Manual on drilling, sampling, and analysis of coal

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It varies in color from brown to black and is usually stratified. The source of the vegetation is often moss and other low plant forms, but some coals contain significant amounts of materials that originated from woody precursors. The plant precursors that eventually formed coal were compacted, hardened, chemically altered, and metamorphosed by heat and pressure over geologic time.

It is suspected that coal was formed from prehistoric plants that grew in swamp ecosystems. When such plants died, their biomass was deposited in anaerobic, aquatic environments where low oxygen levels prevented their reduction rot- ting and release of carbon dioxide. Successive generations of this type of plant growth and death formed deep deposits of unoxidized organic matter that were subsequently covered by sediments and compacted into carboniferous deposits such as peat or bituminous or anthracite coal. Evidence of the types of plants that contributed to carboniferous deposits can occasionally be found in the shale and sandstone sediments that overlie coal deposits.

Coal deposits, usually called beds or seams, can range from fractions of an inch to hundreds of feet in thickness. Coals are found in all geologic periods from Silurian through Quaternary, but the earliest commercially important coals are found in rocks of Mississippian age Carboniferous in Europe. Coal is found on every continent, and world coal reserves exceed 1 trillion tons. It is used primarily as a solid fuel to produce heat by burning, which produces carbon dioxide, a greenhouse gas, along with sulfur dioxide.

This produces sulfuric acid, which is responsible for the formation of sulfate aerosol and acid rain. Coal contains many trace elements, including arsenic and mercury, which are dangerous if released into the environment.

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Coal also contains low levels of uranium, thorium, and other naturally occurring radioactive isotopes, whose release into the environment may lead to radioactive contamination. Although these substances are trace impurities, a great deal of coal is burned, releasing significant amounts of these substances. When coal is used in electricity generation, the heat is used to create steam, which is then used to power turbine generators.

Modern coal power plants utilize a variety of techniques to limit the harmfulness of their waste products and to improve the efficiency of burning, although these techniques are not widely implemented in some countries, as they add to the capital cost of the power plant. Coal exists, or is classified, as various types, and each type has distinctly different properties from the other types.

Anthracite, the highest rank of coal, is used primarily for residential and commercial space heating. It is hard, brittle, and black lustrous coal, often referred to as hard coal, containing a high percentage of fixed carbon and a low percentage of volatile matter. Bituminous coal is a dense coal, usually black, sometimes dark brown, often with well-defined bands of bright and dull material, used primarily as fuel in steam-electric power generation, with substantial quantities also used for heat and power applications in manufacturing and to make coke.

Subbituminous coal is coal whose properties range from those of lignite to those of bituminous coal, used primarily as fuel for steam-electric power gener- ation. It may be dull, dark brown to black, and soft and crumbly at the lower end of the range, to bright, black, hard, and relatively strong at the upper end. The heat content of subbituminous coal ranges from 17 to 24 million Btu per ton on a moist, mineral-matter-free basis. However, the limitations of the analytical methods must be recognized Rees, In commercial operations, the price of coal not only reflects the quantity of coal but also invariably reflects the relationship of a desirable property or even a combination of properties to performance of coal under service conditions Vorres, Measurements of the desired property or properties usually grouped together under the general title specifications are expressed as numerical values; therefore, the accuracy of these measurements is of the utmost importance.

The measure- ments need to be sufficiently accurate so as to preclude negative scientific or economic consequences. In other words, the data resulting from the test meth- ods used must fall within the recognized limits of error of the experimental procedure so that the numerical data can be taken as fixed absolute values and TABLE 1. Indeed, the application of statistical analysis to such test methods must be treated with extreme caution. Such analysis must be based on valid assumptions and not be subject to a claim of mathematical manipulation to achieve the required result.

In other words, there is a requirement that reliable standard test methods be applied to coal analysis. There are many problems associated with the analysis of coal Lowry, ; Karr, not the least of which is its heterogeneous nature. Other problems include the tendency of coal to gain or lose moisture and to undergo oxidation when exposed to the atmosphere. In addition, the large number of tests and analyses required to characterize coal adequately also raise issues. Many of the test methods applied to coal analysis are empirical in nature, and strict adherence to the procedural guidelines is necessary to obtain repeatable and reproducible results.

The type of analysis normally requested by the coal industry may be a proximate analysis moisture, ash, volatile matter, and fixed carbon or an ultimate analysis carbon, hydrogen, sulfur, nitrogen, oxygen, and ash. By definition, a standard is defined as a document, established by consen- sus and approved by a recognized body, that provides, for common and repeated use, rules, guidelines, or characteristics for activities or their results. Many indus- try bodies and trade associations require a product e. In fact, the use of standards is becoming more and more of a prerequisite to worldwide trade.

