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By Austin Metz, Kevin Stanton, Ramin Motamed

"A recent study calibrated Load and Resistance Factor Design (LRFD) resistance factors for local soil conditions in the Las Vegas Valley. As a part of this calibration, an extensive database of drilled shaft load tests and associated subsurface soil information were collected and compiled. This database, deemed the Nevada Department of Transportation Deep Foundation Load Test Database or NDFLTD, was designed with the presentation of load test data, the subsurface soil conditions, and the spatial distribution of the data in mind. In addition, the NDFLTD was developed in a way that allows additional data to be added as it becomes available. As such, the rules of database normalization were followed to allow for additional and different types of data to be added to the database and reports. Microsoft Access was chosen to present the data because it is easily accessible to anyone with Microsoft office software, it has a quick learning curve, and it has the ability to present a relational database. The largest obstacle faced when creating the NDFLTD was normalizing the data used in the LRFD calibration, with the goal of reaching the 5th normal form.INTRODUCTIONLRFD is based on statistical performance of engineering components, as opposed to the more traditional Allowable Strength Design (ASD), which divides the strength of a component by a safety factor. Calibration of resistance factors for LRFD requires a robust statistical analysis of past performance. For drilled shafts this requires a database of full scale load tests (Abu-Hejleh et al. 2014). The FHWA developed the largest US based deep foundation load test database, deemed the DFLTD, collecting data from 1985 to 2003 when funds ran out (Abu-Hejleh et al. 2014). Recently, the DFLTD has been updated to modern standards (Petek et al. 2016). In October of 2007, the FHWA mandated state department of transportations (DOTs) to follow AAHSTO LRFD guidelines for their highway foundation designs (Abu-Hejleh et al. 2014). Since then multiple state DOTs have developed their own, region specific deep foundation load test databases. Florida has a long history of developing databases for deep foundation LRFD resistance factor calibration, with the two main databases being the FL database, and The Deep Foundations Database (Abu-Hejleh et al. 2014). Iowa developed a Microsoft Access based database in 2014 (Garder et al. 2014). Oregon developed a database compiling pertinent data from the DFLTD, Florida DOT’s Deep Foundation Database, as well as from other databases (Smith et al. 2011). Illinois developed the “International Database” for static and dynamic reliability based calibration (Long et al. 2009). Louisiana developed a database for LRFD Calibration of driven piles in 2009 (Abu-Farsakh et al. 2009). The California Department of Transportation has its own internal foundation database, which is housed within the Foundation Testing Branch archive (Smith et al. 2011). In 2016, the Nevada Department of Transportation (NDOT) presented its own LRFD calibration for the Las Vegas Valley (Stanton et al. 2017), and the NDFLTD was developed as a part of that project (Motamed et al. 2016)."

Jan 1, 2017

Jan 1, 1915

By A. N. Diehl

IT is the object of this paper (1) to deal with the elements in blast-furnace gas from the standpoint of their importance, and the part they are to play in future consumption, and (2) to give detailed information about the construction and operation of a plant designed among the first in this country for washing gas on a large scale.

Jan 5, 1914

By Richard F. Link, George S. Koch

About 50,000 assays of mine samples were required in a preliminary investigation of the distribution of gold, silver, lead, copper, and zinc in two large Mexican mines, the Frisco mine at San Francisco del Oro (Chihuahua) and the Fresnillo mine at Fresnillo (Zacatecas). The feasibility of working with so many assays rests directly on the use of machine processing methods. The purpose of this article is to describe the methods used because machine (or data) processing can also be used efficiently to make the many calculations from mine assays needed in mining operations. No particular originality is claimed for these methods, which are straightforward applications of standard procedures for machine processing. Inasmuch as machine processing is essentially a routine job once it is begun, procedures must be organized more completely than is the case where human judgment can be inserted at every step. Before undertaking any work, it is necessary to decide carefully just which data must be processed as well as the exact results desired.

