COAL BLENDING MODEL Theory and Application of the Model by EDWIN
COAL BLENDING MODEL
Theory and Application of the Model
by
EDWIN ALOIS BAUER
B.A.Sc., The University of British Columbia, 19
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF APPLIED SCIENCE
in
THE FACULTY OF GRADUATE STUDIES
Mining and Mineral Process Engineering
University of British Columbia
We accept this thesis as conforming
to the required standard
THE UNIVERSITY OF BRITISH COLUMBIA
December 1988
(c)Edwin Alois Bauer, 1988 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission.
Department of ft\'in\rt^ + M; A<*f»\ Prated gnj.
The University of British Columbia Vancouver, Canada
Date kprfl 1 L A 1
DE-6 (2/88) Pg ii
ABSTRACT
Over the past decade, most Western Canadian coal mines have been forced to mine deposits containing multiple seams of coal, with varying coal qualities. This change in mining practice has caused considerable challenges for coal washery personnel. Blending or homogenization of these multiple seams has been the standard approach in attempting to minimize the disruption to washery operations. The purpose of this research was to develop a method of quantifying the effects of a controlled blending program on preparation plant yield, thus providing a way to optimize the blending program within the constraints of the mining program, the processing unit operations, and the final product quality constraints.
A yield-based objective function called the Coal
Blending Coefficient was developed to evaluate the effects of blending on preparation plant yield. This formula can be described as the difference in yield between blending and batching of the same coals. The Coal Blending Coefficient was then incorporated into a collection of existing computer programs called the CANMET Coal Data Manipulation Programs, and after some modifications, the Coal Blending Model was produced. The Coal Plant Simulation program, which is included in the CANMET program, is the heart of the model, while the Pg iii
Coal Blending Coefficient values allow the model to rank the blends.
To date, approximately twenty runs of the Coal Blending
Model have been tried on coals from three British Columbia coal deposits. The results range from zero benefit of blending for similar quality seams, to potential gains of over five percent increase in yield for highly varied seam qualities. Most runs produced Coal Blending Coefficient values in excess of one, which represent a potential gain in profits of over ten million dollars for the Western Canadian coal industry. Though these initial trials have been successful, further improvements must be made to the Coal Blending Model, and actual field testing performed before this model would be available for use within the industry. Pg iv TABLE OF CONTENTS PAGE NO.
ABSTRACT ii
LIST OF TABLES vi
LIST OF FIGURES vii
ACKNOWLEDGEMENTS viii
I. INTRODUCTION
General 1 Statement of the Problem 1 Scope of the Study 3
II. LITERATURE REVIEW
Introduction to Gravity Separation 5 Float-And-Sink Analysis 10 Method of Analysis 13 Plant and/or Equipment Efficiency 17 Effect of the Raw Coal 18 Effect of the Cleaning Unit 19 Methods of Raw Coal Blending: 25 No Blending 26 Batching 27 Homogenization 29 Blending Prior To Treatment 30 In-Pit Blending 31 Summary 32 Preparation Plant Computer Simulation Modeling.... 33
III. DEVELOPMENT OF THE COAL BLENDING MODEL
Introduction 35 Development of the Coal Blending Coefficient 36 Coal Blending Model Description 41 Model Input 45 Model Output 51 Summary 57
IV. COAL BLENDING MODEL APPLICATION 59
Example Problems and Data Evaluation: 61 Example Problem One: Two Seam Blend 62 Example Problem Two: Three Seam Blend "1" 68 Example Problem Three: Three Seam Blend "2".... 75 Pg v TABLE OF CONTENTS (continued...) PAGE NO.
V. SUMMARY AND REMARKS 81
VI. REFERENCES 84
VII. APPENDICES: 87
A. Coal Blending Model Program Listings.... 88
B. Washability Data Used For Example Problems 92
C. Coal Blending Model Results: Example Problem One.. 101
D. Coal Blending Model Results: Example Problem Two 107
E. Coal Blending Model Results: Example Problem Three 123 Pg vi LIST OF TABLES
PAGE NO.
I. Classification of Coals by Rank 7
II. Cumulative Float Data 39
III. List of Required Input Information 47
IV. Sample Model Inputs 52
V. Sample Batching Results 55
VI. Sample Coal Blending Model Results 56
VII. Coal Production For Example One 66
VIII. Coal Production For Example Two 74
IX. Coal Production For Example Three 76 Pg vii LIST OF FIGURES
PAGE NO.
1. Sample Washability Graph. 11
2. Distribution Curve of a Perfect Separation at 1.50 Specific Gravity 20
3. Illustration of Probable Error (EPM) of a Separation at 1.50 Specific Gravity 21
4. Imperfection as a Function of Probable Error and Specific Gravity of Separation: United States Bureau of Mines 24
5. Benefits of Raw Coal Homogenization 28
6. Coal Blending Model Flowsheet 42
7. Two Seam Blend Model Results: Example One 63
8. Three Seam Blend Model Results: Example Two Coal Blending Coefficient Contours No. 1 70
9. Three Seam Blend Model Results: Example Two Coal Blending Coefficient Contours No. 2 71
10. Three Seam Blend Model Results: Example Two Coal Blending Coefficient Contours No. 3 72
11. Three Seam Blend Model Results: Example Three Coal Blending Coefficient Contours 77
12. Three Seam Blend Model Results: Example Three Blending Feasibility Zones 78 Pg viii
ACKNOWLEDGEMENTS
I wish to acknowledge and thank the following people and organizations for their support and encouragement:
Professor Allan Hall; University of British Columbia
Dr. David Osborne and Tony Walters; Kilborn Engineering
Tom Milner; Quinsam Coal Limited
Ian Parsons; CANMET Coal Research Laboratory
Ross Leeder; Denison Mines Ltd.
I also wish to thank my wife, Maureen, for her help, understanding, and support, for without her encouragement, this thesis may never have been completed. 1
I.INTRODUCTION
GENERAL
The coal mining industry is of significant economic
importance to Canada. In 1984, there were 12 operating coal preparation plants in Western Canada, as well as one in Eastern
Canada, all processing coal for export (Duncan) (1). The plants ranged in capacity from approximately 400 to 2000 tonnes per hour. Total capacity is over 10,500 tonnes per hour of treatment capacity, which is in excess of 50 million tonnes of clean coal per year.
STATEMENT OF THE PROBLEM
Ten years ago, the majority of Western Canadian coal mines worked deposits consisting of one or two economical seams.
Since then, the changes in operating and economic conditions have necessitated multiple seam mining, and some mines currently work up to ten separate seams in a single pit. Even though Rocky Mountain coals have a similar rank to the carboniferous coals of Western Europe and the Eastern United
States, their seam structure is very different from coking coal The Coal Blending Model Pg 2
deposits elsewhere (Butcher)(2). The development of the mountain coal seams was accompanied by severe geological disturbances which caused most of the coal seams to be sheared and the strata to become highly inclined, closely folded and repeated by overthrusts. Mining these multiple seams requires coping with these complex physical conditions, including: variable seam pitch and thickness; rugged, diverse topography; sundry roof and floor strata; as well as the most important variable to the coal preparation process-- variable coal qualities.
Multiple seam mining, with its added complexities, was significant in the lower than expected yields experienced by several Western coal washeries recently. The cost associated with low yields has been calculated by Picard (3), who determined in 1985 that, for each 1% improvement in recovery that could be achieved without loss of quality, the Canadian coal mining industry as a whole would gain $11-13 million per year at the current prices and production rates. Plant yield is affected by a large variation in feed quality that commonly occurs in multiseam mining operations. This variation in coal quality can have diverse effects on the different unit operations in the plant, resulting in a decrease of overall The Coal Blending Model Pg 3
plant yields. Blending or homogenization methods have been proven to help minimize the variations in plant feed, thus improving the overall production yield. In Western Canadian coal mines, most multiple seam mines practice some form of blending, but few of these coal mines have determined how blending affects their washery yield. The rest have developed arbitrary criteria for blending which may or may not optimize washery yield. Coal mines require a reliable method which can be used to establish a blending strategy for the life of the mine, thus optimizing the clean coal yield.
SCOPE OF THE STUDY
The main objective of this research was to develop a method of evaluating the effects of controlled blending on preparation plant efficiency. A criterion for evaluation of the relative plant efficiency due to controlled blending of multiple seams was developed and is called the Coal Blending
Coefficient. Once the Coal Blending Coefficient's formula was determined, the next stage of the study was data collection.
The data collection had to be done in one of three ways: using a pilot plant, an operating mine, or a reliable preparation plant simulation model. Unfortunately, the first two options were not available due to the time and financial constraints of these procedures. A computer simulation model was the most The Coal Blending Model Pg 4
appropriate alternative.
Plant simulation modeling was not the key objective of the project and, therefore, any number of reliable plant simulation models could have been selected for this research. The Coal
Data Manipulation Model (4), produced by CANMET, was chosen for the project for the following four main reasons:
1/ The model was compatible to computer
hardware available at the University of
British Columbia facilities;
2/ The model was accessible to the author at
U.B.C. for research purposes;
3/ The model was written in a modified basic
language familiar to the author; and
4/ The model is user-friendly and simple to
run. The Coal Blending Model Pg 5
The achievement of the following sub-objectives also formed part of this project:
a) To develop a better understanding of the effects of raw
coal blending on preparation plant yield.
b) To investigate the utility of in-pit blending, for
Western Canadian coal mines.
c) To develop in-pit blending criteria to give the maximum
amount of production flexibility, while satisfying
preparation plant needs, and minimizing the capacity
required for raw coal stockpiles.
d) To improve preparation plant yields, thus reducing
coal wastage and improving profits.
II. LITERATURE REVIEW
INTRODUCTION TO GRAVITY SEPARATION
Geologically, coal is a metamorphosed sedimentary rock containing a mixture of constituents which not only vary among different coals, but also vary within a particular seam. This The Coal Blending Model Pg 6
heterogeneous material contains combustible organic minerals
and inorganic mineral matter, formed essentially from plant
remains preserved from complete decay in a favorable
environment, and later altered by various chemical and physical
actions. Coal is, therefore, any mixture of hydrocarbons with
intrinsic and extraneous organic and inorganic impurities.
The formation of coal begins with the conversion of
decaying vegetation into peat. "Coal" is a term which covers
the different stages of coalification from brown coal, to
lignite, to sub-bituminous coal, bituminous coal and on to
anthracite. Each of these stages is indicated by the degree of
conversion of the decaying vegetation. The conversion is an
ongoing change in the ratio of volatile material to fixed
carbons. Volatile matter is the component of the coal
exclusive of moisture that is driven off when the coal is
heated. Therefore, the higher the fixed carbon content, the
greater the degree of conversion.
A method for the standard classification of American coal and its degree of conversion, or "rank", has been developed by the American Society for Testing and Materials. This method of
rating coal by rank is based on chemical analyses and specific physical tests that measure the increasing response of coal to pressure and/or heat (metamorphism). This progressive response TABLE I. CLASSIFICATION OF COAL BY RANK *
Fixed Carbon Volatile Mat• Calorific Value Limits, % ter Limits, Limits, Btu per (Dry Mineral- % (Dry, Min• Lb (Moist,' Matter-Free eral-Matter- . Mineral-Matter- Basla) Free Basis) Free Basis)
Equal Equal Equal or. . or or Greater Less Greater Less Greater Less Agglomerating Claw Qronp Than Than Than Than Than Than Character 1. Mcta-authracite 98 2 I. Anthracitic 2. Anthracite 92 98 8 Nonagglomerating 3. Semianthracite • 86 92 14 1. Low-volatile bituminous 78 86 14 coal 2. Medium-volatile bitumi• 69 78 22 31 nous coal 3. High-volatile A bitu• 69 31 14,000 << II. Bituminous minous coal Commonly ag• 4. High-volatile B bitu• 13,000 * 14,000 glomerating * minous coal 5. High-volatile C bitu-. [11,500 13,000 minous coal 110,500 11,500 Agglomerating 1. Subbituminous A coal 10,500 11,500* III. Subbituminous 2. Subbituminous B coal 9,500 10,500 3. Subbituminous C coal 8,300 9,500 ' Nonagglomerating 6,300 8,300 IV; Lignitic 1. Lignite A 2. Lignite B 6,300.
* From: American Society for Testing and Materials, D 388. ° This classification does not include a few coals, principally nonbanded varieties, which have unusual physical and chemical prop• erties and which come within the limits of fixed carbon or calorific value of the high-volatile bituminous and subbituminous ranks. AU of these coals either contain less than 48% dry, mineral-matter-free fixed carbon or have more than 15,500 moist, mineral-matter-free Btu per lb. B Moist refers to coal containing its natural inherent moisture but not including visible water on the surface of the coal. e If agglomerating, classify in low-volatile group of the bituminous class. <* Coals having 69% or more fixed carbon on the dry, mineral-matter-free basis shall be classified according to fixed carbon, regard• less of calorific value. 'It is recognized that there may be nonagglomerating varieties in these groups of the bituminous class, and there are notable exceptions in high-volatile C bituminous group. The Coal Blending Model Pg 8
is indicated in an ongoing coal series that ranges from lignite through the various ranks of bituminous coal through to anthracite and meta-anthracite, as shown in Table I.
The rank of coal is an indication of the position of a coal in relation to other coals in the coalification series. In summary, the coal's rank shows its maturity in terms of general physical and chemical properties.
According to Jack A. Simon, in Elements of Practical Coal
Mining(5):
"In determination of rank of coal, mineral matter is
excluded from the analysis, as it in no way reflects the
degree of metamorphism of the coal. In the higher ranks
of coal, moisture is generally low and is excluded in
determination of rank. In the lower-rank coals, where
moisture is considered to be a fundamental property of
the coal, moisture is included in the analysis on which
rank is based....
The highest rank of coal, as shown in Table I, is
meta-anthracie. Coal of this rank is relatively rare and
resembles, both chemically and physically, the mineral
graphite (pure carbon). Meta-anthracite has been
described from a number of localities in the world,
commonly associated with ingneous intrusions. It has
also been described from Precambrian rocks and is The Coal Blending Model Pg 9
believed to be derived from algal or fungal
accumulations. Meta-anthracite has been mined
commercially in Rhode Island."
The purpose of a coal preparation plant is to upgrade the quality of the run-of-mine (ROM) coal. In mining, ROM coal is the product that is produced at the coal face, while clean coal describes the coal after it has been upgraded by screening, heavy media separation, flotation or by any other means. In coal cleaning, the separation of the organic minerals from the extraneous inorganic impurities is achieved by exploiting some differences in properties. For gravity separating devices, the principal mineral property used for separation is its specific gravity. Consequently, the specific gravities of the impurities associated with coal have primary importance. The specific gravity of a body is the ratio of the weight of the body in air and the weight of an equal volume of water. The specific gravity of coal can vary between 1.25 and 1.7, due to differences in rank and moisture, and in the methods used to determine specific gravity. The specific gravity of clean coal increases with the change in rank from lignite to anthracite.
Other components being equal, the denser impurities can be removed in the cleaning operation more easily than can the lighter impurities, which approach in density the coal from which they are being separated. The Coal Blending Model Pg 10
FLOAT-AND-SINK ANALYSIS
To determine specific gravity distribution, more commonly called the washability characteristics, of the ROM coal, the preparation engineer must perform a float-and-sink test.
Initially, a size analysis of the ROM coal from the seam in question must be performed. The desired size fractions of the coal are then placed in a bath containing a liquid of a known specific gravity. The coal that floats will then have a specific gravity which is less than the liquid in the bath, and the material that sinks will have a specific gravity greater than that of the bath. By starting with the specific gravity level least expected (normally 1.3), and increasing the specific gravity of the bath by small increments, a specific gravity distribution of the ROM coal can be obtained.
The next step is to determine the ash (inorganic material) content of each float taken from the float-and-sink test. For bituminous and anthracite coals, the percentage of float (or sink) on a selected specific-gravity bath is used to control the ash content of cleaned coal shipments. In order to upgrade a coal in the most profitable way, a careful study of the The Coal Blending Model Pg 11
i i i i i II i i i 2.2 2.1 2.0 1.9 l.B 1.7 1.6 l.S 1.4 1.3 < RELRT3VE DENSITY
Legend: 1. ) Cumulative floats 2. ) Elementary ash curve 3. ) Cumulative sinks 4. ) Relative density distribution curve 5. ) +/- 0.1 Relative density curve
Figure 1. Sample Washability Graph*
•(Produced using the CANMET Coal Data Manipulation Program) The Coal Blending Model Pg 12
washability characteristics is required. Float-and-sink analysis provides the necessary indications of both the degree of difficulty in washing the coal, and the effectiveness of the washer itself. For day-to-day plant control, float-and-sink
separations are needed on the washing products at the
separation density in effect at those times.
Once the float-and-sink determination is completed, the process engineer can develop a washability curve like the one produced using CANMET's Coal Data Manipulation program (4),
shown in Figure 1. The five curves represented on this Sample
Washability graph (Leonard and Mitchell) (6) are as follows:
i) The cumulative floats curve (No. 1 on Legend of Figure 1)
is the curve obtained by plotting the cumulative yield of the floats at each relative density against the mean ash content of the total floats at that density. This curve shows the relationship between cumulative yield of the floats and ash content.
ii) The elementary ash curve (No. 2 on Legend of Figure 1) indicates the highest ash content of a particle likely to be found in any particular yield of floats. The shape of the curve is an indication of the ease or difficulty of cleaning a particular coal. The closer the curve approximates the shape of The Coal Blending Model Pg 13
the letter ' L', the easier the coal is to clean.
iii) The cumulative sink curve (No. 3 on Legend of Figure 1) is
a plot of the cumulative yield of sinks at each relative
density against the mean ash of the total sinks at that
density.
iv) The relative density distribution curve (No. 4 on Legend
of Figure 1), sometimes called the "densimetric or specific
gravity curve", shows the relationship between the relative
density and the theoretical yield for the given size fraction
and coal seam.
v) The +/- Q.l relative density curve (No.5 on Legend of
Figure 1), or "difficulty curve", provides an indication of the
difficulty of separation by giving a direct relationship
between near-density material and the ash content.
METHOD OF ANALYSIS
Run of Mine (ROM) coal does not contain a mixture of pure
constituents. The shales, sandstones, and clays are intermixed with low grade coal and the carbonaceous material is laced with
mineral impurities. Therefore, coal will contain material at The Coal Blending Model Pg 14
all specific gravities between the lightest and heaviest pieces. Even so, the shale and pyrite will fall to the bottom of a container filled with water more rapidly than coal. For example, if the water is given a pulsating motion by compressed air, causing the water to move up and down, the heavy impurities will be kept at the bottom and the coal at the top where it can be recovered. In addition, the specific gravity of the water is sometimes adjusted to the specific gravity of the coal by the use of heavy media to effect a separation of the coal and its impurities.
The weight and specific gravity of coal depends upon the amount and kind of mineral matter or ash that it contains. It also depends on the coal's compactness or porosity and its carbon content. A higher ash content gives higher specific gravity. Similarly, a change in specific gravity is exhibited with air-dried coal in comparison to "fresh" or moisture- saturated coal. The specific gravity of a coal affects its burning quality; the lower the specific gravity, the better the ignition properties in each individual coal. In addition, coal of a given rank has a higher apparent specific gravity when wet than when dry.
Commercially pure coal, that is coal containing only intrinsic impurities, has a specific gravity ranging generally The Coal Blending Model Pg 15
from 1.2 to 1.7, though mostly below 1.4 in ordinary practice for bituminous coal. Anthracite coal of the same purity may be up to 1.7. Shale, sandstone and calcspar have specific gravities ranging from 2.3 to 2.7, while pyrite has a specific gravity of about 5. The difference in specific gravity between pure coal and these impurities, in a free state, is sufficient to enable an almost complete separation to be achieved fairly easily.
The characteristics of the extraneous impurities are of great importance, especially with regard to whether they are free, interwoven or closely interstratified with the coal substance in extremely thin layers, i.e. bone coal. Such finely stratified extraneous impurities may approximate to intrinsic impurities for, although they are capable of being separated from the coal substance, such separation would require the reduction of the whole mass of coal to a very fine state. Such fine particles would not be amenable to economic methods of treatment. Therefore, as these finely divided impurities are intimately intermixed with the coal substance and cannot be separated from it by physical means, there is an economic minimum ash content to which coal can be cleaned, depending upon the intrinsic ash content (which for any coal is seldom less than 1%). The usual average of the purest coal is between 2 and 3% ash content. Generally speaking, the specific The Coal Blending Model Pg 16
gravity increases in proportion to the impurity content, and in the same way forms a continuous range between the two extremes.
The specific gravity analysis must be preceded by a size
analysis of the raw coal. As the impurities of a coal vary
both in different seams and in different size ranges of the
same seam, each size range must be examined separately. It is
also more convenient and more accurate to conduct the specific
gravity analysis on closely sized material-- a maximum size
ratio of 2:1 for each fraction is advisable. In most cases, it
is unnecessary to extend the upper size limit above 6 inches.
For coal samples, the test is usually commenced using a
liquid of S.G. 1.3, and repeated with liquids of progressively
increasing specific gravities, the sinks in each case passing
on to the next liquid of higher specific gravity. The floating material which intermediated in S.G. between the liquid in
which it floated and the previous liquid, is kept separate.
