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And a new generation of safety culture experts are telling mining companies how to use it: It is a situation that is still too common in the mining industry: the latest personal protective gear is in place. The safety rules are known and followed. And then, in a moment of inattention or carelessness, a mistake is made and someone gets hurt or killed. Common wisdom claims that such accidents are impossible to eliminate entirely. Mining is dangerous, and some miners will always be hurt and killed. An increasing number of mine safety experts, however, reject the common wisdom. A year with zero mining deaths is possible, they say; with the use of one of the newest weapons to the mining industry in the safety war: the concept of safety culture. Safety culture refers to the set of attitudes, beliefs, perceptions and values that influence safety in the work environment. It is also sometimes called the way an organization behaves when no one is watching. Robert Peters, of the Office of Mine Safety and Health Research (OMSHR) at the National Institute for Occupational Safety and Health (NIOSH), describes safety culture this way: ?It?s what?s believed on a day-to-day basis. For example, if a miner sees a workplace hazard and he truly believes that his boss wants him to identify the hazard and bring it to the company?s attention, that would be an example of a positive safety culture.?

Jun 1, 2010

By R. Dewey

WHAT IS AI? It's very hard to say. Most researchers and practitioners disagree with nearly any attempted definition, but most would agree that A1 does deal with the development of computer-related methods o f problem-solving. Artificial intelligence is a discipline which seeks to emulate human anatomy and/or thought processes by applying computer science, electronics, and mechanical engineering to the development of natural language processing, machine vision, robotics, and knowledge-based expert systems. Integration of these four fields will someday produce the robots of today's science fiction. A1 addresses problems of structuring large amounts of knowledge and representing relationships with rules and semantic frameworks rather than with mathematical equations. A1 is convergent rather than divergent - - conventional conputer applications use relatively small quantities of input to generate large output, but A1 generally reduces large amounts of information to establish a few major conclusions. The development of A1 has prompted greatly increased efforts on the part of scientists and engineers to understand just how humans think, organize information, approach problem-solving, and form conclusions. Some of the more exciting and possibly far-reaching advances in A1 are coming in this more-or-less soft-science area. Thirty years of A1 research (dating from a 1956 conference at Dartmouth College at which the term A1 was coined) has already spawned many widespread, almost ordinary, products: window graphics, hand-held controllers (mouse). function menus, etc., all in an attempt to make computers and people more compatible. WHAT IS AN ES? A1 can be used to develop EXPERT SYSTEMS, which are computer programs or systems which contain knowledge and rules by which problems can be solved. or at least by which possible solutions can be suggested for very complex problems. A1 can be used to better define problems so that solutions can be found. An ES is designed not to process numbers, but to process information according to rules and logic derived from actual practice and experience. WHY AI? WHY ES? Companies are increasingly aware of the value of accumulated knowledge and experience in designing, building, operating, and maintaining the increasingly complex or expensive physical plants in any business. As knowledge branches out and becomes more specialized, the accumulated learning of a veteran operator or manager or engineer becomes a scarce resource well worth preserving. EXPERT SYSTEMS offer a means of doing that, reinforcing, not replacing, human capabilities.

Jan 1, 1987

By J. Trow

Dowsing is really IESG which inductively locates electric gradients (dv/dx) on the flanks of SP anomalies. "Sensors" are in one?s head. The "meter" consists of one?s body, limbs, and two $.69 welding rods. The method was calibrated near Mamainse Point, Ontario, where IESG-negative chalcopyrite-bornite-chalcocite-native copper ores reveal mineral zoning related to the IESG-positive Keweenaw fault, down which oxidizing solutions moved. In Michigan, the IESG-positive Keweenaw fault suggests that oxygen-bearing solutions from the Jacobsville Sandstone moved downward to oxidize hydrothermal sulfur to produce native copper, and to supply sufficient water to satisfy Walter White.

