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By J. H. Calder, J. C. Hower

Three lithotypes of Phalen coal from Cape Breton County, Nova Scotia, Canada, were subjected to a modified Hardgrove grindability index (HGI) test. The testing scheme differed from conventional (ASTM D-409) Hardgrove testing by, in one case, repeating the test three times prior to removing the -200-mesh fine coal from the Hardgrove mill, and, in a second test, removing fines after each of three successive Hardgrove tests. Only the first stage of the latter testing scheme actually conforms to the standard HGI test. All processed samples were analyzed petrographically by a combined maceral/microlithotype analysis. The increase in the percentage of coal ground to -200 mesh increases through the 60- to 180-mesh fractions for each of the lithotypes for the following two apparent reasons. First, with progressive grinding, more of the oversize material is close to 200 mesh (75 µm), creating a "pool" of particles ready to be ground to -200 mesh, and, second, the removal of fines from the system at each step eases the grinding at the successive step. The fines retained system shows the influence of buffering of further grinding by the particles retained in the grinding mill. The Phalen lithotypes and the series of Central Appalachian coals, evaluated previously by Hower and Wild (1994), differ in that an increase in vitrite and a decrease in trimacerite is observed in successive -200-mesh fractions in two of the Phalen lithotypes. This is the opposite of the trend observed in the slightly lower-rank Central Appalachian coals.

Jan 1, 1998

By A. S. Trimble, J. C. Hower

The petrographic composition of sized coal produced through the progressive grinding of a Central Appalachian high-volatile bituminous coal blend was analyzed for multiple sets either by removing fine, -200-mesh, coal after each test iteration or by retaining the fine coal in progressive test fractions. With prolonged grinding, coarser fractions tend to become depleted in vitrinite and vitrinite-rich microl ithotypes, leading to progressively harder-to-grind coal remaining in the oversize, +200-mesh, fractions. The latter trend is shown both by the maceral and microlithotype composition of the coal and by the increased slope and fractal dimension of size frequency distribution, implying an increase in hardness and resistance to grinding of the oversize coal.

Jan 1, 2000

By Sebastian Avalos, Julian M. Ortiz, Willy Kracht

Semi-autogenous grinding mills play a critical role in the processing stage of many mining operations. They are also one of the most intensive energy consumers of the entire process. Current forecasting techniques of energy consumption base their inferences on feeding ore mineralogical features, SAG dimensions, and operational variables. Experts recognize their capabilities to provide adequate guidelines but also their lack of accuracy when real-time forecasting is desired. As an alternative, we propose the use of real-time operational variables (feed tonnage, bearing pressure, and spindle speed) to forecast the upcoming energy consumption via machine learning and deep learning techniques. Several predictive methods were studied: polynomial regression, k-nearest neighbor, support vector machine, multilayer perceptron, long short-term memory, and gated recurrent units. A step-by-step workflow on how to deal with real datasets, and how to find optimum models and final model selection is presented. In particular, recurrent neural networks achieved the best forecasting metrics in the energy consumption prediction task. The workflow has the potential of being extended to any other temporal and multivariate mineral processing datasets.

Jun 16, 2020

By Carlos Fonseca, Gustavo Usero, Roberto Mentzingen Rolo, Gabriel Moreira, Octavio Rosa de Almeida Guimarães

Geological domain modeling is an important step in mineral resources evaluation. The procedure can be laborious and time-consuming, especially in multivariate settings. However, estimates are significantly improved when carefully limited by geological variables. This paper proposes a workflow for geological domain modeling suited for stratigraphic deposits. The workflow consists in automatically defining the domains by using clustering algorithms, generating the surfaces that represent the contacts by interpolation and subsequent triangulation, and simulating the surfaces. The proposed workflow produces consistent and realistic results and allows the user to test different domain configurations and assess volumetric uncertainty automatically and quickly.