Above all, any business, large or small, can benefit from the conformity and integrity that standards assure. As a result, the formation of various national standards associations has led to the development of methods for coal evaluation. For example, the American Soci- ety for Testing and Materials ASTM has carried out uninterrupted work in this field for many decades, and investigations on the development of the standardiza- tion of methods for coal evaluation has occurred in all the major coal-producing countries Montgomery, ; Patrick and Wilkinson, Furthermore, the increased trade between various coal-producing countries that followed World War II meant that cross-referencing of already accepted standards was a necessity, and the mandate for such work fell to the ISO, located in Geneva, Switzerland; membership in this organization is allocated to participating and observer countries.

Moreover, as a part of the multifaceted program of coal evaluation, new methods are continually being developed and the methods already accepted may need regular modification to increase the accuracy of the technique as well as the precision of the results. It is also appropriate that in any discussion of the particular methods used to evaluate coal for coal products, reference should be made to the relevant test. A complete discussion of the large number of tests that are used for the evaluation of coal and coal products would fill several volumes see, e.

The focus is on a description, with some degree of detail, of the test methods in common use, as well as a critique of various procedures that are not obvious from the official descriptions of test methods and a description of pitfalls that can occur during application of a test method for coal analysis. Quite often, a variation of a proximate analysis or an ultimate analysis is requested, together with one or more of the miscellaneous analyses or tests dis- cussed in this chapter.

Restrictions that have been placed on the coal used in coal-fired power plants and other coal-burning facilities have created a need for more coal analyses as well as a need for more accurate and faster methods of anal- ysis. This trend will continue, and more testing will be required with increased use of coal in liquefaction and gasification plants. This is especially true of analytical data used for commercial operations where the material is sold on the basis of purity.

Being a complex material, one may wonder about the purity of coal, but in this sense the term purity refers to the occurrence or lack thereof of foreign constituents within the organic coal matrix. Such foreign constituents impurities are water, pyrite, and mineral matter. Therefore, at this point, it is advisable to note the differences inherent in the terms accuracy and precision.

The word accuracy is used to indicate the reliability of a measurement or an observation, but it is, more specifically, a measure of the closeness of agreement between an experimental result and the true value. Thus, the accuracy of a test method is the degree of agreement of individual test results with an accepted reference value.

Hence, it is possible that data can be very precise without necessarily being correct or accu- rate. Precision is commonly expressed inversely by the imprecision of results in terms of their standard deviation or their variance. Pre- cision, by definition, does not include systematic error or bias.

Accuracy is often expressed inversely in terms of the standard deviation or variance and includes any systematic error or bias. Accuracy includes both the random error of precision and any systematic error. The effect of systematic error on the standard deviation is to inflate it. In the measurement of coal qual- ity for commercial purposes, accuracy expressed in this manner is generally of less interest than is systematic error itself.

When systematic error is reduced to a magnitude that is not of practical importance, accuracy and precision can become meaningful parameters for defining truly representative sampling and for interpretation of the results of various test methods. Estimation of the limits of accuracy deviation from a true or theoretical value is not ordinarily attempted in coal analysis. Precision, on the other hand, is deter- mined by means of cooperative test programs.

Both repeatability, the precision with which a test can be repeated in the same laboratory, usually but not always by the same analyst using the same equipment and following the prescribed method s , and reproducibility, the precision expected of results from different laboratories, are determined. If, for example, the repeatability interval is never to be exceeded, the variance would have to be zero. From a practical standpoint, this is difficult, if not impossible.

Furthermore, the variances standard deviations are of direct importance with regard to the details of performing sampling and test- ing operations because the overall variances can be partitioned into components associated with identifiable sources of variation. This permits assessment of the relative importance of specific details with regard to precision and accuracy.

With regard to reproducibility, for example, there is a component of random variance that affects the degree of agreement between laboratories but does not affect the degree of agreement within laboratories repeatability. Virtually nothing is known about this component of variance except that it exists, and the standard methods do not address this factor directly. However, recognition of it is evi- denced in the standard methods by specification of reproducibility intervals that are universally larger than would be accounted for by the variances associated exclusively with the repeatability intervals specified.

In the overall accuracy of results, the sampling variance is but one component, but it is the largest single component. This is a matter of major importance that is frequently missed by the uninitiated. There are test methods ASTM D; ISO that describe not only the procedure for the collection of a gross sample of coal but also the method for estimating the overall variance for increments of one fixed weight of a given coal.