Jan 1, 1992

By Brain W. Lawrence

Sublevel stoping generally is a large-scale open stoping method. It sometimes is referred to as long-hole or blasthole stoping. This method usually is applied to strong ore bodies that require minimal support and are surrounded by strong country rock. The ore body should be fairly regular in shape and well-defined. The dip of the footwall normally should be sufficient to allow broken ore to gravitate freely, although the method has been adapted successfully to mine some of the flatter ore bodies. Sublevel stoping is not dependent on the width of the ore body. Widths of less than 6 m (20 ft), however, make the utilization of long-hole drilling techniques more difficult. The main criteria for sublevel open stoping are competent ore and stable host rock, regular ore boundaries, and a footwall dip that exceeds the angle of repose of broken ore. Basically, the method entails providing access to the ore body at various subintervals between the main haul- age levels in order to drill and blast the intervening ore. Stope drilling is carried out from drilling drifts on the sublevels, and the ore is blasted in slices towards an open face, which generally is vertical on the downholes and may be inclined towards the open face for the up holes. The blasted ore gravitates to the bottom of the stope and is collqcted through drawpoints. Fig. 1 illustrates a typical sublevel stoping mine. The method requires extensive ore body development with relatively high capital expenditures. How- ever, much of the development is in ore, and production costs are comparatively low. Productivity rates are in the 13.6 to 27.2 t (15 to 30 st)/manshift range. The drilling, blasting, and loading operations are performed independently, and equipment utilization is high. Large outputs can be obtained with few units and limited personnel. Dilution with waste rock may occur if ore boundaries are irregular or if caving occurs, but 100% of the ore within the stope usually is recovered. Pillar recovery sometimes is a problem. It is at this point that most of the waste dilution occurs. At the time data was gathered for this report (1973), the sublevel open stoping method was used by more than 21% of the metallic ore mines in the US (9 out of 42 mines producing 1088 + t/day (1200 + stpd) and provided more than 12% of the total metallic ore production from these mines. DEVELOPMENT Access to a sublevel open stope mine is gained by a slope or shaft that is normally sunk in the footwall of the ore zone, away from any possible effects from blasting or other production operations in the stoping process. Main level interval is selected and usually varies from 45.7 to 121.9 m (150 to 400 ft), depending on the vertical extent of the ore body, the number of drawpoints required to maintain output, and the eventual stope height. The main haulage drifts are located at the bottom of the stope horizon, either directly in ore or in the footwall, with access crosscuts at intervals. Raises are driven up through the ore to connect to the level above and provide access and ventilation to the sublevel drilling drifts, which are driven horizontally in the ore for the length of the stope. Depending on the drawpoint system to be used, the stope is either undercut by a raise-and-cone system, from a scram or slusher drift, or simply provided with a drilling drift from which access is made at intervals to the main haulage level. A raise driven either at the end or in the middle of the stope (if stope access is from both ends) provides a start for opening up a vertical slot across the stope to establish a free or open face for long-hole drilling and blasting. Sublevel stoping has proved to be a relatively safe and economical system.

Jan 1, 1982

By Brain E. Gombos

The Allen Park Sanitary Sewer Overflow (SSO) Tunnel and relief sewer project, located in the city of Allen Park, MI, is a long-term corrective action designed to bring Sanitary District One?s sanitary system into compliance with its 2005 consent order and service contract with the Detroit Water and Sewerage Department (DWSD). The $20 million project is intended to reduce Allen Park?s wet weather discharges to DWSD, reduce bypass pumping to the Ecorse Creek and limit the future risk of basement flooding by providing storage during wet weather events and eliminating hydraulic bottlenecks in the sanitary sewer system.

