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By Harold L. Lovell

The current interest in sulfur recovery from coal measures is indicated by a recent report prepared for the Public Health Service (1) It was noted that the concentration of pyrites to a product containing 42-48 percent sulfur should be relatively easy with present equipment. It was also pointed out that a utility potential exists for the high-grade iron concentrate which results as a by-product of the consumption of pyrites in the acid-making process. However, economics, marketing characteristics, location, transportation, pyrite levels and coal characteristics all strongly influence the feasibility of fostering industrial development of such processes. The extent of pyrite recovery and product quality is intimately related to pyrite particle size and its degree of liberation, a consideration usually given greater emphasis in metal ore preparation than in processing coals. Consequently, fine crushing to nearly 20 mesh probably will be essential for maximum practical processing. It appears that any process separating pyrites from a coal must involve a reprocessing of the normal preparation plant refuse, although some yields can be attained from certain existing operations as products from, a shaking table or a jig. Further, the existence of millions of tons of coal refuse cannot be ignored as a mined source of raw materials. The recovery of saleable products from such wastes, although untried on a large scale under current conditions, not only offers a realistic source of sulfur but also would achieve a secondary refuse with the minimal contents of substances which incite and propagate the burning of organic and inorganic combustibles. These silicate materials, thus beneficiated, also offer some potential for economic utilization. Some significant tonnages of pyrites have been produced from coal measures in the past, but the experience was, in general, not consistent with current coal preparation practice. The processes involved did not include cyclones and heavy media; nor were they carries out under the sociological environment concerned with pollution as exists today.

Jan 1, 1967

By John Marsden, Mike Botz

A variety of modeling techniques can be utilized to forecast metal production at heap leaching operations. These approaches reflect a wide range of complexity, flexibility, time to implement, cost, and accuracy. For many operators, a spreadsheet-based modeling technique is attractive since the calculations are directly accessible, models can often be developed by site staff, and the results are generally easy to extract and interpret. The authors have developed a spreadsheet-based modeling technique that provides a high degree of flexibility, while still considering detailed operating information for ore properties, leach kinetics, scaleup factors, lift height, and in-heap metal inventories. The technique involves establishing kinetic leach curves for each ore type to characterize metal extractions, followed by application of separate metal recovery curves to define the rate at which leached metals exit the heap in pregnant solution, taking into account delays due to the in-heap solution inventory. At any point in time, the difference between total metal extracted and total metal recovered is equal to the in-heap inventory of the leached metal. This modeling technique is particularly useful for larger multi-lift heaps where delays in metal recovery are appreciable due to in-heap solution holdup. The technique is also applicable to sites with multiple heaps, leach cycles, and/or metal recovery plants (e.g., carbon columns for gold; solvent extraction for copper). This paper describes the modeling technique, including input data required and methods for defining kinetic leach curves and metal recovery curves. The technique is compared against an alternative spreadsheet technique using a simplified in-heap solution inventory calculation to forecast metal production, which has proven to be effective at a number of sites.

By Richard Giffen, Michael Trabold, Pablo Lemus

"As part of the new 2nd Ave Subway Project, an existing tunnel constructed in the 1970’s will be connected to the new subway and used as new running tunnels. The existing tunnel had to be modified to comply with newer structural and fire life safety codes and to be connected to the new cut and cover station at 96th St. This paper will discuss the complexities of tying an existing tunnel constructed over 40 years ago into the new station and allowing for movements due to the unloading of the existing tunnel and the differential settlement of the two structures during both the construction and permanent condition. Topics that will be discussed include structural analysis, ground improvement techniques, selection of support of excavation walls, working in contaminated soil and instrumentation and monitoring of the structures. It will also cover retrofitting the tunnel to comply with updated Fire/Life/Safety requirements. PROJECT OVERVIEW The Second Avenue Subway (SAS) will be the first major expansion of New York’s subway system in over 50 years. To be constructed in four phases, it will run from 125th St. in Harlem to Hanover Square in the Financial District (see Figure 1). For most of its length, the alignment is directly under the Second Avenue roadway."