The various specific gravity fractions are weighed and then
successively crushed and reduced to give a representative
sample for analysis. Usually, the specific gravity increments
should be taken as 0.05 between 1.3 and 1.5 S.G., and then 0.1
up to 2.0 S.G. in the initial analysis. The Coal Blending Model Pg 17
The float-and-sink test is commenced at either the highest or lowest density of coal coarser than 0.5 mm (28 mesh) and as a general principle, the density chosen should allow as much of the sample as possible to be removed in the first stages, for example, discard should be initially floated at the highest density used, with clean and raw coal at the lowest densities.
PLANT AND/OR EQUIPMENT EFFICIENCY
The overall performance of a coal preparation operation is influenced by three factors: the raw coal characteristics, the inherent characteristics of the cleaning unit, and the market considerations. Yancey and Geer (7), and Walters, Ramani and
Stefanko (8) feel that an efficiency coefficient which relates these three factors would directly measure the loss of saleable coal and, therefore, would be of greatest practical value. At the present time, however, no commonly accepted efficiency coefficient linking all three factors exists. There are some accepted efficiency criteria relating the effect of the coal on the cleaning unit. The following discussion will be limited to the efficiency of a specific gravity separation. The Coal Blending Model Pg 18
EFFECT OF THE RAW COAL
Organic efficiency is the criterion most commonly used to describe the plant performance. To some extent, this
efficiency is dependent on the coal type being processed. The
organic efficiency formula expresses the yield of washed coal
as a percentage of the yield of float coal (determined by the washing analysis of the feed). For example:
Organic Efficiency = Actual Yield of Washed Coal X 100
Theoretical Yield at the Same Ash
As noted by A.D. Walters, et al (8), there are some
problems with this formula:
1. Friable coal will degrade during the cleaning process.
Therefore, the theoretical yield determined by an analysis
of the feed cannot always be used in this formula. One
would have to reconstitute the mill feed from the
float-and-sink analysis of the washed coal and discard
material.
2. Along with efficiency, ash reduction must also be
considered. If an ash content of 10% were desired, and
the resultant product was 11%, with an organic efficiency The Coal Blending Model Pg 19
of 95%, then the process has not proven to be efficient,
despite the reports of high efficiency.
3. Organic efficiency is also influenced by the specific
gravity of separation and the inherent characteristics of
the cleaning unit. Therefore, caution should be exercised
when attempting to use organic efficiency to compare
cleaning units treating coals of different density
compositions or operating at different specific gravities
of separation.
EFFECT OF THE CLEANING UNIT
The most widely accepted criterion for measuring the efficiency of coal preparation gravity separation cleaning units is the partition curve, also known as the "Tromp curve",
"error curve", "distribution curve", or "recovery curve". Most computer models use the partition curve to simulate the operation of a gravity separation cleaning unit. Tromp defined the partition (distribution) curve as: 'the continuous function that results when the ratio of washed coal or rejects to raw coal in an infinitesimal increment of gravity is entered as the ordinate against that same gravity as abscissa' (Kindig et al)
(9) . The Coal Blending Model Pg 20
ui UJ a.' ox
T 1.2 1.4 A. 1.6 1.8 2.0 SPECIFIC ! GRAVITY i SEPARATING GRAVITY
Figure 2. Distribution Curve of a Perfect Separation at 1.50 Specific Gravity The Coal Blending Model Pg 21
SEPARATING GRAVITY
Figure 3. Illustration of Probable Error (EPM) of a Separation at 1.50 Specific Gravity The Coal Blending Model Pg 22
The perfect separation would occur when all particles of pure,
100% coal would report to the clean coal, and the rejects would contain no trace of hydrocarbons. The partition curve for this would look like Figure 2. In reality, this is never the
case, thus a typical partition curve always shows some misplaced material, as shown in Figure 3. This divergence of
the curve from the perfect separation curve gives a measure of
the efficiency of the cleaning unit. Three criteria have been
developed for measuring the degree of misplacement: Error Area,
Probable Error, and Imperfection.
1) Error Area: The error area is the area between the curve and a vertical line drawn through the separating specific gravity.
This integrated area under the effected section of the curve can be measured and then compared with a standard to provide a degree of the efficiency of the process. The following is the convention for determining efficiency using this method:
AREA DEGREE OF EFFICIENCY
A = 0 Perfect 0 < A < 30 Excellent 30 < A < 50 Good 50 < A < 100 Fair A > 0 Poor The Coal Blending Model Pg 23
2) Probable Error (Ecart Probable Moyen): This efficiency rating is defined as one half the difference between the relative densities corresponding to the 75 % and 25 % ordinates, as shown in the partition curve (Figure 3). For example:
d25 - d75
2
The steeper the partition curve, the lower the probable error.
A low probable error designates a sharp separation, while a
large probable error denotes a poorer separation.
Probable error as a measure of performance of a cleaning unit has two major drawbacks. First, the "tails" of the curve are not adequately described and second, the calculation is not independent of the specific gravity of the separation.
3) Imperfection: To develop a criterion of efficiency which would be independent of the specific gravity of the separation, the French research organization, Cherchar (Cheradame et al)
(10), developed the concept of "imperfection". The Coal Blending Model Pg 24
1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0
SPECIFIC GRAVITY OF SEPARATION
( THE POINTS PLOTTED ARE FROM TESTS CARRIED OUT
ON FOUR BITUMINOUS WASHERS)
Figure 4. Imperfection as a Function of Probable Error and Specific Gravity of Separation: United States Bureau of Mines The Coal Blending Model Pg 25
Imperfection, for which the symbol I is used, is defined as:
I = Probable Error/specific gravity of separation
(for dense medium)
I = Probable Error/specific gravity of separation - 1
(for jigs)
Cherchar claimed that imperfection was a constant for a particular cleaning unit, but practical experience has shown that there is a slight change in imperfection with changes in the specific gravity of separation. This is illustrated in
Figure 4, which shows the relationship between probable error, imperfection and specific gravity of separation. These results were obtained from tests performed by the U.S. Bureau of Mines on four bituminous washers (Hudy, Jr. J.) (11).
METHODS OF RAW COAL BLENDING
Blending or homogenization systems are commonly employed
in order to compensate for variations in size distribution, moisture content, coal washability and quality parameters such as ash, heat and sulfur contents. The Europeans developed much The Coal Blending Model Pg 26
of the technology through necessity, since the raw coal feed to most of their large coal washeries can vary widely in characteristics from hour to hour. Today, managers of coal mines can choose not to blend, to batch particular coals, or to select one of several available blending options. The major blending options are:
a) Homogenization
b) Blending prior to treatment in the plant
c) In-pit blending
d) Any combination of the above
No Blending:
A mine that chooses not to blend coal simplifies the mine planning process, while minimizing its required ROM coal stockpiles. This option is least expensive, and is best suited to mines mining only one homogeneous seam or mines with coal seams having similar washability curves or physical properties. Coal mines fitting into this category will derive no benefit from determining the Coal Blending Coefficient or from any other blending models. All blending theories exploit differences in the washability data or physical properties, so when there are no differences in the ROM coal, the ideal mill feed is obtained. The best blending or homogenization plans always strive toward, but never achieve this goal. The Coal Blending Model Pg 27
Batching:
The term 'batching' is normally used to describe a unit operation which is not continuous. In coal preparation terminology, batching often refers to the processes of purposefully cleaning only one quality or type of coal at a time. Some Western Canadian coal plants have practiced this form of operation for years. At first glance, this would seem to be an ideal way of operating. The feed for each run would be similar in quality, which should allow for fine-tuning of process equipment. However, batching does have its complications. Firstly, pre-plant stockpiles are required for each quality of coal being mined. Secondly, if all the products are not cleaned to the same quality (i.e. similar ash, sulfur, F.S.I., etc. contents), then either the different coals must each be sold separately, or a post-plant blending facility as well as more coal storage/stock piling would be required.
When batching is referred to in this paper, the term will specifically refer to the operation of cleaning each coal to the same ash content. Some post-blending would be necessary if the other coal properties varied greatly. Figure. 5 Benefits of Raw Coal Homogenization* *(Ruhrkohl A.G.) The Coal Blending Model Pg 29
Homogenization:
Homogenization, or mixing, is effective when a large
number of seams or mining locations are worked. The raw coal
from a variety of previously selected work faces are stockpiled
on an "as come" basis, usually by means of spreaders, or
stackers. Once the pad is full, the ROM coal is reclaimed
using a bucket wheel or draw points, in such a manner as to
give the best possible mix of the deposited coal. Successful
applications are in use in European multiple seam coal
operations, but these require expensive stockpiles and blending
pads [Bethe & Koch (12), Kubitza (13), Osborne & Walters
(14)1. Figure 5 illustrates the before and after
homogenization effects on the ash content of mill feed
samples. Before homogenization, the mill feed ash content was
highly variable, ranging from a low of 26%, to a high of 42%.
A varying ash content in mill feed will directly affect the quality of the final product. Fortunately for those mines with a varying feed quality, the coal cleaning process does perform considerable homogenization (Lazorin, Soloshenko, Slesarev,
Litmanovich, Milyutin, and Chernova) (15), thus producing a
final product with much less fluctuation than the original
feed. After homogenization, the mill feed and final products both reveal smaller amounts of variation. The Coal Blending Model Pg 30
According to Salama (16), Lazorin et al (15), and Abbott
(17), as well as the majority of other authors of coal blending
papers, the benefits of a consistent feed are that
homogenization of ROM coals decreases the losses of coal to
tailings, thus improving the washery recovery and yield.
Homogenization is an excellent tool for pre-averaging
coals from many faces, though the quality of the final product
is still dependent upon the qualities and quantities of each
component in the blend.
Blending Prior to Treatment:
Blending prior to treatment or pre-plant blending involves
the combining of coals at known or assumed qualities in
predetermined quantities. All blending models require that the
quality of coal seams is known, as well as having some form of
control over the quantities received from each seam.
Therefore, mines which blend prior to the plant site are
ideally suited to take advantage of blending strategies,
including the results from the Coal Blending Coefficient model. A particular problem with blending is that either a
large capital expenditure is required for silos or blending
pads, or the coal must be rehandled, thereby increasing the The Coal Blending Model Pg 31
operating costs and producing more fines. In either case, the
necessary large stockpiles delay coal sales and take up valuable space. Blending prior to treatment would be the
blending method preferred by most preparation plant managers,
but the increased space and capital requirements of the system
often work against the acceptance of this method.
In-Pit Blending:
As the name implies, in-pit blending is performed at the
mining stage. The objective of this blending is to achieve a
very rough mixture of seams. Typically, this method involves
blending by truck load: 3 truck loads of seam A to 1 truck load
of seam D, for example. Even in the best situations, control
is usually very poor, and is subject to mining schedules, the weather, and mechanical breakdowns. The truck sizes are
commonly 100 metric tonnes or larger. Although mixing in the
crusher or rotary breaker does occur, as well as in the
stockpiles or silos, the feed quality fluctuates according to
the individual seam qualities. A second problem with the
"blending by truck load" method is that the trucks rarely
arrive at an even distribution. A 3 and 1 ratio too often
becomes a 9 and 3 ratio. A computer dispatch system, as well
as the use of small stockpiles, has improved the feed The Coal Blending Model Pg 32
distribution but has not overcome the typical mining problems of equipment breakdown or shortages of exposed coal. When these conditions occur, in-pit blending is readily disregarded
for the sake of output, and the ROM coal becomes whatever type
is available. On its own, in-pit blending is normally not
effective enough to produce a consistent mill feed, yet is
still a much better process than no blending. When combined with a homogenization program, in-pit blending can be a very
effective method.
SUMMARY
In today's age of multiple seam mining, most mines have
been forced to either blend, homogenize or batch their plant
feed. For Western Canadian open pit coal mines, the
traditional choice has been between batching and blending.
Homogenization is traditionally used in underground operations where 10 or more faces are mined at once, making scheduling almost impossible.
The Coal Blending Coefficient, described later in this
thesis, can be used to compare the efficiencies of blending versus batching, where all the batched coal is cleaned to the
same ash content level. In fact, the coefficient is defined as The Coal Blending Model Pg 33
the difference in yield between blending and batching the same
coals, cleaned to the same ash level, processed by the same plant using the same process strategy.
PREPARATION PLANT COMPUTER SIMULATION MODELING
Early computer applications in coal preparation were basic
data handling routines. However, in the late fifties and early
sixties, the use of operations research techniques and computer
simulation models started to become very popular. Charmbury and
Lovell (18); Kindig, Luckie, and Lovell (9); Brookes and
Whitmore (19); Humphreys, Leonard and Butterworth (20); and
Absil, Keuing, and Meerman (21) were among the early pioneers
in coal process computer modeling. They helped develop the
computer model from a simple data base manipulation program to
a plant simulation model capable of estimating the plant yield
and ash content of the clean coal.
Since the early seventies, much time has been spent perfecting the early computer model concepts. CANMET developed a suite of programs called the "Coal Data Manipulation
Programs" (4) as well as their "Spock Programs", and the U.S.
Department of Energy (22) recently released a new preparation plant simulator. These programs, which are the accumulation of
tens of thousands of hours of programming and research, are The Coal Blending Model Pg 34
capable of predicting the performance of a plant, and of optimizing the yield at a specified ash content of clean coal for a given coal type.
The traditional uses of computer simulation programs as outlined by Rong and Lyman (23) are as follows:
(1) In the design stage: -to determine the optimal technological scheme by comparing several alternative flowsheets; -to optimize the feed size range for each separator in the flowsheet; -to produce detailed estimates of operation conditions for the plant.
(2) For a new plant at startup: -to estimate the performance of separators and entire plants at any operating cut point, in considerable detail; -to predict the optimal ash content of clean coal in each separator (or each coal feed group) when the mass fraction of coal washed in each (separator or each coal feed group) and the ash content of final clean coal are specified.
< 3) For an operating plant: -to determine the optimal operating cut points of all separators so as to maximize yield at a specified ash content of final clean coal; -to investigate sensitivity to operating parameters or to locate bottlenecks in the plant.
Modern simulation and optimization programs are all capable of performing the above functions, and with some modifications and imagination, these programs can be genuinely useful tools for solving many other coal preparation problems.
For example, to calculate the coal blending coefficient and develop the model, a modern coal plant simulation model is The Coal Blending Model Pg 35
required to determine the quality of clean coal given the quality of the ROM coal and operating constraints.
Modern washery computer simulators allow everyone, from researchers to plant managers, an opportunity to simulate the hypotheses without incurring the high expenses and the time required to test out their theories using operating or pilot plants. Once the ideas have been proven in the simulation, then they can be examined under actual operating conditions.
III. DEVELOPMENT OF THE COAL BLENDING MODEL
INTRODUCTION
The initial objective of this study was to develop a method of evaluating the effects of controlled blending on preparation plant efficiency. The lack of such a method has been of major concern to process engineers. Many agreed with
Salama's (16) thoughts: "...it is natural to expect that wide feed variation can cause a diverse effect on the operation of different units in any coal cleaning facility and will result in decreased overall yield ". While some mining engineers still feel that a controlled plant feed is not necessary, others would like to find a way to quantify the effects of The Coal Blending Model Pg 36
controlled blending. This coal blending model is a first attempt at developing such a method.
DEVELOPMENT OF THE COAL BLENDING COEFFICIENT
Coal preparation engineers are interested in determining how effectively a plant can process a given coal type. This project was concerned with how effectively the actual coal blends from a given coal deposit and operation can be processed by a plant configuration. Because a company is financially committed to its existing plant and may not have finances to remodel nor may the production requirements permit remodelling, processing effectiveness is a major consideration for existing plants. Therefore this model fits the coal to the plant, not the plant to the coal.
The objective of the coal blending model is to optimize the clean coal yield without sacrificing clean coal quality or imposing tight production constraints on the mine or plant.
A mathematical formula, the Coal Blending Coefficient, was developed with its objective function to optimize the clean coal yield. The Coal Blending Coefficient is a yield-based ratio because yield maximization, defined as the actual output divided by the optimum or ideal output, without sacrifice of The Coal Blending Model Pg 37
final product quality, produces increased profits, thus is the major objective of all coal mines. The Coal Blending
Coefficient compares batching to blending of the same coals.
Mathematically, the Coal Blending Coefficient is the difference between the plant yield at a set clean coal ash for a particular blend and the yield which would be obtained were
each seam washed separately to the same ash and in the same proportions as for the blend. The mathematical representation
is as follows:
Z = BY-) [~~! (Ai*Wii*Yii) L--1 j=l where: Z = coal blending coefficient BY = the blend yield (%) n = number of seams treated m = number of size fractions treated Ai = The percentage mass of the seam in the blend Wij = Proportion of the size fraction(j) in the seam(i) Yij = Mass yield proportion of size fraction(j) in seam(i)
Page 89 of Appendix A lists the actual Coal Blending
Coefficient program. Line 3800 is the objective function for the Coal Blending Model. The value of the Coal Blending
Coefficient indicates the effectiveness of blending. A high value suggests that a controlled blending program could improve overall plant yield, while a low or negative value suggests that batching would be as good as or more effective than blending. The magnitude of the Coal Blending Coefficient is a direct indication of the expected increase in yield due to
blending versus batching. The Coal Blending Model Pg 38
In an operating washery, the magnitude of the Coal
Blending Coefficient realized from any batching versus blending tests performed would be dependent on a complex function of the washability characteristics of each seam, the mining technique used, the efficiency of the cleaning units, and the final quality specifications. Most coal preparation plant simulation models only take into account the coal seam characteristics, theoretical equipment yields based on their typical distribution curves for standard size distributions, and final quality specifications. Equipment operation problems that could affect the shape of the distribution curves, such as operation over the capacity of equipment, flow surges, or exceptionally clean coal, are not normally built into coal plant simulation models (Leonard & Leonard) (24). These operating problems can often be the difference between the results obtained by a preparation plant model and actual plant results.
The true theoretical yield for a given plant feed can be determined from the coal's washability curve. A positive value for the Coal Blending Coefficient can be obtained from the washability data of blended seams. The following example problem was chosen to demonstrate the possibility of an increase in the Coal Blending Coefficient due strictly to the washability effect. Consider two seams with washability The Coal Blending Model Pg 39
characteristics as in Appendix B, pages 95 (Seam 2) and 96
(Seam 1). The cumulative float data for these seams and a
60:40 blend are shown in Table II.
TABLE II. CUMULATIVE FLOAT DATA
RELATIVE SEAM 1 SEAM 2 BLEND 60:40 DENSITY MASS ASH MASS ASH MASS ASH FRACTIONS % % % % % %
FLOAT 1.30 31.98 3.54 5.95 3.93 21.57 3.59 1.30 1.40 69.95 5.69 46.18 8.16 60.44 6.44 1.40 1.50 77.39 6.86 61.13 10.77 70.89 8.21 1.50 1.60 80.07 7.54 66.38 12.48 74.59 9.30 1.60 1.70 82.00 8.21 69.50 13.85 77.00 10.25 1.70 1.80 83.38 8.78 72.53 15.48 79.04 11.24 1.80 SINK 100.00 20.16 100.00 33.54 100.00 25.51
The seams, blend ratio, and final product ash content were chosen to simplify the mathematics and minimize the amount of error introduced into the problem by trying to interpret values between data points. From Table II, the mass percent of seam 1 obtainable at the desired ash of 8.21 would be 82.00 percent.
The mass percent of seam 2 would be slightly greater than 46.18 percent. Taking the worst scenario, the maximum expected yield at 8.21 percent ash would be 46.65 percent. The blend yield according to the washability data is 70.89 percent. The Coal
Blending Coefficient for this example would be as follows:
C.B.C.= 70.89 - (0.6 * 82.00 + 0.4 * 46.65)
= 70.89 - 67.86 = 3.03 The Coal Blending Model Pg 40
The other important effect on the value of the Coal
Blending Model is the theoretical performance of the cleaning equipment. At any separating gravity, the theoretical yield and quality must be converted to a practical value by means of a distribution curve. Most models base performance on standard or average distribution curves for each cleaning unit, but even these standard curves are not of a fixed form but vary for different separating gravities and particle sizes. Depending on required separation gravities of the batched seams and the blended seam, an increase or decrease in the Coal Blending
Coefficient can be realized after the theoretical yields are converted into practical yields by using cleaning equipment distribution curves. The Coal Blending Model Pg 41
COAL BLENDING MODEL DESCRIPTION
The Coal Blending Model is a collection of computer programs-- some are developed especially for this project, and others are available commercially. A simplified flowsheet for the Coal Blending Coefficient Model is shown in Figure 6.
The Coal Plant Simulation program is the largest and most complicated part of the entire model. Most modern Coal Plant
Simulation Model programs, as previously discussed on pages 33 to 35, are suitable for incorporation into this model and are commercially available. The simulation model that is best able to model the existing plant and produce final results closest to actual results should be chosen. This is a matter of comparing model results with actual field results for different types of coal. The chosen simulation model will then determine the format of data input/output.
