Search Documents

By Jr. Smith

Industrial minerals are just other rocks, except for the unique characteristics that make them useful in an industrial process. There is not a ready market for this type mineral and one or more uses must be developed to sustain production. The name "olivine" is a generic term used to indicate a group of orthosilicate minerals in a solid solution series, with forsterite (Mg2SiO4) and fayalite (Fe2SiO4) as endpoints. Since neither is found alone in nature, the mineral is always a combination of the two. The commercial deposits are high in magnesium and on the high end of the melting scale in the series. The name comes from the olive-green color.

Jan 1, 1992

By Miguel Carrera, Jose Arnal, Julian Ortiz, Maarten Haest, Fouad Faraj

ShovelSense is a complete solution for bulk ore sorting at the mine face that combines robust shovel bucket mounted X-ray fluorescence sensors, with real-time material classification, fleet management integration and supporting cloud-based data infrastructure, to ensure each truck always goes to the right destination. Correct truck destinations are a challenge in many current mining settings because the material classification of a truck, which is the key input into the truck destination, is often based on estimates at block resolution (~20x20x15m), with limited adjustment for blast movement and mixing. In this contribution, we present a geostatistical, data driven approach to estimate the potential value of bulk ore sorting at the mine-face for seven open pit mines. The approach is premised on the assumption that truck loads within blocks follow a simple gamma distribution. Standard ore control data from the seven mines have been used to estimate the potential bulk sorting value at these operations and ShovelSense-integrated dispatch datasets have been used to validate these estimates for specific benches on which ShovelSense operated. ShovelSense results validate the ore control data-based value predictions and show how at mine-face bulk ore sorting value varies between distinct deposit types. In general, deposit types that have higher bulk ore grade contrasts, display more potential ShovelSense value. The manuscript concludes with the limitations and opportunities of applying the proposed value estimation approach to evaluate at mine-face bulk ore sorting opportunities for open pit operations.