Jan 1, 2016

By Smart Chika Obiora, Anthony Chukwu

Lead and zinc have been mined for over 90 years in parts of the Lower Benue rift in southeastern Nigeria. However, there has been little interest in the sustainability of the environment and the inhabitants of the host communities. Adverse effects include soil and food crop contamination, lack of education, poor healthcare, unemployment, and no access to potable water. This work suggests practicable mitigation strategies to ameliorate these negative effects and promote environmental sustainability.

Jul 1, 2023

By John Marsden, Mike Botz

A variety of modeling techniques can be utilized to forecast metal production at heap leaching operations. These approaches reflect a wide range of complexity, flexibility, time to implement, cost, and accuracy. For many operators, a spreadsheet-based modeling technique is attractive since the calculations are directly accessible, models can often be developed by site staff, and the results are generally easy to extract and interpret. The authors have developed a spreadsheet-based modeling technique that provides a high degree of flexibility, while still considering detailed operating information for ore properties, leach kinetics, scaleup factors, lift height, and in-heap metal inventories. The technique involves establishing kinetic leach curves for each ore type to characterize metal extractions, followed by application of separate metal recovery curves to define the rate at which leached metals exit the heap in pregnant solution, taking into account delays due to the in-heap solution inventory. At any point in time, the difference between total metal extracted and total metal recovered is equal to the in-heap inventory of the leached metal. This modeling technique is particularly useful for larger multi-lift heaps where delays in metal recovery are appreciable due to in-heap solution holdup. The technique is also applicable to sites with multiple heaps, leach cycles, and/or metal recovery plants (e.g., carbon columns for gold; solvent extraction for copper). This paper describes the modeling technique, including input data required and methods for defining kinetic leach curves and metal recovery curves. The technique is compared against an alternative spreadsheet technique using a simplified in-heap solution inventory calculation to forecast metal production, which has proven to be effective at a number of sites.

By N. J. Themelis

Autogenous grinding, broadly defined as the self-comminution of ore in a cylindrical tumbling mill without using auxiliary grinding media, was first applied in the early thirties in the so-called Hadsel mills (Figure 1) mainly used in gold mines on the U.S. West Coast. A number of these mills were built in sizes of 20 to 24 ft. in diameter and five-six feet in length but were later abandoned because of operating and maintenance problems. Further development of autogenous grinding led to the Hardinge wet grinding mill (Figure 2), the Aerofall dry grinding mill and others. A tabulation of all known autogenous and semi-autogenous installations around the world was sent recently to the authors by Hr. G. J. Kushner of the Koppers Mineral Processing Division. In the size range of 24 to 32-ft. in diameter, it lists a total of thirty mills used in the processing of copper ores. An additional 120 units are listed in the same size range for the processing of iron ores and other minerals. The largest mills in existence are 36-ft. dia X 15-ft. long mills in Minnesota, powered by 12,000 hp. motors and used in taconite beneficiation. It is indicative of the phenomenal growth of this technology that none of the above one hundred and fifty mills was in operation prior to 1964.

Jan 1, 1978

By David Kress

Mill crushing drive systems are essential to cement producers. With the increased emphasis on operating efficiency, it is vital that these systems be dependable and reliable. No one needs the costs or headaches associated with unscheduled downtime or inefficient machinery operation. A reliable drive system starts with the proper selection of the ring, or girth, gear and continues through proper maintenance. Ideally, selecting the right girth gear brings together the gear manufacturer, the system designer and the end user. The gear manufacturer must know the details of the application, the demands that will be placed on the gear and the nature of the equipment to be driven. Similarly, the user and the system designer must be familiar with the variables that affect gear drive performance and service. For example, an application that places a torque load on the drive in excess of its rated capacity will result in gear tooth distress and, in severe cases, breakage.

