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By Nikhil Dhawan, Veeranjaneyulu Rayapudi

This study investigates upgrading of low-grade banded hematite quartzite iron ore (Fe ~31%). Conventional beneficiation was found to be futile. The susceptibility of iron phases to microwave exposure and their selective absorption assists in the liberation of iron values. Microwave exposure of coarse particles at 540 W for 10 min yielded a concentrate with Fe 56.30% and recovery of 50.68%. Conventional carbothermic reduction at 500 °C, 60 min and 9% charcoal yielded a concentrate with Fe 57.6% and iron recovery of 68%. The presence of sufficiently bonded silica leads to an easy formation of a fayalite phase. The microwave reduction design yielded FeG of 57.6%, FeR of 47% and a yield of 24% at an optimal condition of 540 W, 8 min and 6% charcoal. It was found that a small fraction of microwave-irradiated ore-charcoal mixture melted rapidly, and pure ferrite balls were observed within 8 min. An optical micrograph of a ferrite ball reveals the retained austenite and martensite phase.

By P. D. Rao, D. E. Walsh

Chemical and physical properties of typical low-rank coal (LRC) ash are significantly different than bituminous coal ash. With the exception of extraneous ash, which is incorporated during mining or is due to ash partings within or between coal seams, LRC ash consists primarily of inherent ash that is bonded into the coal's organic matrix or finely disseminated mineral matter. This paper reviews the nature of LRC ash, both inherit and extraneous, and how this impacts the prospects of washing and utilizing LRCs. A literature review, as well as washability data, proximate and ultimate analyses and ash analysis of 25 Alaskan LRC seams are used as a basis for this discussion. The authors' remit research into the nature and distribution of phosphorous in an Alaskan LRC is also discussed

Feb 24, 1997

By Brent A. Elliott, J. Richard Kyle

Texas is a major producer of industrial mineral resources required by the state’s ever-growing population that now exceeds 28 million. Texas typically ranks in the top three states for the value of non-fuel mineral production with a total value of $5.2 billion in 2017, accounting for 6.9% of the total US mineral value. Almost 90% of current Texas industrial mineral value comes from the production of cement, crushed stone, industrial sand, and construction sand and gravel. Construction material consumption is focused in the 25 metropolitan areas of the state with populations of > 100,000 residents. Industrial mineral consumption is dominated by the four most populous regions of the state—Houston, Dallas-Fort Worth, San Antonio-New Braunfels, and Austin-Round Rock—with an aggregate population of more than 18 million. More than 11,000 employees work in Texas mining and processing operations. Texas produces more crushed stone than any other state from more than 200 quarries; a similar number of operations produce sand and gravel. Specialty industrial sand production for use as proppants in hydraulic fracturing for enhanced petroleum production serves as an excellent example of how developments in one industry sector can markedly affect another industry; the production of industrial sand in Texas has markedly increased over the past decade, reaching $1.3 billion in 2014. With Texas’ population projected to reach 50 million by 2050, continuing in-state development and production of industrial minerals will be required to supply its residential, commercial, and industrial users. Favorable geology and economic factors provide opportunities for identification and development of new industrial mineral production sites.

Collaboration between education providers is the key to long-term sustainability and improved quality in mining education. The mining industry is now, more than ever, an industry doing business on a global basis. Staff are recruited by global mining companies in many different countries and can find themselves deployed anywhere in the world. The mining engineer of tomorrow must be willing to take on this international challenge, and must be educated to a level where he or she has a comprehensive grounding in technical aspects of mining engineering, but also a well-founded appreciation of management, social, environmental and cultural issues that may be encountered around the world. In order to deliver such an education, academic providers must collaborate at both a national and international level. This paper provides an overview of progress that has been made in Australia through the national joint venture ? Min¬ing Education Australia (MEA). Supported by the mining industry in Australia, through the Minerals Council of Australia (MCA), MEA has been operational since 2007 and is seeing the development of a range of innovative courses and delivery methods, together with a high level of staff cooperation across the country. MEA has also commenced some international teaching initiatives that are seen as a catalyst for a far greater degree of international collaboration in the future. Such activity is not only to the benefit of the students who are taught by experts from around the world, but it also ensures that individual univer¬sity programs remain viable in terms of staffing numbers and financial performance. The paper also presents some statistics on recent upward trends in mining engineering student numbers from around the world, in response to the global shortage of mining engineers.