Jan 9, 1960

By Ken Witherly

Modern airborne EM surveys typically acquire more data than is processed or analyzed at the time of acquisition Suitable additional processing can provide more diagnostic information, thereby allowing for more effective ranking and hopefully, follow-up of outcomes

Apr 1, 2005

By Shankar Narasimhan

Data Reconciliation is a technique that has been developed more than fifty years ago and has been refined over the past few decades and is now being deployed routinely in several process industries such as refining, petrochemicals, mineral processing and hydro-metallurgy. The main aim of data reconciliation is to obtain accurate estimates of all process variables and parameters using plant measurements that are invariably corrupted by random errors and may also contain biases and other gross errors. These reconciled estimates are subsequently used either in offline exercises such as simulation, retrofitting, and de-bottlenecking or in online optimization and control applications. In this presentation, a brief history of data reconciliation, its assumptions, and uses are reviewed. New developments in this area are highlighted such as robust data reconciliation to handle model uncertainties, and reconciliation using identified models derived purely from operating data. Several case studies in the mineral processing industries reported in the literature are also highlighted to indicate the potential benefits of this technique.

Sep 1, 2012

The objective of the paper is to develop a material balance calculation procedure for a production unit involving two plants separated by a pipeline. The case study is taken from the oil sands industry. The raw sands are first mixed with water in a conditioning plant, then transported through a pipeline to an oil extraction plant. The combination of pipeline dimensions and nominal throughput creates a significant variable time lag between the two plants. As usual, mass balance calculations required for the evaluation of plant performance indicators, such as bitumen recovery, are inaccurate due to measurement errors. In addition, in the present case study, the time lag of the pipe creates an additional source of uncertainty, which may lead to misinterpretations and wrong decisions. Raw data are usually reconciled through steady-state mass balancing, to correct for measurement errors. However, because of the significant pipeline dynamic lag, standard steady-state daily mass balance may fail at giving an appropriate picture of the operations. The proposed solution to the data reconciliation problem includes the use of a pipeline plug-flow model in the mass balance calculation. To fulfil the industrial constraint that current data reconciliation must not modify past reconciled values, while still satisfying dynamic constraints, a daily one-step method, i.e. a unitary filter-ing horizon, is recommended. The method is illustrated with simulation data, and the results com-pared to those of standard data reconciliation methods.

Jan 1, 2014

By K. El-Ouassiti, M. Zouadi, C. Bazin, D. Hodouin

Data reconciliation techniques are used to attenuate the effect of measurement errors and estimate unmeasured variables. This paper illustrates the application of data reconciliation to hydrometallurgy processes using measurements from leaching and solvent extraction obtained from laboratory experiments. The application of data reconciliation provides an efficient way to detect gross and systematic errors and produces reliable performance indices for process evaluation.

Jan 1, 2005

By A. Alfantazi, M. Mahon

The current efficiency in zinc electrowinning is a key indicator of the performance in a cell house. This is typically measured by comparing the weight of the cathode to the electric current applied over the deposition period. This calculation can be cumbersome because the deposition history of each pulled set of cathodes will be unique. It will depend on the applied current and electrolyte conditions from onset of deposition until the cathode is removed and stripped. Not accounting for these can introduce errors to the calculated current efficiency. To track this history and reconcile the current efficiency, a time based computer process simulation was made of an industrial cell house. Two months of hourly recorded measurements from the cell house were input to the simulation, including current to the cell houses, concentrations, flow rate, and temperature of the purified leach solution. The simulation’s predictions of the concentration of zinc in the circulated, spent, and returned electrolyte all showed good agreement with the industrial data over the two months giving a validated zinc balance. The simulation was then tuned to predict the instantaneous current efficiency for all times, as well as the expected masses for the deposits given their deposition history.