Jan 1, 2000

By Hasan Nizamoğlu, Z. Abidin Sarı, Aslıhan Demiraslan, M. Deniz Turan, Tolga Depci

In this study, recovery of copper from solid material (obtained by leaching of chalcopyrite with oxalic acid in the presence of hydrogen peroxide) with a copper oxalate structure was carried out selectively using HCl. The chemical composition of the solid was as 29.3%, 9.7%, and 13.3% for Cu, Fe, and S, respectively. Selective recovery of copper by degrading the copper oxalate structure with a low-solubility product (Ksp = 4.43 × 10−10) was performed by conventional leaching in the presence of HCl. The optimum leaching conditions were determined as 5 M of HCl concentration, 318 K of leaching temperature, 120 min of leaching time, 25 ml/g of liquid–solid ratio and 400 rpm of stirring speed. Under these conditions, approximately 77% of copper and 3% of iron were taken into the solution. According to the characterization of the leach residue that was obtained, the oxalate structure was degraded. Moreover, the results of XRD analysis showed that the sulfur (S) and cubanite (CuFe2S3) phases were mostly observed in leaching residues, and this was supported by the SEM-EDX data. Based on the results, it may be stated that selective copper extraction can be obtained from a chalcopyrite concentrate by a two-step leaching method using a conventional hydrometallurgical technique.

By Rambabu Pothina, Rajive Ganguli

The economics of a mineral processing circuit is dependent on the numerous sensors that are critical to optimization and control systems. The sheer volume of sensors results in mines not being able to keep the sensors calibrated. When a sensor goes off calibration, it results in errors which can severely impact plant economics. Normally, these errors are not detected until the error grows and becomes a large (“gross”) error. Undetected errors are not remedied until the next calibration, which on average are a year apart Beamex (2019) [1] across all industries. Classical statistical methods that depend on linear relationships between input and response variables are typically used to find gross errors, but are not effective for highly non-linear and non-stationary operations in mining and mineral processing industries. Calibration of sensors is time-consuming and generally requires physical intervention that results in equipment downtimes causing production losses. Therefore, in situ detection methods are warranted that do not require physical removal of sensors to compare with standard measurements or well-calibrated sensors. Data-mining based techniques and algorithms have high success rate in tackling such problems. This paper presents results from a groundbreaking multi-year big data research project whose goal was to develop data-mining-based original techniques in a multi-sensor environment to identify when sensors start to stray, rather than wait for errors to grow. The carbon stripping (gold) circuit in the Pogo Mine of Alaska was selected for this project. Maintaining strip vessel temperatures at optimum levels is crucial for maximizing gold recoveries at Pogo, and hence the focus was on the temperature sensors of the two strip vessels. An automated algorithm to detect errors in strip vessel temperature sensors was developed that exploited data from multiple sensors in the strip circuit. This algorithm was able to detect with a high success rate when bias errors of magnitude as low as ± 2% were artificially induced into strip vessel temperature data streams. The detection times of about 1 month were much less than the industry average calibration frequency of 1 year. Thus, the algorithm helps detect errors early, without stopping the circuit. The algorithm alarms can serve as triggers when calibrations are done. Experimental methodology along with results, limitations of algorithms, and future research are also presented in this paper.

By Rambabu Pothina, Rajive Ganguli

The economics of a mineral processing circuit is dependent on the numerous sensors that are critical to optimization and control systems. The sheer volume of sensors results in mines not being able to keep the sensors calibrated. When a sensor goes off calibration, it results in errors which can severely impact plant economics. Normally, these errors are not detected until the error grows and becomes a large (“gross”) error. Undetected errors are not remedied until the next calibration, which on average are a year apart Beamex (2019) [1] across all industries. Classical statistical methods that depend on linear relationships between input and response variables are typically used to find gross errors, but are not effective for highly non-linear and non-stationary operations in mining and mineral processing industries. Calibration of sensors is time-consuming and generally requires physical intervention that results in equipment downtimes causing production losses. Therefore, in situ detection methods are warranted that do not require physical removal of sensors to compare with standard measurements or well-calibrated sensors. Data-mining based techniques and algorithms have high success rate in tackling such problems. This paper presents results from a groundbreaking multi-year big data research project whose goal was to develop data-mining-based original techniques in a multi-sensor environment to identify when sensors start to stray, rather than wait for errors to grow. The carbon stripping (gold) circuit in the Pogo Mine of Alaska was selected for this project. Maintaining strip vessel temperatures at optimum levels is crucial for maximizing gold recoveries at Pogo, and hence the focus was on the temperature sensors of the two strip vessels. An automated algorithm to detect errors in strip vessel temperature sensors was developed that exploited data from multiple sensors in the strip circuit. This algorithm was able to detect with a high success rate when bias errors of magnitude as low as ± 2% were artificially induced into strip vessel temperature data streams. The detection times of about 1 month were much less than the industry average calibration frequency of 1 year. Thus, the algorithm helps detect errors early, without stopping the circuit. The algorithm alarms can serve as triggers when calibrations are done. Experimental methodology along with results, limitations of algorithms, and future research are also presented in this paper.