Jun 25, 2023

By Raimo Matikainen, Pekka Särkkä

HISTORY The history of mining in the Outokumpu Co. shows continuous development of small and medium-sized mines, coupled with a permanent improvement in min¬ing methods and mechanization. Tables 1 and 2 provide a brief outline of the major events over the years of operation. Some of the mines have had relatively short lives as in the case of Nivala, Korsnas, Kylmäkoski, the surface pits of the Kotalahti, Vuonos, and Hammaslahti mines, and some very small pits. The sequence in which the mines started opera¬tions is shown in Table 1 and production increases in Table 2. GEOLOGICAL FRAMEWORK Most of the ore deposits in Finland (see Fig. 1) are situated in middle Precambrian (1500 to 2300 m.y.) formations corresponding to the Baltic shield. The ores and country rocks are generally firm, with a minimum compressive strength of 60 MPa (8700 psi). The sulfide ores, of importance to the national econ¬omy, can be divided into copper-nickel deposits, asso¬ciated with basic and ultrabasic rocks (1900 m.y.), and the sulfide ores found in well-preserved Svecokarelidic crystalline schists (1800 to 2300 m.y.) which contain varying amounts of copper, zinc, cobalt, nickel, and lead. Over 90% of the sulfide ore mined to date in Fin¬land and existing in the known ore reserves belongs to deposits situated in the main sulfide ore belt. This belt extends diagonally across the country over a breadth of Table 1. Sequence in Which Mines Began Operations 1913 Mining started at the Outokumpu mine (now called Keretti) 1928 Large scale systematic exploitation started in the Outokumpu mine Opening of mines: 1942 Nivala mine (1942-54) 1943 Yiojärvi mine (1943-66) 1947 Orijärvi mine (1947-54) (Mining started in 1757) 1948 Aijala mine (1949-58) 1952 Metsämonttu mine (1952-58 and 1964-74) 1954 Keretti's new mine plant 1954 Vihanti mine 1959 Kotalahti mine 1961 Korsnäs mine (1961-1972) 1962 Pyhäsalmi mine 1966 Virtasalmi mine 1967 Kemi mine 1970 Hitura mine 1971 Kylmäkoski mine (1971-74) 1972 Vuonos mine 1973 Hammaslahti mine 1978 Vammala mine Table 2. Ore Production of the Outokumpu Oy Mines Year 1000 t of Ore 1913-1928 252 1929-1954 13 075 1955 1 105 1960 1 784 1965 2 627 1970 3 269 1975 5 825 1976 5445 1977 4 939 1978 5 766 1979 5905 40 to 150 km, from Lake Ladoga to the coast of the Gulf of Bothnia. The main sulfide ore belt includes the Outokumpu copper-zinc, the Kotalahti nickel-copper, the Pyhäsalmi copper-zinc, and the Vihanti zinc ore zones. The Outokumpu ore district occurs in a mica schist area about 60 x 100 km, in association with belts of metamorphic Svecokarelidic quartzites, black schists, dolomites, skarn rocks, and serpentinites. The main ore minerals are chalcopyrite, pyrrhotite, pyrite, and sphalerite. In addition there are nickel and cobalt minerals such as cubanite and cobalt-pentlandite, which have been of economic importance. In this area, Outokumpu Oy exploits the deposits at Keretti and Vuonos. The latter was discovered as an extension of the Keretti ore field about 6 km to the northeast. The Kotalahti geological formation extends across nearly 400 km. The host rock of these mostly pipelike deposits is generally serpentinite, pyroxenite, or norite. The main ore minerals are pyrrhotite, pentlandite, and chalcopyrite. In this zone, the deposits of Kotalahti, Hitura, and Virtasalmi are at present under exploitation by Outokumpu Oy. The Vihanti geological formation is located in west¬ern Finland and is about 40 km wide and some 200 km long. The rock associations are crystalline schists including dolomites, mica schists, mica gneisses, gray¬wacke, and acidic or basic volcanic rocks, which change generally, in connection with the mineralization, into skarn and cordierite-anthophyllite rocks. The host rocks are dolomite, skarn, graywacke, and quartzitic rock and the principal minerals are sphalerite, chalcopyrite, galena, pyrite, and pyrrhotite. The accessory minerals are mainly cubanite, arsenopyrite, molybdenite, and native gold and silver. The two largest ore bodies being exploited at pres¬ent by Outokumpu Oy are the Vihanti mine, which pro¬duces zinc, lead, and copper, and Pyhäsalmi, which con¬tains copper and zinc. Deviating from the sulfide ore types described earlier is the Hammaslahti copper ore located in the southeast-

Jan 1, 1982

By David B. Crouch

Wastes in various forms have always been a part of mining, and management of mine waste has evolved from the early days of "push it over the side and down the creek" to today's highly engineered waste facilities. Changes have been brought about not only by technological advances in the ?3M?s? - mining, milling, and metallurgy - but also by environmental awareness and changing social values that have been manifested in an ever-growing maze of regulations. This is a dynamic era, and the debate goes on. So it is that planners have to anticipate permit and regulatory requirements in the site-selection process along with the traditional criteria. The McLaughlin gold project is an example of how one company, Homestake, has met this planning challenge. In August of 1980, Homestake Mining Company announced a major gold discovery in northern California known as the McLaughlin Project. The property is approximately 80 air miles northeast of San Francisco near the junction of Lake, Napa, and Yolo Counties. This is an area where mercury has been mined off and on for over 100 years; gold has never been mined in the area. The gold is microscopic and finely dispersed in a complex geologic setting. Reserves are estimated at approximately 20 million tons at a grade of approximately 0.16 ounces per ton.