Jan 1, 2014

By Gerald V. Jergensen

Does an idea have merit? What does it cost to implement? Can the concept be implemented successfully? The ultimate proof is to try, then see. However, when there are many millions of dollars at stake, blindly building and trying requires considerable courage. Owners and investors in retrospect might choose other less complimentary words. So we might ask, "How might we establish the feasibility of an idea or concept before committing large sums of money to the ultimate test?" From this basic and prudent question, has evolved the engineering concept of the feasibility study. A feasibility study is simply a systematic evaluation of an idea or concept to determine the prospects for success. In a literal sense, a feasibility study considers an idea in terms of its data base, "builds" the idea on paper, "operates" that idea, calculates the cost and benefits, then measures the probable success in terms of some economic, technical or financial standard. Feasibility studies can be quite modest in scope yet provide useful insights as to the viability of an idea. A study might be initiated only to examine the completeness or validity of the metallurgical data base. Another study could be a search for a workable idea or solution to an already-identified possibly troublesome problem. In this latter case, the question, "Will it work?" may be far more important than, "How much will it cost?" Feasibility studies are sometimes global in scope, involving several dozens of specialists and examining an entire "grass roots" mining complex. Other studies may be less ambitious but equally important in examining an expansion proposal or developing new operating techniques. Studies may be commissioned to remove plant bottle-necks, solve maintenance problems and so on. The terms study and feasibility study are used interchangeably in this chapter. They denote a systematic method to examine a proposed concept or idea. DATA BASE Typically, studies are initiated with a minimum amount of specific information and a maximum number of assumptions. As the work proceeds and the data base expands, assumptions are replaced

Jan 1, 1982

By Dale R. Ralston, Roy E. Williams, Gerry V. Winter, George L. Bloomsburg

GENERAL STATEMENT The primary objectives of any field data gath¬ering effort should be to (1) identify and gather the data necessary for the project and (2) obtain the data in a state-of-the-art manner. All too often the initial field data are collected both areally and tem¬porally in an illogical manner without the guidance of a conceptual model of the ground water flow systems involved or even a review of existing geo¬logic literature on the area of interest. The initial data collected frequently are of limited value while necessary basic reconnaissance information is miss¬ing. Initial field data should be collected with the intent of developing a hydrologic overview of the potential mine site and surrounding area. Ob¬viously, one of the initial objectives is to define the area requiring a hydrologic investigation. The data requirements should be identified by the time frame in which collection should be made and by the corresponding increase in sophistication of the data requirements with development and operation of the mine. The data requirements are summarized in Table 1. INITIAL LEVEL SITE INVESTIGATION Area Determination The initial task of any hydrogeologic investi¬gation is to determine the boundaries of the area requiring study. Obviously, the site of the proposed mine is included in the study area. The areal extent beyond the site may be determined from an eval¬uation of existing geologic and topographic maps. Those formations that overlie the ore body, the formations containing the ore body, and the formation(s) that lies immediately beneath the ore body are of direct concern for proper site recon¬naissance. Additional formations below the ore body may require study depending upon their thick¬ness, hydraulic conductivity, and degree of inter¬connection with the mine workings. This initial viewpoint identifies hydrostratigraphic units based strictly on geologic concepts such as mineralogy and structure. Formation outcrops, synclines, an¬ticlines, faults, and fracture and joint patterns are used to delineate the area of the site reconnaissance. The simplistic hydrogeologic environment (il¬lustrated in Fig. 3, chapter 2) requires that field data be collected via test wells and/or geophysical techniques. This approach is necessitated by the lack of surface features such as formation outcrops, streams, and springs. Fig. 5 (chapter 2) illustrates a slightly more complex hydrogeologic regime. The potential mine sites at locations A, B, C, D, and E each intercept a different ground water flow sys¬tem or combination of flow systems. Therefore, each mine location requires that a different area and size of area be investigated. A more complex geologic setting as illustrated in Figs. 6 and 7 (chapter 2) may be approached differently. The area included for the site recon¬naissance should encompass sufficient surrounding area to include the outcrops of those formations suspected of being influenced by the future mine. Even adjacent areas not suspected of being influ¬enced may be investigated if the formations of in¬terest crop out in those areas. Such an extension of the area of investigation would provide a greater regional understanding of the hydrogeologic properties of the formations (hydrostratigraphic units) of interest. Geologic Investigation The initial step before conducting the site re¬connaissance is to review all existing literature on the geology of the area. Existing information should be augmented with new exploration data on the dip, strike, thickness, and lateral extent of the for¬mations in the area. Exploration hole logs should be reviewed for indications of lost circulation, rub¬ble zones, and water producing zones. Existing aer¬ial photos such as those available from the US Department of the Interior, EROS Data Center,

Jan 1, 1986

By Jeffery L. Kohler, Harvinder Singh, Jon G. Bredeson

A survey of electromagnetic noise reports was performed and a summary of the results are given. Industrial concerns were surveyed for techniques to minimize the effects of electromagnetic noise and are presented. The common types of communication links used in mines today are presented. A mathematical development was presented which determines the probability of bit errors versus distance for various types of communication links designed for in mine use. The probability of undetected errors for the protocols of the communication links is given together with burst error detection.