Jan 1, 2013

By Bright Oppong Afum, Kojo Boakye, Kwaku Boakye

This research developed and simulated a novel multi-indicator Fatigue Detection and Alert System (FDAS) designed to enhance fatigue detection accuracy in mining environments. The system integrates a comprehensive set of inputs: eye blink rate, eye closure duration, yawning frequency, distraction levels, Pre-shift Check-in Scores (Self-report) and Electroencephalography (EEG) Levels. Using MATLAB’s Fuzzy Logic Rule Viewer (FLRV) and Simulink, simulations demonstrated the FDAS’s robust ability to process these diverse physiological and behavioural indicators accurately. It effectively classified operator fatigue into low, moderate, and high fatigue levels, consistently providing appropriate outputs and corresponding intervention recommendations across various mixed-signal scenarios. The system achieved a calculated accuracy of 85.19% across 27 test entries, with a standard deviation of approximately 1.8459, confirming its reliability for real-time fatigue monitoring. These findings highlight the significant potential of this fuzzy logicbased approach to proactively identify early signs of fatigue, substantially enhancing safety and operational efficiency in demanding mining operations.

Feb 22, 2026

By L. Hales

Neural networks are a generalized, multivariable non-linear modeling technique that can be used to model mineral processing operations. Neural networks will be described as will their use in modeling column flotation. Optimization of column flotation will be explored and discussed by using the neural network column models.

Jan 1, 1996

By Babu R. Yama

Artificial Intelligence research has produced several tools for commercial application. Neural Networks, Fuzzy Logic and Expert Systems are some of the techniques that are widely used today. Artificial Neural Networks (ANNs) are excellent predictive, pattern recognition, and data analysis tools. In the mining industry, ANN techniques are being used commercially for real-time process control applications. Modeling of spatial data, ore reserve estimation, tunnel design, longwall stability prediction, and geologic roof classification are additional application areas in which neural networks have been applied successfully. A standard back-propagation algorithm was used to train a series of neural networks for a real-world predictive task. After training and optimizing the neural network architecture, performance of the network is measured on an independent validation set. Results indicate a correlation coefficient of up to 84 % between the actual and predicted values. A neural network model is developed for learning the spatial continuity of a mineral field and, consequently, for predicting sulfur values given coordinate values. The neural network performed not only satisfactorily, but in some cases performed better than the kriging model.

Jan 1, 1997

By C. L. Karr

Researchers at the University of Alabama are investigating artificial intelligence based computer models of mineral processing systems. Two approaches have been found to be particularly effective in developing data-driven computer models. The first approach employs neural networks which are computational paradigms based on the mechanics of the human brain. They are able to extract the basic relationships between input and output variables from large data sets. The second approach combines fuzzy mathematics with genetic algorithms to produce an adaptive modeling system. Fuzzy mathematics provide computers with the capability of manipulating abstract concepts like those which humans use so effectively in decision making. Genetic algorithms are search algorithms that mimic evolutionary processes apparent in nature. Together, these two techniques can be used to produce an effective modeling system. In this paper, the two approaches to modeling are compared and contrasted with respect to accuracy and computational time while used to model three mineral processing systems: (1) a grinding circuit, (2) a hydrocyclone separator, and (3) a flotation circuit.

Jan 1, 1997

By Daniel Hodouin

Artificial neural networks (ANN) are of growing interest in a wide variety of applications. Pattern recognition, speech processing, financial analysis, signal processing and process control are at present the most successful ones. This paper is an attempt to illustrate the potentiality of ANN applied to mineral processing. An introduction to the technology of ANN is first proposed to describe the various components and to explain the various phases encountered in setting up a network. Then examples are given to illustrate the use of ANN dynamic modelling of mineral processing units or plants and in process control.