The Washability Data Input and Storage routine is normally available as part of the Coal Plant Simulator package. This program takes the washability data for each seam and stores the data in a format that can be read by the blending and plant simulation routines. The data for each size fraction and float-sink density of each seam is entered at this point. The Coal Blending Model Pg 42
CANMET INPUT MODEL AND WASHABILITY DATA BLENDING CONSTRAINTS INPUT PROGRAM (Appendix A, Pg ?1)
> f STORE WASHABILITY RETRIEVE PRINT RESULTS DATA FILES TO DISK] WASHABILITY DATA FILES V
f BLEND GENERATOR Next PROGRAM Blend (Appendix A, Pg 90)
> CANMET WASHABILITY DATA COMBINE PROGRAM
CANMET PLANT SIMULATION PROGRAM
Constirain t Chiec k
N COAL BLENDING COEFICIENT SORT AND STORE GENERATING PROGRAM MODEL RESULTS (Appendix A, Pg 89) (Appendix A, Pg 8?)
Figure 6. Simplified Flowsheet For The Coal Blending Model The Coal Blending Model Pg 43
The Blend Generator Program, as the name implies, generates blending ratios for the coal seam quality blending routine. This program was designed to produce all possible ratios within the given constraints, at the given step size.
If two seams were to be run through the model with all possibl combinations tried at a step size of 10, eleven combinations would be generated:
COMB. 1 2 3 4 5 6 7 8 9 10 11
SEAM A 0 10 20 30 40 50 60 70 80 90 100
SEAM B 100 90 80 70 60 50 40 30 20 10 0
As the step size is decreased and the number of seams are increased, the required number of runs is dramatically increased. For all possible combinations using three seams an a step size of five, twenty-one factorial runs, or 231 runs would be required. The Blend Generator is not a standard feature of most simulation packages, and therefore must be written on site. The listing for the Blend Generator Program, written in Hewlett Packard Basic for the CANMET Data
Manipulation Package, is given in Appendix A, page 90. The Coal Blending Model Pg 44
The Coal Seam Quality Blending routine is designed to combine washability data from files, then store these results on a disk for future use. This routine creates a new washability curve by combining washability data from the seams being combined. The program then combines the data by using the ratios of each seam in the desired blend. The way in which this process works is demonstrated in the following example, in which the desired blend being sought is 40% seam A, 60% seam B:
% of seam A in the first washability range is 5 %
% of seam B in the first washability range is 10%
% of Blend in the first washability range is
(.4*5)+(.6*10)=8%
The process is repeated for all washability ranges, thus creating a new set of washability data.
The next routine in the model is the Constraint Checking program. This routine simply compares the final coal quality with the initial quality constraints. If the final product fails to meet the input quality constraints, then the next blend in the sequence is tried. If the final product falls within the specified constraints, the Coal Blending Coefficient is then calculated for the blend in question. All the desired information is stored for future printing. The next run is The Coal Blending Model Pg 45
then generated. Once all the possible blends have been attempted, the stored results are then ranked by their coal blending coefficient values, and printed in descending order.
The sorting program is listed in Appendix A, page 89.
MODEL INPUT
The interactive input routine for the CANMET Coal Data
Manipulation program prompts the user when input is required.
This feature is slower than a program using a data file, but
improves the ease of use. The Hewlett Packard programming
requires conversion into machine code for each run, and this
increases the time required to run the program. The listing for the Model Input and Washability Data loading program is given in Appendix A, page 91.
Three types of input information are required to run the model. The first is the washability data of each seam
involved in the blending process, while the second is the model constraints, and the third is the blend generating constraints. A summary of the input requirements is shown in
Table III.
The accuracy and the detail of the washability data is critical to the accuracy of the model results. At least seven The Coal Blending Model Pg 46
float-sink density data points are required for the various size fractions in order to ensure results of reasonable accuracy. The CANMET Data Manipulation program will accept up to twenty float-sink relative density data points. The accuracy of the Plant Simulation Model can be directly affected by the quantity of data points, therefore the more data points, especially at the tail ends of the distribution curve, the greater the accuracy of the final results. If these data points are unavailable, the model must interpolate between the available data points and estimate the actual shape of the distribution curve [A.D. Walters, et al (8); R.X. Rong and G.J.
Lyman (23); A. Jowett (25)]. The Coal Blending Model Pg 47
TABLE III. LIST OF REQUIRED INPUT INFORMATION
1. WASHABILITY DATA INPUT
-Float-sink results for each size fraction of each seam.
-Weight percentage of each size fraction.
-Sulfur, calorific values and/or moisture contents for each float-sink fraction.
2. MODEL CONSTRAINTS
-Number of seams
-Number of size fractions
-Washability data file names
-Required clean coal ash
-Clean coal sulfur range
-Option ranges
-Minimum acceptable yield
-Cleaning equipment's relative density operating range
-Plant simulation program set-up
3. BLEND SELECTION INPUT
-Percentile ranges of each seam allowed in the blend
-Step size for the run The Coal Blending Model Pg 48
The CANMET Coal Data Manipulation blending program requires all washability data subfiles to contain the same number of float-sink cuts with mass %, ash %, and the same sulphur, B.T.U., and/or moisture options. When files containing unequal data points must be used, they must be modified to contain identical numbers of data points and option values.
The second set of input, as outlined in Table III, is the
Model Constraints. This input sets up the amount of data file
space required, controls counters in the different programs, and sets quality specifications for the final product. Input of the number of seams, number of washability size fractions, and the name of washability data files are essential for setting up memory space, locating proper data files, and
setting up counters throughout the Coal Blending Model.
The required clean coal ash is the most important constraint affecting the results of the simulation model. This variable is the target value for the simulation program. The
CANMET Coal Data Manipulation model was set up such that each cleaning unit is cleaned to the same clean coal ash level.
Some experts feel that for optimal cleaning performance each cleaning unit should clean to the same elementary ash level
(R.X. Rong and G.J. Lyman) (23). This theory was not tested as The Coal Blending Model Pg 49
part of this thesis, as the modification would have to be made
to the coal plant simulation program.
The Sulfur, B.T.U, Calorific Value, and Yield Constraints
do not affect the operation of the plant simulation model, but
are used as a selection process. Blends which fail to meet the
required constraints are not saved, thus are not used in
determining the best coal blending coefficient values.
The Cleaning Equipment Relative Density Constraint limits
the operating ranges for the different cleaning equipment. If
the required relative density to achieve the desired clean coal
ash were too high or low, the run would be discontinued and a
new blend tried.
The Plant Simulation Program must be set up to attempt to match the operation of the existing plant to be modeled. Some modern simulation programs are very detailed. They not only have models for all the process equipment, but also take into account water additions. A good model is set up to match the
existing process and consistently produces results that match the existing plant. The Coal Blending Model Pg 50
The third type of input controls the operation of the
Blend Generating Routine (or Blend Generation Program). The first set of data in this routine is the Percentile Blending
Range for each seam in the blend. The default for this input is "0,100", or all percentile ratios between 0 % and 100 %.
This input allows the programmer to limit the blending range.
Limiting the range of blending minimizes the number of runs required for each trial and saves computer time. The mine plan may limit the possible blending ratios, or a more detailed study may be required using a tighter limit on blending ratios.
A second set of data in the Blend Generating Routine is the Percentile Step Size Increment, which also controls the number of blends to be run in one trial. For example, if four seams with three size fractions were to be blended, with no constraints on the Percentile Blending Ratios and using a unit step size, then 4,598,126 different blends would require evaluation to complete the trial. If the constraints are such that each blend qualifies to be run through the model, then the program could take up to 12 days to complete using the Hewlett
Packard microcomputer. A normal program run of four seams with three size fractions, using a step size of 10, requires about
30 minutes from blend selection inputs until the printing of results. The Coal Blending Model Pg 51
The Blend Generation Program is deliberately designed to determine coal blending coefficient values for different blending ratios within a fixed grid pattern. The grid is controlled by the blend selection input, therefore the programmer can adjust the grid to suit immediate requirements.
This method was chosen over a single point search routine, as an improved understanding of the effects of varying blends on plant yield is thus obtained. This information shows feasible blending regions, rather than a single point which may be impractical.
MODEL OUTPUT
The Coal Blending Model requires a routine to store the results that meets the previously discussed model constraints as each blend is run through the plant simulation program.
Once all the required blends have been run, a sorting routine ranks the results in descending order, with the blend having the highest Coal Blending Coefficient listed first. Tables IV,
V, and VI, when combined, are a typical coal blending model printout. In the first section of Table IV, each seam is assigned a Type Number, which is used for blend identification later in the printout. Each size fraction, its respective cleaning unit type, and the weight percentage of the total sample contained in the size fraction are also listed. TABLE IV. SAMPLE MODEL INPUTS
Type # Seam Name Size Fraction C UNIT '/. Weight y. Minimum X Maximum
1 Coal fl +12.7 mm HMB 35.00 10 90 12.7.X 0.6 mm HMC 48.25 - 0.6 mm 16.75
2 CoalB +12.7 mm HMB 59.58 20 80 12.7 X 0.6 mm HMC 32.98 — 0.6 mm 7.68
3 CoalC +12.7 mm HMB 42.28 30 70 12.7 X 0.6 mm HMC 47.68 - 0.6 mm 10.20
4 Coal D +12.7 mm HMB 45.58 10 40 12.7 X 0.6 mm HMC 43.50 - 0.6 mm 11.88
Clean Coal fish • 8.00 Sulfur minimum a -1.00 Maximum * 2.40 Specific Gravity min. 1.28 Maximum • 1.90 The Step Size • 10.86 The Coal Blending Model Pg 53
The final two columns in the first section give the minimum and maximum percentile values that each seam can contribute to the blend.
The second section of Table IV lists some of the important operating constraints, including the Target Clean Coal Ash, the
Sulfur Constraint Range, the Specific Gravity Range, and the
Blending Ratio Step-size.
The third section of the printout, Table V, lists the
Cleaning Unit Relative Density, Yield and Quality Results from the Plant Simulation Model for each size fraction of each individual seam in the blend after being cleaned to the target ash. The overall individual seam yield, ash, and sulfur content are also listed. The Coal Blending Coefficient is always zero for this section by its definition. For this section only, if a cleaning unit is unable to operate at the required relative density to achieve the target ash, the model accepts the product produced at maximum or minimum relative density.
Table VI, the fourth and final section of this printout, lists the results of each blend in the same format as for the individual seams. The blends are ranked in descending order by the value of their total Coal Blending Coefficients, starting The Coal Blending Model Pg 54
with the blend having the highest Coal Blending Coefficient.
Since the CANMET Coal Data Manipulation programs did not have a model for froth flotation, all -0.6 millimeter fractions were assumed to clean to the same clean coal ash, and produce the same yield. The amount to which this assumption will distort the final results is not known. TABLE V. SAMPLE BATCHIHG RESULTS
SIZE CLEANING MODEL MODEL MODEL MODEL MODEL tt T1:T2:T3:T4 FRACTION UNIT S.G. YIELD ASH SULFUR FACTOR
109:8:0:0 •12.7 mm HMB 1.546 72. 12 8.000 .613 ZERO 12.7 X 0.6 mm HMC 1.893 75.82 7.726 .624 ZERO - 0.6 mm 0.000 80.00 8.000 .608 ZERO TOTAL 0.000 75.23 7.867 .616 ZERO
0:100:0:0 •12.7 mm HMB 1.363 35.38 7.997 1.265 ZERO 12.7 X 0.6 mm HMC 1.671 81.30 8.000 1.384 ZERO - 0.6 mm 0.000 80.00 8.000 1.400 ZERO TOTAL 0.000 53.88 7.999 1.339 ZERO
0:0:100:0 + 12.'? mm HMB 1.451 69. 18 8.001 . 945 ZERO 12.7 X 0.6 mm HMC 1.556 85.21 8.000 . 986 ZERO 0 • S ffiin 0.000 80.00 8.000 .980 ZERO TOTAL 0.000 77.91 8.000 .920 ZERO
0:0:0:100 +12.7 mm HMB 1.428 84.54 7.999 1.976 ZERO 12.7 X 0.6 mm HMC 1.897 92.49 7.443 2.806 ZERO - 0.6 mm 0.000 80.00 8.000 1.200 ZERO TOTAL 0.000 87.50 7. 744 1.912 ZERO TABLE VI. SAMPLE COAL BLENDING MODEL RESULTS
SIZE CLEANING MODEL MODEL MODEL MODEL MODEL Ti:T2:T3:T4 FRACTION UNIT S.G. YIELD ASH SULFUR FACTOR, -i 1 IO: 50: 30: 10 +12.7 nm . HUB 1.425 56.66 8.000 1.285 5. 72 12.7 X 0.6 mm HMC 1.644 83.65 8.000 1. 179 .38 - 0.6 mm 0.000 80.00 8.000 1. 150 0. 00 TOTAL 0.000 69.68 8.000 1.-230 3.09
2 19: 40: 30: 28 +12.7 mm HMB 1.428 60.65 8.000 1. 372 4. 74 12.7 X 0.6 mm HMC 1.663 85.04 7.995 1.251 .64 ** Q • 6 flint 0.000 80.00 8.000 1. 130 0.00 TOTAL 0.000 72.57 7.998 1.298 2.63
3 10: 40: 40: 10 +12.7 mm HMB 1.430 59.20 7.997 1.25fc 4.79 12.7 X 0.6 mm HMC 1.628 84.01 8.000 i. 'yts . 36 -0.6 mm 0.000 80.00 8.000 1 . 100 0.00 TOTAL 0.000 71.52 7.998 1. 186 2.54
4 20: 40: 30: 10 +12.7 mm HMB 1.431 59. 10 7.998 1.242 4. 72 12.7 X 0.6 mm HMC 1.664 83. 10 7.996 1.113 .54 - 0.6 mm 0.000 80. 00 8.000 1.078 0. 00 TOTAL 0.000 71.25 7.997 1. 170 2.53
5 10: 30: 30: 30 +12.7 mm HMB 1.430 64.83 7.998 1. 451 3. 64 12.7 X 0.6 mm HMC 1.682 86.28 8.000 1. 321 . 79 - 0.6 mm 0.000 80.00 8.000 1. 110 0.00 TOTAL 0.000 75.41 7.999 1. 361 2. 10 The Coal Blending Model Pg 57
SUMMARY
The Coal Blending Model is a collection of programs which evaluate the effect of different coal blends on overall plant yield. The Coal Plant Simulation Program is the heart of the model, while the Coal Blending Coefficient allows the model to rank the results from the simulation program, thus forming a method for the evaluation of coal blending.
Since each run of the simulation program facilitates thousands of calculations, blend selection inputs, although not required, are useful for controlling the amount of data to be analyzed. This minimizes the required number of runs through the Coal Blending Model, thus saving computing time.
Currently, the model has only been tried using the CANMET
Coal Data Manipulation programs as the plant simulation program. This program is user-friendly, and only a limited understanding of computer operations is required to use it, but the version used lacks a model for flotation, and does not lend itself well to the complete modeling of a washery process.
Other current simulation models are perhaps better suited for actual field testing. Despite some of the shortfalls of the current model, the Coal Blending Model has shown that the effects of blending can be quantified using the Coal Blending The Coal Blending Model Pg 58
Coefficient, and that there is potential for an increase in overall plant yield when a controlled blending program is followed. The Coal Blending Model Pg 59
IV. COAL BLENDING MODEL APPLICATION
The Coal Blending Model is designed to assist in solving coal blending problems by providing the decision-maker with a
large information base on which to make decisions. The model
selects blend combinations which first meet the given sulfur, ash and size constraints and then prioritizes them from the magnitude of their Coal Blending Coefficients. This screening filtering, and ranking of pertinent blending data aids decision-makers in selecting the best blending strategy for their particular operation.
The model can be used effectively for both long- and
short-term planning.
Short-term uses could include:
a) Evaluating the effect of mining another
seam.
b) Investigating the consequences of
introducing a new mining method which alter
the plant feed size distribution (for
example, replacing shovels with ripper
tractor-crawlers in the pit, or changing th
blasting method). The Coal Blending Model Pg 60
c) Experimenting with equipment changes in the
mill.
Long-term uses could include:
a) Developing a mining schedule based
on optimizing the benefits of ROM coal
blending.
b) Developing optimum-sized preplant stockpiles
to minimize rehandling and optimize the
benefits of ROM coal blending.
To date, trials using the model have produced coal blending coefficients from slightly negative values up to a 5% indicated yield improvement. In tightly constrained models, moderate gains of 2% are common. For mines with an unlimited supply of coal and no quality control constraints, optimization of this coefficient would give the most economical blend for a given plant configuration, but actual operations with resource and quality restrictions must evaluate the model output to determine the best operating blend within these limits. Thus for most coal mines, the blend with the highest Coal Blending
Coefficient is not necessarily the best choice, but the information available from the Coal Blending Model allows a sound economical alternative to be selected. The Coal Blending Model Pg 61
The determination of a feasible blending range, with its optimum values, allows a mine to set a stable long-term mining schedule which accommodates the preparation plant needs while providing for a cost effective short-term mine plan.
EXAMPLE PROBLEMS AND DATA EVALUATION
To assist in describing and evaluating the results from the Coal Blending Model, three example problems will be discussed. All three examples were run using the the same cleaning equipment, the same seam size fractions, and actual washability data from a coal deposit in British Columbia. In order to get a complete picture of the variability of Coal
Blending Coefficient values, no constraints were put on the clean coal product, except for the required target ash. These examples are also typical of results obtained for other coal deposits in British Columbia.
The Coal Plant Simulation program set-up for all three example problems consisted of three stage cleaning:
a) a heavy medium bath (HMB) treating the plus 12.7 mm
material
b) a heavy medium cyclone (HMC) treating the minus 12.7 to
plus 0.6 mm fraction The Coal Blending Model Pg 62
c) flotation was assumed for the minus 0.6 mm fraction,
but since the CANMET Coal Data Manipulation Programs
used do not have the capability to simulate a flotation
cell, an arbitrary yield was assigned for each run.
(If the actual yield for these seams were known, then
correct values could have been used in the
calculations.)
The actual washability data for the seams used in the example problems is shown in Appendix B. The quality of the seams vary moderately, with seams A and D being very clean, while seams B and C are relatively dirty.
Example Problem One : Two Seam Blend
This example problem evaluates the blending potential for a preparation plant washing two seams with moderately varied washability properties. Seams A and B were chosen for this trial, because of their difference in washability analysis.
The assumed in pit reserve for this example is ten million tonnes for each seam. The target ash was set at seven percent for the gravity separation circuits, while the flotation circuit was assumed to produce a product containing eight percent ash with a yield of eighty percent for all seams and blends. All potential blends were run through the Coal Blending
Model, using a step-size of five.
The Coal Blending Model Pg 64
The Coal Blending Model printout for this example problem is listed in Appendix C. This includes the model input, batching results and all the potential twenty-one model results. A blend of 65 percent Seam A and 35 percent Seam B had the highest Coal Blending Coefficient of over four. Figure
7 compares the Coal Blending Coefficient values to the percentage of seam A in the blend. The inflection point at the maximum Coal Blending Coefficient is important for two reasons. This point is associated with the blend that gives the highest increase in yield over batching. Using the yield totals for the batching section of the model printout, the expected yield for seam A would be 72.1 %, while seam B would be considerably lower at 41.22 %. Based on these batching results the expected average yield of a blend containing 65% seam A and 35% seam B would be [.65*72.1 + .35*41.2 ], 61.3% compared with the actual Coal Plant Simulation Program result of 65.4%. The difference between the actual blending results and the expected results based on the batching values gives the value of the Coal Blending Coefficient for this blend. An increase in yield from 61.3 % to 65.4 %, for a plant currently producing one million tonnes per year would increase annual production by 66,880 tonnes. This extra production would come from coal that is currently being discarded to the tailings. The Coal Blending Model Pg 65
This gain can only be achieved if the plant in this example were batching previously and the coal reserves allowed for constant blending at 65 % seam A, and 35 % seam B.
For most cases, as is the case in this example, the actual in-pit reserves will not match the optimum blending ratio. For these cases, the inflection point associated with the maximum
Coal Blending Coefficient is still of importance. The inflection point divides Figure 7 into two distinct sections— zone A and zone B. In example 1, the in-pit reserve ratio falls into zone A.
To illustrate the potential benefits of blending, and demonstrate the importance of the inflection point, three following blending scenarios were investigated. The total coal production for each case is shown in Table VII.
1. Batching
2. Blending at the maximum Coal Blending Coefficient until
seam A is depleted, and then using up seam B
3. Always blending at the ratio of the in-pit reserves. The Coal Blending Model Pg 66
TABLE VII. COAL PRODUCTION FOR EXAMPLE ONE
Scenario Total Tonnes of
Coal Recovered
1 11330000 tonnes
2 11960900 tonnes
3 11576000 tonnes
By adopting blending Scenario Number Two, this mine would be maximizing their clean coal production for the given plant configuration and clean coal quality constraints. This scenario takes full advantage of the maximum benefits of blending that are associated with the washery configuration and the coal seam characteristics. Scenario One, batching, is the best example of feeding the preparation plant blends from the extreme ends of zones A and B, thus disregarding the importance of the inflection point. It is not coincidence that Scenario
One also produces the least amount of total production.
Although maximizing yield is always foremost in the mind of management, the Coal Blending Model can provide some guidelines for the in-pit blending program that will receive The Coal Blending Model Pg 67
some benefit from a blending program, yet still allow mine planners some flexibility in their plans. Scenario Four would produce blends from only one side or section of the inflection point or axes. Using Example One, the mine planner would have to work with blends in zone A, as the in-pit reserves fall on this side of the inflection point. Any blend would be acceptable as long as the blend contained 65% or less of seam A. The results of such a program will always be somewhere between those of Scenarios Two and Three. The strategy for
Scenario Four is very simple-- as long as the blending program is within the zone that contains the in-pit reserves, the major gains from blending will be realized, while still allowing the for some flexibility by mine planners to minimize mining costs. This strategy will likely produce the greatest profits overal1.