Jan 2, 1981

By B. Samanta

Abstract - Ore reserve estimation, based on sparse drill hole data, was conducted for a placer gold property in Nome, Alaska. A problem with sparse data is that random subdivision of the data into modelling and evaluation subsets (as is commonly done) becomes a problem, as random selection may result in biased/skewed subsets. Therefore, a technique that combined data segmentation with genetic algorithms (GA) was applied to divide the samples into three equivalent subsets: training, validation and testing. Data segmentation was done on the basis of the distribution of gold values. Neural network and a variety of kriging techniques were used to estimate gold grades. A multi-layer feed forward neural network along with "early/quick stop" training was used for neural network modelling. A comparative evaluation of kriging and neural network methods was then performed. The results revealed that neural network was generally superior to the kriging techniques for gold grade estimation in the Nome deposit.

Jan 1, 2002

By C. Sunderman, R. Jacksha

"Mine monitoring through various sensors is a vital component of successful miner safety and health programs. Data from environmental, geotechnical, infrastructure, and other types of sensors are increasingly being used to discover and mitigate health and safety concerns in underground mines. In many smaller underground mines, as well as in new development headings of larger underground mines, leaky feeder communication systems may be the only available means to transport crucial monitoring data. In addition, data transport is increasingly being delivered using Internet Protocol (IP) while older forms of serial communication are being retired. This paper presents the selection, configuration, and testing methodologies that were employed by researchers from the National Institute for Occupational Safety and Health (NIOSH) to integrate commercially available land mobile data radios into an existing leaky feeder communication system to provide Internet Protocol data transport. INTRODUCTION To enhance the health and safety of their mining workforce, mine owners and operators are increasingly installing environmental monitoring and control systems in underground mines. Real-time, mine-wide monitoring is becoming a reality with the implementation of the Industrial Internet of Things (IIoT) into the underground mining industry [1]. However, not all underground mines, especially smaller mines and new development headings in larger mines, have the information technology (IT) infrastructure in place to handle the data transport requirements for the newer IP-based technologies that are part of IIoT. This was the case with a mine in the Western United States; it lacked the infrastructure to perform critical monitoring in remote headings. The mine partnered with the U.S. National Institute for Occupational Safety and Health’s (NIOSH’s) Spokane Mining Research Division (SMRD) to develop and evaluate a cost-effective solution for real-time monitoring of geotechnical conditions in relatively remote sections of the mine. This paper describes SMRD’s solution to leverage the mine’s existing leaky feeder system to achieve IP data transport using commercially available land mobile data radios. DATA RADIO SELECTION The primary selection criteria for the data radios were network data format, modulation type, and radio channel spacing. The network data format decided upon was Internet Protocol. This format allowed for straightforward integration between the IP-enabled data acquisition system located in a remote heading and the network switch located in the control room. It also eliminated the added complexity of additional network hardware such as Ethernet to Serial converters. IP additionally provided a direct path to integration into higher bandwidth networks, such as fiber optic, should they become available."