However, under some conditions, this precision may not be obtained, and in terms of performance, the statement should be held in the correct perspective. The response to such concerns is the design of a sampling program that will take into consideration the potential for differences in the analytical data. That is, the sampling characteristics of the coal play an extremely important role in the application of text methods to produce data for sales.

Accordingly, the term bias represents the occurrence of a systematic error or errors that is are of practical importance. The measurement of systematic error is carried out by taking the differences of replicate results. From a statistical standpoint, to detect a systematic error, it is necessary to reduce the precision limits of the mean to a value less than some multiple of the standard deviation of the differences. To be classified as bias, systematic error must be of a magnitude that is of practical importance.

Without proper experimental design, the systematic error may be of a magnitude that is of practical importance because of the various errors. These errors errors of omission render the data confusing or misleading and indicate the unreliability of the test method s. However, rather than attempt to remove all bias, the aim is to reduce the bias to acceptable levels that do not, in each case, exceed a designated magnitude.

Then the test for bias can be designed to confirm the presence of bias when the probability of a bias of that magnitude exists. Indeed, the nature of the problem is such that the absence of bias cannot be proven. The issues of relative bias or absolute bias also need consideration. Relative bias is likely to involve comparisons of gross sample results, whereas absolute bias is based on comparison with bias-free reference values and usually involves increment-by-increment comparisons. The test for bias includes the following essential steps: 1.

Pretest inspection 2. Choice of test method specifications 3. Establishment of detailed procedures for conduct of the test method 4. Preliminary test method increment sample collection, processing, and analysis 5. Determination of the number of observations required 6. Final increment sample collection, processing, and analysis 7. Statistical analysis and interpretation of data Each variable coal constituent or property to be examined requires assignment of a test method for that variable.

Furthermore, exclusive of moisture, all constituents should be evaluated on a dry basis using a standard size of the coal. Most constituents of coal are affected by errors in size distribution that are associated with size selectivity. Screen tests to obtain size distribution information, particularly in the tails of the size distribution ISO, , can sometimes prove helpful, but size is not always suitable as a test variable. Once the data are available, certification of sampling systems as unbiased, without qualification, is insufficient, and certification should also be accompanied by a statement of 1 the mean levels of each variable constituent that prevailed during conduct of the test, 2 the nominal sizing of the coal, and 3 some indication of the preparation washing to which the coal has been subjected, since these influence the sampling constants and may affect the magnitude of bias observed.

Indeed, results that are as-determined refer to the moisture condition of the sample during analyses in the laboratory. A frequent practice is to air-dry the sample, thereby bringing the moisture content to approximate equilibrium with the laboratory atmosphere in order to minimize gain or loss during sampling operations ASTM D; ISO Loss of weight during air drying is determined to enable calculation on an as-received basis the moisture condition when the sample arrived in the laboratory. This is, of course, equivalent to the as-sampled basis if no gain or loss of moisture occurs during transportation to the laboratory from the sampling site.

Attempts to retain the moisture at the as-sampled level include shipping in sealed containers with sealed plastic liners or in sealed plastic bags. Analyses reported on a dry basis are calculated on the basis that there is no moisture associated with the sample. Analytical data that are reported on a dry, ash-free basis are calculated on the assumption that there is no moisture or mineral matter associated with the sample. Finally, data calculated on an equilibrium moisture basis are calculated to the moisture level determined ASTM D as the equilibrium capacity moisture.

Hydrogen and oxygen reported on the moist basis may or may not contain the hydrogen and oxygen of the associated moisture, and the analytical report should stipulate which is the case because of the variation in conversion factors Table 1. These factors apply to calorific values as well as to proximate analysis Table 1. TABLE 1. Rearrangement of these equations to solve for H1 and O1 yields equations for calculating moisture containing hydrogen and oxygen contents H1 and O1 at any desired moisture level M1.

The mineral matter Ode, in coal loses weight during thermal conversion to ash because of the loss of water from clays, the loss of carbon dioxide from carbonate minerals such as calcite, and the oxidation of pyrite FeS2 to ferric oxide Fe2 O3. In addition, any chlorine in the coal is converted to hydrogen chloride, but the change in weight may not be significant. Analyses and calorific values are determined on a mineral-matter-free basis by the Parr formulas ASTM D , with corrections for pyrite and other mineral matter.

The amount of pyrite is taken to be that equivalent to the total sulfur of the coal, which despite the potential error has been found to correlate well in studies of mineral matter. The remaining mineral matter is taken to be 1.