Jan 1, 1991

By Robert Bissonette, Samir Sbai

A critical component of implementing autonomous systems is the ability to use information from a robust sensory and information system to make sound, predictable, and repeatable decisions to assure safety. This means that any such system would need to evaluate what objects (people, equipment, boulders, etc.) of interest exist in that environment (with relevant data about identity, trajectory, characteristics, etc.), project a future continuum of those objects (including considerations for variabilities), and make control intervention choices to minimize risk due to exposures in the present operational area. The components of an overall system would include: a) sensor and data fusion, b) probability projection of future states, c) generation and evaluation of alternate futures, and d) implementation of best course of action to reduce risk. The National Institute for Occupational Safety and Health (NIOSH) Spokane Mining Research Division (SMRD) is studying this framework for applications for autonomous mining equipment. This paper focuses on using information from the sensor fusion engine to generate a continuous projection of future and alternate states (b and c above) incorporating the factors of confidence, accuracy, tolerance, and other variabilities. We refer to this as Machine Situational Awareness (MSA).

Jun 25, 2023

By M. Hepokoski, M. Klein

"Mine refuge shelters are designed to protect mine workers from hazardous environmental conditions after a mine disaster, but high temperature and humidity levels inside these shelters may pose a significant safety risk. Due to the safety risks associated with human testing, detailed thermal models of shelters and human occupants have been developed using TAITherm simulation software. These models are used to predict the temperature and humidity within the shelter resulting from metabolic heating, evaporation due to sweat and respiration, moisture and heat from the shelter’s carbon dioxide scrubbing system, and heat transfer within the shelter. A detailed human thermoregulation model simulates the sensible and latent heat generated by the shelter occupants, and predicts the occupant’s body core temperature and moisture lost due to sweating and respiration. This information is used to assess the safety of the shelter. This paper presents the technical details of the human thermal model, validation comparing the human model to human subject test data, and results of a mine shelter analysis. IntroductionPortable mine refuge chambers are used in U.S. coal mines to provide protection to mine workers from hazardous conditions following a traumatic event. Although these shelters are designed to supply clean air and sustenance for up to 96 hours, prolonged exposure to the mine shelter environment itself can pose a substantial risk to human safety. Heat generated by the shelter occupants combined with heat from the carbon dioxide (CO2) scrubbing system can raise the shelter interior temperatures and relative humidity to dangerous levels that can lead to heat stress in humans. Unfortunately, the thermal burden associated with mine shelter exposure is not well characterized due to potential hazards associated with underground human subject testing. In order to assess the thermal burden on people within a mine shelter environment, a detailed thermal model was created to accurately predict the temperatures and humidity levels within the shelter, and the impact of these environmental conditions on human occupants. The model consists of a mobile inflatable tent-type mine shelter with 23 humans, and includes the surrounding mine environment. The thermal simulations were performed using a validated commercial heat transfer prediction computer software. Additionally, a module of the software provided the capability to simultaneously model the thermophysiology of 23 unique humans contained within the mine shelter. The human thermal models accounted for the thermal interaction with the environment and provided a core temperature response prediction that can be used to evaluate survivability in heat stress situations (U.S. Army, 2003). The models can also be used to determine maximum occupancy in order to maintain safe temperature and humidity levels inside the shelter in specific mine environments, to optimize shelter size for maximum heat dissipation, or to simulate active cooling systems."

Jan 5, 2017

By Chiranjibi Santi, Amit Kumar Gorai, VIVEK KUMAR HIMANSHU

Air overpressure (AOp) and peak particle velocity (PPV) are the most undesirable effects of blasting in mines. It is an urgent need to design a predictor model for AOp and PPV for universal applications to minimize environmental effects and damages that occur due to blasting. The present study attempts to design an artificial neural network (ANN) model for the prediction of AOp and PPV in different conditions. In this study, the blast design parameters (number of holes, depth of the blast hole, stemming length, spacing, burden, distance of vibration monitoring location from the blast site, charge weight per delay) of two active mines (coal and iron ore) are considered in four different conditions for training and testing of the model for the prediction of AOp and PPV. The model was trained and tested in four different combinations of data (trained using data of one mine and tested using data of another mine, trained and tested using data of coal mine, trained and tested using data of an iron ore mine, trained and tested using combined data of both the mines) for examining the applicability in different conditions. The results indicate that R2 values are ranged from 0.886 to 0.908 and 0.8728 to 0.8959, respectively, in the prediction of PPV and AOp. A comparative study of the performances of the developed model with the other empirical model is also demonstrated. For this, the site constants of different empirical models were estimated individually for both the mines. The study results indicated that the ANN model performs much better than all the empirical models. It can be inferred from the results that blast vibration cannot be accurately predicted only from charge per delay and distance from the blast hole. The ANN model was considered many other factors and thus can predict the vibration level more accurately.