Jan 1, 1983

By T. Hackett

Western underground coal reserves are tremendous, but recovery in western seams can be poor because of mining problems caused by deep cover, geologic anomalies, and thick seams. For instance, many seams contain a rock parting too thick to be extracted economically with the coal. This forces the operator to mine the coal above or below the parting. Subsequently, the rock pressures induced by mining make the part left difficult or impossible to extract by standard mining methods. Because upper and lower parts of the seam are frequently of minable thickness, the presence of rock partings can result in a significant loss of coal. Given a longwall recovery of 60 pct and equal thickness for the two parts of the seam, overall recovery is reduced to less than 30 pct if one part only is mined. The coal left in place is unavailable to meet the nation's energy needs, or to produce revenues for coal companies or government. [ ] Multi-slice longwall mining has the potential to recover the portion of split seams that are now left in the mine. Using superimposed standard longwalls with chain pillars, overall recovery could be doubled, depending on panel and pillar widths. Using a combination of advancing and retreating longwalls in descending slices, overall recovery could be improved to more than 80 pct. Because of the potential for improved recovery, the Bureau of Mines is analyzing the ground control factors affecting multi-slice longwall under western mining conditions and is conducting field trials at a planned multi-slice operation.

Jan 1, 1987

By M. P. Saunders

A comprehensive, site specific water management plan is of primary importance to the successful implementation, operation and decommissioning of any mining project. Formulation of a plan requires an orderly planning process consisting of identifying problems, establishing planning criteria based on the guidelines and requirements of regulatory agencies, and an iterative procedure of identifying, investigating, and evaluating plan elements and alternative plans. A typical uranium surface mine operation consists of a mine pit or pits, spoil pile areas, crusher, processing plant, and tailings disposal area. A water control plan addresses the problems of diversion of natural runoff from undisturbed areas around the mine; and diversion, collection, and treatment of runoff from within the mine area. A water control plan is required to determine the location and size of appropriate control and detention structures; their cost; and the schedule for permit activity, design, and construction. The plan must be formulated to meet the requirements of both the State and Federal regulatory agencies.

Jan 1, 1981

By A. Lashgari, V. Kecojevic

This paper presents research on the environmental impact of digging and loading equipment used in surface coal mining. Environmental impact was assessed through the measurement of equipment exhaust and dust emissions, and sound level. In this study, exhaust emission refers to carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), sulfur oxides (SOx) and volatile organic compounds (VOCs). Dust generation refers to fine particles (PM2.5), inhalable particles (PM10) and total suspended particulate matter (TSP). Sound level refers to the sound pressure level at different distances from the equipment. Modeling of the environmental impact of digging and loading equipment was conducted using the Microsoft Visual Studio.NET software package. This research was a part of a broader project involving the development of a software system for the selection of productive, cost-efficient and ecofriendly mining systems, sponsored by the Appalachian Research Initiatives for Environmental Sciences (ARIES). This research may assist mining professionals in quantifying the environmental impact of digging and loading equipment, and developing strategies for reducing the overall impact of such equipment in surface mining.

Jan 1, 2013

By T. Ritzel

Predictive maintenance technologies including vibration analysis, tribology, infrared thermography, ultrasonic detection, and electrical measurements have been applied to large electric mining shovels at Cyprus Sierrita. The predictive program was initiated by Cyprus Sierrita and P&H Mining Equipment at the Cyprus Sierrita Mine in Tucson, Arizona during August of 1996 on the P&H model 2300 and 4100 electric shovels. The utilization of these technologies has shown the potential for improving electric mining shovel availability and minimizing maintenance costs. Predictive technologies provide the tools to assess machinery condition. Availability is enhanced by the condition based planning of component replacement. Maintenance costs are minimized by focusing resources through condition based prioritization.