For two seam blends, a non-linear graph indicates that an optimum blending strategy exists. If the branch of the graph, containing the overall in-pit blending ratio is concave, as in zone A, then the optimum blending scenario is normally blending at maximum coal blending coefficient until Seam A is exhausted.
If the branch of the graph is convex as in zone B, then the optimum solution is usually blending at the in-pit reserve ratio. For graphs that have a near linear branch, through the zone containing the in pit blending ratio, the results will be The Coal Blending Model Pg 68
identical for cases two and three. In fact, so long as the blending ratio falls within the proper zone, the final tonnes of clean coal produced would be identical.
Example Problem Two: Three Seam Blend "1"
This example problem evaluates the blending potential for a preparation plant washing three seams with moderately varied washability properties. Seams A, C,and D were chosen for this trial, with assumed proven in pit reserves of twelve million tonnes for seam A, twelve million tonnes for seam C and sixteen million tonnes for seam D. The target ash was set at seven and one half percent for the gravity separation circuits, while the flotation circuit was assumed to produce a product containing eight percent ash with a yield of eighty percent for all seams and blends. All potential blends were run through the Coal
Blending Model, using a step-size of ten. A restricted second run was performed at a step size of five to develop better contour lines around the blend with the maximum Coal Blending
Coefficient.
The Coal Blending Model printout for the first run of this example problem and the top 14 blends of the second run are listed in Appendix D. This includes the model input, batching results, sixty-three of the potential sixty-six model results The Coal Blending Model Pg 69
from the first run, and the top fourteen of two hundred and thirty-one model results from run two.
Figures 8, 9 and 10 are similar graphs of the Coal
Blending Coefficient contour lines, extrapolated from all data points generated by the two runs of the Coal Blending Model.
The first graph, Figure 8, compares Coal Blending Coefficient results to variations in the percentage of seams A and B in the blend. The center line drawn through the inflection points of the contour lines divides the graph into two distinct sections.
As in the first example, we will call these zones A and B.
Figures 9 and 10 compare Coal Blending Coefficient results to variations in the percentage of seams A and C, and seams C and
D respectively. All three graphs present identical results, but from a different view. By combining these three figures, a three-dimensional model can be generated.
The region within the contour line that indicates a Coal
Blending Coefficient of 4.5 represents the highest yield improvement over batching. A blend of 20:15:65 of seams A, C, and D respectively produced the highest Coal Blending
Coefficient of 4.51. As noted in Example Problem One, the maximum Coal Blending Coefficient value is important, but is not necessarily an optimum operating point. Percentage of Seam A in the Blend
Figure 8. Three Seam Model Results: Example Two
Coal Blending Coefficient Contours No. 1 £
© 90.
0 10 30 50 70 Percentage of Seam A in the Blend
Figure 9. Three Seam Model Results: Example Two
Coal Blending Coefficient Contours No. 2 cr 90. A O 1.0 o fl tt 0
n V 70 s A: a. H- B a 09 •rl X O fl 50. a 0 n w o 0 to 30 a 0 o ZONE B 0 au 10
0 fO 30 50 4.5 70 Percentage of Seam D in the Blend
Figure 10. Three Seam Model Results: Example Two 99 Coal Blending Coefficient Contours Ho. 3 to The Coal Blending Model Pg 73
confirm this statement. The Coal Blending Coefficient values for a two seam blend at this target ash and using the described unit operations combining seams A and C are all zero or slightly negative. Therefore, seams A and C could be considered as one seam, thus simplifying this problem down to a two seam blend.
As in Example One, the following three scenarios, shown in
Table VIII, are evaluated in Example Two to determine the total production for each case:
1. Batching
2. Blending at the optimum Coal Blending Coefficient for
as long as possible, and then batching
3. Blending at the in-pit seam ratio.
The relatively straight contour lines found in Figures 8,
9 and 10 indicate that seams A and C have similar washability properties, thus there is no advanatage to blending these two seams, as demonstrated in runs numbered 58 through 63 on page
118 in Appendix D. The Coal Blending Model Pg 74
TABLE VIII. COAL PRODUCTION FOR EXAMPLE TWO
Scenario Blend Total Tonnes of
Coal Recovered
1. Batching 30462000 tonnes
2. 20:15:65 20015000 tonnes
00:100:00 6299000 tonnes
100:00:00 5257000 tonnes
TOTAL 31571000 tonnes
3. 30:30:40 31688000 tonnes
Of the above three scenarios, number Three gave the
highest total production. Scenario One, batching, was again
the worst choice. Other combinations can be easily evaluated
using the same method as in the example problems. The Coal Blending Model Pg 75
Example Problem Three: Three Seam Blend "2"
This example problem uses Seams A, B, C to form a three seam blend. The target ash and flotation product ash are both set at nine percent. As in Example Two, two runs were performed, the first using a step-size of ten and the second using a step-size of five. The Coal Blending Model printout for the second run using a step-size of five is in Appendix E.
This printout includes the model input, batching results and ninety-eight of the potential two hundred and thirty-one model results.
Figure 11 is a graph of the Coal Blending Coefficient contour lines extrapolated from all data points generated by the two runs of the Coal Blending Model. The region within the unit contour line represents those blends which give the highest yield improvement over batching. A blend of 40:25:35 of seams A, B, and C respectively produced the highest coal blending coefficient of 1.15. As in Examples One and Two, the following three scenarios will be examined:
1. Batching
2. Blending at the optimum Coal Blending Coefficient for
as long as possible, and then forming a two seam blend
and finally a single seam.
3. Blending at the in-pit seam ratio. The Coal Blending Model Pg 76
TABLE IX. COAL PRODUCTION FOR EXAMPLE THREE
Scenario Blend Total Tonnes of
Coal Recovered
1. Batching 30224400 tonnes
2. 40:25:35 24419200 tonnes
60:00:40 1558000 tonnes
100:00:00 4599600 tonnes
TOTAL 30576800 tonnes
3. 50:20:30 30604000 tonnes
The contour lines have a fairly regular pattern and spacing which indicates that there is little to gain by
juggling blending ratios. This result is confirmed by the close results in Table IX between Scenarios Two and Three.
To complete the analysis of optimum blending effects, a feasible zone based on acceptable sulfur content, calorific values, and/or yield is determined. For this example, only two constraints will be considered: Sulfur and Minimum Yield. 10 30 50 70
Percentage of Seam A in the Blend
Figure 11. Three Seam Model Results: Example Three
Coal Blending Coefficient Contours 90
NON-FEASIBLE ZONE FEASIBLE ZONE AQZ3 Percentage of Seam A in the Blend FEASIBLE ZONE B^g
Figure 12. Three Sean Model Results: Example Three ^
Blending Feasibility Zones ^ The Coal Blending Model Pg 79
The clean coal sulfur content was set to be between 1.0 and 1.2 percent while a plant yield of over 72 percent was required. Using the information generated by the Simulation
Model (shown in Appendix E), the constraining boundaries can be drawn on a graph or one can take advantage of a built in function of the program which ignores all Coal Blending
Coefficient values which do not meet the desired constraints.
Plotting the constraints on a graph gives a final result similar to Figure 12. The feasible zone outlined by the constraining physical properties is split in two by the primary axis generated by the inflection points of the Coal Blending
Coefficient contours. Since the results from Table IX indicate that Scenarios Two and Three produce almost the same results, this three seam example is similar to a two seam example with
straight branches. Under these circumstances, the zones outlined on Figure 12 should be considered as potentially feasible blending zones. Therefore, any blending program using blends from only one zone will be successful. In contrast, blends selected from opposite sides of the primary axis
represent a loss in potentially recoverable clean coal. This does not mean that a consistent feed blend is not required, but
rather that the consistent plant feed ratios be selected from within the same feasible blending subzone. The Coal Blending Model Pg 80
Whenever possible, the secondary axis should also be taken into consideration. The secondary axis divides the zones created by the primary axis into two sections. The function of the secondary axis is similar to that of the primary axis, except that less potential benefit occurs when limiting the blending program to only one side of one zone. If the in-pit reserves, located in zone B, were to contain an abundance of seams B and C and a shortage of Seam A, to obtain a good blending program with maximum flexibility would require that the washery feed blends be limited to blends in zone B that are on the left side of the secondary axis. For the inverse case of an abundance of seam A, and a shortage of seam B and seam C, the blending zone would then be limited to the more confined area to the right of the secondary axis in zone B. Example
Three demonstrates a case where the optimum blend can be considered to be any blend from within a blending zone that is defined by the Coal Blending Coefficient axis and the quality constraints. This example lends itself well to an in-pit blending program, thus eliminating the need for large stockpiles. The Coal Blending Model Pg 81
V. SUMMARY AND REMARKS
The scheduling of production in multiple seam coal mining complicates the planning process, often causing conflicts between the mining production requirements and the preparation plant feed needs. Factors such as sulfur contents, calorific values, size distributions, ash contents, and clean coal
recovery must all be considered in mine scheduling if an in-pit blending program is to be successful and reduction of stockpile
sizes is to be achieved.
The Coal Blending Model presented in this thesis quantifies the effects of a controlled blending program on preparation plant yield, thus providing a method to optimize the blending program within the constraints of the mining program, the washery unit operations, and the final product quality.
The model does not always produce a single optimum blending strategy. For coals with similar washability characteristics, there is often no benefit to blending. In this case, the two coal seams can be treated as one seam for the purpose of blending. In some cases, there is a feasible
zone of blending ratios. This scenario lends itself well to
in-pit blending, since the mine planners can take full The Coal Blending Model Pg 82
advantage of the entire blending zone when developing the mine plan. If a consistent blend within the feasible zone is able to be maintained for at least a week, the mine can have an effective in-pit blending program. The longer a consistent blend is maintained, the greater will be the plant's
efficiency, with additional factors within the plant leading to
even further improvements.
Single optimum solutions are also a possibility. An
evaluation of the model results will determine the best
strategy. Coal mines with large, unproven reserves may wish to
select the blend with the highest Coal Blending Coefficient, and try to maintain that blend within new reserves.
The Coal Blending Model will not select an optimum blending program for the user, but will provide a means of evaluating different blends, thus allowing for the selection of a most appropriate blending program for a mine. For those cases where a blending program proved useful, improvements in coal yield of greater than 1% were obtained in most cases.
This represents a potential extra profit of 11 to 13 million dollars for the Western Canadian coal industry. The Coal Blending Model Pg 83
Some difficulties may arise in evaluating results for program runs involving more than four seams. This is because graphical interpretations cannot be obtained for such blends, which therefore require greater interpretive skills from the user. It is recommended that blends of only three and four
seams be used initially until a data base of Coal Blending
Coefficients is developed for the mine. This will enable the user to make an accurate evaluation of the computer results and then proceed to evaluate blends of five and more seams, based on the experience gained.
The present model requires further improvements and testing before it is suitable for general use, although the concept of the Coal Blending Coefficient has proven to be a potential tool for improvement of the overall effectiveness of
seam blending programs. Initial trials have proven most promising, but more work, with the cooperation of active coal mines, is required to prove the merits of the Coal Blending
Coefficient. The Coal Blending Model Pg 84
REFERENCES
1. Duncan N.J., "Canadian Coal Preparation Plants", A report prepared for the Members of the International Organizing Committee of the International Coal Preparation Congress, CIMM, May, 1984.
2. Butcher, Stanley G., "Coal Preparation in the Western Foothills and Mountains", Coal in Canada, **
3. Picard J. L.,"Coal Preparation Washing Process: A Technological Review", CANMET Report 85-2E, 1985.
4. CANMET Coal Data Manipulation Model; a computer model, 1985.
5. Simon, Jack A., Hopkins, M. E., "Geology of Coal: Nature of Coal", pp. 21 & 24, Elements of Practical Coal Mining, The American Institute of Mining, Metallurgical, and Petroleum Engineers, Inc., Port City Press, Inc., Baltimore, Md, 1973.
6. Leonard, Joseph W., and Mitchell, David R., editors, Coal Preparation, Third Edition, The American Institute of Mining, Metallurgical, and Petroleum Engineers, Inc., New York, 1968.
7. Yancey H.F., Geer M.R., "Efficiency and Sharpness of Separation in Evaluating Coal Washing Performance", Transactions of the A.I.M.E., 190, 507, 1951.
8. Walters A.D., Ramani R.V., and Stefanko R., "A Computer Simulation Model for Coal Preparation Plant Design and Control", Special Research Report SR-102, Penn State University, Feb 1976.
9. Kindig J.K., Lickie P.T. and Lovell H.L., "Mineral Preparation Evaluation by Digital Computer of Washability and Distribution Data", Proceeding of the Symposium and Short Course in Computers and Operations Research in Mineral Industries,1,R-1, April 1966. The Coal Blending Model Pg 85
REFERENCES (cont'd...)
10. Cheradame R.J., Saint-Guilhem P.L.R., Belugou P., "Evaluating Preparation Results", Coal Age, 55, (4), 80, April 1950.
11. Hudy J., Jr., "Performance Characteristics of Coal-Washing Equipment: Dense-Medium Coarse-Coal Vessels", U.S. Department of the Interior, Bureau of Mines [1969] . Report on investigation 7154.
12. Bethe W.P. and Koch G., "New Constructional Designs of Coal Washeries in the Federal Republic of Germany", IX International Coal Preparation Congress, New Delhi, 1982. pp. 1-8
13. Kubitza K., "Principles, Techniques and Economic Aspects of ROM Coal Homogenization", Gluckauf Translation, 8:202-210 (1981)
14. Osborne D.G., and Walters A.D., "Design Criteria for Canada's Export Coal Preparation Plants", 87th Annual General Meeting of CIM 1985, April 21-25, 1985, Vancouver, B.C. Paper 89, ppl3-14.
15. Lazorin A.I., Soloshenko V.S., Slesarev (DGI) V.V., Litmanovich I.M., Milyutin O.M. and Chernova V.A. (Yasinovka Coke Works), "Averaging of Coal in the Cleaning Process", Coke Chemistry, No. 10, pp. 16-18, Allerton Press, Inc, 1979.
16. Salama A.I., "Yield Maximization in Coal Blending", X International Coal Preparation Congress, Edmonton, Canada, 1986. pp 196-216
17. Abbott J., "The Optimization Of Process Parameters To Maximise the Profitability From A Three-Component Blend", Australian Coal Preparation Conference, 1st, Newcastle, NSW, Australia, April 1981, pp. 87-105
18. Charmbury H.B. and Lovell H.L., "Computer Evaluation of Coal Preparation Washability Data", Mechanization, 24, No. 4, 57, April 1962, No. 5, 47, May 1962. The Coal Blending Model Pg 86
REFERENCES (cont'd...)
19. Brookes G.F. and Whitmore R.L., "An Application of the Digital Computer to Coal Preparation", Coal Preparation, 95, May/June 1966.
20. Humphreys K.K., Leonard J.W. and Butterworth J.A., "Computer Program Performs Complete Coal Washability Analysis", Coal Age, 76, 101, July 1971.
21. Absil J.H., Keuning W. and Meerman P.G., "Prediction of Washery Plant Performance by Data Processing", 5th International Coal Preparation Congress, Pittsburgh, F4, 381.
22. Coal Preparation Plant Simulation Model; a computer model by U.S. Energy, Mines, and Resources, 1986.
23. Rong R.X. and Lyman G.J.," Computational Techniques for Coal Washery Optimization- Parallel Gravity and Froth Separation", Coal Preparation , 2: 51-67; (1985).
24. Leonard, IV, Joseph W. and Leonard, Joseph W., "Use of Partition (Tromp) Curves for Diagnosing Performance Problems in Operational Coal Cleaning Equipment", Society of Mining Engineers of AIME, Transactions Vol. 270, 1848--1850, (1982).
