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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 Tom Martin

Mega projects present unique challenges with regard to estimating costs. With such projects, which may span decades, these challenges often begin as soon as a project is conceived. The importance of having a sound, resource based estimate avail-able early in the process cannot be overstated because it provides the basis for ongoing project decisions. For the final phase of providing an updated cost estimate, often while bidding by contractors is underway, the Engineer?s Estimate (EE) must incorporate present market conditions; account for possible volatile material price swings; be based on actual labor and fringe costs; rely on meaningful productivity rates; and accommodate any recent technology advances while identifying and allowing for risk factors. This paper explains the benefits associated with consultants adopting a contractor?s estimating approach when preparing the Engineer?s Estimate on mega projects like the various tunneling projects in New York City.

By G. Abramov

The 20th Century saw the modern mining industry enriched by one outstanding method of extracting of mineral resources called Borehole Mining (BHM). Mean while, despite its successful track record in wide ranging locales, few specialists are yet aware of this technology. The intent of this article is to introduce borehole mining to a wider spectrum of drilling and mining professionals. The BHM method is based on in-situ water jet cutting of rock mass. On Fig. 1 the schematic of the method is presented. The borehole mining tool 1 is lowered into the borehole 2 and high pressure water 3 is pumped down. At the bottom part of the tool, one portion of that water comes out through the hydromonitor nozzle 4 in a shape of water jet 5 and cuts the material 6 creating slurry 7. The other portion of high pressure water then comes to the hydroelevator 8 (jet pump, eductor) which produces a vacuum. When the slurry reaches this vacuum zone, the eductor sucks the slurry and pumps it up to the surface, where rock parts are separated from water in a tank 9 or a pond and clarified water is pumped down again closing the re-circulating BHM water supply system. The borehole mining tool is suspended on a drill rig tower 10 which allows the tool to rotate and move vertically along the borehole axis. While extracting rock mass, underground caverns (stopes) 11 are created. If necessary, compressed air 12 can be injected to the raising slurry flow to create an airlift effect. Also, a secondary agent 13 (such as oil, foam, etc.) can be added to the stope through the gap between the tool and the casing. As seen from the illustration, BHM is the remote mining method of extracting of mineral resources through boreholes by high pressure water jets.

Jan 1, 2001

By A. Founie

The United States continues to be the world’s leading producer and consumer of diatomite. Production of diatomite in the United States during 2004 was estimated to be 635 kt (700,000 st). This was a 2-percent increase from 2003. The value of processed diatomite in the U.S. was about $164 million in 2004. Production was from six companies with 13 processing facilities in four states. Nevada and California were the principal producing states. They accounted for about78 percent of the U.S. production during 2004. U.S. diatomite exports were about 136 kt (150,000 st). Imports were negligible.

Jan 1, 2005

By C. D. Ashley, X. P. Garzon-Villalba, R. M. Lopez, T. E. Bernard

Federal standards for refuge alternatives (RAs) mandate that they not exceed a Steadman apparent temperature (AT) of 95 °F (35 °C) at an assumedmetabolic rate of 325W, a limit that appears to be arbitrary. Occupants in an RA spend most of their time at rest (a metabolic rate less than 325 W), and thermal equilibrium can likely be maintained at an AT > 35 °C. The purpose of this study was to examine the upper limit of sustainable heat stress during 4- and 8-h exposures at rest. Five men underwent five 4-h trials (phase 1: AT range 39 to 49 °C, 90% rh) and five 8-h trials (phase 2: AT range 46 to 56 °C, 90% rh) in a semi-recumbent position. Descriptive statistics for gastrointestinal temperature (Tgi), heart rate (HR), systolic and diastolic blood pressure (SBP and DBP), sweat rate, fluid intake, urine color, urine specific gravity (USG), and changes in body mass are reported. Mean Tgi for all trials ranged from 36.9 to 37.3 °C, and mean HR for all trials ranged from 61 to 75 bpm. To determine the effects of increased heat exposure, differences in heat strain between 4- and 8-h trials were examined via repeated measures analysis of variance (ANOVA). As AT increased, there were no significant changes in ?Tgi and ?HR from 1 to 4 h in the 4-h and 8-h trials. During the 8-h trials, as AT increased, there was a difference in ?Tgi between 4 and 8 h. In conclusion, there was support for sustainable exposures resulting in no significant increase in physiological strain at an AT greater than 35 °C AT, with a sustainable limit (no increases in Tgi due to increases in AT) below 46 °C AT. Although the participants were not representative of coal miners, the results provide support for sustainable exposures greater than 35 °C AT at an average metabolic rate of 155 W.