Jan 1, 1997

By C. P. Newman, T. Gray, G. Beale, T. Cluff

Predictive geochemical and limnologic modeling of pit lakes is an important aspect of modern permitting. One of the key assumptions of many predictive pit-lake models is that highwalls and pit backfill become unreactive once submerged by the filling pit lake. Existing pit lakes provide useful data to test this assumption. The Sleeper pit lake (northwestern Nevada) is near hydrologic equilibrium and contains good-quality water that generally meets regulatory requirements for pit lakes. Despite the overall stable geochemical composition, seasonal trends in the hypolimnion indicate the generation of solutes and fluctuations in pH. This work applies mass balance, analysis of subaqueous pyrite oxidation, and trends in solute concentrations to evaluate the potential causes of long-term solute generation in the hypolimnion of the Sleeper pit lake. Results will aid in refining the effect that inundation of highwalls and waste rock has on ultimate pit lake chemistry and long-term closure planning. In the case of the Sleeper pit lake, ongoing solute loading does not substantially change the closure plan at this time as influent groundwater contains abundant alkalinity. INTRODUCTION As mine pit lakes become more widespread, regulatory agencies are increasingly requiring advanced predictive modeling of pit-lake geochemistry during permitting. The end goal of all those involved in these permitting actions (i.e., the mining company, the regulatory agencies, and the public) is to have pit lakes become geochemically and hydrologically stable for the long term, which may then allow mining permits to be relinquished. The modeling endeavors therefore are important to inform long-term closure of pit lakes. The conceptual models and numerical methods used to predict pit-lake water quality are complex and require substantial amounts of data and a variety of assumptions (Castendyk et al., 2015). One of the common modeling assumptions is that solute generation via acid mine drainage is eliminated (or at least decreased) by the filling of the pit lake and inundation of highwalls and any in-pit waste rock. However, few studies have reported on observations that support or refute this assumption. The water-quality record of the Sleeper pit lake is an ideal dataset with which to test these assumptions. The former Sleeper mine is located in northwestern Nevada (Fig. 1), and has been inactive (in terms of ore extraction) since 1996. The mine extracted Au and Ag from the famous high-grade Sleeper vein and associated widespread stockwork mineralization (Nash et al., 1995). Water quality in the pit lake has been monitored since the cessation of dewatering in 1996. The current pit lake actually occupies three separate sub-pits, the Sleeper, Wood, and Office pits (Fig. 1). The Sleeper and Wood pits undergo regular water-column monitoring using a conductivity-temperature-depth (CTD) probe, and sampling for dissolved inorganic constituents at several depths (~10, ~130, and ~330 ft. below lake surface). Groundwater quality is also monitored using a series of wells (Fig. 1).

Jan 1, 2019

By W. E. Hale

The Institute of Applied Geology (I.A.G.), a joint project sponsored by the University of the Philippines, the Philippine Bureau of Mines and the United Nations Development Programme (Special Fund) undertook during 1965-66 a number of field projects in Northern Luzon Island (Fig. 1). These field operations were of a two-fold nature: during approximately six weeks an orientation survey, involving, geology, geophysical surveying, and geochemical prospecting, was conducted over a partly developed, disseminated copper deposit at Sto. Nino (Fig. 1). The Sto. Nino study demonstrated (Hale and Govett, 19677 Govett and Hale, 1967) the feasibility of geochemical prospecting relative to other exploration methods for the location and delineation of disseminated copper occurrences, the major source of metal in the expanding mineral industry of the Philippines. A vein occurrence at Suyoc (Fig. 1) was similarly subjected to

Jan 1, 1968

By Ronald P. Wright

ARAMIDS UNDERGROUND COAL MINING

Jan 1, 1993

By R. V. Ramani, K. V. Raj

"The air flow problems in open pit mines are complex. Computational fluid dynamics (CFD) models provide a detailed knowledge of the airflow pattern and velocity distribution, temperature, and pollutant concentration within an enclosed domain of the open pit. A range of turbulent model can be selected for varying complexity and accuracy. Pollutant transport models, however, differ in their assumptions and structure as well as in the algorithm they use; as a result, prediction varies from model to model. This paper presents a study of pollutant transport in an actual open pit mine under stable boundary layer. The objective is mainly to test two turbulence models using the same input conditions, model constants, and similar geometry. Measured data are used to compare results of the two CFD models, namely, the kappa-epsilon (?-e) model and the Large Eddy Simulation (LES) model. Despite the complex synoptic situations, different meteorological input data and the fast changing conditions, the simulation results from both the models are in good agreement regarding the dispersion of pollutants.INTRODUCTION Modeling of contaminant transport under Arctic air inversion is an important step for an assessment of the amount of pollutants within the open pit. The Airflow in open pit mines is of larger scale and does not follow the principles of pipe flow. The air flow problems in actual open pit mines are thus far more complex. CFD models provide a detailed knowledge of the airflow pattern and air velocity distribution, temperature, and pollutant concentration within an enclosed domain of an open pit. There is no known application of CFD in three-dimensional modeling of air flow in large open pit mines. Two equation RANS kappa-epsilon (?-e) and Large Eddy Simulation (CFD) models, however, have been developed to solve the stable boundary layer (SBL) problems in Atmospheric Sciences (Baklanov 2000, Basu and Porté-Agel 2006, Dop and Axelsen 2007, Bandopadhyay et al. 2014). Because an exact flow situation in open pit mines is not known a-priori, it is therefore, necessary to investigate various turbulent models to identify the appropriate model that would simulate the flow phenomena with reasonable accuracy, and predict the contaminant distributions within the pit. Dispersion models differ in their assumptions and structures as well as in the algorithm they use and, as a result, predictions vary from model to model. Furthermore, it is also important to investigate the behavior of a CFD model in simulating a complex phenomenon such as the transport and distribution of contaminants in open pit mine under Arctic air inversion. The simulation of an enhanced period of turbulence in SBL is of particular interest because traditional air pollution dispersion models cannot explicitly treat such intermittent events, and yet the SBL is often the worst-case scenario in an open pit pollution transport"

