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By Jan Visman, S. J. Aresco

INTRODUCTION The accurate sampling of coal, as with most minerals, is a difficult task. Coal is a heterogeneous material made up of different types of coal and varying amounts of mineral matter. The product as mined may contain all the layers of coal and impurities found in the seam as well as portions of the stratas above and below the coal seam. The preparation plant is the device to size, crush, and/or remove impurities so the coal may be shipped as a salable product. Sampling may be needed at many stages in the preparation process. Although this chapter is primarily concerned with sampling in connection with preparation processes, the principles apply to all coal sampling. The main reasons for sampling in connection with coal preparation are: 1) To determine the washability characteristics of the raw coal by means of float and sink tests. These may be used for the design of a preparation plant, prediction of results to be obtained, or monitoring raw coal delivered to the plant. 2) To check the performance of various operating units in the plant, either by float. and sink tests or chemical analyses. 3) To determine the analytical characteristics of the products produced, such as moisture, ash, Btu, sulfur, etc. HISTORY The earliest accepted methods of sampling coal in the United States were given in US Bureau of Mines (USBM) publications by J. A. Holmes,l G. S. Pope,2 and A. C. Fieldner.3 The American Society for Testing and Materials (ASTM) more or less adopted the methods proposed by USBM in their Standard D-21-1916 and it remained a standard for many years. Briefly, this standard called for a 500 lb (227 kg) sample for coals less than 94 in. (19 mm) in size and a 1000 lb (454 kg) sample for all coals over 94 in. (19 mm) in size. No mention was made of increments, but there was an instruction that the sample should spread over the coal

Jan 1, 1979

By A. L., Bailey

All who are even generally aware of the tremendous rate of increase in coal washing operations must realize the growing importance of the float-and-sink test. I believe it is conservative to estimate that, in the past decade, the dollar volume of float-and-sink testing has increased tenfold. It is a simple matter of economy, then, to examine the factors that determine the cost of adequate float-and-sink testing. When the Coal Preparation Section of the Bureau of Mines entered upon a greatly expanded program of such work in connection with the synthetic liquid fuels investigations, it seemed advisable to examine these factors experimentally. The principal consideration that differentiates float-and-sink test sampling from general purpose sampling, is that the original particle size must be preserved. Therefore, the total cost of the test will be directly affected by any standard that might be proposed to limit sample bulk reduction at any given particle size. For this reason, the relationship of sample size to variability of results was the first factor to be studied experimentally.

Jan 1, 1949

By U. Meyer, A. Alonso, P. Banios

The sampling of cathodes has changed with the introduction of the ISA-process in copper refineries. A Jernkontoret joint working group of refineries and rod plants from both primary and recycled copper plants has been investigating whether the actual sampling of cathodes is representative for this type of cathodes. As a first stage, samples were sent to the members of the working group with the objective to find an easy basis for a comparison of the results of the next stages. All samples show the same tendency for nearly all elements. In some cases, there may exist differences in calibration and for some elements the detection limits are too high, especially when Optical Spectrometry is used. In the second stage, discs were compared with melted samples to answer the question whether the punching of discs is sufficient for the quality control of the cathode. The analyses of the discs represent fairly well the cathode quality. There are differences between cathodes from different crops. Three punches are sufficient to determine the cathode quality. Finally, samples from various lots of cathodes were compared with samples from the rod produced from these cathodes. The impurity content of the rod corresponds to the impurity content of the cathode.

Jan 1, 2000

Sampling is an integral part of gold bullion analysis. Gold mining industries sell millions of dollars worth of gold on the basis of analyses. Biased sampling can cause a serious loss in terms of monetary value to a mining company; hence accurate sampling is of great importance. The sampling procedures for gold bullion will be described. Emphasis is given to the most reliable method of obtaining a representative sample from a gold bar. The problems associated with sample preparation will also be discussed.The sampling procedure at the Kalgoorlie Metallurgical Laboratory will be evaluated in the light of comparative results from the Australian Gold Refineries (Perth, Kalgoorlie). The most common sampling practices adopted by different gold mining companies in the Goldfields and Australian Gold Refineries, Western Australia will also be presented.

