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By W. H. Schiffbauer

The protection of miners, equipment, and infrastructure is discussed. While the primary focus of the described technology is to prevent miners from being injured, struck-by, or crushed by heavy equipment; another major benefit realized is also the protection of equipment and infrastructure. An attempt is made to define and classify the systems used to provide proximity detection and warnings as well as collision detection and avoidance. Information about the speed of vehicles and human operator response time can be a factor in the choice of what type of system and what features are needed to properly address the needs. How the technology adjusts to compensate for various vehicle speeds, while maintaining the same level of protection is noted. The statistics which justify the need of miner protection are provided. The primary system components required, what attributes they feature, and how they respond in the environment, is briefly highlighted. The physics behind the danger zone marker technology and what makes it so robust and reliable is established. Examples of a few mining applications and specific operational modes are provided for both surface and underground.

Jan 1, 2011

"Quang Ninh province is located in the north east of Vietnam and the coal mining in the province generates two thirds of the province’s GDP. The coal is extracted from both open pit and underground mines for the country’s complete coal export and by a share of more than 90% for domestic coal usage. Overburden generated through open pit mines is piled up nearby in the form of large waste rock dumps. The side-hill fill dumping near open pit mines is the source of environmental degradation in the region. Among the current problems at solid waste rock dump sites are dust emissions during and after dumping as well as Acid Rock Drainage (ARD). One of the major existing problems at waste rock dumps is dump stability (comprising erosion, sliding and subsidence issues). The RAME R&D project (Research Association Mining and Environment in Vietnam) is - among other activities - actively involved in the research for stabilisation and rehabilitation of mine waste rock dumps in Vietnam in the form of several sub-projects. The Institute of Mining Engineering I of RWTH Aachen University is leading the sub-project of mine waste dump stabilisation in co-operation with Chair of Geotechnical Engineering and Brenk Systemplanung GmbH. Mine waste dumping in the form of layers as an alternative to the side-hill fill dumping is expected to bring up environmental and economical benefits by minimising the problems of dump sites with the contribution to a sustainable development. Reduction of the post construction settlements, long term stable dump profile with minimum erosion, improvement of material parameters for geotechnical slope stability through compaction from hauling trucks as well as economical evaluation of new dumping concepts are the areas of the current research. The project has been financed by German Federal Ministry for Research and Education (BMBF). The ultimate aim of the sub-project is the compilation of the project results in the form of a "Best Practice Guide" and software based "Decision Support System" for planning and management of solid mine waste dumps."

Jan 1, 2011

Fluorspar was not mined in the United States during 2004, although a small amount of usable synthetic fluorspar (CaF2) was produced from industrial waste streams. The majority of fluorspar consumed in the United States came from imports or stockpiled material purchased from the National Defense Stockpile (NDS). In addition, consumption is supplemented by use of by-product fluorosilicic acid produced at phosphoric acid plants. In 2004, annual production of fluorosilicic acid was 50kt (55,000 st) or about 88 kt (97,000 st) of 92 percent fluorspar equivalent. In 2004, annual production of fluorosilicic acid was 50kt (55,000 st) or about 88 kt (97,000 st) of 92 percent fluorspar equivalent.

Jan 1, 2005

By P. A. Plunkert

Metallurgical-grade bauxite was imported into the United States from 11 countries in 2004. The principal suppliers of this 10 Mt (11 million st) of imported ore were Jamaica (33 percent), Brazil (25 percent), Guinea(23 percent) and Guyana (11 percent). The average value of imports, cost, insurance and freight (c.i.f.) U.S. ports, was $31/t ($28/st). Calcined refractory-grade bauxite imports were 165kt (182,000 st) with an average value of $146/t ($132/st), c.i.f. U.S. ports. China supplied 70 percent; Guyana, 22

Jan 1, 2005

By F. Maciosek, D. Denton, J. Johnson

Researchers from the Spokane Research Laboratory of the National Institute for Occupational Safety and Health and personnel from Coeur Silver Valley, Wallace, ID, conducted tests using rock strain strips and Split-Set rock bolts instrumented with strain gauges to monitor wall rock strain at the Galena Mine, Osburn, ID. The objective of the test was to identify whether strain on the rock bolts increased prior to a rock burst. Although results were inconclusive, researchers learned that the Split-Set rock bolts yielded in stick-slip fashion in the highly jointed walls of the stope. The bolts were also bent as stress was redistributed following blasting and subsequent movement along joints in the wall rocks.