Jul 30, 2021

By Lynn B. Hales, Randy A. Ynchausti

Introduction There continues to be a large economic opportunity associated with improving process performance through advanced process control systems within the minerals industry. The basis for this opportunity lies in the inherently low efficiencies of many of the unit operations found in mineral processing plants as well as the continual variation that is present in the ores being processed. The ageless target of such control systems is improved recoveries and concentrate grades, higher processing rates and lower unit costs. Many plants are enjoying the benefits of modem, well functioning process control systems but few if any have achieved plant-wide optimization in an economical sense. As new process modeling and control technologies, such as neural networks, continue to evolve and develop, the potential for plant- wide optimization is becoming a closer reality. Neural network technology appears to have a significant potential in the general field of process control and control of mineral processing operations. Neural networks are an emerging technology that have been evolving out of the study of biological systems since the early 1940's. The first software simulation of neural computing networks was reported in 1956 by Nathanial Rochester of IBM Research during the first conference on artificial intelligence which was sponsored by the Rockefeller Foundation. Neural Networks Neural networks can be considered to be a class of computer program that perform their problem solving functions based on a rudimentary model of the human brain and how it solves problems. Traditional computer programs and even computers themselves solve problems or process data sequentially and in a deterministic manner. The human brain, on the other hand, processes data and solves problems in a massively parallel fashion. We think of computers normally in terms of having a single processing unit, sometimes a co-processor to assist in certain activities such as mathematical functions or communications, bytes of memory, processing speed and program/data storage size.

Jan 1, 1992

By Kurt Wiener

A major process control system is in some ways like a complex organism. The extremities, (that is, field instruments) are exposed to many hazards and suffer malfunctions of relatively minor and repetitive nature. Here I equate a stuck valve or dead transmitter with a skin abrasion or cut. The maintenance and repair of the extremities can be done by technicians with basic but thorough knowledge of relatively few problems and their solutions. Here I equate with administering Band-Aids and aspirin. On the other extreme, when the master control device (such as a computer) fails, one does not attempt home remedies. A "brain" specialist is called in. It is, however, crucial that the patient be able to clearly describe his symptoms. Getting down to the case at hand, a complex system consisting of field instruments, instrument racks, interface equipment, and perhaps a computer, may require maintenance at all levels. At the field equipment end where physical damage, corrosive atmospheres, reconfiguration, and routine calibration checks are common, the customer has the opportunity to develop a competent staff of maintenance people. The relatively high maintenance activity assures competence through repetition.

Jan 1, 1980

By Ossi V. I. Hintikka

There are several limestone deposits around the Lohja area in southern Finland. Raw material for cement rock is mined from some of them. The formations are geologically complicated, and therefore selective mining is used whenever possible. One of these mines is the Tytyri underground limestone mine, which is divided into two parts; Törmä and Solhem. In addition to the selective mining system hand sorting or picking must be used at the Tytyri mine to improve the overall grade of the blended limestone. Some means were needed in order to improve the quality and to increase the feed rate by the elimination of hand sorting. Sorting machines were considered and eventually a Sortex 811MW was pilot plant tested at the Ojamo mine near Tytyri. This machine now continues to be used on production.