Jun 25, 2023

By Maral Malekian, Pat Bellett, Eranda Tennakoon, Fernanda Carrea, Moe Momayez

Slope instabilities in open-pit mines pose a safety risk to workers and a financial burden on production. The direct impact of slope stability on safety and production makes slope failure predictions one of the important challenges in the mining industry. Predicting the precise time of slope failure has been the subject of much research in conjunction with the development of innovative monitoring technology designed to prevent sudden failures. This paper investigates the use of AutoRegressive Integrated Moving Average (ARIMA) model to predict the time of slope failure. Input data such as inverse velocity (IV) and dimensionless inverse velocity (DIV) from 20 slope failures were used to train the model predict the failure time. For comparison purposes, the time of slope failure using the traditional inverse velocity method is also provided. We show that ARIMA provides 90% more accurate predictions than the TIV approach.

Jul 12, 2023

By S. Frimpong, D. Ali

For achieving bulk economic excavation, large dump trucks are being used in majority of the earth moving operations resulting in high impact shovel loading operations (HISLO) which exposes the operators to high levels of whole body vibrations (WBV). As the truck ages, hydro-pneumatic suspension struts loses their capability to effectively attenuate the vibration. A system is required to monitor and predict the performance of the suspension struts in real time. Machine learning and artificial intelligence (AI) has been applied for modeling and predicting the suspension system performance for lighter/smaller vehicles. However, no work has been done to implement machine learning or AI for modelling and predicting the performance of hydro-pneumatic struts in large dump trucks. Therefore, current work is going to be a pioneering effort towards developing machine learning and AI models for solving this problem. Support vector machine (SVM) and regularized dual non-linear regression has been implemented in order to achieve the goal. 3D virtual simulator for CAT793D was used to conduct experiments in MSC.ADMAS environment. The two main recorded outputs were the RMS accelerations in the vertical and horizontal directions at the operator seat for characterizing the performance of the suspension system. During the development and the training of the models, eighty percent (80%) of the total experimental data was used and the remaining 20% was used during the testing and validation of the developed models. SVM model showed the desired accuracy in terms of hydro-pneumatic suspension system performance prediction for large dump trucks. These models can be implemented in the dump truck controller which can then be used to monitor the performance of the suspension system in real-time, and with that proper maintenance and/or replacement can be scheduled by the maintenance personnel. Workplace safety, operator’s health and the overall system efficiency can be greatly improved with an implementation of such an intelligent system. INTRODUCTION Large capacity dump trucks are being employed in any earth moving operation throughout the world for achieving bulk economic excavation [1, 2]. A large dynamic impact force is produced with large capacity shovels dumping material weighing 100 tons or more in to the dump truck under gravity. This dynamic impact force generates high frequency shockwaves which travels throug0068 the truck body, chassis and reaches the operator’s cabin and thus exposes the operator to severe levels of whole body vibrations (WBV). Recommended safe limits have been listed by the International Standards Organization (ISO) in sections 1, 2, 4 and 5 of ISO 2631 (1997, 2003, 2001 and 2004). An operator can got through a long term back, shoulders, arms and neck disability and disorders if exposed to the WBV levels beyond those limits. The dynamic impact force generated as a result of the high impact shovel loading operations (HISLO) was modelled by Ali and Frimpong [2]. Furthermore, the complete methodology for optimizing the dumping process and reducing the impact force has been provided by Ali and Frimpong [1]. The vibration attenuation system present in the dump truck requires improvement in addition to the dumping process optimization. The vibration attenuation system in the dump truck commonly consists of hydro-pneumatic suspension struts. As the dump truck ages, its suspension system deteriorates and therefore loses its capability to effectively attenuate the shockwaves and the resulting vibrations produced by the dumping process. The deterioration tales place due to the contamination of the hydraulic oil or oil and nitrogen mixing or due to the gas accumulator diaphragm rupturing. The monitoring of the output vibration levels can be used to evaluate the effectiveness of any suspension system. With the dump truck suspension system, the vibration levels at the operator’s seat can be used for the evaluation of the effectiven

Jan 1, 2019

By K. KAKLIS, O. SAUBI, Z. Agioutantis, R. JAMISOLA

Machine learning in the form of artificial neural networks was applied to investigate whether specimen load evolution can be predicted as a function of acoustic emission (AE) signals in the case of three-point bending (TPB) marble specimens instrumented with piezoelectric sensors. The ultimate objective of this study is to develop a model that can quantify rock behavior under loading that can lead to rock-failure prediction in underground structures subjected to bending, such as roof failure in development or production openings.

