50 µm are difficult to be collected by the air bubbles, resulting in low recoveries. Furthermore, fine particle flotation suffers from low carrying capacities and poor selectivity due to entrainment problems. (Bethell et al., 2005; Luttrell et al., 2014). In addition, the froth products containing ultrafine coal are difficult to dewater. Mechanical dewatering in general becomes inefficient with decreasing particle size due to small cake porosity and high surface area, resulting in high moistures (Hucko et al., 1988). The cost often becomes prohibitive with particles of smaller than ~45 µm (Bethell et al., 2005). Moreover, the high-moisture products are difficult to handle and incur high shipping costs and lower thermal efficiencies (Honaker et al., 2013)"

Jan 1, 2016

By D. Bogunovic

The objective of this research was to conduct field-scale experiments at an operating surface coal mine in order to determine the impact of the bucket fill factor on dragline production rate and energy consumption. Data collected from a dragline monitoring system were recorded in a specifically designed software tool and the relationship among these parameters was established. an algorithm for the determination of the ?best? fill factor was developed and integrated in the software. It was determined for the analyzed dragline in the mine that energy consumption in the digging phase can be reduced by 36% and production rate can be increased by 1.4% for a bucket fill factor of about 80%, a fill distance of 19.8 m (65 ft) (i.e., 3.1 bucket lengths) and a bucket fill time of 15 sec. the method developed and applied in this study may help dragline operators to determine the fill factor that will increase production rates and reduce energy consumption in specific surface coal mines. Mining Engineering, 2011, Vol. 63, No. 8, pp. 48-53. Official publication of the society for Mining, Metallurgy and Exploration, Inc.

Jan 1, 2011

By H. I. Meyer

The mine is a large open-pit copper mine located near Tucson, AZ. Mining operations involve shovels digging at relatively fixed locations and haul trucks moving the muck to a primary ore crusher, a primary waste crusher, and directly to waste dumps. The total investment in shovels and trucks is some $100 million. Fig. l is a schematic drawing of the operation. A static method of truck assignment is used; i.e., each driver is given one particular shovel to serve until reassigned by the dispatcher. A dynamic system is one where trucks are reassigned after each trip. The problem is to compute a near optimum assignment of trucks for efficient operation.

Jan 1, 1979