Jan 1, 1971

By D. K. Adjei, G. Ofori-Sarpong, R. K. Amankwah

"Mercury (Hg) is toxic and has long-term effect on the muscle tissues, the brain and the central nervous system functions due to its bioaccumulation and biotransformation effect. Hg pollution around the world is high and this has attracted much global concern such as the Minamata Convention on Mercury, held in 2013. For several years, mercury has been the chemical of choice for Artisanal and Small-Scale Mining (ASM) gold extraction, accounting for about one-third of the global mercury consumption. A greater percentage of this ends up in the environment through open burning of amalgam, spillage and indiscriminate disposal of waste. To break this wall of mercury pollution, it is very important for the mercury used to be recycled through the use of mercury retort units. This brings into the limelight, the Lantern Retort which tries to synergise the high conductivity of steel and the see-through effect of glass, thus, improving the amalgamation process. A research conducted on improving the original Lantern Retort arrived at an appropriate distillation length of 5.08 cm which was used in redesigning a more efficient retort. The improved Lantern Retort recovered about 98% of the mercury used. INTRODUCTION Artisanal and Small-scale mining (ASM) is an informal mining activities which employ quite simple tools such as pickaxes, sluice boxes, shovels, chisels, metal bars, mattocks and water pumps for mining and processing of gold ores. The artisanal and small-scale mining (ASM) sector has served as source of employment for many people in developing countries including Ghana (Aryee, 2001; Hilson and Potter, 2003; Amankwah and Anim-Sackey, 2004; Amankwah et al., 2010) and has provided a substantial amount of foreign exchange through its activities (Hilson, 2001; Styles et al., 2010). Hentschel et al. in 2003 estimated that about thirteen (13) million people are said to be engaged directly in the small-scale mining activities worldwide. However, an estimated 100 million people are said to depend on this sector for their livelihood mainly in developing countries. In China alone, a projected number between 3 and 15 million people are engaged in artisanal and small-scale mining activities (Hentschel et al., 2003), whilst in Ghana, it is estimated that more than 1,000,000 people are employed directly or indirectly in the artisanal and small-scale mining activities, with 10% being women (Amankwah and Anim-Sackey, 2004; Amankwah and Ofori-Sarpong, 2014). In Ghana, ASM gold production has grown from a low of 2.2% in 1989 to a high of 34% in 2014. This figure is estimated to increase with proper documentation. This indicates that the sector has made significant socioeconomic impact on many individuals and communities as a whole. Notwithstanding the above positive contributions, the sector has also contributed to negative impacts on human, aquatic life and the environment in general due to indiscriminate mercury emission. This ‘pollution wall’ needs to be broken, and several interventions have been put in place including the use of retort units like the lantern retort (Adjei et al., 2014; Amankwah and Ofori-Sarpong, 2014)."

Jan 1, 2017

By J. E. Brownhill

This paper does not deal with the typical start-up issues of equipment, production capacity or work force. This is a description of the challenges faced and the changes made by the project team to bring to fruition the reconstruction of Port Inland. Many honored traditions and norms had to be overturned to find the winning combination that provided the productivity, flexibility and cost necessary to survive in today's competitive minerals environment. This paper covers the innovation in terms of machinery, operations, and management philosophy that permitted the renovation and reopening of Port Inland as a commercial limestone producer in the spring of 1992. Port Inland, constructed by Inland Steel in 1930, operated as a captive source of metallurgical grade limestone for the steel industry until its closure in 1989. Located in the Upper Peninsula of Michigan on the north edge of Lake Michigan, the operations consist of a deep water port facility with crushing, screening and stockpile storage for 500,000 tons of finished product at the port. Ninety-nine percent of the stone is shipped via lake boat to ports within the Great Lakes. The operation is unique in that both metallurgical Dolomite and Limestone are produced on site. In 1930, Port Inland was at the fore front of technological advancement. It was the first major mining operation to use roller bearings and other equipment innovations. Over the 60 years of operation, Inland Steel placed emphasis on steel making technology and iron ore mining at the detriment of the limestone operation. By the early 80's, Port Inland was no longer a leading competitor. Inland Steel, unable or unwilling to spend the capital to modernize, closed the facility in the fall of 1989.