Jan 2, 2010

By · J. B. Boisvert, O. Leuangthong, T. Acorn

Optimizing final pit limits for stochastic models provides access to geologic and economic uncertainty in the pit optimization stages of a mining project. This paper presents an approach for optimizing final pit limits for a highly variable and geologically complex gold deposit. A heuristic pit optimizer is used to manage the effect of geological uncertainty in the resources within a pit shell with multiple uncertainty rated solutions. The uncertainty rated pit shells follow the meanvariance criterion to approximate the efficient frontier for final pit limits. Stochastic dominance rules are then used in a risk management framework to further eliminate sub-optimal solutions along the efficient frontier. This results in a smaller set of final pit shells that could be further analyzed for production scheduling. Additionally, the original solutions are analyzed for changes in the mining limits and two regions are targeted as potential regions for further exploration.

By · J. B. Boisvert, O. Leuangthong, T. Acorn

Optimizing final pit limits for stochastic models provides access to geologic and economic uncertainty in the pit optimization stages of a mining project. This paper presents an approach for optimizing final pit limits for a highly variable and geologically complex gold deposit. A heuristic pit optimizer is used to manage the effect of geological uncertainty in the resources within a pit shell with multiple uncertainty rated solutions. The uncertainty rated pit shells follow the meanvariance criterion to approximate the efficient frontier for final pit limits. Stochastic dominance rules are then used in a risk management framework to further eliminate sub-optimal solutions along the efficient frontier. This results in a smaller set of final pit shells that could be further analyzed for production scheduling. Additionally, the original solutions are analyzed for changes in the mining limits and two regions are targeted as potential regions for further exploration.

By Tom Dettweiler, Robina Sharpe, Wright. Michael

The International Seabed Authority and a number of countries have or are in the process of developing environmental impact assessment guidelines and legislation for seafloor mineral development. The formal decision to grant a project an environmental permit is based on an environmental and social impact assessment (ESIA), culminating in an environmental impact statement (EIS). The EIS needs to be supported by sufficient data upon which an assessment of impacts can be made and mitigation measures developed. Given the remote locations of many seafloor prospects, collection of sufficient environmental data to inform an EIS is often a difficult, expensive and lengthy process.

Sep 1, 2014

By K. A. Grace

K.A. Grace's article advocates usage of the terms describing resources as defined by the US Bureau of Mines (USBM) and the US Geological Survey (USGS). Originally recommended in 1943, the terms were revised in 1976 and again in 1980. Mr. Grace further recommends that the term reserves should be severely restricted and that it should encompass mining and processing factors. The list of references quoted in the article does not, however, mention the study concerning reserves that was made over a period of almost four years by a joint Committee on Definitions. This committee was sponsored by three societies - the American Institute of Mining, Metallurgical, and Petroleum Engineers (AIME), the Society of Economic Geologists (SEG), and the American Institute of Professional Geologists (AIPG). Most of the detailed work was done by a working party appointed by the Society of Mining Engineers (SME) of AIME. After studying previous definitions in the US as well as in the United Kingdom, Canada, Australia, France, and other European countries, the following definitions were proposed and accepted in 1974 by the SME board of directors. (Ore reserve definitions in Rhodesia, South Africa, or New Zealand were not mentioned as having been reviewed.) Table 1 lists definitions from MINING ENGINEERING, July 1975. Notice in Table 1 it was mentioned, under Resources, that the definitions of reserves were recommended for the purposes of commercial evaluation. It was further stated that the terminology adopted by the USBM and the USGS, as released to the public, covering resources, was recognized as such. Mr. Grace also recommends that reserve calculations should allow for future losses in ore tonnage, ore grade, milling, and smelting. Unfortunately, it might take years to develop a prospect after it has been discovered. Mining methods have to be tested before being finalized in order to know what tonnage of ore is going to be lost, or how much dilution is likely to occur. The same problems are present in concentrating or in smelting. Operating mines usually know how mined grade compares with ore reserve grade. They can usually predict fairly closely what their final metal recoveries are probably going to be. It is, however, expecting too much to have to delay quoting reserves from say a recently drilled prospect. Any responsible mining geologist or mining engineer (or company for that matter) should state several things about an ore reserve calculation: that it is or is not a preliminary estimate only; that estimated grades have not been diluted to allow for a future, as yet unknown, mining method; that metal recoveries are or are not only tentative, based perhaps on drill hole samples only or on no metallurgical testing at all. Reserves of a partially explored prospect are always quoted when it becomes necessary to raise capital. If they are described as preliminary only (really just tonnage and grade estimates and not true "reserves") in addition to being accompanied by some of the items just mentioned, nobody is going to be misled. If, on the other hand, a report by a member of the SME or SEG is intentionally misleading, the individual must be reported and eventually disbarred from his or her society. To summarize, let us stay with the definitions of ore, ore reserves, and related terms as recommended and accepted by SME. I might add that on occasion I have used a fourth category in my ore reserve calculations, namely Geologically Possible Ore. This category is more or less the same as Inferred ore defined by the USBM and USGS. I have never given a grade to this category, which may be based only on geological mapping, geochemical sampling, or geophysical traversing.