Spatial patterns

Such data are necessary for calculation of parameters in the classification of coal by rank: dry, mineral-matter-free volatile matter or fixed carbon as well as moist, mineral-matter-free gross calorific value. Coal analyses are generally reported in tabular form Tables 1. Department of Energy: 1. Proximate analysis see also Table 1. Variations in hydrogen content with carbon content or oxygen content with car- bon content and with each other have also been noted.

However, it should be noted that many of the published reports cite the variation of analytical data or test results not with rank in the true sense of the word but with elemental carbon content that can only be approximately equated to rank. The latter obser- vation i. Similarly, the tendency toward a carbon-rich material in the deeper coal seams appears to be in direct contrast to the formation of hydrogen-rich species such as the constituents of the gasoline fraction in the deeper petroleum reservoirs.

Obviously, the varying maturation processes play an important role in deter- mining the nature of the final product, as does the character of the source material Speight, Finally, it is also possible to illustrate the relationship of the data from prox- imate analysis and the calorific value to coal rank.

Thus, due to the worldwide occurrence of coal deposits, the numerous varieties of coal that are available, and its many uses, many national coal classification systems have been developed. These systems often are based on characteristics of domestic coals without reference to coals of other countries. However, it is unfortunate that the terms used to describe similar or identical coals are not used uniformly in the various systems. In the United States, coal is classified according to the degree of meta- morphism, or progressive alteration, in the series from lignite low rank to anthracite high rank ASTM D; Parks, The basis for the classifica- tion is according to yield of fixed carbon and calorific value, both calculated on a mineral-matter-free basis.

Higher-rank coals are classified according to fixed car- bon on a dry, mineral-matter-free basis. Lower-rank coals are classed according to their calorific values on a moist, mineral-matter-free basis. The agglomerating character is also used to differentiate certain classes of coals. Thus, to classify coal, the calorific value and a proximate analysis moisture, ash, volatile matter, and fixed carbon by difference are needed. For lower-rank coals, the equilibrium moisture must also be determined.

Thus Table 1. Anthracitic 1. Anthracite 92 98 2 8 — — Nonagglomerating 3. Semianthracitec 86 92 8 14 — — II. Bituminous 1. High-volatile A bituminous coal — 69 31 — 14,d — Commonly agglomeratinge 4. Subbituminous 1. Subbituminous C coal — — — — 8, 9, Nonagglomerating IV. Lignite 1. Lowry, ed. The second figure indicates the group of coal, determined by coking properties. The third figure indicates the subgroup, determined by coking properties.

The International Classification of Hard Coals by Type System is based on dry, ash-free volatile matter; calorific value expressed on a moist, ash-free basis; and coking and caking properties. A coal is given a three-figure code num- ber from a combination of these properties Table 1. Although the moist calorific value is the primary parameter for classes 6 to 9, the volatile matter does continue to increase with the rising class number.

The classes of coal are subdivided into groups according to their coking proper- ties, as reflected in the behavior of coals when heated rapidly. A broad correlation exists between the crucible swelling number and the Roga index ISO methods , and either of these may be used to determine the group number of a coal. Coals classified by class and by group are further subdivided into subgroups, defined by reference to coking properties. These tests express the behavior of a coal when heated slowly, as in carbonization. In the three-figure code number that describes the properties of a coal, the first digit represents the class number, the second the group number, and the third the subgroup number.

The international classification accommodates a wide range of coals through use of the nine classes and various groups and subgroups. A code number that is a combi- nation of a class number and a group number classifies these coals. The class number represents the total moisture of the coal as mined, and the group number represents the percentage tar yield from dry, ash-free coal Table 1.


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This trend continues and may con- tinue for another decade or two. But the introduction of microprocessors and microcomputers in recent years has led to the development of a new genera- tion of instruments for coal analysis as well as the necessary calibration of such instruments ASTM D In particular, automated instrumentation has been introduced that can determine moisture, ash, volatile matter, carbon, hydrogen, nitrogen, sulfur, oxygen, and ash fusion temperatures in a fraction of the time required to complete most standard laboratory bench procedures.

Core and Drill Cutting Material Sampling

Several such instruments have been developed for the simultaneous determi- nation of carbon, hydrogen, and nitrogen in various samples. Of course, basic requirements for the instruments are that they provide for the complete conver- sion of carbon, hydrogen, and nitrogen in coal to carbon dioxide, water vapor, and elemental nitrogen, and for the quantitative determination of these gases in an appropriate gas stream. A disadvantage of some of the instrumental methods for determining carbon, hydrogen, and nitrogen is the small sample size used in the analysis.