By J. L. Mehaffey

A variety of chemicals offered by Armak were evaluated as dewatering aids for aqueous slurries of silica sand, sparsand and feldspar; an established commercial dewatering aid was used as a control. A number of Armak's potential dewatering aids yielded lower moisture retention values than did the commercial product on all of the mineral samples. In addition to the chemical dewatering evaluations, some of the mechanisms involved in the removal of water from these mineral samples were examined.

Jan 1, 1983

By John Marsden, Mike Botz

A variety of modeling techniques can be utilized to forecast metal production at heap leaching operations. These approaches reflect a wide range of complexity, flexibility, time to implement, cost, and accuracy. For many operators, a spreadsheet-based modeling technique is attractive since the calculations are directly accessible, models can often be developed by site staff, and the results are generally easy to extract and interpret. The authors have developed a spreadsheet-based modeling technique that provides a high degree of flexibility, while still considering detailed operating information for ore properties, leach kinetics, scaleup factors, lift height, and in-heap metal inventories. The technique involves establishing kinetic leach curves for each ore type to characterize metal extractions, followed by application of separate metal recovery curves to define the rate at which leached metals exit the heap in pregnant solution, taking into account delays due to the in-heap solution inventory. At any point in time, the difference between total metal extracted and total metal recovered is equal to the in-heap inventory of the leached metal. This modeling technique is particularly useful for larger multi-lift heaps where delays in metal recovery are appreciable due to in-heap solution holdup. The technique is also applicable to sites with multiple heaps, leach cycles, and/or metal recovery plants (e.g., carbon columns for gold; solvent extraction for copper). This paper describes the modeling technique, including input data required and methods for defining kinetic leach curves and metal recovery curves. The technique is compared against an alternative spreadsheet technique using a simplified in-heap solution inventory calculation to forecast metal production, which has proven to be effective at a number of sites.

Sep 3, 2019

By T. Braun

In 1911, a young mining engineer named Bartlett Thane assembled a large claim block, 4 miles southeast of Juneau, Alaska. Across the Gastineau Channel on Douglas Island, the Alaska Treadwell Gold Mining Company had, by 1904, produced gold valued at more than three times the purchase price of Alaska in 1867 (Kelly, 2010). Thane knew his deposit was lower grade than other mines or prospects in the area; however, if the deposit was developed on a large-scale, the trend and size of the deposit made the project potentially economic. In 1911, Thane developed a business plan for the project and successfully attracted investor interest. In 1912, Daniel C Jackling visited the property at the request of an east coast investment group. Upon inspection of 5 years of production records for the Perseverance Mine, Jackling saw an opportunity to apply the low-grade/high volume milling technology which was widely adopted to the copper porphyry deposits of the southwestern U.S. With a design capacity of 6,000 tons per day (5,454 tonnes/day), Jackling’s innovative mill design would require high volume underground mining methods and the power of two new hydroelectric projects. By 1915, the Alaska Gastineau Mining Company was in full production. Between 1915 and 1919, the mine and mill set production records for haulage and throughput. The hydroelectric projects proved to be successful engineering marvels. Operational difficulties related to ore grade, refractory elements and labor shortages interrupted production on an increasing basis. In 1921, the mining company permanently shut down operations. INTRODUCTION The Juneau Gold Belt begins at Windham Bay near the southern end of Stephens Passage and extends approximately 100 miles north to Berners Bay (Figure 1). The first large-scale and sustained underground mine, operated by the Alaska Treadwell Gold Mining Company in the late 1880’s, established the Juneau-Douglas area as the regional hub for transportation and development. In the mid-1890’s, the combined population of Juneau and Douglas reached approximately 3,000 residents, largely driven by employment and support demands of several small to mid-size underground gold mines in the region. By 1904, the value of the cumulative gold production of the Alaska Treadwell was five times greater than the purchase price of Alaska in 1867 (Kelly, 2010). By the turn of the 20th century, economic growth in the Juneau-Douglas area relied on supplies delivered from the lower 48. Passenger and freight shipping lines required 3 to 4 days to make the one-way trip from Seattle to Juneau. Established shipping routes required experienced crews due to navigation hazards and adverse weather conditions. Even with precautions at the time, steam ships and freighter vessels experienced breakdowns or encounters with natural hazards that resulted in damage or in some cases, sinking. Interestingly, with no roads or railroads connecting Juneau to other communities in southeast Alaska, Juneau still relies on seaborn shipping in the 21st century.