Jan 8, 1985

By Gregory Yates

INTRODUCTION Project Description The Silver Line is a Bus Rapid Transit (BRT) Line and is Boston?s newest transit service. Silver Line Phase I extends along Washington Street entirely on the surface in priority bus lanes from Dudley Station in Roxbury through the South End and Chinatown neighborhoods to downtown Boston. The Phase I opened in July 2002. Silver Line Phase II consists of an underground transit tunnel from South Station to the South Boston Waterfront with underground stations at Courthouse and World Trade Center to Silver Line Way east of D Street. Phase II continues through the Ted Williams Tunnel to all the terminals at Logan Airport, and on the surface to the Boston Marine Industrial Park and City Point. Phase II opened in December 2004. Silver Line Phase III is a one mile tunnel connection to the existing Phase II tunnel in the vicinity of South Station and will eventually portal on Tremont Street just north of Marginal Road. After leaving the portal, the buses will use dedicated bus only lanes on the surface roadway network to connect to the Phase I service. Figure 1 shows the alignment of the Silver Line upon completion of the Phase III project.

By Qinghua Tian, Zhipeng Xu, Dong Li, Xueyi Guo, Liu Zhu

A possible process for extracting tellurium and antimony from a residue generated in alkaline sulfide leaching of telluriumbearing alkaline skimming slag was proposed. The central composite design was employed to define the optimal leaching conditions for tellurium and antimony extractions from the residue sample. Using a 23 factorial matrix, the best performance for tellurium and antimony extractions (96.36% and 99.64%) were obtained at 175 g L−1 Na2S concentration for 80 °C during 60 min. The notable degree for influencing tellurium and antimony extractions was leaching temperature, Na2S concentration, and leaching time. The analysis of variance results indicated that the regression model was significant and suitable to be used for the optimization of independent variables within the range. The model was validated under optimal operating conditions based on the experimental design results. Antimony and tellurium in the leach liquor were separated and recovered by H2O2 oxidation followed by Na2S-Na2SO3 reduction. 98.93% of antimony was precipitated selectively during H2O2 oxidation, while 95.06% of tellurium was precipitated during Na2S-Na2SO3 reduction. NaSb(OH)6 and elemental tellurium was obtained as the product.

By C. Deutsch

Resource estimation for the West Leeville deposit is prepared using a conventional explicit approach. The geologic model is developed using interpretive methods based on visual logging. Grade shells are then prepared at low and high grade cutoffs. The low grade shell includes material of interest (Au > 0.010opt), while the high grade shell is developed slightly below the economic cutoff grade for mining. Grade estimates are made within these boundaries. This paper documents a conditional simulation study to evaluate the uncertainty contributed by both the grade shells and grade estimates. Multiple realizations are generated for the grade shells and the grades. The full combinatorial of realizations are merged to assess the uncertainty and the relative contribution of the grade shell and grades.