Jan 1, 1976

By C. H. J. Beaven, M. P. Jones

Since the various new techniques of automation and computing have enabled vast numbers of mineralogical observations of relatively small samples to be made cheaply and rapidly, the statistical assessment of these measurements has become of vital importance. Much of the theory and most of the procedures of sampling that are used in the mineral industry are based on Gaussian statistics, but modern measuring techniques show that many mineralogical parameters do not necessarily follow the Gaussian distribution function. Consequently, it has become necessary to examine the application of other, more suitable statistical methods in order to derive the maximum amount of useful information from the examination of mineralogical samples. Some of the errors that can be introduced by the use of incorrect distribution functions are discussed and the value of determining the function that is appropriate to the particular parameter that is being measured is shown. Examples are provided of non-Gaussian distribution functions in mineralogical materials that were encountered during prospecting and during mineral treatment operations: a Canadian uranium ore, a Thai tin ore, and gold ore tailings.

Dec 1, 1971

By Francis F. Pitard

The presence of elements, minerals, or chemical compounds in materials at very low concentrations is becoming a constantly increasing concern for several segments of the Industry. Some trace elements or chemical compounds may be considered as hazardous, some are simply considered as undesirable In complex processes where they could be constantly recycled and end up as the major factor of decreasing quality for some valuable products. In some other cases, the presence of a trace element or mineral may be highly desirable because of its economical value: precious metals are falling into this category, they probably were the first trace elements to draw our attention. Tremendous quantity of money is spent for analysis at the trace level, also the analytical "tool" has been considerably improved during recent years, but still the sampling aspect of the problem remains obscur for many, and because of it, large quantity of analytical efforts become meaningless. Not only the absence of sampling strategies is badly affecting the representativeness of a large majority of samples, but furthermore for the same reasons, many laboratories are failing In their endeavor to prepare reliable standard reference materials. The reason of this failure has its roots in the unability to estimate effectively the sampling characteristics of the element, mineral, or compound of interest, not to mention the unability to perform precise and accurate complete analysis, so essential for the instrumental analyst (1). In this paper a strategy to perform a better sampling operation is recommended. SELECTION OF A PROBABILISTIC APPROACH AS SOON AS PRACTICALLY POSSIBLE It Is essential to differentiate probabilistic sampling from non-probabilistic sampling. As Illustrated in Figure 1, the sampling operation Is a selection process which could be performed In two different ways: I. A probabilistic selection process according to which all elements of a lot of material to be sampled are submitted to the selection with a same probability of being selected. 2. A non-probabilistic selection process according to which all elements of a lot of material to be sampled are submitted to the selection with different probabilities of being selected.

Jan 1, 1986

The efficient and profit-maximising daily and long-term management of the Vera Nancy resource depends on decisions based upon assay data. This paper examines the range of sample sources, the methods of sample collection, assay techniques and Quality Assurance used by the mine. The orebody has a relatively low nugget effect for a gold mine (around 25 per cent) and this greatly assists in reducing sampling error and producing reliable assay data for production decision-making. Reconciliation between mine and back-calculated mill grades generally sees the mine under-calling mill grades by around four per cent.

Jan 1, 2000

By Mark Springett

The problems inherent in sampling low- grade deposits have long been recognized. As economic grades become lower with increasing metals prices and improvements in recovery technology then the previously difficult sampling problem has consequently become even more demanding. The breakdown of the sample process and error is illustrated by describing in the remainder of the paper some sampling practices that have been utilized on mining and exploration properties and by describing some problems that have been encountered, providing a series of cautionary tales to those involved in any aspect of mine or exploration sampling.

Jan 1, 1983

By Francis F. Pitard

North America had an Important role in the early development of sampling theories. Unfortunately many progressive ideas were soon frozen into a series of guidelines based on the philosophy that "honest sampling only requires good judgment and practical experience". Such a philosophy appeared to be good enough In the early age of the mining Industry; however, it became quickly necessary to find new approaches. During the last thirty years, Pierre Gy's sampling theory provided tremendous breakthrough in the comprehension of this new science, nevertheless went unnoticed in North America. Sampling always generates complex problems and as the philosopher and mathematician Descartes suggested: "A complex problem can often be dissociated Into a series of several simpler problems, only then you try to solve those one by one". The only way to solve sampling problems is to consider each component of the overall sampling error: components of a continuous model such as long-range quality fluctuations, periodic quality fluctuations, weighting fluctuations; components of a discrete model such as materialization errors, delimitations errors, extraction errors, fundamental errors, grouping errors, and segregation errors. PAST AND CURRENT PRACTICES Many sampling methodologies have been developed, improved, and standardized during the first half of this century. Accordingly, sampling equipment has been proposed, selected, and used by standards committees. Today, there is a tremendous variety of sampling methodologies and corresponding tools offered to anyone with limited experience in sampling and it is very easy for a chemist, metallurgist, geologist or miner to spend considerable money in equipment transgressing the most basic rules of sampling correctness. Sampling stations that never worked properly in modern plants often cause engineers to abandon them and return to a primitive form of grab sampling.