Jan 1, 2019

By Paul O. Knorr

The Bureau of Ocean Energy Management (BOEM), a bureau within the U.S. Department of the Interior, has responsibility over both energy and non-energy mineral development on the United States Outer Continental Shelf (OCS) under the OCS Lands Act (“OCSLA”). BOEM’s Marine Minerals Program (MMP) manages federal offshore mineral deposits through non-competitive, negotiated agreements for sand and gravel (“sand”) used in coastal restoration efforts and the competitive leasing of critical and hard economic minerals (“critical minerals”). As the steward of OCS critical minerals, BOEM MMP is responsible for understanding where critical minerals are located, identifying and understanding their environments, managing activities that affect these resources, and implementing pertinent federal policies. Fulfilling these responsibilities involves the collection and analysis of environmental, geological, and geophysical data; supporting the science needed to understand the impacts of resourcerelated authorized activities on the biological, physical, and sociocultural environments; encouraging emerging technologies that can reduce the environmental impact of activities; and communicating with stakeholders to foster an understanding of existing federal regulations and potential needs to revise the legal framework. Four U.S. federal rules in the Code of Federal Regulations (CFR) currently inform MMP’s procedures: 30 CFR 580 (prospecting for minerals), 30 CFR 581 (leasing of minerals), 30 CFR 582 (operations in the OCS related to minerals), and 30 CFR 583 (negotiated noncompetitive agreements for sand). Other federal laws and regulations are also pertinent, particularly those supporting the National Environmental Policy Act, Endangered Species Act, National Historic Preservation Act, Marine Mammal Protection Act, Coastal Zone Management Act, Clean Air Act, Federal Water Pollution Control Act, and Magnuson Stevens Fishery Conservation and Management Act.

Feb 22, 2026

By Ralph T. Buscarello

For practical purposes, the terms "natural frequency," "resonance" and "critical speed" are synonymous. A part passing though its "critical" or "critical speed" may also be said to be "resonant" or "resonating." The vibrations of a precisely balanced part can be magnified by the structure in which it is assembled. Anyone who has driven an automobile knows that it will vibrate more at a certain speed than at others. According to the formula for centrifugal force, vibration should increase steadily with a rise in rpm. What happens instead is that the vibration not only in- creases with r m. but suddenly rises at a much higher rate through the critical speed, and then apparently smooths out as the rpm passes beyond it. To visualize what happens, consider a simple flat spring with a weight mounted at one end. When the spring is deflected by pulling down on the weight and then letting it go, the spring will oscillate, and the spring-and-weight system will vibrate at its natural frequency. If the timing or direction bf the impulses imparted to the spring did not coincide with its natural frequency, the result would be an irregular vibration that would not build up. If, on the other hand, the timing and direction of the impulses did coincide with the spring's natural frequency, the result would be a larger and larger amplitude. If the impulses were continued indefinitely, the amplitude of the spring's vibrations would go on rising [while its frequency stayed the same] until the spring broke or the amplitude of the vibrations reached an equilibrium [because frictional or other forces would tend to damp it]. Resonance magnifies the amplitude of vibrations in a relatively undamped system between 100 to 200 times over that of nonresonant vibrations. Frictional or viscous damping often reduces the magnification [from 10 to 20 times], but even with this reduction the amplitude would still be large enough to cause excessive wear, and sometimes even fractures. For example, a blower might show only 0.001 in. of vibration on the manufacturer's test stand. Installed, the blower could pass into its critical speed [the speed at which the frequency of the vibrations caused by the rotor coincides with the supporting structure's natural frequency], and the 0.001 in. of vibration could be resonated to 0.010 in., or as much as 0.020 in. The cure for such a condition would not be to lower the vibration of the blower by further balancing or better alignment but to separate the two frequencies by at least 20 to 30%.