Nov 8, 2019

By R. L. Virta

Six companies mined fire clay in Missouri and Ohio during 2004. Production, based on a preliminary survey of the fire clay industry, was estimated to be 398 kt(438,700 st), valued at $9.81 million. This was slightly less than the production and value figures from 2003. Missouri was the leading producer state. It accounted for more than 70 percent of the U.S. production. Consumption Domestic producers sold or used fire clay primarily for refractory applications. This application accounted for 79 percent of the market. Refractory products made using fire clay include firebrick and block, grogs, high-alumina brick and specialties, refractory mortars and mixes, and saggers.

Jan 1, 2005

By Euclid P. Worden

INTRODUCTION Today, conventional raise boring is an accepted method of development in underground mines and on major construction projects. Over the years that this technique, and its associated machines and tools, have been under development, many articles have been written on the subject. To a great extent, these papers have reported operating results of one or more specific projects or have been generalized reviews of state-of-the-art machines and tools. This paper is intended as a review of the technique from an operational standpoint. Conventional raise boring, as opposed to the related variants box hole drilling and underground blast hole drilling, is a two step process consisting of the pilot hole drilling and reaming cycles. This author has covered the subject of pilot hole drilling in another article (1) . A good review of the current machines and equipment has been presented by Monroe (2) and an overall review of this entire technology was published by E&MJ (3) and Mining Journal, April, 1983 (4) . The subject of the reaming cycle is presented here together with some of the technical aspects of how the drilling tools are intended to be used. OPERATIONS Bit Change After the pilot bit has broken through at the end of the pilot hole cycle, a changeover takes place at both the machine and

Jan 1, 1985

By Joseph L. Petrillo

In July 1997, Kvaerner Environmental signed a unique contract with Echo Bay Alaska called the Transfer Risk and Accelerate Closure (TRAC). The contract called for Kvaerner to assume the responsibilities and obligations associated with closeout of the Alaska-Juneau (A-J) Mine. Kvaerner is an international engineering and construction company with global interdisciplinary experience in the mining industry and environmental remediation. Echo Bay’s requirements called for Kvaerner to: •Provide a fixed price for closure with no change orders. •Negotiate, prepare and implement a final closeout plan as outlined by Echo Bay. •Complete a closure program that exceeded current regulatory requirements. •Improve, expand and maintain a proactive public and community relations program. •Hire Echo Bay employees where possible. •Provide adequate performance guarantees and judicial relief of environmental claims.

Jan 1, 1999

By Patrick Scott, Germán Schmeda, Morgan Mullins, Liam Knudsen, Bradley S. Van Gosen, Carma A. San Juan, Nicholas A. Karl, Jeffrey L. Mauk, Clayton Forbush

The objective of the US Geological Survey’s mineral deposit database project (USMIN) is to develop a comprehensive twentyfirst century geospatial database that is the authoritative source of the most important mines, mineral deposits, and mineral districts of the US. Since May 2017, the project has focused on critical minerals. Data for critical minerals that are produced as products are relatively robust, whereas data for critical minerals that may be recovered as byproducts are commonly of much poorer quality. Similarly, more is known about critical minerals that occur in conventional deposits than where those critical minerals occur in unconventional deposits. For example, rare earth elements occur principally in deposits hosted by alkaline igneous rocks, but there is potential for their production from phosphate rock mining, which is less documented. Lithium (Li) has been recovered from pegmatites and brines, but other Li-bearing deposit types have been delineated that may go into production. Cobalt may be produced as a byproduct or coproduct from a wide range ofmineral deposit types, whereas rheniumis a byproduct of copper ore. Significant opportunities for research exist that could help identify new sources of critical minerals, and may also help increase production and recovery from existing sources.