25. Jowett, Alan, An Appraisal of Partition Curves for Coal-cleaning Processes",International Journal of Mineral Processing, 16: 75-95, Elsevier Science Publishers B.V., Amsterdam (1986). The Coal Blending Model Pg 87
APPENDICES The Coal Blending Model
APPENDIX A:
Coal Blending Model
Program Listings COAL BLENDING COEFFICIENT PROGRAM 3780 PROGRAM TO CALCULATE THE C.B.C 3798 FOR R»l TO,8 s 3791 Sun_b1tnd-8 ~ 3792 FOR 1-1 TO Z 3793 3um_blend»Sum b1end+B1end(I,R> 3794 Model<1,R,5>-Model<1,R,5>+Blend
SORTING AND STORING PROGRAM 3828 Table
3980 Exi 11: NEXT LI 3990 Exitk: NEXT Kk 4O00 Exi tj: NEXT Jj 4010 Exiti: NEXT Ii
«
o MODEL IHPUT PROGRAM
1480 INPUT "How many sets of data do you wish to blend (max 4; Oef ault 3>",Z 1498 INPUT "How many sizes fractions do you wish to work with? Def ault 3",S_s 1588 ~* INPUT "What Is the name of the coarsest size fraction? Defaul t +28 MESH",Size_na*e$
APPENDIX B:
Washability Data Used
For Example Problems The Coal Blending Model Pg
co on h- a', r-- cm oo in VO © co * CO N M * 'fl ij) N N
K (0 ii ffi t ^ c r>- on © co <3 CO IN- Cf» CM CO ~« CO CO N Cs — CM IN. -~ CM * C\ 'O CO CO o> (A lA N f4 S f N - ui « -I « © © © © © © J£ (A 00 m vo |N- © c c y o CO •> ••- *> 1 i i i i i 1 lA u •» .— C ffl IT) © © © © © © C O CO m vo |Nw © C£ a Lu — WASHABILITY ANALYSIS: SEAM A SIZE FRACTION: 12.7 X 0.6 mm PROPORTION OF RAW COAL: 48Z Cumulative data Re 1 at i ve Elementary data Densi ty Float Si nk Frac t i ons Mass X Ash. y. s y. Mass 'A Ash X s y. Mass y. Ash y. s y. Float- 1.30 42.67 3.46 0.44 42.67 3.46 0.44 100.00 24. 12 0.95 1.30 - 1.40 22.88 f. 30 0.63 65.55 4.88 8.51 57.33 39.49 1.33 1.40 - 1.50 4.89 18.24 1.84 70.44 5.73 0.54 34.45 60.87 1.39 1.50 - 1.60 1.98 25.83 1.48 72.42 6.28 0.57 29.56 67.92 1.92 - 1.60 - 1.70 1.70 35.85 1.67 74. 12 6. 94 0.59 27.58 78.94 1.95 1.70 - 1.80 1.65 43.74 1.73 75.77 7.74 0.62 25.88 73.30 1.97 1.80 - Sink 24.23 75.31 1.99 100.80 24. 12 0.95 24.23 75. 31 1.99 WASHABILITY ANALYSIS: SEAM B SIZE FRACTION: 150 X 12.7 BD PROPORTION OF RAW COAL: 601 Cumulative data Relat ive Elementary data Dens i ty Float Sink Frac t i ons Mass 'A Ash V. s y. Mass '4 Ash 'A- s y. Mass 'A Ash y. s y. J Float- 1.30 5.95 3.93 0.70 5.95 3.93 0.70 100.00 33.54 1.79 1.30 - 1.40 40.23 8. 78 1.37 46. 18 8. 16 1.28 94.05 35.41 1 .86 1.40 - 1.50 14.95 18.83 3.67 61. 13 10.77 1.87 53.82 55.32 2.23 1.50/- t.60 5.25 32.-45 3.86 66.38 12.48 2.02 38.87 69.35 1.68 1.60/- 1.70 3. 12 43.03 5.37 69.58 13.85 2. 18 33.62 75. 11 1. 34 1.70/ - 1.80 3.03 52.87 2.61 72.53 15.48 2. 19 30.50 78.39 0.93 1.80 - Sink 27.4? 81.21 8. 74 180.00 33.54 1.79 27. 47 81.21 0. 74 WASHABILITY ANALYSIS: SEAM B SIZE FRACTION: 12.7 X 0.6 an PROPORTION OF RAW COAL: 33Z Cumu1 at i ve dat a Relat ive Elementary data Dens i ty Fl oat Si nk Fract i ons y. Mass fish y. s y. Mass X fish y. s y. Mass 'A fish y. S Float- 1.30 31.98 3.54 0.69 31.98 3.34 8.69 100.00 20. 16 1 . 85 1.30 - 1.40 37.97 7.58 1.31 69.95 5.69 1.03 68.02 27.98 2. 39 1.40 - 1.50 7.44 17.85 3.07 77.39 6.86 1. 22 30.05 53.86 3. 75 1.50 1.60 2.68 27.38 4.27 88.07 7.54 1.32 22.61 65.71 3. 98 1.60/- 1.70 1.93 35.84 5.09 82.88 8.21 1.41 19.93 78.87 3. 94 1.70/- 1.80 1.38 42.97 4.86 83.38 8.78 1.47 18.00 74.63 3. 82 1.80/ - Sink 16.62 77.26 3.73 100.00 28. 16 1.85 16.62 77.26 3. 73 WASHABILITY ANALYSIS: SEAM aC SIZE FRACTION: 150 X 12.7 mn PROPORTION OF RAW COAL: 421 Cumulative data Re 1 at i ve Elementary data Density Float Sink Frac t i ons - Mass \ fish 'K S X Mass 'A fish y. s y. Mass '< fish y. s y. Float- 1.30 27.40 4.32 0.79 27.40 4.32 0.79 100.00 19.56 1. 06 1.30 - 1.40 36.23 8.88 1.07 63.63 6.92 0.95 72.60 25.32 1. 16 1.40 - 1.50 10.60 28.28 0.89 74.23 8.82 0.94 36. 37 41.69 1. 26 1.50 - 1.60 7.72 31.68 0.77 81.95 10.98 0.92 25.77 50.49 1. 41 1.60 - 1.70 4.97 41.69 0.64 86.92 12.73 0.91 18.05 58.54 1. 68 1.70 - 1.80 3.24 50.77 1. 17 90. 16 14. 10 0.92 13.08 64.94 2. 08 1.80 - Sink 9.84 69.61 2.38 100.00 19.56 1.06 9.84 69.61 2. 38 WASHABILITY ANALYSIS: SEAM C SIZE FRACTION: 12.7 X 0.6 na PROPORTION OF RAH COAL: 48Z Cumulative data Re 1 at ive Elementary data Densi ty Float Si nk Fract i ons Mass 'A fish v. S v. Mass '/. Ash '/. s y. Mass 'A fish y. s y. Float- 1.39 47.22. 3.73 8.75 47.22 3.73 8.75 100.00 14.81 1. 16 1.30 - 1.40 27.38 9. 11 1.81 74.52 5. 70 8.85 52.78 24. 72 1 .52 1.40 - 1.50 8.65 21.26 1.28 83. 17 7.32 0.89 25.48 41.44 2. 07 1.50 - 1.60 4.19 31.24 1.42 87.36 8.47 0.92 16.83 51.81 2.47 1.60 - 1.70 2.84 39.66 1.87 90.20 9.45 0.95 12.64 58.62 2.82 1.70 - 1.80 2.18 47.25 2.84 92.38 18.31 0.97 9.80 64. 12 3. 10 1.80 - Sink 7.78 68.72 3.39 100.00 14.81 1. 16 7. 70 68. 72 3.39 H tr A CS o CB M A a WASHABILITY ANALYSIS: SEAM D a SIZE FRACTION: 150 X 12.7 mm a PROPORTION OF RAW COAL: 461 M X o A Cutnul at i ve dat a Relative Elementary data Densi ty F1 oat Sink Fract"i ons Mass '4 Rsh V. s y. Mass '4 fish y. s y. Mass 'K fish X s y. Float- 1.30 17.23 3.82 1.33 17.23 3.82 1.33 100.00 11.89 2.89 1.30 - 1.40 66.03 8.86 2. 11 83.26 7.82 1.95 82.77 13.58 3.21 1.40 - 1.50 8.81 18. 17 3.31 91.27 8.73 2.09 16.74 32. 18 7.57 1.50 - 1.60 2.06 25.97 5.46 93.33 9. 11 2. 16 8.73 45.83 11.29 1.60 - 1.79 1.12 35.89 5.95 94.45 9.42 2.21 6.67 58.91 13.09 1.70 - 1.80 0.89 46.26 7.18 95.34 9.77 2.25 5.55 53.94 14.54 1.80 - Sink 4.66 55.41 15.94 100.00 11.89 2.89 4.66 55.41 15. 94 00 VO WASHABILITY ANALYSIS: SEAN D SIZE FRACTION: 12.7 X 0.6 BB PROPORTION OF RAW COAL: 441 Cumulative data Relat iwe Elementary data Densi ty Fl oat Sink Frac t i ons Mass V. Ash V. S Mass 'A Ash y. S X Mass X Ash y. s y. Float- 1.30 41. 17 3.32 1.28 41. 17 3.32 1.28 100.00 12.81 2.46 1.30 - 1.40 40.77 7.33 2.01 81.94 5.32 1.6*4 58. 83 18.09 3.29 1.40 - 1.50 6.26 17.66 3.81 88.28 6. 19 1.80 18.06 42.38 6. 17 1.50 - 1.60 1.88 27.51 4.78 98.00 6.62 1.86 11.88 55.50 7. 42 1.60 - 1.70 1.46 34.86 5. 10 91.46 7.07 1.91 10. 00 60.53 7. 90 1.70 - 1.80 0.99 43.05 5.24 92.45 7.45 1.94 8.54 64.92 8.38 1.80 - Sink 7.55 67.79 8.79 100.00 12.01 2.46 7.55 67.79 8.79 The Coal Blending Model Pg 101 APPENDIX C: Coal Blending Model Results: Example Problem One The Coal Blending Model Pg 102 '3 £ •»- C0 CO X CD CD fl) £ 3 CO CO C 2: •\" •» CO IO IO CO CO CO cn CO CO is- in CT. CO • • • • • • 0) IO CO CO CM |N- CO IO CO CO CO •* 1- CO •V CM CM o o ZZ zz z: zc I X X X O II II c o £ £ £ £ -r- £ £ 3 3 *> £ £ u CO fl) £ * £ • X X c £ £ £ CO £ fl) fl) u. £ £ ZZ zz Iv. X X CM (N. • CO CO CM CO ^~ a CO • CO co + CM + CM IN- CO ^ IO 1 TA 1 c £ fl) £ II II >. II £ X £ fl) (rt 3 > to Ol CC CC £ fl) Isl CO .— .— i. — fl) A) U CO o o fl) ~ o o O £ u a. O *t • c< ^ C 3 — CO (V .-* CM fl) <~ u Cu — 0i CU — 3 a. x 1- O CO co t- SIZE CLEANING MODEL MODEL MODEL MODEL MODEL Tl: T2 FRACTION UNIT S.G. YIELD ASH SULFUR FACTOR 100: 0 +12.7 mm HMB 1. 453 65. 43 7. 000 . 590 ZERO 12.7 X 0.6 mm HMC 1. 704 74. 14 6. 999 . 595 ZERO - 0.6 mm 0. 000 80. 00 8. 080 . 600 ZERO TOTAL 0. 000 72.08 7. 185 .594 ZERO 0:100 +12.7 mm HMB 1. 337 16.24 7. 003 1 . 124 ZERO 12.7 X 0.6 mm HMC 1.519 77.45 7. 000 1. 242 ZERO - 0.6 mm 0. 008 80. 00 8.800 1.200 ZERO TOTAL 0. 000 41. 22 7. 148 1.209 ZERO 1 65: 35 +12.7 mm HMB 1.379 51.10 7. 002 .871 9. 04 12.7 X 0.6 mm HMC 1 .651 75. 27 7. 000 . 368 . 24 - 0.6 mm 0. 000 80. 00 8.000 .810 0. 00 TOTAL 0. 000 65. 38 7. 136 .836 4.11 2 70: 30 +12.7 mm HMB 1. 401 53. 70 6. 998 . 847 8. 79 12.7 X 0.6 mm HMC 1 .662 75. 17 7. 005 . 774 . 27 - 0.6 mm 0. 000 80. 00 8. 060 . 780 0. 00 TOTAL 0. 000 66. 75 7.141 .866 3. 93 3 75: 25 +12.7 mm HMB 1.419 55. 65 6.999 .823 7. 79 12.7 X 0.6 mm HMC 1. 671 74. 98 6.999 . 750 . 22 - 0.6 mm 0. 000 80. 08 8. 606 . 756 6. 88 TOTAL 0. 000 67. 75 7. 144 . 780 3. 39 4 60: 40 +12.7 mm HMB 1. 368 45. 43 7. 661 . 894 6. 05 12.7 X 0.6 mm HMC 1. 641 75. 44 7. 606 .839 . 25 - 0.6 mm 0. 000 86. 00 8. 680 . 846 6. 66 TOTAL 0. 000 62. 59 7. 131 .864 2. 86 5 80! 20 +12.7 mm HMB 1. 425 57. 29 6. 997 . 788 6.33 12.7 X 0.6 mm HMC 1. 679 74. 80 6. 997 .716 . 17 - 0.6 mm 0. 008 86. 00 8. 680 . 726 8. 66 TOTAL 0. 000 68. 59 7. 147 . 745 2. 68 6 85: 15 +12.7 mm HMB 1.431 59. 05 6. 999 . 752 4.31 12.7 X 8.6 mm HMC 1. 686 74. 63 7. 660 .683 . 13 - 8.6 mm 0. 000 80. 60 8. 000 . 696 0. 66 TOTAL 0. 000 69. 43 7. 154 .711 1. 93 7 55: 45 +12.7 mm HMB 1 . 363 40. 78 7. 802 .926 3. 92 12.7 X 0.6 mm HMC 1. 632 75. 58 7. 006 . 873 . 25 - 0.6 mm 0. 000 80. 00 8. 006 .876 6. 60 TOTAL 0. 000 66. 12 7. 127 . 894 1. 93 8 90: 10 +12.7 mm HMB 1.437 61. 02 7. 000 .710 3. 28 12.7 X 0.6 mm HMC 1.693 74. 48 7.000 . 654 . 10 - 0.6 mm 0. 000 80. 00 8.000 . 660 0. 00 TOTAL 0. 000 '70.31 7. 158 . 676 1.32 9 $0, 50 +12.7 mm HMB 1. 358 36.85 7.001 . 945 2. 36 12.7 X 0.6 mm HMC 1. 622 75. 74 7. 000 . 903 . 25 - 0.6 mm 0. 000 80. 00 8. 000 . 900 0. 00 TOTAL 0. 000 57.88 7. 122 . 923 1. 23 10 45: 55 +12.7 mm HMB 1.355 33. 59 7.000 . 970 1. 36 12.7 X 0.6 mm HMC 1.612 75.89 6. 999 .939 . 24 - 0.6 mm 0. 000 80. 00 8. 000 . 930 0. 00 TOTAL 0. 000 55. 87 7. 117 . 95-3 . 76 11 95: 5 +12.7 mm HMB 1.443 63. 06 6.995 . 655 1. 57 12.7 X 0.6 mm HMC 1. 699 74.30 7. 080 . 627 . 85 -0.6mm 0. 000 80. 00 8. 000 . 630 0. 00 TOTAL 0. 000 71.16 7. 161 .638 . 63 12 40: 60 +12.7 mm . HMB 1. 351 30.67 6. 998 . 988 . 58 12.7 X 0.6 mm HMC 1. 603 76. 85 6. 999 . 974 .23 - 0.6 mm 0. 000 80.00 8.000 . 960 0. 00 TOTAL 0. 000 53. 94 7.111 .979 . 38 13 35: 65 +12.7 mm HMB 1 .349 28. 17 7. 000 1. 005 . 10 12.7 X 0.6 mm HMC 1 .594 76.21 7. 000 1 . 005 .21 - 0.6 mm 0. 000 80. 00 8. 000 . 990 0. 80 TOTAL 0. 000 52. 15 7. 108 1 . 003 . 13 14 30: 70 +12.7 mm HMB 1.347 26. 01 7. 002 1 . 824 -. 13 12.7 X 0.6 mm HMC 1. 584 76. 38 7. 000 1 . 040 . 20 - 0.6 mm 0. 000 80. 00 8. 000 1 . 020 0. 80 TOTAL 0. 000 50.48 7. 104 1. 029 .01 15 188: 0 +12.7 mm HMB 1. 453 65. 43 7. 000 . 590 -.04 12.7 X 0.6 mm HMC 1.704 74. 14 6. 999 . 595 -.00 - 0.6 mm 0. 000 80. 00 8.000 . 600 0. 00 TOTAL 0. 000 72. 08 7. 167 . 594 0.00 16 0:100 +12.7 mm HMB 1.337 16. 24 7.003 1. 124 0. 00 12.7 X 0.6 mm HMC 1.519 77. 45 7. 000 1.242 . 00 - 0.6 mm 0. 000 80. 00 8. 000 1 . 200 0. 00 TOTAL 0. 000 41. 22 7. 078 1. 169 0. 00 17 5: 95 +12.7 mm HMB 1.339 17.51 7. 000 1. 109 -.20 12.7 X 0.6 mm HMC 1.530 77. 25 7. 800 1.210 . 04 - 0.6 mm 0. 000 80. 00 8. 000 1. 170 0. 00 TOTAL 0. 000 42. 66 7. 088 1. 148 -.10 18 25: 75 +12.7 mm . HMB 1.345 23. 91 6. 999 1. 040 -.38 12.7 X 0.6 mm HMC 1.574 76. 53 7. 00k 1. 074 . 16 - 0.6 mm 0. 000 80. 00 8. 000 1. 050 0. 00 TOTAL 0. 000 48. 79 7.098 1.054 -. 15 19 20: 80 +12.7 mm HMB 1.343 22. 18 7.002 1. 059 -.36 12.7 X 0.6 mm HMC 1.563 76. 69 7. 000 1. 109 . 12 - 0.6 mm 0. 000 80. 00 8. 000 1 . 080 0. OO TOTAL 0. 000 47. 24 7. 095 1. 079 -. 16 28 15: 85 +12.7 mm HMB 1.341 20. 47 7. 002 1 . 080 -.39 12.7 X 0.6 mm HMC 1.551 76. 86 7.000 1. 142 . 08 - 0.6 mm 0. 000 80. 00 8. 000 1.110 0. 00 TOTAL 0. 000 45. 66 7.091 1. 105 -. 19 21 10: 99 +12.7 mm HMB 1. 340 18. 86 6. 999 1 . 091 -.39 12.7 X 0.6 mm HMC 1.540 77. 04 7. 000 1. 176 . 85 - 0.6 mm 0. 000 88. OO 8. 000 1. 140 0. 00 TOTAL 0.000 44. 10 7. 085 1. 124 -.21 The Coal Blending Model Pg 107 APPENDIX D: Coal Blending Model Results: Example Problem Two The Coal Blending Model Pg 108 5 £ CO CO CO X CD CO CO n> •-t *—* z: .V 3 £ CO CO CO C •f— Z! •\" *> CO in in CO CO CO CO CO CO cn o CM CM CO CM in m CO - r— 0) IO CO CO CM IN- CO in CO CO .—1 T»- CO CO rf CO .\- - . CM CM 1— z o o o z: z: z: z: z: i z I z X X U II II c o £ £ £ £ •w- £ £ £ 3 3 *> u CO CO CO n) £ • £ • £ • X X 4. £ CO £ £ CO £ £ CO £ fl) fl) U. £ £ £ z: z: X X X (to • CO • CO • CO CO CO CO CO N CM • CM CM • -w- • CO • CO- • CO in co CM co co + CM + CM + CM rs- co co 1 1 1 s zfl) II II IX II •* £ > 0> 0fl)) cc o fl) N CO ,— i. — D n) <* IJ) CO o o o o Q. o o o . r- 3 Q. X 1— U CO CO I- SI2E CLEANING MODEL MODEL MODEL MODEL MODEL # T1.T2.T3 FRfiCTION UNIT S. G. YIELD ASH SULFUR FACTOR 180:0:0 +12.7 mm HMB 1. 483 69. 53 7. 500 .596 ZERO 12.7 X 0.6 mm HMC 1 . 782 75. 24 7. 499 .611 ZERO - 0.6 mm 0. 000 80. OO 8. 000 . 680 ZERO TOTfiL 0. 000 74. 04 7. 590 . 604 ZERO 0:180:0 +12.7 mm ' HMB 1. 434 66. 45 7. 500 . 947 ZERO 12.7 X 0.6 mm HMC 1.513 83. 38 7.500 . 894 ZERO - 0.6 mm 0. 000 80. 00 8. 000 . 900 ZERO TOTfiL 0. 000 75. 89 7. 554 .914 ZERO 0:0:100 +12.7 mm HMB 1. 361 63. 59 7. 503 1. 900 ZERO 12.7 X 0.6 mm HMC 1. 891 92. 42 7. 443 1. 949 ZERO -0.6mm . 0. 000 80. 00 8. 000 1. 900 ZERO TOTAL 0. 000 77. 94 7.528 1. 925 ZERO 1 30: 0: 70 +12.7 mm HMB 1. 384 75. 56 7. 561 1.684 10. 45 12.7 X 0.6 mm HMC 1. 838 86.98 7. 498 1. 569 . 69 - 0.6 mm 0. 000 80. 00 8. 668 1.516 0 . 00 TOTFIL 0. 000 81. 23 7. 563 1.616 4. 