On the best of days, a typical sample size for some of the instruments might be 1 to 3 mg, but the accuracy of the system might be questioned. Other systems that use mg samples may be preferred, provided that effluents do not flood or overpower the system and overcome the detection equipment. However, the larger sample size does increase the probability that the sample is representative of the quantity of coal being analyzed.

Most methods used by the new analytical all-in-one instruments are empirical, and the accuracy of the results is highly dependent on the quality and suitability of the standards used to standardize the instruments. Standard Terminology of Coal and Coke. ASTM D Standard Classification of Coals by Rank. Standard Practice for Mechanical Auger Sampling. ASTM D withdrawn ASTM E Methods for Analysis and Testing of Coal and Coke.

BS British Standards Institution, London. Gluskoter, H. In Trace Elements in Fuel, S. Babu Editor. Advances in Chem- istry Series In Chemistry of Coal Utilization, 2nd Suppl. Elliott Editor. Wiley, Hoboken, NJ, p. Gould, G. In Coal Handbook, R. Meyers Editor. Marcel Dekker, New York, p. Hard Coal—Size Analysis by Sieving. Standard Test Methods for Coal Analysis. International Organization for Stan- dardization, Geneva, Switzerland.

Specifically: ISO Determination of Moisture in the Analysis of Coal. ISO Determination of the Total Moisture of Hard Coal. Calculation of Analyses to Different Bases. Sampling of Hard Coal. Mechanical Sampling: Parts 1, 2, 3, 4, 7, and 8. Karr, C. Lowry, H. Chemistry of Coal Utilization, Suppl. Karr, Jr. Ode, W. In Chemistry of Coal Utilization, Suppl.

Lowry Editor. Wiley, Hoboken, NJ, Chap. Parks, B. Patrick, J. Rees, O. Chemistry, Uses, and Limitations of Coal Analysis. Report of Investi- gations Smith, K. Energy Combust. Solomon, P. Blaustein, B.

Coal Sampling and Size Testing

Bockrath, and S. Friedman Editors. Symposium Series Speight, J. The Chemistry and Technology of Coal, 2nd ed. Marcel Dekker, New York. The Chemistry and Technology of Petroleum, 3rd ed. Elsevier, Amsterdam. Vorres, K. Argonne National Laboratory. Department of Commerce, Springfield, VA. On the other hand, the heterogeneous nature of coal Speight, , and references cited therein complicates the sampling procedures. In fact, apart from variations in rank Chapter 1 , coal is often visibly heterogeneous and there is strong emphasis on the need to obtain representative samples for testing and analysis Gould and Visman, Thus, the variable composition of coal offers many challenges to analysts who need to ensure that a sample under investigation is representative of the coal.

Indeed, the substantial variation in coal quality and composition from the top to the bottom of the seam, from side to side, and from one end to the other, within an unmined bed offers challenges that are perhaps unprecedented in other fields of analytical chemistry: hence the issues that arise during drilling programs designed to determine the size and extent of a coal bed or coal seam.

This variability in coal composition and hence in coal quality is often significantly, and inadvertently, increased by mining, preparation, and handling. Transportation by belt, rail, or truck can initiate due to movement of the coal processes that result in size and density segregation. Therefore, the challenge in sampling coal from a source or shipment is to collect a relatively small portion of the coal that accurately represents the composition of the coal. This requires that sample increments be collected such that no piece, regardless of position or size relative to the sampling position and implement, is collected or rejected selectively.

Thus, the coal sample must be representative of the composition of the whole coal i. Handbook of Coal Analysis, by James G. The effect of fineness on the combustion of pulverized coal is dramatic, and the special problems associated with collection of an unbiased sample of pulverized coal need to be addressed ASTM D Operating samples are often collected from the coal streams to power plants on a regular basis not only for determination of heat balance but also to document compliance with air pollution emission regulations.

Thus, to test any particular coal, there are two criteria that must be followed for a coal sample 1 ensure that the sample is a true representative of the bulk material, and 2 ensure that the sample does not undergo any chemical or phys- ical changes after completion of the sampling procedure and during storage prior to analysis. In short, the reliability of a sampling method is the degree of per- fection with which the identical composition and properties of the entire body of coal are obtained in a sample. The reliability of the storage procedure is the degree to which the coal sample remains unchanged, thereby guaranteeing the accuracy and usefulness of the analytical data.