Jan 1, 2004

By R. J. Boyd

SUMMARY The productivity of drill and blast methods of mining in hard rock is limited by the cyclic nature of the operation, and a plateau of performance has been reached, even with the most advanced equipment developments. Higher mine operating costs and lower metal prices have more than ever generated the need for breaking through these productivity barriers. After initial field testing The Robbins Company has designed and manufactured, on a joint venture basis with Mount Isa Mines, Ltd., Australia, a prototype "Mobile Miner" for continuous cutting of hard rock. This paper describes the cutting concept, the initial application of a completed 1,156 m (3792 ft.) long 14% decline, actual performance and delay analysis, developmental modifications, anticipated performances of a fully developed machine, and possible future applications. Sincere appreciation is expressed to the management of Mount Isa Mines, Ltd., for allowing access to the data used in this paper. The views expressed here are those of the author and not necessarily those of Mount Isa Mines, Ltd. INTRODUCTION A paper titled, "Design and Development of a Mobile Mining Machine", was presented by J.P. Kindsvater at the RETC, New York, in 1985. This paper described the evaluation of a test fixture in an andesite quarry near Seattle, followed by design, construction and

Jan 1, 1987

By E. F. Schnitzer

During 1996 and 1997, Oregon experienced flooding on a scale not seen in many years. Some gravel pits located near rivers experienced erosion. In several cases, breaches occurred between the gravel pit and the river. Initial evaluation of several sites that experienced these breaches showed that impacts to the river system were complex and varied significantly from site to site. The impacts to the adjacent river system may be viewed as positive and negative. Several flood-plain-mining sites in Oregon located in areas of historic river flow reverted to active riverbeds. In many cases, state and federal fisheries biologists and university researchers saw the resulting increase in channel complexity and habitat as favorable. The Oregon Department of Geology and Mineral Industries —Mined Land Reclamation Program (DOGAMI-MLR) is studying the effects to the off-channel areas that resulted from the 1996 floods. More data is needed to make sound flood-plain decisions regarding mining.

Jan 1, 1999

By A. G. Yapo, T. W. Camm

"All-in sustaining cost is a metric used by mining companies to reflect the cost of gold mining in a consistent format useful to both investors and mining professionals. Cost reporting focused on the direct cost of mining and processing ore was summarized in the non-GAAP cash cost developed by the Gold Institute in 1996. In 2013, a group of mining companies, working with the World Gold Council, developed a more inclusive approach to reporting costs designed to solve the dilemma of showing a more comprehensive reflection of recurring costs involved in producing gold, without discouraging investors. INTRODUCTION Mining today plays a key role in the development of our civilization as a source of essential raw material and provider of essential fuels, producer of jobs, and a factor in support of the international balance of monetary payment (Camm, 2014). Professionals in mining locate, develop, design and manage ore deposits in an environmentally safe and profitable manner. As mineral deposits become increasingly scarce, new challenges face the industry. A current trend is to an increased emphasis on underground mining techniques for deeper deposits. Operations are safer today than before as companies understand better their work environment and the importance of mining responsibly. A continual challenge for the industry is accurately reflecting the costs and selling price of ore. An enduring characteristic of mining is the situation where the market typically determines the price of a commodity; the main control a company has on the bottom line is to control the cost of production. An attempt to bring light and clarity on the cost of their business will give a better idea to investors on the true profitability of the mining business. Gold producers face this struggle to accurately reflect the cost of production while also seeking to attract the interest of the investment community (Hill, 2013). In order to have a consistent format to report on their production costs, leading gold producers through their alliance inside the World Gold Council (WGC), worked on the adoption of a new cost framework: the All-in Sustaining Cost (AISC) and All-in Cost (AIC). Since 1996, the traditional cash cost reporting has focused only on the mining and processing costs incurred in mining an ounce of gold, which included the costs of goods sold (labor, energy, and consumables costs) and royalties (Table 1). But cash cost reporting ignores many important aspects, like sustaining capital, general and administrative expenses, and site rehabilitation at the end of the mine life (Whelan, 2013). The cash cost was used to attract many investors into the business. In fact the high gross margin (sales minus cash costs) has been promoted the past decades by the industry instead of the net or operating margin. As a result, even when the gold price was high, nearly $1900 per ounce in August 2011, gold producers were not reporting excessive profits in their cash flow / income statements, to the disappointment and incomprehension of investors (Milstead, 2014). The truth was simply that the other costs omitted in the traditional cash cost were reducing the apparent profits."