46 2 10: 30: 60 +12.7 mm HMB '1.389 74. 47 7. 562 1.615 9. 39 12.7 X 0.6 mm HMC 1 . 651 88. 12 7. 564 1 . 464 . 38 - 0.6 mm 0. 000 80. 00 8. 686 1. 476 0. 68 TOTAL 0.000 81. 27 7. 559 1. 536 4. 34 3 20: 20: 60 +12.7 mm HMB 1. 484 74. 89 7. 500 1. 665 9. 56 12.7 X 0.6 mm HMC 1. 692 87. 21 7. 500 K 456 . 35 - 0.6 mm 0. 060 80. 00 8. 006 1.448 0. 66 TOTAL 0. 000 81 . 08 7. 560 1. 5.18 4. 33 4 30: 10: 60 +12.7 mm HMB 1.415 75.38 7. 496 1 . 600 9. 78 12.7 X 0.6 mm HMC 1. 739 86.20 7. 506 1.452 . 22 - 0.6 mm 0. 000 80. 00 8. 000 1.410 8 . 00 TOTAL 0. 600 80.87 7. 561 1. 509 4.31 5 40: 0: 60 +12.7 mm HMB 1.421 75. 83 7. 498 1.591 10. 25 12.7 X 0.6 mm HMC 1.814 85. 19 7. 497 1. 445 . 67 -0.6mm 0 . 000 80. 00 8. 066 1 . 388 6. 66 TOTAL 0. 000 80. 64 7.564 1. 496 4. 26 6 20: 10: 70 +12.7 mm HMB 1.377 73. 75 7. 501 1. 685 8. 77 12.7 X 0.6 mm HMC 1. 740 88. 00 7. 568 1. 574 . 23 - 0.6 mm 0. 686 80. 00 8. 000 1 . 548 6. 60 TOTAL 0. 006 80. 90 7. 561 1 .618 3. 95 7 20: 30: 50 +12.7 mm HMB 1. 420 74.03 7. 497 1.513 8. 38 12.7 X 0.6 mm HMC 1 . 652 86.36 7. 504 1.349 . 39 - 0.6 mm 0. 000 80.00 8. 000 1.346 8. 60 TOTAL 0. 000 80. 37 7. 560 1.417 3. 33 8 10: 40! 50 +12.7 mm HMB . 1.414 73. 70 7. 496 1 . 523 3. 29 12.7 X 0.6 mm HMC 1.616 87. 12 7. 588 1.359 . 28 - 0.6 mm 0. 000 80. 80 8. 888 1. 370 0. 08 TOTAL 0. 800 80. 53 7. 555 1 . 431 3. 88 9 0: 40: 60 +12.7 mm HMB 1.379 72. 99 7. 498 1. 622 8. 17 12.7 X 0.6 mm HMC 1.613 88.89 7. 588 1. 473 . 28 - 0.6 mm 0 . 000 88. 88 8. 800 1.500 0. 00 TOTAL 0. 000 80.92 7. 552 1. 542 3. 30 10 0: 50: 50 +12.7 mm HMB 1. 404 73. 28 7. 503 1. 536 8. 13 12.7 X 0.6 mm HMC 1 . 591 87. 93 7. 584 1 . 373 . 23 - 0.6 mm 0. 000 80. 00 8. 000 1. 400 0. 88 TOTAL 0 . 000 80. 67 7. 556 1. 447 3. 75 11 30: 20: 50 +12.7 mm HMB 1. 423 74. 27 7. 496 1. 588 8. 37 12.7 X 0.6 mm HMC 1 .693 85.44 7. 500 1.329 . 33 - 0.6 mm 0.000 80. 00 8. 000 1.318 0. 00 TOTAL 0. 000 80. 10 7. 561 1.398 3. 74 12 40: 10: 50 +12.7 mm HMB 1 .427 74.55 7.500 1.487 8. 39 12.7 X 0.6 mm HMC 1. 738 84. 45 7. 500 1.318 . 20 - 0.6 mm 0.000 80.00 3. 000 1. 288 0. 80 TOTAL 0. 000 79. 81 7.566 1 . 382 3. 63 13 50: 0: 50 +12.7 mm HMB 1.431 74. 96 7. 502 1. 483 8. 80 12.7 X 0.6 mm HMC 1.806 83. 45 7.499 1 . 388 . 06 - 0.6 mm 0. 000 80. 00 8. 080 1. 258 0. 00 TOTAL 0. 000 79. 55 7.570 1. 378 3. 57 14 10: 20: 70 +12.7 mm HMB 1.374 72. 36 7. 498 1. 694 7. 63 12.7 X 0.6 mm HMC 1.692 89.84 7.501 1. 575 . 38 - 0.6 mm 0. 000 80. 00 8. 000 1. 578 8. 00 TOTAL 0. 800 88. 78 7.557 1.626 3. 56 a o 15 0: 60: 40 +12.7 mm HMB 1.419 72.35 7.497 1 . 438 6. 91 o 12.7 X 0.6 mm HMC 1 . 569 86.96 7.580 1 . 268 15 - 0.6 mm 0. 008 80.00 8.000 1 .300 0. 06 TOTFIL 0. 000 79.87 7. 551 1 . 345 3. 16 n s 16 10: 50: 40 +12.7 mm HMB 1 . 422 72.52 7. 500 1 . 424 6. 84 o. 12.7 X 0.6 mm HMC 1. 593 86. 19 7.500 1 . 248 25 H- S - 0.6 mm 0. 000 80. 00 8.000 1 .270 6. 00 W TOTAL 0. 000 79.65 7.556 •1 . 326 3. 13 x o 17 20: 40: 40 +12.7 mm HMB 1. 425 72. 71 7. 499 1 .410 6. 79 a re 12.7 X 0.6 mm HMC 1 .618 85. 40 7. 500 1 . 233 a 30 1 - 0.6 mm 0. 000 80.00 8. 000 1 . 240 8. 00 TOTAL 0. 000 79.42 7. 559 1 . 369 3. 63 18 30: 30: 40 +12.7 mm HMB 1. 429 72. 95 7. 503 1 . 397 6. 78 12.7 X 0.6 mm HMC 1 . 655 84.62 7.503 1 .220 a 38 -0.6 mm 0. 000 80. 00 8. 000 1 .210 8. 00 TOTAL 0. 000 79.22 7. 565 1 . 292 3. 07 19 0: 30: 70 +12.7 mm HMB 1.372 70. 88 7. 496 1 . 694 6. 39 12.7 X 0.6 mm HMC 1. 649 89. 92 7. 504 1 . 580 38 -0.6 mm 0. 000 80. 00 8. 000 1 . 600 8. 00 TOTAL 0. 000 80.38 7. 554 1 . 633 3. 86 28 40: 20:, 40 +12.7 mm HMB 1 . 432 73. 17 7. 501 1 . 333 6. 73 12.7 X 0.6 mm HMC 1 . 694 83. 72 7. 500 1 . 265 a 33 - 0.6 mm 0. 000 80. 00 8. 060 1 . 186 6. 00 TOTAL 0. 000 78. 94 7. 566 1 . 274 2. 98 21 50: 10: 40 +12.7 mm HMB. 1 . 435 73. 49 7. 500 1 . 361 6. 77 12.7 X 0.6 mm HMC 1 . 735 82. 73 7. 496 1 . 191 a 19 - 0.6 mm 0. 000 80. 00 8. 000 1 . 156 6. 00 T3 TOTAL 0. 000 78. 66 7. 567 1 . 253 2. 88 22 68: 8: 48 +12.7 mm HMB 1 . 439 73. 88 7. 497 1. 349 7. 13 12.7 X 0.6 mm HMC 1 . 798 81. 74 7. 493 1 . 173 . 84 - 0.6 mm 0. 880 80. 00 8. 000 1. 120 8. 80 TOTAL 8. 000 78. 41 7. 570 1. 234 2.81 23 28: 8: 88 +12.7 mm HMB 1.370 70. 67 7. 503 1. 768 6. 13 12.7 X 0.6 mm HMC 1.890 88.79 7. 494 1. 695 . 18 - 0.6 mm 0. 000 88. 88 8. 800 1. 640 8. 00 TOTAL 0 . 000 79. 86 7. 559 1. 720 2. 70 24 8: 78: 38 +12.7 mm HMB 1 . 424 71.00 7. 499 1. 332 5. 30 12.7 X 0.6 mm HMC 1 . 551 86. 03 7. 500 1. 170 . 18 - 0.6 mm 0 . 000 80. 00 8. 008 i: 200 0. 00 TOTAL 0. 000 78. 91 7. 552 1. 243 2.41 25 10: 18: 80 +12.7 mm HMB 1 . 369 69. 47 7. 501 1. 767 5. 88 12.7 X 0.6 mm HMC 1. 743 89.85 7. 500 1. 696 . 26 - 0.6 mm 0. 000 80.00 8. 000 1. 670 8. 88 TOTAL 0. 000 79. 72 7. 558 1.724 2. 38 26 10: 60: 30 +12.7 mm HMB 1 . 427 71. 17 7. 503 1.311 5. 22 12.7 X 0.6 mm HMC 1 . 572 85.26 7. 500 1 . 153 . 13 - 0.6 mm 0 . 000 80.00 8. 000 1. 170 0. 08 TOTAL 0. 000 78.69 7. 557 1. 222 2. 37 27 20: 50: 30 +12.7 mm HMB 1 . 430 71.30 7. 508 1. 297 5.11 12.7 X 0.6 mm HMC 1 . 595 84. 48 7. 508 1. 135 . 25 - 0.6 mm 0. 000 80.00 8. 080 1. 140 8. 88 TOTAL 0. 000 78. 45 7. 559 1. 203 2. 32 28 30: 40: 30 +12.7 mm HMB 1 . 433 71. 53 7. 504 1.282 5. 88 12.7 X 0.6 mm HMC 1 . 621 83. 70 7. 500 1.115 .31 - 0.6 mm 0. 000 80. 00 8. 000 1.110 8. 88 TOTAL 0. 000 78. 25 7. 564 1. 183 2. 38 29 40: 30: 30 +12.7 mm HMB 1 .436 71. 76 7. 502 1 . 258 5. 04 12.7 X 8.6 mm HMC 1. 657 82. 93 7. 503 1 . 095 .33 - 0.6 mm 0. 000 80. 00 8. 800 1. 080 0. 00 TOTAL 0. 000 78.04 7?568 1. 159 2. 28 30 50: 20: 30 +12.7 mm HMB 1.439 72. 02 7.500 1 . 241 5.02 12.7 X 0.6 mm HMC 1 . 694 82. 02 7. 497 1. 076 . 32 - 0.6 mm 0. 000 80. 00 8. 800 1. 050 0. 00 TOTAL 0. 000 77. 78 7. 567 1. 138 2.21 31 60: 10: 30 +12.7 mm HMB 1 .443 72. 35 7.502 1.213 5. 86 12.7 X 0.6 mm HMC 1. 734 81.04 7. 496 L. 057 . 18 - 0.6 mm 0. 000 80. 00 8. 000 1 . 020 0. 00 TOTAL 0. 000 77. 51 7. 571 1.114 2. 12 32 70: 0: 30 +12.7 mm HMB 1. 448 72. 76 7. 500 1. 202 5. 38 12.7 X 0.6 mm HMC 1 .794 88.07 7. 499 1. 038 . 84 - 0.6 mm 0 . 000 80.00 8. 000 . 998 0 . 00 TOTAL 0. 000 77. 27 7. 574 1 . 093 2.06 33 0: 20: 80 +12.7 mm HMB 1 .368 68.32 7.496 1. 764 4.14 12.7. X 0.6 mm HMC 1. 690 90. 86 7. 580 1 . 697 . 37 - 0.6 mm 0. 000 80. 00 8. 000 1. 706 0. 00 TOTAL 0. 000 79. 57 7. 552 1 . 727 2. 05 34 0: 80: 20 +12.7 mm HMB 1 .428 69. 54 7. 499 1.212 3. 58 12.7 X 0.6 mm HMC 1. 536 85. 13 7.508 1. 077 . 07 - 0.6 mm 0 . 000 88.00 8. 000 1 . 100 0. 00 TOTAL 8. 000 77. 92 7. 551 1. 137 1 . 62 35 18: 70: 28 +12.7 mm HMB 1. 430 69. 65 7. 499 1 . 196 3. 44 12.7 X 0.6 mm HMC 1. 553 84. 33 7. 508 1 . 056 . 10 - 0.6 mm 0 . 000 88. 80 8. 000 1. 078 0. 00 TOTAL - 0. 000 77.66 7. 554 1.117 1 . 55 36 20: 60: 20 +12.7 mm HMB 1.433 69. 81 7. 500 1. 171 3. 35 12.7 X 0.6 mm HMC 1.575 83.56 7.508 1.033 . 18 - 0.6 mm 0. 000 80.00 8.000 1. 040 8. 88 TOTAL 0. 000 77. 45 7.558 1.091 1.52 37 30: 50: 20 +12.7 mm HMB 1.436 69.97 7.500 1. 148 3. 24 12.7 X 0.6 mm HMC 1.597 82.81 7.500 1.010 . 26 - 0.6 mm 0. 800 80.00 8. 000 1.010 8. 80 TOTAL 0. 000 77.24 7.562 1.067 1. 50 38 40: 40: 20 +12.7 mm HMB 1.439 70. 20 7.502 1. 129 3.19 12.7 X 0.6 mm HMC 1.623 82. 04 7. 500 . 998 . 32 - 0.6 mm 0. 000 80.00 8.000 .980 0. 00 TOTAL 0. 000 77.04 7.566 1. 844 1. 48 39 50: 30: 20 +12.7 mm . HMB 1. 443 70.41 7.499 1. 104 3. 13 12.7 X 0.6 mm HMC 1.659 81. 29 7.503 .969 .41 - 0.6 mm 0.000 80.00 8. 000 . 950 0. 00 TOTAL 0. 000 76. 84 7. 569 1 . 020 1.47 48 60: 20: 20 +12.7 mm HMB 1. 447 70. 76 7. 504 1. 078 3. 17 12.7 X 0.6 mm HMC 1.695 80.36 7. 499 .948 . 38 - 0.6 mm 0. 888 80. 00 8.000 . 920 8. 00 TOTAL 0. 000 76. 61 7.573 .994 1. 42 41 70: 10: 28 +12.7 mm HMB 1. 453 71. 17 7.500 1. 051 3. 28 12.7 X 0.6 mm HMC 1. 733 79.38 7.499 .922 . 16 -0.6 mm 0. 000 80.00 8.000 . 890 0. 00 TOTAL 0. 000 76.37 7. 574 .966 1. 37 42 80: 0: 20 +12.7 mm HMB 1. 459 71. 70 7.580 1. 031 3. 65 12.7 X 0.6 mm HMC 1.789 78.42 7.499 . 988 . 82 - 0.6 mm 0. 000 80.00 8. 000 .868 8.00 TOTAL 0. 000 76. 17 7. 578 . 942 1. 36 43 io: 0: 90 +12.7 mm HMB 1.365 66. 72 7.500 1.832 2. 66 12.7 X 0.6 mm HMC 1. 890 90. 58 7.472 1.819 . 05 - 0.6 mm 0. 000 80. 00 8.000 1.778 0. 00 TOTAL 8. 000 78.75 7. 546 1.819 1. 20 44 e: 10: 90 +12.7 mm HMB 1.364 66.02 7. 501 1. 831 2. 17 12.7 X 0.6 mm HMC 1.745 91. 73 7.500 1.819 . 28 - 0.6 mm 0 . 000 80. 00 8. 800 1. 888 0.00 TOTAL 0. 000 78. 84 7. 555 1. 822 1 . 10 45 o: 90: 10 +12.7 mm HMB 1.431 68.01 7. 498 1 . 883 1 . 79 12.7 X 0.6 mm HMC 1.523 84. 24 7.500 .932 . 03 - 0.6 mm 0. 000 80. 00 8.000 1 . 000 0 . 00 TOTAL 0. 000 76.90 7. 551 1. 029 .81 46 10: 80: IO +12.7 mm HMB 1.433 68.07 7. 500 1. 061 1 . 60 12.7 X 0.6 mm HMC 1. 539 83. 47 7. 500 . 953 . 09 - 0.6 mm 0. 000 80. 00 8. 880 .970 0. 00 TOTAL 0. 000 76. 65 7. 554 1 . 002 . 74 47 20: 78: 18 +12.7 mm HMB 1. 436 63. 25 7. 500 1. 038 1.51 12.7 X 0.6 mm HMC 1.556 82.70 7. 500 .932 . 15 - 8.6 mm 0. 000 80. 00 8. 000 . 940 8. 00 TOTAL 0. 000 76. 45 7. 558 . 977 . 72 48 30: 60: 10 +12.7 mm HMB 1.439 68.39 7. 504 1.011 1. 38 12.7 X 8.6 mm HMC 1.577 81 . 92 7. 500 .903 . 28 - 8.6 mm 8. 000 80. 00 8. 000 .910 0. 00 TOTAL 0 . 000 76. 22 7. 563 . 950 . 69 49 60: 30: 10 +12.7 mm HMB 1 .451 69. 07 7. 583 . 920 1.19 12.7 X 8.6 mm HMC 1.660 79. 64 7. 583 . 836 . 39 - 8.6 mm 0. 000 80. OO 8. 808 . 820 0 . 08 TOTAL 0.000 75. 66 7. 574 . 366 . 67 The Coal Blending Model Pg 117 ID CD CD CO 00 CD CO rt CO CD CO co *—« CD in CM 'v0 CD Tf T-4 CD CD CD CD CD CD CO CD CD CO CM 00 CD CO CM CM CD CO CM CO CD CO rt TH CD co CD CD CD CD CD CD CD CD T-H CD T-H CD T-H CD CD T-H CD i CD CD 1 CD CD ON CD IV CO CD CO CO •M- CD CD CD rv -rH rv CD CD CO T-H CD rt IV CD IV CM in 00 rv in in in ON rv 00 CO CM ON T"H ON CO CO 00 CO T-H ON T-H CD CD rt ON CD T-H CO rv IV rv CO CO 00 CO CO ON CO CO iv CO 03 rv rv CO in CO CO CO ON CO ON ON CD CN CD CD CD CD CD CO CD CD CD •vi• CD CO CD CO T-H CD CD CO CD ON CD 00 CS CD CD T-t CD 0"* CD CO CD CD CD CO CD CD CD ce CD CD CD rv CD CD CD rv CD ON CD CO CD CD CD in in •st CD in in m CD in in m CD in tn m CD in m LO CD in in rt CD in in in CD in rv CO rv (V IV CO rv IV IV CO rv rv IV CO rv IV rv CO IV IV IV CO IV IV iv CO rv T-H CD cr. 0N CD CO CO CO CD co •vt CD in CO 00 CD in 00 rt CD rt in CO CD ON CO CO CD CD IV rt CD CO in TH CD CD rt rv CD rt ON IV CD CM in CM CD CD •st CO CD CO CD CO CD in 00 CD CD in CO T-H CD CO CN CO CD in ON IV CD in ON in CD Ti• CO CO CD in |V CO IV CO CO CO IV CO CO CO rv CO iv CO IV CO IV CO rv CO iv CO r• CO CO CO rv CD m CD CD CO m CD CD CM ON CD CD CO m CD CD CO co CD CD 00 CM CD es Tf CO CD CD IV 00 CD CD rt CM CD CD rt ON CD CD m ON CD CD co CO CD CD CO CO CD CD co -—i CD CD rt IV CD CD CO CD CD Tl" in CD CD CO CD CD Tj- rv CD CD Tt IV CD CD rt in CD CD' T-H r« CD CD T-H T-H CD CD r4 CD CD T-H CD CD T-H CD CD TH CD CD T-H T-H CD CD m u m o o o o o o z: z: z: z: z. z: z: z: z: z: z: z: X X X X X X X X X X X X X X £ £ £ £ £ £ £ £ £ £ £ £ CO CO CO CO CO CO CO £ m £ • £ • • £ > £ • £ • £ CD £ £ CD £ £ CD £ £ CD £ £ CD £ £ CD £ £ CD £ £ £ £ £ £ £ £ rv X _J rv X _J IV X _l IV X _i IV X _l rv X _l IV X _J • CO cc • CO cc « CO CC > CO cc > CO CC • CO CC > CO cc CM rv • 1- CM IV 1- CM IV m 1— CM rv • «1 - CM IV • I— CM iv • 1- CM rv > 1— T-H CD o TH • CD o • CD o —* • CD o T-H CD o T-H • CD o T-l • CD o + CM 1— + CM 1— + CM —t + CM 1- + CM 1- + CM 1— + CM I— T-H 1 T-H I T-H 1 T-H 1 T-H 1 T-H 1 T-H 1 (9 CD CD CD CD CD OD *H T-H *-H T-H #_ •mm mm aB mu CD CD CD CD CD CD CD in CM T-H CD « ,, CD CD CD CD CD CD CD in rt CO CD ON IV T-H CD —« CM CO rt in CO in in in in in in in 57 8: 8:188 +12.7 mm HUB 1.361 63. 59 7. 503 1.900 .88 12.7 X 0.6 mm HMC 1 .890 92. 42 7.443 1.943 -.01 - 0.6 mm 0. 000 88-. 88 8.000 1. 900 0. 88 TOTAL 0. 000 77.93 7. 532 1.919 -.00 58 18: 98: 0 +12.7 mm HMB 1.436 66. 53 7. 500 .918 -.22 12.7 X 0.6 mm HMC 1.526 82. 59 7.500 . 868 . 04 - 0.6 mm 0. 000 88. 88 8. 800 . 870 0. 80 TOTAL 0. 000 75. 65 7. 554 . 889 -.85 59 90: 10: 0 +12.7 mm HMB 1.473 68. 74 7. 501 . 639 -.47 12.7 X 0.6 mm HMC 1. 733 76. 28 7.503 .648 . 16 - 0.6 mm 0. 000 80. 00 8. 800 .630 0. 00 TOTAL 0. 000 74. 15 7. 582 . 6*38 -.87 68 88: 20: 0 +12.7 mm HMB 1 . 466 68. 20 7.502 . 675 -.66 12.7 X 0.6 mm HMC 1. 696 77. 14 7.505 . 677 . 29 - 8.6 mm 0. 000 80. 00 8. 888 . 668 O. 88 TOTAL 0. 000 74. 32 7. 588 . 674 -.09 61 20: 88: 0 +12.7 mm HMB 1. 439 66. 61 7.585 . 888 -.41 12.7 X 8.6 mm HMC 1. 541 81 . 83 7. 500 . 838 .09 - 8.6 mm 0. 000 80.00 8. 880 .848 0. 00 TOTAL 0. 000 75. 41 7.559 .859 -.11 62 70: 30: 0 +12.7 mm HMB 1.459 67. 69 7.50O .716 -.83 12.7 X 0.6 mm HMC 1. 661 73. 84 7. 503 . 704 .37 - 0.6 mm 0. 000 88. 00 8. 800 . 690 0. 