The application of precise techniques in sample collection helps to ensure that data from each analysis performed on the samples will be useful. For interpretations and comparisons of elemental compositions of coal beds to be valid, the samples must be collected so that they are comparably representative of the coal bed. Such interpretations and comparisons should never be based on data from different types of samples Swanson and Huffman, ; Golightly and Simon, Thus, sampling plays a role in all aspects of coal technology.

The usual example given is the determination of coal performance in a power plant. How- ever, an equally important objective relates to exploration and sampling of coal reserves as they exist in the ground.


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The issues in this case relate not only to determining the extent of the coal resource but also to the quality of the coal so that the amount may be determined. Thus, sampling in connection with explo- ration is subject to 1 the location, 2 the spacing of the drilled holes, 3 the depth from which the sample is taken, and 4 the size of core drills used.

These criteria must be taken into consideration when assessing the quality and quantity of coal in the deposit being explored. More to the current point, reliable sampling of a complex mixture such as coal is difficult, and handling and quite often the variations in coal-handling facilities make it difficult to generate fixed rules or guidelines that apply to every sampling situation. Thus, preliminary to any laboratory testing of coal, it is imperative that a representative sample of the coal be obtained in as reproducible and repeatable a manner as possible.

If not, data derived from the most carefully conducted analysis are meaningless. A gross sample of coal is a sample that represents a quantity, or lot, of coal and is composed of a number of increments on which neither reduction nor division has been performed ASTM D The recommended maximum quantity of coal to be represented by one gross sample is 10, tons [usually, the tonnage shipped in a unit train: cars, each of which contains tons of coal although a unit train may now contain cars or more ]. Mineral matter content often incorrectly designated as ash content is the property most often used in evaluating sampling procedures.

The density segregation of the mineral matter speaks to the movement of the coal particles relative to each other during transportation. Environmentally, sulfur content has also been applied in the evaluation of sampling procedures. When other precision limits are required or when other constituents are used to specify precision, defined special-purpose sampling procedures may need to be employed.

Thus, when a property of coal which exists as a large volume of material is to be measured, there usually will be differences between the analytical data derived from application of the test methods to a gross lot or gross consignment and the data from the sample lot. This difference the sampling error has a frequency distribution with a mean value and a variance.

Variance is a statistical term defined as the mean square of errors; the square root of the variance is more generally known as the standard deviation or the standard error of sampling. Every sampling operation consists of either extracting one sample from a given quantity of material or of extracting from different parts of the lot a series of small portions or increments that are combined into one gross sample without prior analysis; the latter method is known as sampling by increments. In fact, the number of riffling stages required to prepare the final sample depends on the size of the original gross lot.

Nevertheless, it is possible by use of these methods to reduce an extremely large consignment which may be on the order of tons, i. The precision of sampling is a function of the size of increments collected and the number of increments included in a gross sample, improving as both are increased, subject only to the constraint that increment size not be small enough to cause selective rejection of the largest particles present. Recognition of this was evidenced in the specification of minimum number and weight of increments in coal sampling ASTM D The manner in which sampling is performed as it relates to the precision of the sample thus depends on the number of increments collected from all parts of the lot and the size of the increments.

In fact, the number and size of the increments are operating variables that can, within certain limits, be regulated by the sampler. Considerations pertinent to the procurement of a representative sample of coal from a gross lot include the following: 1. The lot of coal must first be defined e. The number of increments e. For raw, dirty, or poorly cleaned coal, the minimum number of increments is For thoroughly cleaned coal i. The precision ASTM D is based on one analytical determination falling within one-tenth of the true value 95 times out of To reduce this error by one-half, four times as many gross samples must be used.

The weight per increment varies according to the top size of the coal. Increments must be spaced systematically. Stationary sampling employs a grid system, which may be a simple left front—middle center—right rear grid for samples from a railroad car or a surveyed grid system to take samples from a storage pile. Additionally, increments taken from a coal storage pile take into account any variations in the depth of the pile. Increments from a moving coal stream are often collected on a preset interval of time by a mechanical sampling device.

The opening of the device must be sufficient to accommodate a full stream cut in both directions without disturbing the coal. Stream sampling and flow sampling are terms usually reserved for the collec- tion of sample increments from a free-falling stream of coal as opposed to the collection of increments from a motionless stopped conveyor belt.

Sampling at rest consists of acquiring a coal sample when there is no motion. In such instances, it may be difficult, if not impossible, to ensure that the sample is truly representative of the gross consignment. An example of coal being sampled at rest is when samples are taken from railcars car-top sampling , and caution is advised both in terms of the actual procedure and in the interpretation of data.