Jan 1, 2017

By Joel Darmstadter

The position of the coal industry in America’s fuel and power picture remains one of prime importance. Measured in Btu terms, the industry is the country’s leading energy producer and an important exporter. Foreign coal sales yield annual proceeds of about $4 billion. Coal’s one-fifth share of the nation’s energy consumption is nearly as high as that of natural gas. Coal is the electric utility sector’s principal fuel supplier. It accounts for about55% of the electricity generated at power stations.

Jan 1, 1999

By Meyer Klein

Decision theory is the formal theory of the logic of decisions in view of the decision maker's objectives, preferences, I beliefs, and available information, It usually deals with weighty economic problems involving irrevocable (or costly to reverse) decisions. Capital investment planning problems constitute an instance par excellence for application of the decision theory concepts. Decision theory as it is presently conceived has evolved in recent years. At first it concentrated on decisions in the face of total lack of information and on games with intelligent adversaries. The results of these efforts proved theoretically interesting, but practically of little applicability. In the last few years, stress has shifted to the introduction of subjective probabilities and preferences, and the results have been eminently successful in applications both in government and with- in business firms in the resolution of complex problems.

Jan 1, 1970

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 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 J. Fritz, V. Gangrade, J. Briton, K. M. Ajayi, M. L. Harris, G. Cole, M. Young

Mine workers using diesel-powered equipment experience the highest occupational exposure to diesel particulate matter (DPM). This problem could be aggravated in underground stone mines due to their unique ventilation challenges with the large openings for airflow. Hence, adequate ventilation in these mines requires a combination of effective ventilation planning and delivering needed air quantities using auxiliary fans and stoppings. To meet this challenge, the National Institute for Occupational Safety and Health (NIOSH) developed the Air Quantity Estimator (AQE) software as a mine planning tool to help underground mine operators estimate the air requirements necessary to dilute DPM in the main air stream to statutory levels. The major parameters required for the calculations are the engine’s horsepower, DPM emission rate, the percentage operating time, catalytic converter efficiency, and filter efficiency. In efforts to provide major updates to this software, this study describes the recent development of a revised version of the Air Quantity Estimator (AQE 2.0). With the revised version, users have access to a comprehensive database of over 40,000 pieces of equipment, can define their specific target DPM level, and can create specific equipment for a customized database, in addition to having an improved easy-to-use interface. The software output provides an estimated total airflow necessary to dilute DPM based on the projected emissions, and the user can generate a related results report. The results also provide the mine personnel with a tool to identify vehicles that are high DPM contributors and could further be used to optimize the ventilation requirement by making changes to the percentage operating time of the engine. This software provides the mine with a user-friendly tool that could help reduce the DPM exposure of workers.

Feb 1, 2023

The 21st Annual American Mining Hall of Fame Awards Banquet sponsored by the Mining Foundation of the Southwest will be held at the Sheraton Tucson Hotel in Tucson, AZ on Saturday, Dec. 6, 2003. This year’s inductee, guest of honor and featured speaker at the banquet will be Thomas J. O’Neil, recently retired president and chief operating officer of Cleveland Cliffs Mining. Prior to Cliffs, O’Neil spent 10 years with Cyprus Minerals. He was also professor and head of the Department of Mining and Geological Engineering at the University of Arizona. As representatives of mining heritage, the Hall of Fame will induct James Boyd and Thomas F. Walsh. Walsh discovered a rich gold telluride vein in Ouray, CO, which became the Camp Bird gold mine. Boyd was a former director of the U.S. Bureau of Mines, vice president of Kennecott Copper and later president of Copper Range.