Feb 8, 2021

By Ebrahim Farrokh

Ghomroud water conveyance tunnel project is under construction using shield Tunnel Boring Machines (TBM) for a total length in excess of 50 km. Phase 1 of the project included 36 km of tunnel divided into four lots (1, 2, 3, and 4) of nine km each. Lots 3 and 4 of this tunnel for a total length of 18 km were combined into one award and have been constructed using a double shield (DS) TBM or one path system. Extreme ground convergence in some sections of the tunnel has stalled TBM performance in early reaches, due to face collapse and shield jammings. This paper presents the latest update on the tunnel progress and impact of ground convergence on machine performance based on the information obtained from field observations. Also, the method and results of tunnel convergence measurements were studied in conjunction with geological parameters and an attempt was made to correlate TBM operational parameters and ground convergence. The result of the analysis indicates a good correlation between machine?s operational parameter and tunnel convergence and can be used as an indicator of the potential for high rates of convergence. An early warning on ground convergence is essential for taking precautionary measures to avoid TBM jamming and related long delays and costs.

By Frederick A. Mumpton

Recent findings by medical workers on the association of certain zeolite minerals with the high incidence of pleural mesothelioma in two small Turkish villages have caused considerable excitement both in medical circles and in the synthetic and natural zeolite businesses. The 42 cases diagnosed between 1970 and 1977 in one community of 600 population in a region of altered volcanic tuff represent a virtual epidemic of this rare malignancy which normally strikes only about one person in a million. Cancer workers around the world expect that detailed environmental and epidemiological studies of the disease in these areas will shed considerable light on the cause of this particularly lethal form of lung cancer. Scientists and engineers developing uses for zeolite materials in industry and agriculture, however, are justly concerned that the preliminary results available on this situation will be used by environmental and regulatory organizations to label an entire group of miner- als as carcinogens on the basis of what is little more than circumstantial evidence. Although there is no question as to the large number of cases of mesothelioma in these areas of central Anatolia, the work to date has suffered from a lack of sound geological and mineralogical input. Ataman (1) stated that a "correlation" exists between mesothelioma and zeolites in this region; however, the geological data needed to document a direct relationship between the presence of zeolites in the volcanic tuffs surrounding the villages in question and the rate of malignant lung disease in the inhabitants have g been obtained, nor has evidence that suggests a cause-effect relationship between zeolites and cancer been reported. To provide fundamental information on the distribution of zeolite minerals in areas of central Turkey where high incidences of pleural mesothelioma have been reported and to evaluate from first-hand knowledge the published reports and news releases of medical workers engaged in assessing the problem, the following investigation was made.

Jan 1, 1979

By J. R. Heberger

"“Safety Pays in Mining” web application developed by the U.S. National Institute for Occupational Safety and Health Mining Program, helps mines determine the potential costs associated with mining injuries. This web app groups injuries by type, either by the cause of the injury or by the nature of the injury. When the user selects one of more than 30 common types of mining injuries, the app provides information on the distribution of costs of workers’ compensation claims for that type of injury. Based on other user inputs, the app will estimate the total costs of the selected injuries, including an estimate of additional indirect costs, the estimated impact of total injury costs on mining company profits, and provide some examples of other items, such as services or equipment, on which companies could spend the savings that result from the prevention of injuries. This paper reviews the app by discussing its development, how it is used to show the true costs of mining injuries, and how mines can benefit from using it.IntroductionInjuries on the job cause pain and suffering. They can also profoundly affect profits and daily operations. In addition to paying direct costs or increased premiums for workers’ compensation insurance, a company might need to pay overtime for other workers to fill an injured worker’s job role, cover training costs for a replacement worker or divert administrative resources in the wake of an injury. “Safety Pays in Mining” is a web app that estimates the distribution of these injury costs and assesses the impact that occupational injuries have on a company’s profits.The costs of specific types of occupational injuries in mining are not readily available as mining and insurance companies do not usually share this information. As a consequence, companies only have cost information based on previous experience with their own employees. Therefore, if a mine never experienced a finger amputation for one of its miners, for example, it would not be aware of the possible costs associated with this type of injury. In addition, injury costs are unique in that the cost distribution is so wide that just using the average cost of a specific injury type does not provide adequate information. Some injuries involve immensely high costs, and even though the risk of these high-cost injuries occurring is low, mines need to be aware of the potential impact on their company’s financial health."