Nov 1, 2022

By K. KAKLIS, O. SAUBI, Z. Agioutantis, R. JAMISOLA

Three-point bending (TPB) tests were conducted on prismatic Nestos marble (Greece) specimens. The specimens were instrumented with piezoelectric sensors, and comprehensive recordings of acoustic emission (AE) signals were obtained. Machine learning in the form of artificial neural networks (ANNs) was then applied in an effort to investigate whether specimen load evolution can be predicted as a function of AE signals. A number of ANN models were developed, and the optimum model was selected based on the highest coefficient of determination (CoD) value as well as the lowest root mean square error (RMSE) value that was calculated for each model. The best performing ANN model exhibits accuracy above 99% with an RMSE value below 4%. It can be concluded that ANNs can potentially be applied to predict rock behavior under load especially when such loads lead to failure.

Sep 7, 2022

By John A. DesLauriers

INTRODUCTION This paper will update the status of small sized tunnel boring machines used in both the Mining and Civil Industries. I will mention a) new developments in small size hard ground tunnel boring machines, b) review North American performance records of the Atlas Copco Mini/Midi Fullfacers, and c) compare relative costs in driving a 1200m (4000 ft) typical utility tunnel using a leased TBM versus the conventional drill and blast method. NEW DEVELOPMENTS JARVA MACHINES Of all small rock tunnel boring machines currently in use, the Jarva MARK VI and MARK VIII are receiving the most enthusiastic acceptance. These circular fullface borers using usually 15 inch single disc cutters (manufactured also by Jarva) are designed on the 'T' bracing principle. Previously, Jarva's line of tunnel boring machines, even their smallest, was designed on the 'X' or double diagonal bracing configuration with a gripper in each quadrant. In small tunnels where net room is so very important, the 'T' scheme with gripping only at the spring line nets precious room around the cutter unit for passage of men and supplies. It allows freer un-

Jan 1, 1981

By C. Hendricks

This paper is based upon field studies conducted in a western Canadian open pit coal mine. This work has involved the adaptation of microprocessor-based instrumentation to monitor various operating parameters on-board blasthole drills and mining shovels. A review of instrumentation and monitoring methodology will first be presented. Based upon experience from field-based studies, the paper will subsequently focus on the application of monitoring technology within the framework of an integrated Equipment Monitoring System. Such a system will permit the real-time performance evaluation of key equipment involved in surface mille production.

Jan 1, 1991

By I. Ocak

Initial investment for mechanical boring of tunnels is found to be high in most cases. Conventional drilling and blasting is not the possible especially in urban area. In these conditions impact hammer offers many advantages over conventional drill and blast techniques and boring tunnels. These include improved safety, minimal ground disturbances, elimination of blast vibration, reduced ventilation requirements, reduced cost etc. Therefore, hydraulic impact hammers have been used widely in metro tunnelling projects in Istanbul since 1992. Accumulated and published data from various tunnelling projects serve to improve predicting the machine performance and scheduling of job duration. This paper is prepared under this objective. Machine utilization time of impact hammer was evaluated in this study. The main rock formation named Kartal formation arepaleozoic aged sedimentary rocks, shale, sandstone, siltstone, andesite dykes and sediment fillings. The first stage of the project is commissioned to Yapi Merkezi- Yuksel- Dogus- Yenigun- Belen consortium.