Jan 1, 2003

By A. A. El-Midany

Traditionally, the choice amongst different upgrading techniques or in finding the optimum operating conditions for a given upgrading technology depends on whether one is looking at the grade or the recovery of the valuable mineral in the concentrate. In fact, the conclusions are not usually the same. This is because the best technique or optimum operating conditions for the highest grade are not the same as the conditions to achieve the maxi-mum recovery. Therefore, a unique measure that takes into consideration both grade and recovery is urgently needed. Finding such a measure is the objective of this paper. A proposed measure provides a selectivity index in the range of 0 to 1, where 0 is no selectivity and 1 is ideal selectivity. The index can be obtained by plotting the so-called Fuerstenau upgrading curve, which relates the recoveries of the components in products of separation and a running regression applying a one-parameter equation. The measure was applied to assess the selectivity of selective flocculation under different operating conditions when used as a sensitive upgrading technique for ultrafine ground ores. After applying the proposed selectivity measure in the case of the selective flocculation of ultrafine Egyptian iron ore without the addition of cations, it was found that the optimum conditions are pH 11, 1 kg/t sodium silicate and 0.4 kg/t potato starch with a selectivity index of 0.55. With the addition of cations, the optimum conditions were found to be pH 11, 1 kg/t sodium silicate and 2 kg/t potato starch with a selectivity index of 0.65. It should be noted that determining these optimum conditions using the traditional grade or recovery measures was highly ambiguous.

Jan 1, 2008

By Edward Holloway

The basis for the selection of the ultimate pit for an open-pit mining operation is generally opaque. Some form of value-based analysis will generally guide the final decision; however, the value will often gradually plateau while the ultimate pit size continues to increase. There is no established framework to guide specialists in the selection of the ultimate pit, with such decisions regularly made on a somewhat arbitrary basis. The key component that is missing from the analyses typically used to select the size of the ultimate pit is risk. Once risk is quantified within the analysis framework, the decision-mak-ing range is significantly reduced and the process for select-ing the ultimate pit becomes more consistent, replicable and defensible. The technique outlined in this paper provides an approach to including risk in the process used to select the ultimate pit.

Jun 1, 2024

By W. M. Shaver, W. R. Dengler, F. A. Edwards

INTRODUCTION The Macassa Division of Lac Minerals Ltd. is a high grade gold mine that has been operating in Kirkland Lake, Ontario for the past 51 years. It produces approximately 120,000 tonnes of ore per year, averaging approximately 18.7 grams per tonne (0.45 ounzes per ton) of gold. Over the years, the ore body has been developed to a point where mining takes place below the 1,220 m (4,000 feet) elevation and 1,830 m (6,000 feet) west of the original shaft. The mine is currently serviced by two surface and two winze shafts. (Figure 1). The ore body extends below the 1,930 m (6,400 feet) Level which is the bottom of the existing mining operation. An ambitious underground exploration program has substantially increased these reserves. Concurrent with the discovery of greater reserves, has been rapidly escalating mining costs, particularly labour which constituted 66% of the total cost in 1981. These costs continued to escalate as the major proportion of mining was carried out to the west, far away from the existing hoisting systems. This required three lift hoisting for men, materials and ore. I n addition to the increased travel time and ore handling expense, increased humidity and temperature and ventilation and compressed air losses have added to the inefficiency of the operations. As a result, studies were initiated in 1980 to assess the future of the Macassa operation.

Jan 1, 1985

By Mark Colwell

As per most other earth science engineering problems, the underground coal geotechnical environment and the way in which roof and rib support interacts with the rock mass are complex issues. While the problem should not be oversimplified (i.e., the dominant failure mechanisms or critical data input parameters should not be ignored), without question judicious simplification is at the heart of all good engineering design. Engineers play a vital role in supplying the world with solutions and products; however it is crucial that engineers make practical and readily useable contributions. One way to ensure this is to employ simplification in the engineering process.