Dec 1, 2018

By Tyler Acorn, Brandon Wilson, Jeff Boisvert

Project-scale decisions in surface mining operations rely on the optimization and subsequent evaluation of pit limits. This process ignores the ability for mine plans to adapt as more information is gathered. Stochastic methods, which consider uncertainty in the pit optimization, generally act to refine the boundaries of the pit on a fine scale. This paper extends uncertainty-based methods to consider unique scenarios through a clustering of the realizations that are being optimized. This results in the generation of multiple sets of similar realizations. A separate pit is optimized on each set of realizations, resulting in the production of a series of planning scenarios. This accounts for the adaptability of mine planning as more information is gained. A decision-making framework is then applied to the resulting scenario plans to select the optimal choice. The improvements stem from the joint uncertainty considered when realizations are grouped that is not considered when the probability of a block being in any optimized pit is considered. Mining operations today can benefit from considering additional planning options as identified and evaluated in this workflow.

By Andrea Brickey, JUDITH BUABA, RICHARD AMOAKO

The global mining industry has recorded significant declines in accident and injury rates attributed to the advancement in technology, increased enforcement, and safety consciousness. A goal of the mining industry is to achieve zero injury and occupational illness on all mine sites, prompting increased research into ways to further reduce mine accidents. A machine learning technique known as multiclass logistic regression is applied on a 10-year injury dataset from the Mine Safety and Health Administration (MSHA) to determine a miner’s susceptibility to a class of injury and to help identify significant risk factors associated with different classes of injury. The data is aggregated based on injury classification to provide statistically relevant results. The analysis identifies specific risk factors that influence a mine worker’s susceptibility to a given class of injury, i.e., non-fatal with no days lost or restricted activity, non-fatal with days lost and/or days of restricted work activity, and fatal and total permanent or partial permanent disability. These factors include miner’s age, mine type (coal vs. non-coal), experience on the current job (years), shift start time, employment type (operator vs. contractor), mining district, and type of accident. The results of the analysis indicate that a miner’s experience on the job, i.e., the number of years worked in a current job, is a significant risk to injury occurrence, even for those with decades of total mining experience. We further show the differences and similarities between the surface and underground mine incidents.

Nov 3, 2020

By H. Kinilakodi

The authors previously developed a methodology that combines injury and citation measures into an overall mine safety performance evaluation tool, called the safe performance index (SPI). It can be easily adopted by mine operators to monitor trends in their injury and citation experiences as a risk assessment method. In this paper, six normalized safety measures and the SPI are used to evaluate the health and safety risk that existed at mines in the two years preceding the occurrence of a fatality. The percentage of mines is given for which the risk was high or where trends of some of the safety measures indicated moderate risk. In 50% of the mines, this mine safety performance tracking method could have been helpful to the companies, state agency or the U.S. Mine Safety and Health Administration (MSHA) in recognizing and addressing emerging problems with actions that may have been able to predict high-risk conditions, the fatality and/or other serious injuries. The approach would have given extra scrutiny to the risk for mines that encompassed 74% of the fatalities during 2007-2010.

Jan 1, 2012

By Jacob Carr, Chenming Zhou, Nicholas Damiano, James Noll, Jingcheng Li

Machine-related injuries are one of the major safety concerns in underground coal mines. Severe injuries and fatalities occur when a miner is struck, crushed, or pinned by mining equipment such as a continuous mining machine (CMM), shuttle car, or a scoop. Proximity detection systems (PDSs) have been applied in mining to reduce these types of injuries and fatalities. All of the PDSs that are currently approved by the Mine Safety and Health Administration (MSHA) for use in underground coal mines are magnetic-field based and could be affected by metallic objects such as trailing cables. Researchers from the National Institute for Occupational Safety and Health (NIOSH) investigated the influence of trailing cables on the performance of PDSs. In particular, the magnetic field coupled from proximity system generators to a de-energized trailing cable was characterized. The results show that significant energy can be coupled from the proximity system generators to a trailing cable when there is a closed loop in the cable. The effect on PDS performance from the magnetic field radiated around an energized trailing cable was also quantified for different current amplitudes in the cable. It is shown that the magnetic field caused by the electric current in the trailing cable mainly consists of a 60-Hz signal and its harmonics which causes little interference to the PDS. The results presented in this paper can help PDS manufacturers to design better systems that are more immune to these effects.