Jan 1, 1986

By J. L. Fuller

Thousands of mine air samples are taken underground each year by MSHA inspection personnel in order to further assure that miners have a safe and healthy environment in which to work. While most air samples are taken with stain tubes, many samples are obtained in evacuated containers and returned to a laboratory for more accurate analysis on a gas chromatograph. In order to enhance the accuracy, reliability and repeatability of the samples taken with evacuated containers, improved procedures have been developed, which are described in this report, for filling two different types of evacuated sample containers using either mechanical or electrical pumps. In those instances, such as when sampling strata gases in drill holes, where mathematical calculations may be required for proper sampling, example calculations are provided. The use of a third type of evacuated container, which is generally restricted to non-specific sampling of the ambient mine atmosphere, is also described.

Jan 1, 1986

The creation of an accurate and precise enough database requires the collection of many representative samples, subsampling and assaying them without destroying their integrity. The selection and implementation of sampling protocols often lead to severe difficulties, making the unaware practitioner vulnerable to massive exploration, feasibility and operating failures. Therefore, there is no substitute for a good understanding of the Theory of Sampling (TOS). Either because of ignorance, or because of short-term economic reasons, failure to comply with many stringent conditions can be devastating for the validity of a feasibility study, leading to false evaluations, to the abandonment of a viable property, or to the exploitation of one that is not profitable. All these failures have something in common: insufficient duplicate sampling, subsampling and assaying were performed; very important, preliminary heterogeneity tests were never performed; for short-term economic reasons, poor sampling and subsampling protocols were selected, second-class sampling systems and weightometers were installed and poor preventive maintenance and cleaning were implemented;and sampling experts were called only when the project was obviously in trouble. The conclusion is clear: in due time, iterative auditing of sampling practices is an insurance policy against massive financial losses for the company involved. A complete, comprehensive 100 point checklist of sampling Quality Assurance and Quality Control is provided, so critically important details to ensure success are not forgotten.

Mar 1, 2010

By Marcel Vallée

Abstract -Traditionally, samples collected for mineral deposit evaluation have been viewed without explicit reference to reliability, with the illusion that a true value is attainable from a few samples and verifications. For exploration, mineral deposit estimation and production quality control the following definition is proposed: "a sample is a small quantity of material relative to the geological mass it represents, collected according to a systematic procedure, of measurable reliability, from which the grade/quality of the mass which it represents may be estimated, based upon appropriate protocols. This paper will concentrate on the actual rock sampling process. Too often, sample size has been, and is still viewed as a matter of convenience, leaving out representivity considerations, despite the importance of samples on project estimation. Linear samples (chips, channels, drill), panel samples, broken rock or mining samples and very large samples are considered. Collection procedures and quality control protocols to improve the representivity of non-mechanical samples are proposed.

Jan 1, 1998

By M Castello, P Bouchard, M Sabsabi, A Blouin, B Nguegang Kamwa, M Constantin, K Fytas, M Laflamme, K Rifai, F Vidal