Jan 1, 2018

By C. Sunderman, R. Jacksha

"Mine monitoring through various sensors is a vital component of successful miner safety and health programs. Data from environmental, geotechnical, infrastructure and other types of sensors are increasingly used to discover and mitigate health and safety concerns in underground mines. In many smaller underground mines, as well as in the new development headings of larger underground mines, leaky feeder communication systems may be the only available means to transport crucial monitoring data. In addition, data transport is increasingly being delivered using Internet Protocol (IP), while older forms of serial communication are being retired. This paper presents the selection, configuration and testing methodologies employed by researchers from the U.S. National Institute for Occupational Safety and Health (NIOSH) to integrate commercially available land mobile data radios into an existing leaky feeder communication system to provide IP data transport.IntroductionTo enhance the health and safety of their mining workforce, mine owners and operators are increasingly installing environmental monitoring and control systems in underground mines. Real-time, mine-wide monitoring is becoming a reality with the implementation of the Industrial Internet of Things (IIoT) into the underground mining industry (Zhou et al., 2017). However, not all underground mines, especially smaller mines and new development headings in larger mines, have the information technology infrastructure in place to handle the data transport requirements for the newer Internet Protocol (IP)-based technologies that are part of IIoT.This was the case with a mine in the Western United States. It lacked the infrastructure to perform critical monitoring in remote headings. Therefore, the mine partnered with the U.S. National Institute for Occupational Safety and Health’s (NIOSH) Spokane Mining Research Division (SMRD) to develop and evaluate a cost-effective solution for the real-time monitoring of geotechnical conditions in relatively remote sections of the mine. This paper describes SMRD’s solution to leverage the mine’s existing leaky feeder communications system to achieve IP data transport using commercially available land mobile data radios (NIOSH, 2013; Forooshani et al., 2013; Novak, Snyder and Kohler, 2010; Yarkan et al., 2009). The solution, fully evaluated in laboratory and mine environments, requires no modifications to the existing system, is economical, simple to implement, and reliable. It also allows for transition to higher-bandwidth IT networks, such as fiber optic or WiFi, should they become available."

Dec 1, 2018

By Frédéric Flament

The aim of this paper is to present the development of a data validation software as component of a commercial mass balance package. Data reconciliation through mass balance is basically an optimization problem constrained by the law of mass conservation. As any optimization problem solved with a modern and robust software application, erroneous information or starting point will always lead to a solution, whether it is realistic or not. Moreover, good information wrongly weighted by an incorrect error model will lead to the same bad ending. In an industrial context where competition requires accurate information, data reconciliation without validation can be disastrous and calls for data validation before and after reconciliation. The challenge in automated data validation resides in the development of general theoretical solutions. Until now, none has been presented and only partial solutions are available. The development presented in this paper incorporates some of these partial solutions. The integration of human knowledge into the application paved the way to a more general solution. The combination ?theoretical validation ? human expertise? proved to be flexible and reliable enough to be integrated in a commercial data validation package. Numerous examples though industrial applications are presented. These applications demonstrate the validation of raw measurements, user support in the development of error models and validation of reconciled measurements.

May 1, 2001

When the writer first began his search for the early history of coal he was amazed at the paucity of information in literature about it, and while after six years many of the reasons for such a scarcity are understood, there are still many cases, even within the last two centuries, when one who can appreciate the tremendous part coal has played in the development of modern times, finds it hard to realize how little attention was paid to this material in those early clays. Occasionally a traveller or observer is found who foresaw how valuable coal was to be when industries were developed, but these were few and to most of those recording its occurrence it was just another mineral. George Washington was farsighted in his view of the development of this country and the need for means of transportation across the mountain barrier, but it was at least sixteen years after he must first have known of coal before he made any reference to it in his journals. He did, however, knowingly or not, select some valuable coal properties in the lands lie obtained in the West. This was then almost entirely an agricultural country, and what industries there were found a great abundance of wood fuel within easy access, there were no steam plants, and all iron was made with charcoal; in fact, the "captive mines" of the iron industry then were large timber "plantations," and when these were exhausted the furnace usually was abandoned and another one built elsewhere, as transportation of charcoal was quite expensive. Along the seaboard the cities and industries began to import coal from England and Nova Scotia early in the eighteenth century, but until the war of the Revolution began the total quantity of coal used yearly in this continent did not exceed nine thousand tons. In 1800 only two places, Pittsburgh and Richmond, Virginia, were using coal to any extent for domestic purposes and it was much later. than this that the amount of coal used in Philadelphia, New fork, and Boston exceeded that of wood. Practically all of the early travellers and writers mentioning coal are noted in the following pages. Several Englishmen who were evidently familiar with its use and value at home, mention its presence as being of great future promise to the young nation, but to nearly all it was more or less of a curiosity and the smoke caused by its use an abomination, and it