By R. L. Virta

Twenty-three companies mined kaolin in nine States in 2004. Production was estimated to be 7.6 Mt (8.3 million st) valued at $912 million, based on preliminary data. This was a slight decrease from 7.68 Mt (8.46 million st) valued at $939 million in 2003.Georgia was the leading producer state with an estimated 6.5 Mt (7.1 million st) in production. It was followed, in decreasing order of tonnage, by South Carolina, Alabama, California, Texas, Arkansas, Nevada, Florida and North Carolina. Georgia accounted for nearly the entire domestic water-washed, delaminated, and pigment-grade calcined kaolin production. Consumption Sales to the paper industry accounted for 49 percent of domestic sales and 64 percent of total sales. Other major markets for domestic sales were refractory products (10 percent), paint (5 percent), fiberglass (4 percent), catalysts (3 percent) and rubber (2 percent).Paper coating and filler markets accounted for about 87percent of export sales of kaolin.

Jan 1, 2005

By Guowen Dong, Qiyong Li, Qiang Li, Tiejun Chen, Zhihong Wu, Junying Wan

In order to search for a more economical and effective roasting additive for extracting vanadium from stone coal and solve the question of the disposal of PVC waste, PVC waste was proposed as a novel roasting additive to enhance extraction of vanadium from stone coal and realize the comprehensive utilization of resources. By adding this roasting additive, the leaching rate of vanadium reached 94.5% under the conditions that the PVC waste addition was 10 wt%, the roasting temperature was 800 °C, the roasting time was 1 h, the sulfuric acid concentration was 15 vol%, the liquid-to-solid ratio was 1.5 cm3 /g, the leaching temperature was 95 °C, and leaching time was 4 h, which increased by 8.4% compared with that of blank roasting. The thermodynamics calculation showed that the decomposition reaction of mica was performed easier with the participation of HCl produced by pyrolysis of PVC. Meanwhile, The SEM-EDS and aperture test analyses demonstrated that more cracks and voids appeared in the roasted sample by roasting with PVC waste, which could facilitate the release and extraction of vanadium. Additionally, the TG-DSC analyses indicated that PVC could provide large amounts of heat for the roasting process to promote the decarbonization and roasting efficiency of stone coal because of its high calorific value.

By Guowen Dong, Qiyong Li, Qiang Li, Tiejun Chen, Zhihong Wu, Junying Wan

In order to search for a more economical and effective roasting additive for extracting vanadium from stone coal and solve the question of the disposal of PVC waste, PVC waste was proposed as a novel roasting additive to enhance extraction of vanadium from stone coal and realize the comprehensive utilization of resources. By adding this roasting additive, the leaching rate of vanadium reached 94.5% under the conditions that the PVC waste addition was 10 wt%, the roasting temperature was 800 °C, the roasting time was 1 h, the sulfuric acid concentration was 15 vol%, the liquid-to-solid ratio was 1.5 cm3 /g, the leaching temperature was 95 °C, and leaching time was 4 h, which increased by 8.4% compared with that of blank roasting. The thermodynamics calculation showed that the decomposition reaction of mica was performed easier with the participation of HCl produced by pyrolysis of PVC. Meanwhile, The SEM-EDS and aperture test analyses demonstrated that more cracks and voids appeared in the roasted sample by roasting with PVC waste, which could facilitate the release and extraction of vanadium. Additionally, the TG-DSC analyses indicated that PVC could provide large amounts of heat for the roasting process to promote the decarbonization and roasting efficiency of stone coal because of its high calorific value.