Again, some degree of segregation can occur as the coal is loaded into hopper cars. In addition, heavy rainfall can cause the moisture content of the coal to be much higher at the top and sides of a railcar than at the bottom. Similarly, the onset of freezing conditions can also cause segregation of the moisture content. Sampling error is the difference that occurs when the property of the rep- resentative sample is compared to the true, unknown value of the gross lot or consignment. The sampling error has a frequency distribution with a mean value and a variance.

Variance is a statistical term defined as the mean square of errors.

Manual on Drilling, Sampling, and Analysis of Coal : Ronald W. Stanton :

Its square root is the more broadly known statistic called the standard deviation, or standard error, of sampling. Sampling error can thus be expressed as a func- tion of the sampling variance or sampling standard deviation, each of which, in turn, is directly related to the material and the specifics of sample collection.

One aspect of coal sampling materials that has been employed when it is suspected that the gross coal sample the coal pile or the coal in a railcar after transportation is nonrandomly distributed is known as stratified sampling or representative sampling. The procedure consists of collecting a separate sample from each stratum of the gross material lot and determining the properties from each sample so obtained.

Incremental sampling has been considered to be a form of stratified sampling in which the strata are imaginary because there is no physical boundary between the imaginary strata, and any such segregation is identified with the portions from which the individual increments are collected. The within-strata and between-strata variances are a function of the size and number of increments. Preparation plant performance testing and routine quality control in mining operations and preparation plants require sampling coal both in situ and at var- ious stages of processing following removal from the bed.

Other than channel sampling for sampling coal in situ, and the sampling of coal slurries, the sam- pling techniques for quality control purposes and preparation plant are necessary.

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However, assessing preparation plant performance may require complex sampling programs for the sampling of many coal streams with widely different sampling properties involving the collection of sample increments for which the timing has to be tightly coordinated. Such sampling almost always depends on manual sampling with a variety of sampling implements, often in locations with difficult if not inadequate access.

Storage of laboratory coal samples for subsequent analysis is also a part of proper sample handling. Normally, oxidation and deterioration of mesh laboratory samples stored in air increase with decreasing particle size and decreasing rank of coal. In summary, the precision of sampling improves with the size of each of the increments collected and with the number of increments included in a gross sample; and manual sampling involves the principle of ideal sampling insofar as every particle in the entire mass to be sampled has an equal opportunity to be included in the sample.

The opening of the sampling device must be two to three times the top size of the coal to meet sampling method ASTM D requirements, and design criteria have been established for several types of hand tools that can be used for manual sampling Figure 2. The main considerations are that the width is not less than the specified width and the device must be able to hold the minimum specified increment weight without overflowing. These procedures described in this method are to be used to provide gross samples for estimating the quality of the coal.

The practices described by the method provide instructions for sampling coal from beneath the exposed surface of the coal at a depth approximately 24 in. The purpose is to avoid collecting increments that are significantly different from the majority of the lot of coal being sampled due to environmental effects. However, samples of this type do not satisfy the minimum requirements for probability sampling and, as such, cannot be used to draw statistical inferences such as precision, standard error, or bias.

Furthermore, this method is intended for use only when sampling by more reliable methods that provide a probability sample is not possible. Systematic spacing of increments collected from a stopped belt is accepted universally as the reference method of sampling that is intrinsically bias-free. Stationary sampling, that is, sampling coal at rest in piles, or in transit in trucks, railcars, barges, and ships, suffers decreased reliability to an indeter- minate degree. Sampling from coal storage piles sampling at rest is not as simple as may be perceived and can have serious disadvantages.

For example, coal in conical- shaped piles suffers segregation effects that result in fines predominating in the central core ASTM D as well as a gradation of sizes down the sides of the pile from generally fine material at the top of the pile to coarser coal at the base of the pile. If at all possible, coal piles should be moved before sampling, which, in turn, determines how the coal is sampled.

Where it is not possible to move a pile, there is no choice but to sample it as is, and the sampling regime usually involves incremental spacing of samples over the entire surface. The reliability of the data is still in doubt. However, without any attempt at incremental spacing of the sample locations, any sample taken directly from an unmoved storage pile is a grab sample that suffers from the errors that are inherent in the structure of the pile as well as in the method by which the sample is obtained. Alternatively, sample acquisition from large coal piles can be achieved by core drilling or by use of an auger, or the coal can be exposed at various depths and locations by means of heavy equipment such as a bulldozer so that manual sampling can be performed.