Jan 1, 2011

By A. Adhikari, P. Tukkaraja, S. Jayaraman Sridharan

Shafts are critical components of the mine ventilation systems and contribute significantly to the mine ventilation pressure. Estimation of shaft pressure losses is an important aspect of mine ventilation planning and shaft frictional pressure losses are extensively studies. Shock losses contributed by shaft buntons are estimated using the interference factor model developed half a century ago. This study aims to develop a better performing prediction model for shaft buntons using state of the art experiment and numerical data, and machine learning techniques. Results show that the present prediction model is performing poorly, and the prediction performance can be improved by incorporating additional predictor variables. The Artificial Neural Network standardized Machine Learning model developed in this study is able to predict the shaft bunton shock loss with high accuracy (R2 = 0.956).

Jun 25, 2023

By G. Kris Kapoor

Each new period of public concern, whether rooted in things political, social, economical, or technological, brings with it new words or phrases which highlight that new interest. With people's awareness of our rapid depletion of readily available energy sources and the enormous increase in energy .costs came the new, and now often heard, terms "energy intensive", "energy sensitive", and "energy conservation". Since its birth in 1926, Fuller Company had been directly associated and involved with energy intensive products and processes. We are located in the heart of the Cement Industry. Many of our products and processes are geared to the needs of the portland cement manufacturer, and a look at the inferno within an operating cement or lime kiln will certainly convince anyone that here is an energy intensive process. Fuller Company, then, has always been energy sensitive. Process kilns, hard rock crushers, tube and roller mills, fluid bed thermal reactors, pneumatic compressors and conveyors, material coolers - all are Fuller Company products utilizing or transferring large amounts of energy. Consequently, much of our success in the marketplace depends on how wisely we design and plan for efficient use of power and for conservation of each unit of heat available.

Jan 1, 1975

By A. Smithson

It is generally accepted by British mining engineers that coal will continue to be worked by the. advancing or retreating longwall system for the foreseeable future. At the coal face, the emphasis will be on better machine utilization; increased equipment reliability; modular design and more standardization; remote control and monitoring; and a continuing drive to increase productivity and safety. Improvements at the face can be sustained only if there are corresponding improvements in efficiency elsewhere in the mine. Coal handling systems, for example, must be able to accept increased tonnages without creating bottlenecks. As workings move further from the shafts, the time taken to transport men and materials must be kept within reasonable limits. Development drivages must he on schedule to be ready for the planned opening of new faces, and face ends must keep up with faster moving faces.

Jan 8, 1981

By William G. Kegel

Apart from a usable product and good 'mining conditions, the greatest asset for a profitable coal mining organization is an effective mine maintenance program. The first step in achieving this is to have good mechanics-or men who want to be mechanics and are interested in knowing more about the design and control of the machines in their charge. A good mechanic's knowledge and ability result from ambition, curiosity, and determination. Starting with these qualities, the aspiring mechanic can launch his career by learning all he can about mechanics, electricity, and hydraulics. Though the path is rough, the end result is rewarding. Mining machinery probably receives as much, if not more, abuse as any other heavy equipment in use today. Considering the conditions under which much of the repair work must be done, it is essential that the mine operator has the best men and tools to perform the work. Mining machines, from their inception, have utilized the electric motor; and down through the years of mechanization, this power source has undergone many changes to better adapt it to the job. The first motors used were direct-current (d-c) motors since d-c power was the most economical power source for mining at the time of early mechanization. These motors were large open-type machines which are seldom used in modern mining. Because of the mine environment, the d-c motor has been reduced in size to better suit the application in mining machines and is now manufactured with dust-tight or explosion-proof enclosures. The d-c motor is constructed with either (or both) series and shunt fields located on the stationary part of the motor (stator) and- an armature coil wound on the rotating part of the motor (rotor). Power is supplied to the armature by brushes which are held stationary and make sliding contact with the armature. The brushes requires regular and careful maintenance because worn or defective brushes will cause heat or arcing which can destroy the motor. D-c motors can be used as d-c generators when mechanical power is supplied to them by the rotating shaft. In the case of a locomotive, this principle is used in dynamic braking. The momentum of the locomotive drives the motor and generates d-c power. The power is regulated with resistors and provides opposition to the motion of the locomotive.