By S. Lolon

Spontaneous combustion in underground coal mines has become a serious problem particularly in the caved area (gob). Recent statistic has shown that approximately 17% of total 87 underground coal mine fires in the United States are attributed to spontaneous combustion (De Rosa, 2004). Spontaneous combustion results from a self-heating process in exothermic conditions. The accumulated heat, if not removed, is conducive to the rapid increase of temperature and may result in mine fires or explosions. It is well accepted that the interaction between oxygen and coal substances is the main cause for spontaneous combustion, while other factors such as pyrite, moisture, and bacteria play a secondary role to the self-heating of coal. Therefore, only coal oxidation is considered in this study. Coal oxidation occurs as coal comes into contact with air. This process involves complex phenomena in terms of heat transfer, chemical surface absorption, and energy balance related to inherent properties of coal (Wang et al., 2003). For simulation purpose, overall reactions can be simplified as suggested by Mitchell (1990): C + O2 CO2 + heat [65°- 94°C] (1) CO2 + C 2CO + heat [100°- 150°C] (2) Stoichiometric reactions (1) and (2) show that 2.66 grams of oxygen are required to oxidize 1.0 gram of carbon. Once the temperature exceeds 100°C, the reaction has little chance to stop. The crucial step in reducing spontaneous combustion risk is locating the ignition point of spontaneous combustion (hot spot). This information is useful in the effort of developing a preventive method effectively. In this study, this was conducted based on the best gathered information: ventilation surveys conducted in an existing longwall mine located in the western US; the laboratory experiments performed on a physical gob model; and the CFD models to investigate the flow behavior in the gob, the oxidation of coal, and heat transfer phenomena. The hot spot location is determined as a function of oxygen concentration and gob temperature. The critical values are the following: 5% (by volume) for oxygen and 100°C for gob temperature. CHARACTERISTICS OF GOB MATERIAL AND MODELS Permeability Concept Permeability is one of the key parameters in any study dealing with porous medium. This is determined by particle size and the ratio of void volume to the total volume (porosity) of porous medium. This relationship is known as the Carman-Kozeny equation (Scheidegger, 1957) and is given mathematically as [ ] where k* = theoretical specific permeability, m2 dm = the mean particle size, m n = porosity However, permeability tests with various particle sizes were carried out at the University of Utah?s ventilation model (Figure 1) to verify this relationship. These tests indicated a necessity to modify this theoretical relationship. A factor of 0.898 was obtained to make up the different between theoretical permeability and the experimental one. The modified version of (3) is given by: [ ] This equation is used to determine permeability of the simulated mine gob throughout the study. [ ] Mine Gob Material The gob is represented by zones filled with material of given size distribution. For physical measurements and CFD simulations, the material used were crushed rock and coal. Due to compaction, three different characteristics of gob material were used in the model: unconsolidated, semiconsolidated, and consolidated. In the real condition, the largest coal-rock particles are more likely to be located in the area behind the shields. This material is freshly broken and unconsolidated. The size of these broken particles is based on a study carried out by analyzing images taken from the area behind the shields in three coal mines in the United States (Pappas and Mark, 1993). The results have shown that the mean size of materials behind the shields is about 1.22 m. The permeability associated with this size was then obtained from (4) and permeability tests. This was 4.68 x10-7 m2. For semiconsolidated and consolidated zones, due to the lack of experimental data, these were determined through CFD simulations. These simulations were designed by assigning a permeability of 3.15 x 10-8 m2 for consolidated zone and 7.98 x 10-9 m2 to the other zone. The airflow pattern in the gob assigned with given permeabilities was expected to follow the experimental distribution (Brunner, 1985). The mean particle sizes for the semi-consolidated and consolidated zones were 0.02 and 0.006 m, respectively; smaller than those of the unconsolidated zone. Figure 2 shows the 3D view of permeability changes in the gob.

Jan 1, 2009