00 TOTAL 0. 000 74. 48 7. 576 . 707 -.11 63 30: 70: 0 +12.7 mm HMB 1. 442 66. 72 7. 500 . 859 -.57 12.7 X 0.6 mm HMC 1.553 81 . 06 7. 580 .312 . 14 - 0.6 mm 0. 000 80. 00 8. 000 .810 0. 00 TOTAL 0. 000 75. 19 7. 561 . 831 -. 14 Type # Seam Hame Size Fraction C UNIT '/. Weight y. Mini mum y. Maximum 1 Coal fl +12.7 mm HMB 35. 00 0 48 12.7 X 0.6 mm HMC 48.25 - 0.6"mm 16. 75 2 CoalC +12.7 mm HMB 42. 28 0 •48 12.7 X 0.6 mm HMC 47. 68 -0.6mm 18. 28 .3 Coal D +12.7 mm HMB 45.58 50 30 12.7 X 0.6 mm HMC 43. 58 - 0.6 mm 11. 88 CIean Coal fish = 7. 59 Sulfur minimum = 0. 00 Maximum = 2.40 Specific Gravity min. - 1.20 Maximum = 2. 00 The Step Size = 5. 00 SI2E CLEANING MODEL MODEL MODEL MODEL MODEL # T1.T2.T3 FRACTION UNIT S. G. YIELD ASH SULFUR FACTOR 100:8:0 +12.7 mm HMB 1. 483 69. 53 7.586 . 596 ZERO 12.7 X 0.6 mm HMC 1. 782 75. 24 7.499 .611 ZERO ' - 0.6 mm 8. 888 86. 66 8. 866 . 688 ZERO TOTAL 8. 888 74.64 7. 596 . 684 ZERO 0:100:0 +12.7 mm HMB 1 . 434 66. 45 7.588 . 947 ZERO 12.7 X 0.6 mm HMC 1 .513 83. 38 7. 506 . 894 ZERO - 0.6 mm 0. 000 88. 68 8.000 . 968 ZERO TOTAL 0. 000 75. 89 7.554 .914 ZERO 0:0:100 +12.7 mm HMB 1.361 63. 59 7. 503 1. 986 ZERO 12.7 X 0.6 mm HMC 1 . 891 92.42 7. 443 1 .949 ZERO - 0.6 mm 8. 888 86. 66 8. 688 1. 988 ZERO TOTAL 8. 868 77. 94 7.528 1. 925 ZERO 1 28: 15: 65 +12.7 mm HMB 1. 387 75. 17 7. 502 1 . 647 9. 93 12.7 X 0.6 mm HMC 1.712 87. 62 7. 500 1.517 .31 - 0.6 mm 0. 000 86. 88 8. 888 1 .490 6. 60 TOTAL 0. 000 81.36 7. 561 1 . 569 4.51 2 35: 0: 65 +12.7 mm HMB 1.410 75.98 7.502 1. 643 10. 45 12.7 X 0.6 mm HMC 1 .828 86. 88 7.496 1. 505 . 08 -0.6 mm 0. 888 86. 86 8.886 1. 445 O. 00 TOTAL 8. 880 81. 06 7. 564 1. 555 4. 49 3 25: 10: 65 +12.7 mm HMB 1. 390 75. 34 7. 495 1. 645 10. 03 12.7 X 0.6 mm HMC 1. 739 87. 11 7. 586 1.511 . 23 - 0.6 mm 0. 000 86. 80 8. 888 1. 475 0. 00 TOTAL 0. 000 81. 22 7.568 1.56*3 4. 47 4 30: 0: 70 +12.7 mm HMB 1. 384 75. 50 7.581 1. 684 10. 24 12.7 X 0.6 mm HMC 1. 838 86. 98 7. 498 1 . 569 . 08 - 0.6 mm 0. 688 88. 68 8. 868 1.510 8. 88 TOTAL 8. 868 81. 23 7.563 1.610 4. 46 5 30: 5: 65 +12.7 mm HMB 1 . 399 75. 57 7. 499 1. 644 10. 1 1 12.7 X 0.6 mm HMC 1 . 773 86. 59 7. 499 1.506 . 16 - 0.6 mm 8. 868 88. 88 8. 688 1. 460 0. 60 TOTAL 6. 600 81. 18 7. 563 1. 558 4. 44 6 15: 20: 65 +12.7 mm HMB 1. 383 74. 58 7. 563 1. 655 9. 53 12.7 X 0.6 mm HMC 1. 692 88. 12 7. 581 1 .517 • jb - 8.6 mm 0. 000 88. 68 8. 666 1 . 505 0 . 60 TOTAL 0. 000 .81.31 7. 568 1 .575 4. 37 7 25: 15: 60 +12.7 mm HMB 1.411 75. 18 7. 497 1.604 9. 78 12.7 X 0.6 mm HMC 1.713 86.72 7. 582 1. 450 .29 - 0.6 mm 0. 000 86. 00 8. 000 1. 425 0. 00 TOTAL 0. OOO 81.00 7.561 1 .512 4. 35 8 18: 30: €0 +12.7 mm HMB 1.389 74. 47 7. 562 1 .615 9. 37 12.7 X 0.6 mm HMC 1.651 88. 12 7. 584 1. 464 . 33 - 0.6 mm 8. 868 88.86 8. 800 1 . 470 0. 00 TOTAL 8. 868 81.27 7. 559 1 . 536 4. 34 9 20: 20: 60 +12.7 mm HMB 1.484 74.89 7. 500 1. 60S 9. 53 12.7 X 0.6 mm HMC 1.692 87.21 7. 500 1. 456 . 35 - 0.6 mm 8. 888 80.00 8. 888 1. 440 0. 00 TOTAL 8. 868 81. 08 7. 560 1.518 4. 33 18 15: 25: 60 +12.7 mm HMB 1. 392 74. 62 7. 496 1.613 9. 38 12.7 X 0.;6 mm HMC 1. 672 87. 78 7. 500 1. 457 . 40 - 0.6 mm 6. 868 88. 88 8. 000 1. 455 0. 00 TOTAL 6.868 81. 16 7. 557 1. 524 4. 32 11 30: 10: 60 +12.7 mm HMB 1.415 75.38 7.496 1. 668 9. 78 12.7 X 0.6 mm HMC 1.739 86. 28 7.500 1.452 .22 - 0.6 mm 8.888 88.88 8. 888 1.416 0. 00 TOTAL 8.888 88.87 7. 561 1.569 4.31 12 35: 5: 60 +12.7 mm HMB 1.418 75. 63 7. 501 1. 591 9. 90 12.7 X 0.6 mm HMC 1.771 85.78 7. -499 1. 446 . 15 - 0.6 mm 0. 000 88. 60 8. 000 1.395 0. 00 TOTAL 0. 000 88.77 7. 565 1.500 4. 38 13 5: 35: 60 +12.7 mm HMB 1. 386 74.23 7. 505 1.617 9. 25 12.7 X 0.6 mm HMC 1. 631 88. 51 7.500 1. 466 . 33 - O.6 mm 8. 688 80. 66 8. 000 1. 435 0. 80 TOTAL 8. 860 81.31 7. 557 1 . 534 4. 29 14 40: 0: 60 +12.7 mm HMB 1.421 75. 83 7. 498 1. 591 10. 03 12.7 X 0.6 mm HMC 1.814 85. 19 7. 497 1. 445 . 07 - 0.6 mm 8. 888 38. 88 8. 000 1. 336 0. 00 TOTAL 0. 000 88. 64 7. 564 1. 496 4. 26 The Coal Blending Model Pg 123 APPENDIX E: Coal Blending Model Results: Example Problem Three The Coal Blending Model Pg 124 £ 3 £ •r- © CO X CD CO CD <= 5 £ ••- CD CO CO C - r— ZZ .\" «-> II II c o £ £ £ £ £ £ •p«->- u CO CO CD rt) £ £ • £ > x x i. £ CO £ £ CO £ CO £ . it) rt) li. £ £ £ |V X |V X iv X Ol • CO • CO • CO CO CO CO CO N CM IV • CM IN. m CM |V • CO rf CM CO -r- rl • CO • CO CO co + CM + CM + CM —i in 1 1 rH 1 0> s rt) z II II x ii £ Si £ > Ol Ort)l CC m o X £ rt) N to >— r— r— c — rt) — C o rt)o rt)o rt) •- U CO o o o 0 £ O u Q. c •r- Ol * C 3 — 01 Of CM CO rt) cc: _l o LU i- O o o o o o o O o o O o « o 0. Ct. 0. ct 0. Cn Ct. cn cm cn oc cn o cc Ul LU LU Ul LU Ul Ul Ul Ul Ul LU LU N rsi N rvi (\l N INI iM f\l N M cn CO t CO CO VO CO VD CD CM CO CM _I LO rt CD CO r- rv CD vo rt CO CO CO VO VO vo vo rt •vr •vt -st ON ON ON ON _l o —H t «-< -c to CO VO CD cr. CD CO CO CD IO CO CO CO _i z CD CM CD CO CD vo CO CD ON CO CO CO LU to CO h- CO CO CD IV. CO cr> ON CO CO CO cc O« OS IV. CO cr. 00 ON CO CO cr. ON ON CO CO CD VO LO Cr> CO 0> VD IO CD —H _l (=) IV CD VO CO 00 CD CM VO IV- CD ON LU _l a LU LO VO CD vo CD CO CO CO rt 00 CO o r-i IV- r-. CO r- IO CO CO VO IV- CO CO CO > fs. co CO co CO CM CD CD 0N rt CD CO _l • LO CD CD CD CO CTv CD CD CO LO CD CD LU L3 VO OS CO CD •vt CO CO CD LO VO CO CO «O to —« CD CO —H CD CO CD CO -C (J z t—1 1- z l-H m o m o m o cc z E: IC LU I z X z X X _l O £ £ £ £ Z vo vo co UJ o « £ £ • ISJ CD £ £ CD• £ £ CD £ 1- £ £ £ to u X _J (V- X _J IV. X _J cc « VO cc • CD CC CO CC Ct. CM rv. 1- CM |v- 1- CM• IV. 1— u. —4 CO• o • CD o —-4 • CO• o + CM• 1- + CM t- + CM 1— —-4 1 1 1 CO CO CD CO >> CO CO CO --4 CM CD a. 1- CD CO • • CD • > • > —-i CO CO 1- 1 40: 25: 35 +12.7 mm HMB 1.489 68. 14 9. 000 1 . 106 1. 49 12.7 X 0.6 mm HMC 1.898 83. 36 8.982 . 926 1. 03 - 0.6 mm 8. 888 86.88 9.666 . 985 0. 60 TOTAL 8.800 76.31 8.992 1. 002 1. 15 2 45: 25: 30 +12.7 mm HMB 1.498 68. 25 9. 681 1.097 1. 63 12.7 X 0.6 mm HMC 1.898 82. 47 8. 848 . 906 .86 - 8.6 mm 8. 800 86. 00 9.686 . 898 8. 88 TOTAL 0. 000 76.01 8.933 . 987 1.11 3 35: 30: 35 +12.7 mm HMB 1. 479 66. 55 9. 001 1. 154 1. 36 12.7 X 0.6 mm HMC 1.827 83. 69 8. 998 . 958 1. 62 - 0.6 mm 8. 880 88. 66 9. 686 . 945 6. 66 TOTAL 8.888 75. 57 9. 888 1 . 644 1 . 68 4 35: 25: 40 +12.7 mm HMB 1.485 68. 67 9. 664 1.114 1. 46 12.7 X 0.6 mm HMC 1 .881 83. 95 8. 996 . 936 . 99 - 0.6 mm 8. 888 88. 86 9. 668 .928 6. 68 TOTAL 8. 888 76. 49 9. 866 1.612 1.07 5 40: 30: 30 +12.7 mm HMB 1. 481 66.63 9. 863 1. 147 1.47 12.7 X 0.6 mm HMC 1. 898 82. 88 8. 982 . .946 .91 - 0.6 mm 8. 688 88. 88 9. 866 . 936 0. 00 TOTAL 8. 688 75. 36 8.959 1. 031 1. 07 6 40: 20: 40 +12.7 mm HMB 1.508 69.52 9.000 1.053 1.33 12.7 X 0.6 mm HMC 1.815 83. 66 8. 997 . 902 1.07 - 0.6 mm 6. 888 86. 88 9. OOO .888 0. 00 TOTAL 8. 668 77. 16 8.998 . 963 1. 07 7 45: 20: 35 +12.7 mm HMB 1.514 69. 52 9. 002 1.843 1.35 12.7 X 0.6 mm HMC 1.898 82. 96 8.938 . 888 1. 04 - 0.6 mm 6. 888 86. 68 9. 000 . 865 0. 66 TOTAL 8. 868 76. 89 8. 973 . 951 1. 06 8 45: 30: 25 +12.7 mm HMB 1.484 66.76 9. 005 1. 139 1. 64 12.7 X 0.6 mm HMC 1.390 81.96 8. 751 . 924 . 68 - 0.6 mm 0. 000 80.00 9. 000 .915 0. 00 TOTAL 0. 000 75.01 8.894 1.018 1.04 9 50: 25: 25 +12.7 mm HMB 1. 508 68.26 9. 000 1. 087 1.66 12.7 X 0.6 mm HMC 1.890 81. 58 8. 701 . 886 . 66 - 0.6 mm 0. 000 80. 00 9. 000 . 875 0. 00 TOTAL 0.000 75. 66 8.868 . 971 1.03 10 35: 20: 45 +12.7 mm HMB 1.500 69.52 9. 002 1. 865 1. 33 12.7 X 0.6 mm HMC 1.785 84.21 8. 999 .916 . 96 - 0.6 mm 0. 000 80.00 9. 000 . 895 0. 00 TOTAL 0. 000 77.37 9. 008 . 978 1. 02 11 50: 30: 20 +12.7 mm HMB 1.489 66.88 9. 001 1. 133 1.79 12.7 X 0.6 mm HMC 1.890 81. 06 8.605 . 985 .48 - 0.6 mm 0. 000 80. 00 9. 000 . 988 0. 00 TOTAL 0. 000 74. 72 8. 829 1 . 004 1.82 12 35: 35: 30 +12.7 mm HMB 1. 474 65. 02 9. 000 1. 193 1. 26 12.7 X 0.6 mm HMC 1.890 83. 30 8.954 . 979 . 95 - 0.6 mm 0. 000 80.00 9.000 . 970 8. 8@ TOTAL 0. 000 74. 56 8. 981 1. 876 1. 80 13 55: 30: 15 +12.7 mm HMB 1.497 66.98 9. 001 1. 126 1. 92 12.7 X 0.6 mm HMC 1.890 80. 14 8. 455 . 884 . 25 - 0.6 mm 0. 000 80. 00 9. 000 . 885 0. 00 TOTAL 0. 000 74. 40 8.763 . 989 . 97 14 40: 35: 25 +12.7 mm HMB 1.476 65. 12 9. 001 1 . 185 1 . 39 12.7 X 0.6 mm HMC 1. 890 32. 37 8. 884 . 959 . 72 - 0.6 mm 0. 000 80. 00 9. 000 . 955 0. 00 TOTAL 0. 000 74.26 8.917 1. 861 . 96 15 30! 30: 40 +12.7 mm HMB 1 .477 66. 45 9. 003 1. 163 1 . 23 12.7 X 0.6 mm HMC 1. 788 84. 24 8.999 . 972 . 88 - 0.6 mm 8. 000 80.00 9. 000 . 960 0. 00 TOTAL 0. 000 75. 71 9. 001 1.057 . 96 16 30: 25: 45 +12.7 mm HMB 1.482 67. 93 9. 004 1. 123 1. 25 12.7 X 0.6 mm HMC 1.775 84. 52 8. 999 . 947 . 87 - O.6 mm 0. 808 88. 00 9. 000 . 935 8. 86 TOTAL 8. 880 76. 64 9. 881 1. 024 . 96 17 30: 20: 50 +12.7 mm HMB 1 . 491 69. 48 9. 662 1. 073 1.27 12.7 X 0.6 mm HMC 1. 762 84. 79 8. 999 . 932 . 86 - 0.6 mm 0. 000 88. 88 9. 668 .910 0. 00 TOTAL 8. 000 77. 57 9. 661 . 991 . 96 18 30: 35: 35 +12.7 mm HMB 1. 472 64.97 9.886 1. 198 1. 16 12.7 X 0.6 mm HMC 1.886 83. 98 8. 999 .998 . 93 - 0.6 mm 8. 868 86. 60 9. 668 . 985 6. 88 TOTAL 0. 688 74. 77 9. 000 1 . 885 . 95 19 50- 20: 30 +12.7 mm HMB 1.518 69. 48 9.882 1 . 832 1. 32 12.7 X 0.6 mm HMC 1. 898 82. 08 8. 790 . 872 . 83 - 8.6 mm 8. 686 80. 00 9. 000 .858 0 . 08 TOTAL 8. 860 76.51 8. 986 . 936 . 95 28 30: 40: 30 +12.7 mm HMB 1.469 63. 58 9.O04 1. 227 1.13 12.7 X 8.6 mm HMC 1.857 83.69 8. 999 1.014 . 94 - 0.6 mm 0. 000 80.00 9. 006 1.010 8. 08 TOTAL 0. 000 73. 84 9. 002 1.113 . 95 21 45: Ts:' 48 + 12. 7 'mi*. HMB " 1.521 70. 76 9. 006 991 .97 12.7 X 0.6 mm HMC 1. 852 83.37 8. 999 . 871 1.15 - 0.6 mm 0. 808 86. 00 9. 660 . 848 0. 00 TOTAL 0. 000 77. 70 9.000 .917 . 94 22 45: 35: 20 +12.7 mm HMB 1. 478 65.20 9. 000 1. 178 1.51 12.7 X 0.6 mm HMC 1.890 31.45 8. 664 . 940 .51 - 0.6 mm 0. 000 80. 00 9.000 .940 0. 00 TOTAL 0. 000 73. 95 8. 857 1.047 . 92 23 55: 25: 20 +12.7 mm HMB 1.514 68.22 9. 003 1. 076 1. 65 12.7 X 0.6 mm HMC 1.890 80. 69 8.559 . 867 . 45 - 0.6 mm 0. 000 80. 00 9.000 . 860 0. 00 TOTAL 0. 000 75.29 8.806 . 955 .92 24 50: 35: 15 +12.7 mm HMB 1. 480 65. 37 9. 003 1. 174 1 . 73 12.7 X 0.6 mm HMC 1.890 80. 52 8.504 . 920 . 29 - 0.6 mm 0. 000 80. 00 9. 888 . 925 0. 00 TOTAL 0. 000 73.69 8.789 1.034 . 92 25 40: 15: 45 +12.7 mm HMB 1.518 70.78 9. 001 1 . 001 . 99 12.7 X 0.6 mm HMC 1. 797 83. 93 8.998 .887 1. 05 - 0.6 mm 0. 000 88. 00 9. 000 . 855 0. 00 TOTAL 0. 000 77. 93 8. 999 . 931 .91 26 35: 40: 25 +12.7 mm HMB 1 . 470 63. 60 9. 000 1. 227 1 . 20 12.7 X 0.6 mm HMC 1.890 82. 81 3. 866 .995 • 77 - 0.6 mm 0. 000 80. 00 9. 000 . 995 0. 00 TOTAL 0. 000 73. 54 8. 944 1 . 103 .91 27 55: 35: 10 +12.7 mm HMB 1. 484 65.50 9.005 1. 168 1. 90 12.7 X 0.6 mm HMC 1. 890 79.60 8. 346 . 903 . 08 - 0.6 mm 0. 000 80.00 9.000 .910 0. 00 TOTAL 0. 000 73. 41 8. 722 1. 021 . 90 28 60: 30: 10 +12.7 mm HMB 1 . 506 66. 98 8. 995 1.117 1 . 96 12.7 X 0.6 mm HMC 1.890 79. 26 8. 304 . 864 . 87 -0.6mm 0. 000 80. 80 9. 000 . 878 0 . 00 TOTAL 0. 000 74.07 8.695 . 974 . 89 29 25: 38: 45 +12.7 mm HMB 1. 475 66. 39 9. 000 1 . 170 1 . 13 12.7 X 0.6 mm HMC 1.764 84. 83 8. 999 .981 . 78 - 0.6 mm 0. 000 80. 00 9. 000 . 975 0. 00 TOTAL 0. 000 75.89 9.000 1.066 . 87 30 40: 40: 20 +12.7 mm HMB 1. 472 63. 68 9. 000 1.220 1. 34 12.7 X 0.6 mm HMC 1.890 81. 85 8.711 . 980 . 54 - 0.6 mm 0. 000 80. 00 9. 000 . 980 0. 00 TOTAL 0. 000 73. 23 8. 879 1 . 091 . 87 31 50: 15: 35 +12.7 mm HMB 1.525 70. 75 8. 995 . 979 . 95 12.7 X 0.6 mm HMC 1.890 82. 55 8.878 . 852 .99 - 0.6 mm 0. 000 80. 00 9. 000 . 825 0. 00 TOTAL 0.000 77. 36 8. 942 . 901 . 86 32 35: 15: 50 +12.7 mm HMB 1.514 70. 77 9. 002 1.012 . 98 12.7 X 0.6 mm HMC 1.772 84. 48 8. 999 . 897 . 94 - 0.6 mm 0. 000 80. 00 9. 000 .870 0. 00 TOTAL 0. 000 78. 14 9.000 .942 . 86 33 25: 40: 35 +12.7 mm HMB 1.467 63. 53 9.001 1.233 1. S3 12.7 X 0.6 mm HMC 1. 793 84. 31 8. 999 1. 027 . 84 - 0.6 mm 0. 000 80. 00 9. 000 1. 025 0. 00 TOTAL 0.000 74. 01 9. 000 1. 124 . 86 34 25: 25: 50 +12.7 mm HMB 1. 479 67. 84 9. 001 1.131 1.13 12.7 X 0.6 mm HMC 1. 753 85. 08 9. 008 . 961 . 76 - 0.6 mm 0. 008 80. OO 9. 000 . 950 0. 80 TOTAL 8. 800 76. 80 9. 008 1. 036 . 86 35 25: 20: 55 +12.7 mm HMB 1. 436 69. 36 9. 004 1. 082 1.14 12.7 X 0.6 mm HMC 1. 742 85. 34 9. 008 . 941 . 74 - 0.6 mm 0. 000 80. 88 9. 008 . 925 0. 00 TOTAL 8. 000 77. 73 9. 002 1 . 081 . 85 36 55: 28: 25 +12.7 mm HUB 1. 522 69. 47 9. 001 1. 022 1. 32 12.7 X 0.6 mm HMC 1. 898 81 . 20 8. 652 . 852 .62 - 0.6 mm 0. 000 80.00 9. 000 . 835 6. 60 TOTAL 8. 000 76. 15 8.844 .921 .85 37 25: 35: 48 +12.7 mm HMB 1.471 64. 90 9. 000 1.208 1. 65 12.7 X 0.6 mm HMC 1.778 84. 