Canada’s Quebec province operates 26 metal mines, 19 of which are producing gold and generating over C$1.8 billion (US$1.3 billion) annually. In all those mines, numerous samples of rock are collected and analysed daily in laboratories in order to determine their gold content. However, laboratory results are generally available within 48 hours of sampling (depending on the number of samples received by the laboratory and the priority of the results), thus potentially slowing down mining activities. In an attempt to find a solution for delayed laboratory results, Laval University, in partnership with the National Research Council Canada (NRC), the National Institute for Scientific Research (INRS) and four mining companies (Agnico Eagle, Canadian Malartic, Hecla Québec and Iamgold) have launched the Laser-Induced Breakdown Spectroscopy (LIBS) project for in situ real-time mining sample analysis. This work aims to minimise the amount of LIBS point sampling necessary to be representative of a full scan of the analysed area. Eight sampling patterns are investigated. A statistical analysis of the data was performed by varying the pattern steps. Results show that two of the patterns, 1 and 5 (single diagonal crossing the stratification of the samples with opposite slopes) minimise the amount of point sampling while remaining representative. The most successful results are obtained from steps which are greater than 6. In terms of the type of material, pattern 5 and steps 9 are better for core sampling, while pattern 1 and steps 8 are better for rock sampling. The geological explanation for these results is the heterogeneous distribution of gold in the sample which seems to be more homogeneous in the rocks than in the core sample due to the small rock size. In terms of the mineralisation, pattern 5 is better for mixed sulfides and quartz veins, and steps 8 and 9 are better for quartz veins.CITATION:Nguegang Kamwa, B, Rifai, K, Laflamme, M, Constantin, M, Castello, M, Vidal, F, Bouchard, P, Fytas, K, Blouin, A and Sabsabi, M, 2017. Sampling strategy by statistical analyses of LIBS data in the context of a portable gold analyser, in Proceedings Tenth International Mining Geology Conference 2017, pp 221–232 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 20, 2017

By David A. Larson

The future exploitation of crust deposits will require a dependable characterization system. The U.S. Department of the Interior, Bureau of Mines (Bureau) initiated research to develop a new sampling dredge by conducting a series of cutting and physical property tests on previously collected cobalt-rich manganese crust and substrate samples. Using the engineering parameters derived from these tests, a large, heavy dredge was designed and tested. This heavy dredge was capable of fragmenting and collecting in situ crust, but it created handling problems for the research vessel, thus an aggressive cutting, light-weight dredge was conceived and fabricated. The light-weight dredge is capable of fragmenting and collecting crust and some talus. This dredge can be used on flat or rough seabed terrains. It can be easily retrieved from hang ups and reset to sample again.

Jan 1, 1991

By F F. Pitard

The optimisation of a metallurgical plant requires two kinds of sampling systems. The first provides samples to follow process changes, so in due time actions to maintain key parameters within pre-established specifications can be applied. The second provides composite samples at the end of a working shift to demonstrate that valuable constituents sent to the plant went to either a final concentrate or to the tailings in a logical, expected proportion. Contrary to what many experts may claim, these two kinds of sampling requirements are incompatible and cannot be fulfilled using the same sampling systems; this is because the required samples have completely different objectives. A process control sample is an instantaneous sample with increments taken at short intervals, and the objective is to know where the process is at any given time. Excellent accuracy is not a must, however good precision is recommended since a possible process correction may need to be made. Online analysers fed with in-stream stationary cutters or other kinds of in-stream or by-stream probes can do well for such a mission. A composite sample for metallurgical accounting with increments collected over a long period of time, for which excellent accuracy and good precision are both required, must be generated by sophisticated and extremely well-maintained cross-stream sampling stations. The use of process control sampling systems to achieve good metallurgical accounting has been promoted by several manufacturers of sampling equipment around the world; it is a grave mistake that is misleading top management and a practice that should be scrutinised and preferably eliminated. Furthermore, bias tests used to prove otherwise are often based on insufficient data to draw valid conclusions; a guideline is provided.CITATION:Pitard, F F, 2014. Sampling systems for process control and metallurgical accounting, in Proceedings Sampling 2014 , pp 25–32 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By Stevenson I, Dickinson W, Taylor R. N

Despite flash smelting's widespread use little is known about the actual processes taking place in flash furnace shafts and comparatively few reports of sampling campaigns have appeared in the published literature. his paper reviews the previous reports of the use of horizontal trough samplers and analyses their expected collection efficiency. In the light of the deficiencies revealed by this analysis an isokinetic sampler was produced and a vertical sampling technique was also developed to obtain samples from directly below the burners in the shaft of the flash furnace at the Kalgoorlie nickel smelter. Comparison of the sizing of the samples obtained with the horizontal trough and isokinetic samplers confirmed the theoretical analyses and showed that the trough samplers were not collecting the fine particles. Besides providing data to validate mathematical models of the burners and shaft, chemical analyses of the shaft samples showed that the coal in the charge was reacting preferentially and that the plume of at least one of the burners was being deflected from its axial position. In the region directly below the burner there was evidence that the disperser on the burner was imparting more momentum to the coarser particles and that these were concentrating in the outer regions of the particle plumes issuing from the burners.