Jan 1, 2007

By Kent C. Condie

Precambrian terranes in the Rocky Mountain region decrease progressively in age from the Archean Wyoming Province (> 2.5 b.y.) to the late Proterozoic in West Texas (figs. 1,2). Within the Wyoming Province, most dates fall near 2.7 b.y. although some are recorded at 2 3.8, 2.9, and 2.6 b.y. Although Penokean (- 1.8 b.y.) deformation and plutonism are recorded in southeastern Wyoming, most Precambrian rocks south of the Wyoming shear zone, which separates the Archean and Proterozoic provinces, are < 1.76 b. years in age. Supracrustal rocks in Colorado, western Arizona, and northern New Mexico fall in the range of 1.72-1.76 b.y., those in central New Mexico about 1.65 b.y., those in southeastern Arizona and southwestern New Mexico about 1.70 b.y., and those in West Texas 1.1-1.2 b.y. The Wyoming Province is comprised chiefly of 2.7 or 2.9 b.y. tonalitic gneiss terranes intruded by 2.6 b.y. granites in the central and southern parts of the province. Supracrustal rocks are minor and include greenstone belts comprised chiefly of pillow- ed tholeiites and graywackes and remnants of quartzite-shale successions. Metamorphic grade in greenstone-gneiss terranes ranges from upper greenschist to amphibolite facies and in quartzite-gneiss terranes from upper amphibolite to granulite facies.

Jan 1, 2013

By W. P. Arnott

This paper presents real time photoacoustic measurements of diesel-soot black-carbon (BC or EC) and Dusttrak nephelometer total carbon (TC) concentrations in a Nevada gold mine. Comparisons with time-integrated filter-based measurements of EC and TC accomplished using the NIOSH 5040 method were found to be 50% smaller than the integrated real time measurements. This work was initiated primarily as a demonstration project for the usefulness of photoacoustic instruments in measuring BC in the mine environment. Real time black carbon measurements are very useful for determining miner exposure, for providing feedback in mine ventilation systems, and for quantifying machine specific emission rates to understand the operating conditions for specific machines that produce greatest black carbon concentrations. This paper reports real time measurements of DPM from a loaded and empty hauler as it is operated in a drift with a 12% grade. The photoacoustic instruments were demonstrated to be satisfactory for BC measurements in the mine environment.

Jan 1, 2009

By Michael Kukay, Paul Conrad, Cosmas Opoku-Ware

This project is exploring the potential for developing trees tolerable to degraded un-reclaimed mine site soils and tailings as a solution to re-establishing long-term tree growth on those sites. The project incorporates growing tree seedlings in an underground greenhouse grown from seeds planted in the degraded mine soils in which they will eventually be planted. The outcome of the project is expected to lead to a successful solution for re-establishing tree growth in soils and tailings containing high metal concentrations with minimal post-planting human intervention. The research is being conducted in an underground greenhouse located 100 ft below the surface in the old Orphan Boy Mine Underground Mine Education Center (UMEC) located on Montana Tech’s campus in Butte, Montana.

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 Eugie Kabwe

Rock bolts are components of tunnel support structures and their efficacy in reinforcement requires the appropriate estimation of the bolt pre-tension. However, cases of ineffective rock bolt application due to loosening are common which leads to the potential failure of the support structures, thus negatively affecting the tunnel stability. The effective employment of pre-tensioned bolt within support structures requires an appropriate installation tension as a result of sufficient bolt head/nut pre-load. Henceforth, this paper presents a load indicator washer (LIW) capable of withstanding assigned static loading as well as provides an appropriate pre-tension. The different LIW breadths are numerically analysed in the finite element code (ABAQUS) to estimate deformation when a designated 60-kN pre-load is applied. The numerical simulation employs a bi-linear isotropic hardening constitutive law governed by the von Mises yield criterion. The simulation also considers the nominal temperature of the nutLIW-rock bolt connection. Therefore, a long-term relaxation effect on bolt pre-tension as a result of stress relaxation is neglected. The compressive force required to achieve the LIW-predetermined deformation is the bolt pre-tension. It is drawn from the simulation results that the 1.5-, 2.0-, 3.0-, 3.5-, and 4.0-mm-thick LIWs are completely flattened when subjected to 28-, 42.5-, 65-, 76-, and 88-kN pre-load respectively.