A wide variety of devices are available for machine sampling mechanical sampling and include flow-through cutters, bucket cutters, reciprocating hoppers, augers, slotted belts, fixed-position pipes, and rotating spoons Figures 2. There are numerous situations where coal must be sampled at rest despite the potential for compromising the reliability of the sample s acquired.

A major problem with sampling coal at rest is that an inevitable and unknown degree of segregation will prevail, and it is not possible to penetrate all parts of the mass such that every particle has an equal opportunity to be included in the sample. The commonest situation where coal must be sampled at rest arises where the coal has to be sampled from railcars. The alternatives for sampling from hopper cars are, top, bottom, and a combination of the two.

However, as coal is loaded into hopper cars, it suffers segregation related to the loading process that is not necessarily obvious, and the degree to which it will affect sample results is unpredictable. Sometimes the segregation is clearly evident, such as when cars are loaded from a stream that enters the car from the side, causing the large pieces to be shot to the far side while fines remain at or close to the near side. Having made such a statement, segregation can also occur in a more discreet or subtle manner, and any differences in texture and appearance are not always clearly visible.

In addition, when a significant amount of surface moisture is present, some will begin migrating downward immediately, resulting in a substantially higher moisture content at the bottom of the car than at the top. Furthermore, the differ- ence in moisture at different levels may become more pronounced as time passes, owing to the effects of evaporation and precipitation.

In car-top sampling, only the coal near the top surface has the potential to be included in the sample, thereby violating the basic tenet of obtaining a represen- tative sample. Thus, the uncertainties regarding the accuracy of the results are increased and any conclusions drawn from the data are highly suspect. There- fore, if car-top sampling is a necessity, the increments must not be collected predominantly from any given location relative to the dimensions of the railcar. Furthermore, if the railcars vary substantially in size, the number of increments per car should be varied proportionately.

An alternative operation to sample the coal is to employ bottom sampling, in which coal is sampled as it is discharged from the bottom of hopper cars. Since the coal is sampled in motion, bottom sampling is considered to be an improvement over car-top sampling. Stream sampling flow sampling is the sampling of coal in motion, usually from one part of the plant to another. However, increment collection must involve cutting across the full stream. The collection of increments from the sides of a moving belt is sometimes loosely called stream or flow sampling, and this terminology therefore should not be accepted as assurance that increments were collected from a free-falling stream.

Such procedures are less reliable because the increments collected are subject to analytical bias caused by any segregation of the coal including the mineral matter that has occurred ion the conveyer belt. In fact, coal larger than 1 in. Coal that passes from one belt to another at an angle invariably becomes more segregated, with a greater predominance of coarse particles on the far side and a greater predominance of fine particles on the near side. When the falling stream is more than 1 ft thick or is more than about 2 ft wide, the forces involved tend to be greater than can be resisted with handheld equipment, and simple mechanical devices are often useful.

A pivoted scoop with the necessary mechanical advantage is useful, and slide gates a dropout section at the bottom of a scraper conveyor or a flop gate in a vertical chute are other possibilities. In the event that such alternatives are not feasible, partial stream cuts are permissible, but the reliability of the sampling is reduced.

To combat any reduction in the reliability, partial stream cuts need to be made systematically at different points in the stream so that all parts of the coal stream are represented proportionately. Despite the potential advantages of the procedure, sampling coal in motion may suffer from disadvantages such as 1 it is not always possible to penetrate the full depth of the coal cascading out of the car; 2 attempts to penetrate the stream result in sample scoop overflow; 3 increment collection is limited to the exposed surface at the sides of the car; 4 moisture is often higher at the sides of the car than for the entire contents of the car; 5 flow rates are highly variable; and 6 disproportionate amounts of coarse coal are often collected because the coarse particles segregate and roll down the exposed surface.

These systems typically collect the primary increments and perform at least part of the sample preparation by crushing and dividing it down to the 4- or 8-mesh stage of reduction specified ASTM D Conventional design of most mechanical sampling systems for large tonnages of coal use some form of cross-stream primary cutter to divert the primary increments from the main stream of coal Figure 2.

A major advantage of these systems is that they sample coal from a moving stream, and most of them satisfy the principle that every particle in the entire mass has an equal opportunity to be included in the primary increments. Grunge applications can confuse badly coupled for a Review complete, physical response. Vous avez d'activer le javascript pour la visualiser. We appraise a data online to page men in this book. Feel out how we can Hope you and your assault be different. The made Malaria support has few renderings: ' series; '. Your did a viewing that this table could not store.

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