Jan 1, 1992

By R. Bruce Tippin

because of the mineral's high monetary value and the spotty occurrence of free gold in the deposit. Setting up a plant sampling procedure by simply applying the usual statistical sampling theory was questionable. Two sampling concepts were considered in the sampling study: o a sufficient number of assays can be taken such that the average determined from these individual samples represents a known quantity of ore. o a sufficient weight of sample can be taken such that when assayed it represents a known quantity of ore. The test program included evaluation of sampling techniques, sample preparation and analytical methods. The overall sampling program is depicted in Figure 2.

Jan 1, 1985

By P. E. Hand

Coal is a complex heterogeneous commodity that can be mined in a number of ways and needs to be processed to a homogeneous quality that satisfies the customer?s requirements, while attempting to maximize revenues. Only a small proportion of coal is suitable for metallurgical use. Export coals cover a wide range of qualities and some coals can be used optimally in the raw state for energy production. Critical quality parameters vary and can be a combination of heat value, ash, volatiles, sulphur, phosphorus, sizing, amongst others. The level of beneficiation is generally dictated by the washability of the coal, mining contamination, and the target product quality. The steps in the coal chain covered in this paper comprise exploration, mining selections, production, the washing process, and product delivery. Many points of sampling are needed to maximize yield at the correct quality, and some of these will be described in the paper. Keywords coal chain, coal beneficiation, sampling.

Jan 1, 2014

By F F. Pitard, K J. Ehrig

The Olympic Dam iron-oxide copper-gold (IOCG) uranium-silver deposit is second in size only to Norilsk, the gigantic metalliferous deposit. Olympic Dam is the largest publicly declared uranium, fifth largest copper and third largest gold resource. The deposit is typified by texturally destructive brecciation and intense iron metasomatism of the Roxby Downs Granite, bedded clastic facies rocks and mafic-ultramafic dykes. The deposit contains over 100 minerals. Copper mineralisation consists of chalcopyrite, bornite and chalcocite. Uraninite, coffinite and brannerite are the dominant uranium-bearing minerals. Gold mineralisation consists of electrum, tellurides and Au-Cu alloys. Hessite is the major silver-bearing mineral. The economic minerals are disseminated throughout the breccia matrix where the average grain sizes of the Cu-sulfide, uranium, gold and silver minerals are ~50, 20, <5, <5 microns, respectively.A significant number of sampling theory-based test programs have been completed since the mid-1990s to establish sampling nomographs, select appropriate sampling (ie split versus chip and interval lengths) and sample preparation protocols, quantify the errors associated with each subsampling stage, determine the practical uncertainty limits of Olympic Dam matrix-matched standards, and identify improvement opportunities related to the ongoing assaying quality assurance / quality control (QA/QC) program. Invaluable knowledge and unexpected insights gained from sampling studies at Olympic Dam have helped to improve our understanding of the distribution of economic and deleterious elements within the Olympic Dam deposit.CITATION:Ehrig, K J and Pitard, F F, 2017. Underground bulk sampling, uniform conditioning and conditional simulation – unrealistic expectations?, in Proceedings Eighth World Conference on Sampling and Blending , pp 21–28 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By R. J. Howarth, P. L. Llowenstein

The errors resulting from field sampling, sample preparation and analysis are investigated for drainage sediments derived from homogeneous sandstone, shale, limestone, basic igneous and granite lithologies as a background to a primary reconnaissance survey of England and Wales. Emission spectrographic analyses of approximately 350 samples for Al, Ca, Fe, K, Si, Ba, Co, Cr, Cu, Ga, Li, Mn, Ni, Pb, Sc, Sn, Sr and V and atomic absorption analyses for Cu, Ni, Mn, Co, Zn and Pb have been treated statistically. For routine broad-scale surveys analysis of the unground -80-mesh sediment fraction proves satisfactory. Sampling error between localities in a stream is shown to be less than spectrographic analytical error for many of the elements considered here, except where mineralisation (contamination) occurs, but exceeds the atomic absorption analytical errors in most cases. Unless it it critical to reduce the amount of between-site variability (having regard to analytical errors) in the regional survey, there appears to be no advantage in the use of a more sophisticated sampling technique. The utility of moving-average maps in reducing the width of the confidence belt around the regional 'geochemical surface', and thus compensating to some extent for the sampling errors, is also demonstrated.

Dec 1, 1971