Jan 1, 1942

By F. Wang, P. Rosario, A. Vazirizadeh

Advances in data science, machine learning, and artificial intelligence are transforming mining and mineral processing, and making them more algorithm intensive. The paradigm is shifting from one of detection and control to one of prediction and optimisation. To build up reliable prediction and optimisation models these steps should be passed: collect, aggregate, cleanse, and process large amounts of complex, structured, and unstructured data as a first stage. Next, the right tools must be used to extract meaningful features from the operational data for the build-up of a prediction model. A grinding circuit is one of the challenging areas in terms of determining its overall efficiency and the prediction of product quality. In a processing plant, some of the KPIs are typically unmeasurable or infrequently measured for real-time application, e.g. ore grindability and grind size. However, these variables are required to calculate the grinding circuit efficiency and to model the operation performance. In this paper, advanced analytic tools have been used to extract one selected KPI (cyclone overall P80 or final grind size) and its relationship with measured variables for an industrial dataset. The results illustrate that the performance of the grinding circuit can be predicted for real-time monitoring by means of measured data. Keywords: Grinding circuit, data-driven, machine learning, process modelling, hybrid modelling

Jan 1, 2020

By M. Szumny, P. Mertuszka, K. Fuławka

Multi-face destress blasting is the basic method of reducing rock bursts hazard in Polish copper mines. Blasting operations of this type are carried out regularly, twice a day in order to minimize the geomechanical threat while maintaining high extraction efficiency. Unfortunately, the assessment of the effectiveness of this type of work until recently was based solely on determining whether a given destress blasting triggered a seismic tremor or not. Information on the characteristics of seismic waves generated by blasting has so far been omitted in analyzes of this type. The lack of reliable knowledge about the generated seismic effect makes the introduction of constructive corrective actions impossible, which in turn significantly reduces the triggering potential of conducted destress blasting. This study presents the results of comprehensive work aimed at increasing the effectiveness of active rock burst prevention in Lubin underground copper mine. For this purpose, an innovative system for continuous monitoring of seismic waves induced by multi-face blasting was developed, and a new method for seismic assessment of the effectiveness of the destress activities was developed. Based on the monitoring data and the comprehensive analysis of waveforms, the effectiveness of individual blasting operations was determined, and on this basis, modifications to the drilling and blasting patterns aimed at increasing the generated seismic effect were proposed. The use of innovative methods of monitoring and data analysis made it possible to increase the effectiveness of the conducted activities, in terms of the magnitude of seismic vibrations, up to 250%. It should be emphasized that the introduced modifications were aimed at increasing the effectiveness of blasting operations while maintaining the current level of costs. As a result, the proposed solution turned out to be highly effective, significantly affecting the safety of the work carried out in Polish copper mines. Thus the proposed approach is planned to be implemented in other Polish copper mines belonging to KGHM in the near future

Jan 1, 2024

By C Zhang, R Liang, I Canbulat, S Saydam, B Li

The integration of digital twins in mining represents a significant advancement towards enhancing operational efficiency and decision-making. Central to this development is the role of visualisation, a crucial element in mining digitalisation. This paper aims to develop a data-driven visualisation solution for the construction of mining digital twins, highlighting how this innovation revolutionises the representation of physical mining environments. It spotlights the shortcomings of conventional visualisation methods, particularly their inability to accurately depict complex underground environments and their predominantly historical orientation. To address these challenges, this paper proposes a novel, data-driven approach. This approach extensively utilises CAD files, encompassing data from geological surveys to intricate mine plans, thereby significantly elevating the precision of digital twins. It supports real-time updates and enables flexible interaction with a variety of data types. Moreover, it introduces a comprehensive data diagram alongside the adaptation of a 3D tile index. This strategy ensures the efficient rendering of extensive mining environments, allowing for a more dynamic and interactive digital twin model. In conclusion, the implementation of data-driven visualisation in the construction of mining digital twins marks a pivotal advancement in the industry’s digital transformation. It promises a more detailed, accurate, and dynamic depiction of mining operations.

Sep 1, 2024