Jan 1, 1970

By Earl M. Frizzell

This paper addresses considerations for the use of artificial support of pit walls in surface mines, a new project of the Bureau of Mines. Results to date indicate that a polymer-coated cable with embedded grit could provide good anchorage for stabilizing benches and highwalls, and an electronic method of recording discontinuities in the field is being reviewed and developed for application to mining. The objectives of the work in progress are to define the engineering parameters and evaluate the concepts for artificial supports in order to provide safe working environments when pit slopes are steepened to increase ore recovery and reduce overburden handling.

Jan 1, 1986

By A. S. Haugh

OHSAS 18001 is a series of international standards for occupational health and safety management. It is comprised of two parts, 18001 and 180029. OHSAS 18001 was formulated by international certifying bodies and is based on BS8800 and was first published in 19996,11. OHSAS 18001 was developed to be compatible with ISO 9001 and ISO 14001 in order to facilitate integration of quality, environment, and occupational health and safety management systems5. It is a voluntary standard and the overall aim of OHSAS 18001 is to enable organizations to control their occupational health and safety (OH&S) risks and improve overall health and safety performance5. OHSAS 18001 is widely accepted in the UK, Europe, and Asia, is gaining momentum in North and South America, and it was used as the basis and conforms to the requirements of ANSI/AIHA Z.10-2005: American National Standard for Occupational Health and Safety Management Systems. It defines a set of requirements for an occupational health and safety management system suitable for any kind and size of organization4. Businesses of all sizes are developing and implementing occupational health and safety management systems (OHSMS) that are in compliance with the OHSAS 18001 standard.

Jan 1, 2012

By Botelho Junior, Amilton Barbosa, Denise C. R. Espinosa, David B. Dreisinger

Copper and cobalt can be found on nickel laterite ores, and cobalt can be found also on copper ores, and many contaminants such as iron, aluminum, and magnesium are associated with these ores. In hydrometallurgical process, a purification step is necessary after leaching due to the presence of these impurities. Chelating resins are more selective for some metals than others, making them more efficient than cationic resins. This overview discusses chelating resin applications to recover copper, nickel, and cobalt from mining process and mining tailings and the effect of contaminants in leach solution. Chelating resins with iminodiacetate functional group can be used for selective copper recovery, and both iminodiacetate and bis-picolylamine resins are highly selective for nickel and cobalt. Chelating resins with the same functional group can have different performances on the kinetics of loading, because of variations of structure, the density of functional group, and degree of cross-linking. This article reviews commercial chelating resins that can be applied in leach solutions with different compositions, and also possible innovations for uses of chelating resins to recover metals from mining process and mining tailings.

By W. T. Reid

Analysis of the energy resources available in the United States confirms that coal will be needed to satisfy the future energy needs. The trends in the market place, particularly economic and political, suggest that the bulk of the coal will be consumed for generation of electricity. The utilization of coal to produce electricity will require technical solutions to the variable characteristics of coal and ash, development of methods to improve coal quality, and public acceptance of the cost of compliance with environmental standards.

Jan 1, 1983

By K. V. K. Prasad

Forecasting mined grade variability from exploration information is a challenging task in mine planning. For effective planning of activities such as workplace scheduling, ore grade quality control etc. development of realistic numerical/simulation models of in-situ variability from exploration information is an essential first step. Geostatistical conditional simulation (GCS) is one of the well known methods to develop these simulations. Recently, stochastic fractal models based on the assumptions of scale-in variance and self-similarity have been used for developing simulations of several natural phenomena. It has been suggested that these models might permit generation of short-scale variability information from exploration data with greater fidelity when the data satisfies the attendant assumptions. In this paper the stochastic fractal models are reviewed and their relationship to geostatistical variogram models is examined. A comparison of the two simulation techniques has been per-formed using coal sulfur data from a mined out coal property. The results of this comparative analysis are also presented in the paper.

Jan 1, 1992