Jan 1, 1994

By M. Schreiner, J. Brune, D. Theisen, C. S. -J. Tsai

This study reports that routine mining activities could produce a high number of nanometer sized particles which have not been well characterized and may represent an unacknowledged exposure present in the mining environment. A preliminary survey of the particle emission from the feed-leg drilling activity was conducted in the excavations of an experimental mine. The level of particulate exposure was monitored by real time direct reading instruments include a NanoScan scanning mobility particle sizer (measurement range 10-420 nm) and an optical particle sizer (measurement range 0.3-10 μm). Particulate morphological and structural examination was conducted through transmission and scanning electron microscopy and x-ray dispersive analysis of samples collected by a thermophoretic sampler, and a novel nanoparticle sampler. The real time instrument data revealed high concentrations (> 3.5 x 106 particles/cm3) of ultrafine/nanoparticles generated from the drilling activity. Analysis of particle sampler specimens with energy-dispersive x-ray spectroscopy showed a large amount of submicron silica, spherical primary particles and agglomerated soot particles rich in carbon. Exposure to particles in the nanometer size from various sources within the mining environment may be associated with the poorly understood rise in respiratory and systemic disease among miners. INTRODUCTION Exposures to mine dust have been measured and evaluated for decades. Exposures to aerosolized dust such as coal or silica particles can cause lung and other diseases (1-7). One way that The Mine Safety and Health Administration (MSHA) characterizes inhalation exposures within the mining environment is through measuring the respirable dust mass concentration within the breathing zone of workers (8). Respirable particulate matter (RPM) is of great concern due to its ability to deposit in the alveolar region of the lungs (9-10) where it can affect respiratory function. Interventions championed by MSHA have greatly reduced the prevalence of coal workers pneumoconiosis (CWP) and progressive massive fibrosis (PMF). Although great progress has been made, the prevalence of CWP and PMF appears to be trending upwards and the measured increase in prevalence is not elucidated in RPM measurements (11-12). Though the presence and risk associated with ultrafine particles such as emission from diesel engine within the mining environment has been previously established (13-14). There is suspicion within the mining industry that this resurgence of lung disease may be due to very fine particulate matter from various source that is not properly characterized by current sampling methods. Nanometer sized particles, in the range of ultrafine particles, fall within the RPM size range and have been found to deposit in all regions of the respiratory tract (15). Nanoparticles are commonly accepted as particles that are greater than 1 nm in two or three dimensions but smaller than 100 nm (16). Once in the lungs, nanoparticles can enter the blood stream (17) and selectively affect other target organs such as the heart, liver, bone marrow, lymph nodes, spleen, and brain (15,18-19). The size of nanoparticles has been shown to correlate with their translocation behavior on secondary target organs (20-21). There is strong evidence that the clearance mechanisms used to rid the lungs of particulate matter are not as effective on nanometer sized particles, leading to a greater fraction of never-cleared particles which may enhance disease development (20). Research has demonstrated that nanometer sized particles have unique properties (22) whose adverse health impact is greater than what has been found with micrometer sized particles of the same type (23-26). The large ratio of surface area to mass compared to larger particles is believed to make nanoparticles a greater hazard. Utilizing mass to measure these types of exposure will be very difficult to accurately characterize the quantity of

Jan 1, 2019

By Jeffery L. Kohler

The research and development of a pattern recognition system which can predict incipient failures and safety hazards in the mine power network is described. An examination of mine electrical safety hazards revealed they are often related to the electrical equipment down-time experienced on mine sections. Based on this, a method is proposed that can improve both production and safety, without compromising either. Equipment failure modes are examined to illustrate how the ultimate failure can be predicted for enough in advance to allow a convenient and safe repair, followed by a discussion of actual monitoring system performance. Finally, the paper is concluded by projections of the system's utility to industry.

Jan 1, 1977