Jan 1, 2015

By Gerald L. Dollinger, Joseph A. Roby, David Krauter, Kenneth Deering

Three high performance TBM's equipped with large diameter (483mm) disc cutters are currently operating in Norway. This paper summarizes the design philosophy, field performance and ongoing technical development of these cutters. Included are discussions of the early problems encountered with their usage and the solutions to these problems that have been developed. Also included are discussions of the penetration rates and cutter usages observed. From this data it is concluded that high performance TBM's with large diameter cutters can produce significant improvements in both overall performance and in cutter costs under hard rock conditions.

Jan 1, 1991

By Raymond T. Moore

The Federal Coal Mine Health and Safety Act of 1969 (FCMHSA) begins with this statement: "Congress declares that the first priority and concern of all in the coal mining industry must be the health and safety of its most precious resource -- the miner; . . ." At the Federal level this responsibility is shared by the Department of the Interior and the Department of HEW. The health research and standard setting activities under the Act are largely the responsibility of the Department of HEW, and with the exception of Title 4, Black Lung Benefits, have been delegated to our Institute, which I will refer to henceforth as NIOSH. In addition, we bear certain joint responsibilities with the Department of the Interior. These include dust sampling and respirator approval. To complete the picture, the Department of Labor has recently assumed Black Lung Benefit respon¬sibilities from the Social Security Administration under Title 4 of the Act.

Jan 1, 1974

By C. Huang, S. Lin, Y. J. Wang

Introduction A mine characteristic curve is of great importance for both theoretical analysis and daily management of a mine ventilation network. Ventilation engineers are well acquainted with the ways of obtaining and using a mine characteristic curve that is conventionally associated only with single-fan networks. However, for a multiple-fan network, difficulty has long been recognized in defining the curve, not to mention, obtaining or using it. To extend the concept of mine characteristic curves for a multiple-fan network, a subsystem-based approach has been introduced by Wang (1992a). He defines a subsystem characteristic curve for a multiple-fan network and discusses the numerical procedure for constructing the curve. A graphical method of obtaining a subsystem characteristic curve for serial-parallel, multiple-fan networks has also been accomplished (Wang, 1992b). In spite of the maturity of the fundamental concepts related to and the numerical analysis tool for a multiple-fan ventilation network, information regarding the related laboratory tests is very scarce. To make up this gap, laboratory experiments have been done by using a two-fan experimental network. This paper presents the methodology and major findings regarding the construction and features of a subsystem characteristic curve. Characteristic curves and measurement fundamentals A characteristic curve A characteristic curve is a graphic presentation of the relationship between any two variables of a two-terminal component. It is typically defined in the form of a quantity-pressure curve for a ventilation component, which can be a single branch (airway), a fan, a regulator, a portion of a network or even a whole network. If a component is a single branch, the curve is called a branch characteristic curve. If it is a fan, then the curve is called a fan characteristic curve, and so on. Figure I illustrates the characteristic curves of some typical ventilation components. A general method for obtaining a characteristic curve from measurement is to apply an adjustable-pressure source between the two terminals of a component and measure the quantities corresponding to the different pressures. Mine characteristic curve A single-fan network can be easily divided into two ventilation components, the fan and the remaining network. The latter consists of only branches and regulators. Under this subdivision scheme, two characteristic curves can be constructed. They are the fan characteristic curve and the characteristic curve of the remaining network. The latter is referred to as the mine characteristic curve or the system characteristic curve. Although the general method for constructing a characteristic curve from measurement can be applied to obtain a mine characteristic curve, there is a shortcut for constructing the curve by introducing a mine resistance factor R. It is a constant if all of the resistance factors in the network are constant. R relates mine pressure H with quantity Q as in: H=RQ2 (1) For a given R, Eq. (1) can be directly used to plot a mine characteristic curve by assigning a series of Q values and calculating the corresponding H values. Hence a shortcut to constructing a mine characteristic curve is to measure one set of mine pressure H and quantity Q values, calculate the mine resistance factor R using Eq. (1) and then plot the curve. Subsystem characteristic curve Applying a similar scheme as is used for a single-fan system, divide a multiple-fan network into two components, a fan under consideration and the remaining network that contains all the other elements (branches, regulators and remaining fans) of the network. The fan under consideration