57 8.999 1. 004 .81 - 0.6 mm 0. 000 80. 00 9. 000 1 . 006 0. 06 TOTAL 0. 000 74. 93 8. 999 1. 695 . 85 38 60: 25: 15 +12.7 mm HMB 1.519 68. 22 9. 002 1 . 869 1. 67 12.7 X 0.6 mm HMC 1. 898 79.88 8. 487 .846 .25 - 0.6 mm 8. 000 88. 86 9. 000 . 845 0. 00 TOTAL 0. 000 74. 94 8. 738 . 94*6 . 83 39 45: 40: 15 +12.7 mm HMB 1. 474 63. 76 9. 004 1.215 1 . 47 12.7 X 0.6 mm ' HMC 1. 898 86. 91 8. 556 .959 .32 - 0.6 mm 8. 000 86. 88 9. 086 . 965 0 . 00 TOTAL 0. 000 72. 93 8.816 1.677 . 83 48 25: 45: 30 +12.7 mm HMB 1. 464 62. 14 8. 998 1. 263 . 94 12.7 X 0.6 mm HMC 1.813 84.88 8. 997 1. 853 . 85 - 0.6 mm 0. 000 86. 88 9. 886 1.056 0 . 80 TOTAL 8. 000 73.64 .8.998 1. 154 .82 41 30: 45: 25 +12.7 mm HMB 1. 465 62. 13 8. 998 1. 258 . 99 12.7 X 0.6 mm HMC 1. 898- 83. 22 3.914 1. 040 . 79 - 0.6 mm 8. 800 80. 00 9. 066 1. 035 0. 00 TOTAL 8. 068 72. 78 8. 964 1. 144 . 32 42 30: 15: 55 +12.7 mm HMB 1. 583 78. 77 3. 995 1 . 626 . 99 12.7 X 0.6 mm HMC 1.752 85. 03 9. 066 . 969 . 33 - 0.6 mm 6. 600 80. 00 9. 000 • S 8 5 0 . 68 TOTAL 0. 000 78. 36 8. 998 . 956 . 81 The Coal Blending Model Pg 132 T-H CO © © cr. IO © © 00 rv © ON © CO © OT rt ON © 00 CD © © 00 CD © © rv CO T-H © CO OTC O © CO a-. LO © IV CO TH © rv © CO © IV IO © IV Ct. CO © rv TH © © TH © TH © TH © TH © © CO © © rv rt © LO rt CM T-H © ©. ON in ON CD CO © cr> CO ON © CO ON (V © OT T"H © CD cr. IV rv CO LO CM CM CO CM in TH IV CO CM © CO © CO in CO CO co 1-1 OT 0* CO CO CO CM © © T-H OJ © © T-H cr. CO CO 00 © ON ON ON CM ON cn © ON CO CO OT TH T-H — CD co © rt cr. ON © T-H © T-H © CD © 00 © ON TH in © 00 T-H CM © ON IV rt © CM CD CO © CO ON IV © ON © rv © © © ON © ON © ON © ON © © © rt cr. rt © 00 CD ON © ON Cr* ON © ON © rv © ON © ON © ON © ON © ON © © IV ON IV © 00 OS CO ON CO CO CO ON CO O- 00 ON OT ON 00 cr. co ON 00 cn CO ON OTO N 00 CO 00 ON 00 T-H CO © CO CO ON © ON T-H IV © ON CO © rv 00 LO © ON © rv © CM m T-H © T-H T4 © © CM CO CO © © CM CM © rt © co © rt 00 IO © LO CO ON © CO iv IV © © CM CO © CO © CO © CM CM CM © CM CM CO © CO © IO © 00 CO ON © CM © TH © IV (V CO CO IV CO CO CO rv CO CO 00 IV IV CO 00 rv IV 00 00 IV CD rv 00 rv iv 00 00 IV _, © © © © © © © CO © © © 00 CD © © T-H CM © © IO © © © 0- © © © CO o. © © CO ON © © CO ON © © CM © © © © CO © © rv ON © © CM ON © © LO CO © © CO © © rt CO © © LO CO © © m IV © © rt CO © © in 00 © © T-H © © T-H T-H © © T-H T-H © © T-H - © © TH T-H © © T-H T-H © © T-H T-H © © m o m o CJ m o n o m o o s: x zz ZZ X ZZ zz IZ zz X zz zz zz X X X X X X i. X X X X X X X £ £ £ £ £ £ £ £ £ £ £ £ £ £ CO CO co CO CO CO CO £ a £ a £ a £ a £ a £ a £ a £ © £ £ © £ £ © £ £ © £ £ © £ £ © £ © £ £ £ £ £ £ £ £ (v X _l IV X _l IV X _l IV X _i IV X _l IV X _J IV X _1 • CO X a CO X a co X a co X a CD X a CD X a CO X CM IV a f- CM IV a 1— CM rv a h- CM IV a h- CM rv a 1— CM IV a K- CM IV a 1- T-H • © o T-H a © o T-H a © O T-H a © O T-H © o T-H a © O T-. a © o + CM —I + CM t- + CM 1— + CM h- + CM 1— + CM 1— + CM 1- T-H T-H • 1 1 1 1 1 1 © IO © IO © © © CM CM rt CD T-H CO a. a. a. .a a. © © IO © in © in T-H LO rt T-T T-H rt T-H) .a .a a. • a mm © IO LO IO in © i.n. IO CM CO rt CM IO in CO rt LO CO rv CO ON rt rt rt rt rt rt rt 50 20! 25: 55 +12.7 mm HMB 1.477 67. 79 9. 005 1 . 139 1.06 12.7 X 0.6 mm HMC 1.732 85. 63 8.995 . 969 .62 - 0.6 mm 0. 000 80.00 9. 000 . 965 0.00 TOTAL 0. 000 76. 98 9. 000 1.045 . 77 51 20! 20: 60 +12.7 mm HMB 1.483 69. 28 9.005 1.091 1. 06 12.7 X 0.6 mm HMC 1.724 85.90 9. 000 .952 . 63 - 0.6 mm 0.000 80.00 9.000 . 940 0. 00 TOTAL 0. 000 77.90 9. 002 1.012 . 76 52 60: 20: 20 +12.7 mm HMB 1. 527 69.47 9.000 1.011 1. 33 12.7 X 0.6 mm HMC 1.890 80.33 8.503 . 833 .42 - 0.6 mm 0. 000 80. 00 9.000 . 820 0. 00 TOTAL 0. 000 75. 80 8. 776 . 905 • 76 53 40: 45: 15 +12.7 mm HMB 1.468 62.28 9. 003 1. 254 1. 26 12.7 X 0.6 mm HMC 1.890 81.31 8.612 1. O02 . 35 - 0.6 mm 0.000 80.00 9. 000 1 . 005 0. 06 TOTAL 0. 000 72. 19 8. 841 1. 121 . 76 54 55: 40: 5 +12.7 mm HMB 1.477 63.93 9.005 1.201 1 . 74 12.7 X 0.6 mm HMC 1.890 79.03 8.241 .919 -. 12 - 0.6 mm 0. 000 80.00 9.000 .935 0. 00 TOTAL 0. 000 72.33 8. 683 1. 049 . 76 55 20: 35! 45 +12.7 mm HMB 1.469 64.85 9. 000 1.207 . 96 12.7 X 0.6 mm HMC 1.754 85. 15 9. 000 1.017 . 68 - 0.6 mm 0. 000 80. 00 9.000 1.015 0. 00 TOTAL 0. 000 75. 10 9.000 1. 106 . 76 56 20: 40: 40 +12.7 mm HMB 1.466 63. 47 8. 999 1.241 . 92 12.7 X 0.6 mm HMC 1.766 84. 89 8. 999 1. 036 .71 - 0.6 mm 0. 000 80.00 9.000 1. 040 0. 00 TOTAL 0 . 000 74. 17 8. 999 1. 134 . 75 5? 20: 30: 50 +12.7 mm HMB 1.473 66. 25 9. 000 1. 173 .97 12.7 X 0.6 mm HMC 1.742 85. 40 9. 000 . 991 . 66 - 0.6 mm 0. 000 80. 00 9. 000 . 990 0. 00 TOTAL 0. 000 76. 03 9. 000 1. 075 . 75 58 65: 25: 10 +12.7 mm HMB 1. 523 68. 19 9. 001 1 . 060 1. 67 12.7 X 0.6 mm HMC 1. 890 78. 92 8. 253 . 828 . 05 - 0.6 mm 0. 000 80. 00 9. 000 . 830 0. 00 TOTAL 0. 000 74. 58 8. 669 . 925 . 74 59 40: 10: 50 +12.7 mm HMB 1. 524 72. 06 8. 998 . 943 . 59 12.7 X 0.6 mm HMC 1. 783 84. 19 8. 999 . 865 1. 03 - 0.6 mm 0. 000 80. 00 9. 000 . 830 0. 60 TOTAL 0. 000 78. 68 8. 999 . 893 . 73 60 20: 45: 35 +12.7 mm HMB 1.462 62. 11 8. 998 1. 271 . 85 12.7 X 0.6 mm " HMC 1.781 84. 61 8. 999 1.064 . 72 - 0.6 mm 0. 000 80. 00 9. 000 1. 065 0. 00 TOTAL 0. 000 73. 21 8. 998 1. 165 . 73 61 20: 50: 30 +12.7 mm HMB 1.459 60. 82 9. 000 1. 293 . 82 12.7 X 0.6 mm HMC 1.797 84. 34 8. 998 1.086 . 76 - 0.6 mm 0. 000 80. 00 9. 000 1.090 0. 00 TOTAL 0. 000 72. 28 8. 999 1. 189 . 73 62 30: 50: 20 +12.7 mm HMB 1. 461 60. 80 8. 998 1. 288 . 93 12.7 X 0.6 mm HMC 1. 890 82. 70 8. 824 1. 059 .61 - 0.6 mm 0. 000 80. 00 9. 000 1. 060 0. 00 TOTAL 0. 000 71. 74 8. 928 1. 170 . 72 63 20: 55: 25 +12.7 mm HMB 1. 456 59. 57 9. 003 1. 32b . 77 12.7 X 0.6 mm HMC 1. 827 84. 84 8. 998 1.119 . 78 - 0.6 mm 0. 000 80. 00 9. 000 1.115 0. 00 TOTAL 0. 000 71. 33 9. 001 1. 220 .71 64 45: 45: 10 +12.7 mm HMB 1.470 62.31 9. OOO 1. 245 1.36 12.7 X 0.6 mm HMC 1. 898 88. 36 8. 453 . 983 . 14 - 0.6 mm 0. 000 80. 08 9.000 .998 0. 00 TOTfiL 0. 000 71.88 8.774 1. 186 .71 65 55: 10: 35 +12.7 mm HMB 1. 535 72. 12 9.000 . 985 .61 12.7 X 0.6 mm HMC 1.898 82. 16 8.827 . 828 . 94 - 0.6 mm 0. 000 80.00 9.000 .785 0. 80 TOTfiL 8. 000 77. 86 8.928 . 849 . 70 66 20: 15: 65 +12.7 mm HMB 1. 491 70. 70 8.995 1. 846 . 92 12.7 X 0.6 mm HMC 1.717 86. 13 9. 884 . 933 .61 - 0.6 mm 0. 000 88. 88 9. 000 .915 0. 00 TOTfiL 0. 008 78. 76 9. 888 . 988 . 69 67 35: 10: 55 +12.7 mm HMB 1.521 72. 06 9. 000 . 959 . 62 12.7 X 0.6 mm HMC 1. 760 84. 72 9. 888 . 888 . 90 - 0.6 mm 0. 000 88. 88 9. 000 . 845 0. 00 TOTfiL 0. 000 78. 98 9. 880 .988 . 69 68 60: 15: 25 +12.7 mm HMB 1.533 78.78 8.998 .957 . 98 12.7 X 0.6 mm HMC 1. 898 88. 84 8. 598 .816 . 60 - 0.6 mm 0. 888 88. 00 9. 888 . 795 0. 00 TOTAL 8. 888 76. 65 8.815 . 878 . 68 69 15: 35: 50 +12.7 mm HMB 1. 468 64. 84 9. 882 1.214 . 98 12.7 X 0.6 mm HMC 1. 733 85. 74 9. 888 1. 021 . 57 - 0.6 mm 0. 000 80. 00 9. 000 1.030 0. 00 TOTAL 0. 880 75. 29 9. 081 1.113 . 68 78 25: 55: 20 +12.7 mm HMB 1. 457 59. 53 9. 882 1.315 .81 12.7 X 0.6 mm HMC 1. 898 83. 16 8. 884 1. 097 . 65 - 0.6 mm 8. 888 80. 00 9. 888 1 . 100 8. 80 TOTAL 6. 888 71. 04 8. 955 1. 206 . 68 71 35: 50: 15 +12.7 mm HMB 1.463 60. 85 8. 998 1. 281 1.04 12.7 X 0.6 mm HMC 1.890 81. 72 8. 665 1. 040 . 38 - 0.6 mm 0. 000 80. 00 9. 000 1. 045 0. 80 TOTAL 0. 000 71.44 8. 863 1 . 157 . 67 72 50: 5: 45 +12.7 mm HMB 1.537 73. 51 9. 003 . 858 . 23 12.7 X 0.6 mm HMC 1.827 83.37 8.998 . 825 1.21 - 0.6 mm 0. 000 80. 00 9. 000 . 775 0. 00 TOTAL 0. 000 79. 03 9. 000 . 831 . 67 73 15: 30: 55 +12.7 mm HMB 1.472 66. 22 9. 000 1. 179 .91 12.7 X 0.6 mm HMC 1. 723 85. 98 8.999 1 . 005 . 54 - 0.6 mm 0. 000 80. 00 9. 000 1 . 005 0. 00 TOTAL 0. 000 76. 21 9. 000 1. 086 . 67 74 15: 25: 60 +12.7 mm HMB 1. 475 67. 65 9. 000 1.141 . 90 12.7 X 0.6 mm ' HMC 1.716 86. 22 9. 002 . 981 . 53 - 0.6 mm 0. 000 80.00 9. 000 . 980 0. 00 TOTAL 0. 000 77. 13 9. 001 1. 053 . 66 75 15! 50: 35 +12.7 mm HMB 1. 458 60. 86 9. 001 1. 301 . 78 12.7 X 0.6 mm HMC 1. 769 84. 95 8. 999 1. 098 . 63 - 0.6 mm 0''. 000 80. 00 9. 000 1. 105 0. 00 TOTAL 0. 000 72. 47 9. 000 1. 199 . 66 76 30: 10: 60 +12.7 mm HMB 1 .517 72. 07 9.001 . 972 . 64 12.7 X 0.6 mm HMC 1. 742 85. 27 9. 000 . 890 . 82 - 0.6 mm 0. 000 30. 00 9. 000 . 860 0. 00 TOTAL 0. 000 79. 13 9. 000 . 921 . 66 77 65: 20: 15 +12.7 mm HMB 1.530 69. 47 8. 995 1 . 001 1. 34 12.7 X 0.6 mm HMC 1.890 79. 44 8. 356 .811 .21 - 0.6 mm 0. 000 80. 00 9. 000 . 805 0. 00 TOTAL 0. 000 75. 43 8. 708 . 888 . 65 78 15: 45: 40 +12.7 mm HMB 1.461 62. 10 8.998 1. 276 . 79 12.7 X 0.6 mm HMC 1. 755 85. 23 9. 668 1.672 .61 - 0.6 mm 0. 000 86.86 9.886 1 . 638 6. 60 TOTAL 0. 000 73. 40 8.999 1. 173 . 65 79 15: 40: 45 +12.7 mm HMB 1. 464 63. 42 8.997 1 . 248 . 82 12.7 X 0.6 mm HMC 1.742 85. 48 9.888 1 . 848 . 57 - 0.6 mm 0. 000 80.00 9.000 1.055 6. 68 TOTAL 0.000 74. 33 8.999 1 . 145 . 65 80 50: 45: 5 +12.7 mm HMB 1. 471 62.33 9. 000 1. 241 1. 44 12.7 X 0.6 mm HMC 1. 898 79. 40 8. 292 . 961 -.69 - 0.6 mm 8. 888 88. 88 9. 000 .975 8. 86 TOTAL 8. 888 71. 56 8. 787 1. 093 .65 81 15: 55: 30 +12.7 mm HMB 1. 455 59. 61 9.003 1. 328 . 73 12.7 X 0.6 mm HMC 1.784 84. 68 8.999 1. 128 . 66 - 0.6 mm 8. 800 88. 60 9. 006 1. 130 0 . 00 TOTAL 8.800 71.53 9.681 1.230 . 64 82 55: 5: 40 +12.7 mm HMB 1.541 73.56 9. 681 .843 .25 12.7 X 0.6 mm HMC 1. 898 82.64 8.915 . 866 1 . 12 - 0.6 mm 8. 000 88. 88 9.688 . 766 0. 00 TOTAL 8. 000 78. 73 8. 966 .814 . 64 83 15: 20: 65 +12.7 mm HMB 1.488 69. 14 9. 862 1 . 899 . 90 12.7 X 0.6 mm HMC 1. 709 86.43 8.999 . 966 . 49 - 0.6 mm 0. 000 86. 66 9. 000 . 955 8. 00 TOTAL 0. 000 78. 04 9. 666 1 . 624 . 63 84 20: 60: 20 + 12.7 mrn HMB 1. 453 58.32 9. 008 1 . 341 . 68 12.7 X 0.6 mm HMC 1. 898 83. 63 8. 945 1 . 142 . 69 - 0.6 mm 8. 608 86.86 9. 068 1 . 148 0. 60 TOTAL 0. 008 76. 32 8. 979 1 . 243 . 63 85 60: 10: 36 +12.7 mm HMB 1.540 72. 18 9. 001 .895 . 65 12.7 X 0.6 mm HMC 1.890 81. 33 8. 692 . 805 . 76 - 0.6 mm 0. 000 80. 00 9. 000 . 770 0. 00 TOTAL 0.000 77. 52 8. 857 . 836 . 62 86 45: 5: 50 +12.7 mm HMB 1.533 73.46 9.001 .874 . 22 12.7 X 0.6 mm HMC 1.792 83. 91 8.999 . 836 1.11 - 0.6 mm 0. 000 80. 00 9.000 . 790 0. 00 TOTAL 0. 000 79.24 9. 000 .845 .62 87 30: 55: 15 +12.7 mm HMB 1.458 59. 53 9. 001 1.315 . 88 12.7 X 0.6 mm HMC 1.890 82. 17 8. 725 1. 083 . 43 - 0.6 mm 0. 000 80. 00 9. 000 1.085 0. 80 TOTAL 0.000 70. 72 8. 891 1. 198 . 62 88 25: 10: 65 +12.7 mm HMB 1.514 72. 08 9. 001 . 983 . 67 12.7 X 0.6 mm HMC 1.725 85.81 9. 000 . 905 . 70 - 0.6 mm 0. 000 80. 00 9. 000 . 875 0. 00 TOTAL 0.000 79. 35 9. 001 . 934 .62 89 40: 56: 10 +12.7 mm HMB 1.464 60. 83 8. 998 1. 274 1 . 10 12.7 X 0.6 mm HMC 1.890 80. 75 8. 507 1. 024 . 16 - 0.6 mm 0. 000 80. 00 9. 000 1.030 0. 00 TOTAL 0. 000 71.11 8.800 1. 145 .61 98 15: 15: 70 +12.7 mm HMB 1.487 70. 65 9.003 1. 057 . 87 12.7 X 0.6 mm HMC 1.703 86. 65 8. 995 .945 . 47 - 0.6 mm 0. 000 80. 00 9.000 . 930 0. 80 TOTAL 0. 000 78.94 8 ."999 . 993 .61 91 15: 60: 25 +12.7 mm HMB 1 .452 58. 35 9. 000 1. 345 . 63 12.7 X 0.6 mm HMC 1.804 84. 39 8. 999 1. 154 . 68 - 0.6 mm 0. 000 80. 00 9. 000 1. 155 0. 00 TOTAL 0. 000 70.56 9. 000 1. 253 . 60 92 65: 15: 20 +12.7 mm HMB 1.538 70. 83 9. 000 . 941 1. 03 12.7 X 0.6 mm HMC 1.890 79. 96 8. 455 .796 .38 - 0.6 mm 0. 000 80. 00 9. 000 . 780 0. 80 TOTAL 0. 000 76. 30 8. 750 .852 . 66 93 70: 20: 18 +12.7 mm HMB 1.535 69. 50 8. 998 . 991 1. 38 12.7 X 0.6 mm HMC 1.890 78.58 8.205 . 796 . 62 - 0.6 mm 0.000 80. 00 9. 000 .790 0. 00 TOTAL 0.008 75. 10 8. 641 .874 . 58 94 10: 45: 45 +12.7 mm HMB 1. 460 62. 12 8.999 1.279 . 75 12.7 X 0.6 mm HMC 1.733 85. 84 9. 000 1.085 . 49 - 0.6 mm 0. 008 80. 00 9.000 1. 095 0. 68 TOTAL 0 . 000 73. 59 9. 000 1. 18} . 58 95 10: 40: 50 +12.7 mm HMB 1 .463 63. 43 8.997 1. 254 . 78 12.7 X 0.6 mm HMC 1.723 86. 07 8.999 1. 061 . 45 - 0.6 mm 0. 000 80. 00 9. 000 1. 070 0. 06 TOTAL 0. 000 74. 52 8.998 1. 155 . 58 96 15: 65: 20 +12.7 mm HMB 1. 449 57. 16 9. 000 1.371 . 56 12.7 X 0.6 mm HMC 1 .879 84. 09 8. 998 1. 190 .71 - 0.6 mm 0. 000 80. 00 9.000 1. 180 6. 00 TOTAL 0. 000 69. 60 8.999 1. 284 . 58 97 10: 35: 55 +12.7 mm HMB 1 . 466 64. 75 8. 999 1.222 . 78 12.7 X 0.6 mm HMC 1.715 86. 34 9.001 1.035 • 45 - 0.6 mm 0. 000 80. 00 9. 000 1. 045 0.00 TOTAL 0. 000 75. 45 9.000 1. 125 . 58 98 I©: 50: 40 +12.7 mm HMB 1 . 457 60. 86 9. 002 1. 307 .71 12.7 X 0.6 mm HMC 1. 744 85. 57 9. 000 1. 189 . 50 - 0.6 mm 0. 000 80. 00 9. 000 1. 120 0. 00 TOTAL 0. 000 72. 65 9. 001 1. 209 . 57 CO CM fv m Cn CO CM CD CM •r- (V in CO co cr> CM |V CM IV CO CO —* m CO •* M- rH CO CO .\" co cn CM J— 1—1 O m O m CJ «ZZ ZZ ZZ zz ZZ X X X X X X o