Jan 1, 1981

By Wenhua Li, Tsuyoshi Adachi

Resource nationalism is essentially mandatory government intervention in natural resources businesses by political or economic means in order to benefit the nation and the people. It is attacking the mining industry more and more rampantly by all kinds of means since the twenty-first century. Poor countries who count on a resource-led economic growth usually find themselves trapped into “resource curse”. The harmfulness of resource nationalism for investors is that one event can quickly escalate and lead to a chain of events which make projects commercially unavailable. In spite of historical and theoretical social investigations in the causes of resource nationalism, rare studies engaged in quantification of dominant parameters of it. The objective of this study is to find significant factors that dominate the occurrence of resource nationalism for important metal and energy resources producing countries and quantify their marginal effects. The study applies binary choice logit model for panel data using pooled method. One feature of the research is that binary data set of occurrence of resource nationalism are sorted out by authors referencing U.S. Geological Survey’s reports. The results indicate that high-technology export (% manufactured export), ores and metals exports (% merchandise exports), rule of law (world governance indicator), trade (% GDP), and natural resource rent except forest (% GDP ) dominant the occurrence of resource nationalism for high and upper middle income group countries; government effectiveness (world governance indicator), policy perception index (The Fraser Institute), high-technology export (% manufactured export), and mineral rent (% GDP) dominant the occurrence of resource nationalism for lower middle and low income countries. According to our model, probability of occurrence of resource nationalism in 90 countries are predicted. Top 10 risky countries in 2012 are estimated to be North Korea, India, Honduras, Indonesia, Kazakhstan, Burkina Faso, Mongolia, Cuba, Bolivia, and Peru. The study is a primary trial of researching on resource nationalism and provides some insights for theoretical building and simulation on the issue.

Jan 1, 2017

By William D. Leech

Lebanon used a TBM for the firsttime to excavate a tunnel in the country. A main beam TBM, built in 1979, bored the 3.8 m (12.5-ft) diameter by 4,020 m (2.5-miles) Madiq Tunnel. The TBM bored through karstic terrain of dolomitic limestone, limestone and marly-limestone rock having near horizontal beds with more than twelve faults crossing the axis of the tunnel. The TBM also encountered more than six major karst features, filled with various combinations of boulders, clay, void space and water. The excavation through these collapsed-breccia zones drastically slowed the TBM?s progress. When complete, which the Madiq Tunnel is a part, the Kesrouane Water Project along the coast will bring fresh and irrigation waters to the parched and heavily populated region north of Beirut. The paper will describe the tunnel geologic features, karst genius, TBM upgrades and performance, and TBM/karst difficult situations

By G. L. Brooke

At present, there are two known cobalt deposits in the 48 contiguous states. This paper is a brief description of one of these deposits. It is a Mississippi Valley type deposit, but somewhat atypical in that the metal of greater interest is cobalt as opposed to lead, zinc, and copper. The history and present work are outlined along with a discussion of the geology and mineralogy.

Jan 1, 1981

By G. R. Brunskill

The molybdenite flotation plant at the Magma Copper Co. San Manuel concentrator has been in operation since 1956. In January of 1980, the plant was converted from a hydrogen peroxide-ferrocyanide process to the current sodium cyanide-sodium hydro- sulfide process. This paper is an operational review of Magma Copper Co.'s molybdenite recovery circuit, column cell flotation experience, and use of on-stream X-ray fluorescence analysis.

Jan 1, 1987

By M. F. Bradley, G. M. Schoen

The Magmont Mine, a 50/50 venture between Cominco American Incorporated (the Operator) and Dresser Industries, Inc., (Halliburton), is a metallic mining and milling facility in the new lead belt of Missouri. The mine is located approximately 100 miles southwest of St. Louis. Legislation passed in 1992 by the Missouri legislature requires all metallic mining and processing facilities to apply for a Metallic Minerals Waste Management permit (MMWM) for their waste facilities. Regulations were subsequently promulgated by the Missouri Department of Natural Resources (DNR). Cominco obtained a MMWM permit (MM-006) from the Missouri DNR in 1992.

Jan 1, 2001