Jan 1, 1994

By H. EI-shall

In this paper, the results of a fundamental study involving zeta potential and turbidity determinations of solid suspensions are discussed. Illustrations of how these results are utilized to design field applications of solid grade polymers to clarify mine drainage water are presented. Other applications in different industries are also reported. The operational and economical advantages are examined.

Jan 1, 1994

By Olli Järvinen

The precious metal refinery process is divided into the five process stages: 1 .copper/nickel leaching in autoclave 2. selenium roasting furnace 3. doré metal smelting furnace 4. silver electrolysis 5. gold recovery system. The process has been developed during the years in Outokumpu Harjavalta Metals, which treats about 600000 kg /year copper anode slime. The slime treatment process route in Outokumpu Pori plant has been developed from year 1941. During this period the process has been improved radically. The major changes has been the atmosphere leaching into the autoclave leaching, the sulfuric acid roasting furnace was changed into sulfuric dioxide / oxygen roasting. The old doré smelting furnace has changed into the TROF converter and the gold electrolysis / aqua regia process has changed into the quick hydrochloric acid leaching process. The current production in Pori plant is 30000 kg of silver, 1000 kg gold, 30000 kg of selenium and some hundred kg of platinum- palladium concentrate.

Jan 1, 1995

By Jill Dill Pasteris

Several mineralogical prospecting techniques are used in diamond exploration. Most are concerned with identifying indicator minerals such as garnet and ilmenite, which are derived from mantle xenoliths hosted by kimberlites. The first goal of such prospecting is to locate kimberlite intrusions; the second goal is to identify the diamond-bearing kimberlites. Explorationists have worked much less on the indigenous kimberlite phases. The kimberlitic opaque oxides, ilmenite and particularly spinels, promise to be useful in discriminating between intrusion episodes in identified kimberlites, and perhaps in the evaluation and prediction of diamond grades. Several petrologists have showed that spinel compositions and zoning patterns are specific to certain intrusive facies in South African and Canadian kimberlites. Careful evaluation may indicate a correlation between spinel parameters and diamond content.

Jan 1, 1983

By J. Kulczycka

The concept of sustainable development is be-coming present in the policies of increasing number of industries and governments. The complexity affects not only production aspects, but has also special relevance for environmental decision making. Not only producers are re-evaluating the services they expect from the environment and concomitantly increasing their willingness to sacrifice other consumption in favour of enhanced environmental services, but the character of environmental issues is becoming more complex as well. Incomplete information, uncertainty, system wide change, trans-frontier impacts, current causes that have far reaching future effects, irreversibility, and possibilities of catastrophic change all complicate the environmental decision making process. Non-ferrous metals production, due to a relatively low level of metals content in ore, results in generating huge amounts of tailings, exceeding usually 90% of the mine output. They must be stored in special facilities, which have the significant impact on the environment both during tailing management facilities (TMF) operation and after their closure. One of the most essential impacts of operating and closed TMFs is their eolic activity, displaying in worsening air quality, aero-sanitary conditions in the neigh-boring villages and contamination of soils close to the facility by heavy metals.