One of the biggest challenges for the mining industry is, quite literally, how to the keep the equipment rolling. There is a limited amount of companies that manufacture the 4.2-m- (14-ft-) tall, 5,670-kg (12,500-lb-) tires needed for the haul trucks that are approaching the 362 t (400 st) pay-load class, such as Terex?s MT6300-AC and Caterpillar?s 797F. And, while these might be the most impressive tires, they are not the only ones that are in short supply. The shortage of tires has affected just about every kind of machine, and the demand for those tires has been extremely high for more than five years with no end to the shortage in site. American Tire Corp. (www.americantire.us) is one of the companies working to supply tires to the mining industry. It announced that the demand for its 1.6-m (63-in.) tires that have a zero failure history globally is great and that the company signed contracts worth more than $500 million at MinExpo. A relatively new player in the field of large tires for mining equipment is Titan Tire Corp., (www.titan-intl.com), a subsidiary of Titan International Inc. It shipped its first 1.6 m (63 in.) off-the-

Jan 1, 2008

By J. Hansen

This paper has been written for presentation during the Open Pit Mining Session at the SME Annual Meeting and Exhibit, Denver, Colorado, February 26 to 28, 2001. The paper addresses the application of automated monitoring of electric rope shovels to improve performance and blasting technique.

Jan 1, 2001

By J. D. Morgan

The US economy continued to grow steadily in 1988, reaching an annual rate of $5 trillion in the last quarter (US trillion = 1012). The value of domestically processed mineral-based materi¬als rose 20% to $300 billion (US billion 109). The value of metals produced from US ores rose 40% to more than $10 billion, industrial minerals rose 6%&apos; to $20 billion, and recycled scrap more than doubled to $10 billion. Increasing economic activity stimulated metal prices. Yearly lows and highs were 95 cents and $1.68 for copper, 52 cents, and $1.30 for aluminum, 34 cents and 42 cents for lead, and 43 cents and 75 cents for zinc. A number of mining and metal companies experienced significantly increased profitability. Consumer demand strongly affects mining because the US economy is relatively saturated with long-lived products. Consumer, mortgage, and Federal debt continued to rise. About 246 million US citizens already possess 170 million licensed motor vehicles and 100 million dwelling units. New car production remained at the 1987 level of 7.1 million units. Truck and bus production, however, rose 7% to 4.1 million units. New housing starts fell 7% to 1.5 million units. Imports supplied a significant proportion of total US consumption of several important mineral materials. By year-end, imports of crude and refined petroleum exceeded domestic crude oil production. Such imports cost $42 billion. Imports of nonfuel mineral-based materials were valued at $44 billion and exports at $35 billion. The US and Canada-the world&apos;s two largest trading partners-consummated a historic free trade agreement. In February, President Reagan transferred responsibility for stockpiling strategic and critical materials to the Secretary of Defense. And, in July, the GSA group that bought, stored, rotated, and sold stockpiled materials was transferred to the Defense Department&apos;s Defense Logistics Agency. Concern about apartheid in South Africa continued, resulting in increasing attention to chromium, manganese, platinum-group metals, cobalt, vanadium, and gold. The Defense Production Act, authorizing priorities and allocations, supply expansions, voluntary agreements, and the National Defense Executive Reserve, was amended to include provisions for averting harm to national security from foreign takeovers. The DPAct, in effect through September 1989, is now up for further extension. Under the Act, the US Bureau of Mines maintains the Emergency Minerals Administration. During the year, consultations were held with Canada to strengthen the North American Defense Industrial Base. Coal production, 60% from open pits, rose 5% to 870 Mt (960 million st). Nearly four-fifths was burned to generate 57% of US electricity. Exports included 56 Mt (62 million st) of metallur- gical coal and 29 Mt (32 million st) of steam coal, with a total value of $4 billion. Domestic petroleum produc¬tion fell 2% to 574 hm3 (3.6 billion bbl). Uranium mining, including recovery from phosphates, was unchanged at 5.9 kt (6500 st). Nonfuel minerals Major metals Raw steel production-a major con¬sumer of many minerals-rose 14% to 92 Mt (102 million st). Domestic iron ore production rose 25% to 59 Mt (65 million st), about 96% pelletized. Net imports rose 37% to 16 Mt (18 million st). Raw steelmaking capacity of 102 Mt (112 million st) was unchanged. Voluntary Restraint Agreements with 21 steel exporting nations limited im¬port penetration to about 20% of the domestic market. Domestic producers of bulk ferroal¬loys of chromium, manganese, and sili¬con operated at about 75% of capacity. The US mined no manganese or chro-

Jan 1, 1989