Jan 1, 2005

By Thomas B. Borak, Keith J. Schiager, Janet A. Johnson

INTRODUCTION Several major factors introduce uncertainties into the assessment of radon progeny exposure to miners using time-weighted average radon progeny concentrations: uncertainty in the measurement of radon progeny concentrations in specific areas, assignment of an individual miner's time to those areas, variation in radon progeny concentration between measurements and potential human errors involved in calculating concentrations and handling data. The currently available grab-sampling methods for determining working level were analyzed to determine the magnitude of the uncertainty due to each of these factors. For all measurement methods studied, the variation in the airborne concentration with time in operational areas of a mine is the dominant factor in the uncertainty in determining annual radon progeny exposures for individual miners. Uncertainties relating to accuracy of the method and precision of measurement were found to contribute a significantly greater portion of the total uncertainty than human errors. Under normal conditions, if the technicians performing the measurements are conscientious and well trained, human error contributes little to the total uncertainty of the radon progeny exposure determination. The primary goal of radiation monitoring is the reduction of radiation exposure to the lowest reasonably achievable level below regulatory limits. Monitoring personnel in mines should be trained not only to obtain accurate estimates of miner radiation exposures but also to recognize and, when possible, to implement correction of situations which result in unnecessarily high radon progeny exposures. ESTIMATION OF UNCERTAINTY DUE TO HUMAN ERRORS Human errors affecting the assignment of annual radon progeny exposure to individual miners can be placed in two categories: those related to the measurement of radon progeny concentration in specific mine areas and those related to estimation of occupancy time for individual miners and transcribing data to permanent records. The former are specific for the measurement method used; the latter are common to all methods. Errors in Determination of Working Level All systems for determining radon progeny concentration require measurement of several parameters, which include volume of air sampled, count rate and decay time. These quantities and appropriate constants are used in a basic equation, specific to the system, which estimates working level. An unintentional random mistake in measurement of any one of these parameters or in the selection of proper constants will contribute to the uncertainty in the determination of working level. In our analysis of human error we separated each measurement method into a sequence of independent operations, with each step subject to operator error. For each operation we estimated the probability of occurrence and the consequence of errors to obtain a resulting uncertainty. Certain types of errors result in specific consequences. For example, we assumed that an error of 5 seconds in timing of a 5-minute sample results in a fractional error of 1/60 (1.7%). Other types of errors can result in a range of uncertainty. Transposing digits read from a scaler can produce errors ranging from near zero to approximately 60%. In these cases we calculated the statistical variance for the distribution of errors. We assigned the square root of the variance divided by the mean as the consequence factor for that type of error. This is essentially the same as a coefficient of variation. The product of the probability of occurrence and the consequence factor is the fractional uncertainty in the measurement due to that particular error. The total uncertainty due to human errors is calculated by taking the square root of the sum of the squares of the uncertainties generated by all manual operations. Uncertainties Due to Human Error for the Kusnetz Method One of the techniques most commonly used to estimate working level in U.S. uranium mines is the Kusnetz method. A generalized way to express the equation used to compute WL by this method is: WL = (Net Alpha Counts)/(V)(ST)(CT)(E)(K) where: V = sample flow rate in liters/min ST = sampling time in min CT = counting time in minutes E = absolute counting efficiency K = Kusnetz conversion factor (dis/min-L per WL), as a function of decay time in minutes. The example of human error analysis presented here is based on the Kusnetz procedure having a timing sequence of 5 minutes sampling time, 40 minute decay time, 2 minute counting time. During the sampling procedure a stop watch is used to determine the timing interval. We assume that it is common to make small timing errors of a few seconds, but larger timing errors occur infrequently. Errors greater than 30 seconds are considered to be essentially non-existent since we assume that the

Jan 1, 1981