&EPA
United States
Environmental Protection
Agency
Industrial Environmental Research
Laboratory
Research Triangle Park NC 27711
EPA-600/7-79-204
August 1979
A Technique for
Predicting Fly Ash
Resistivity
Interagency
Energy/Environment
R&D Program Report
-------
RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
gories were established to facilitate further development and application of en-
vironmental technology. Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The nine series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
6. Scientific and Technical Assessment Reports (STAR)
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8. "Special" Reports
9. Miscellaneous Reports
This report has been assigned to the INTERAGENCY ENERGY-ENVIRONMENT
RESEARCH AND DEVELOPMENT series. Reports in this series result from the
effort funded under the 17-agency Federal Energy/Environment Research and
Development Program. These studies relate to EPA's mission to protect the public
health and welfare from adverse effects of pollutants associated with energy sys-
tems. The goal of the Program is to assure the rapid development of domestic
energy supplies in an environmentally-compatible manner by providing the nec-
essary environmental data and control technology. Investigations include analy-
ses of the transport of energy-related pollutants and their health and ecological
effects; assessments of, and development of, control technologies for energy
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EPA REVIEW NOTICE
This report has been reviewed by the participating Federal Agencies, and approved
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This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
-------
EPA-600/7-79-204
August 1979
A Technique for Predicting Fly Ash Resistivity
by
Roy E. Bickelhaupt
Southern Research Institute
2000 Ninth Avenue, South
Birmingham, Alabama 35205
Contract No. 68-02-2114
Program Element No. EHE624
EPA Project Officer: Leslie E. Sparks
Industrial Environmental Research Laboratory
Office of Energy, Minerals, and Industry
Research Triangle Park, NC 27711
Prepared for
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Research and Development
Washington, DC 20460
-------
ABSTRACT
The objective of the research reported herein was to develop
a technique for predicting the electrical resistivity of fly
ash from an as-received, ultimate coal analysis and the chemical
composition of the concomitant coal ash produced by simple labora-
tory ignition. This research was motivated by the obligatory
need to know this particulate property. The information is re-
quired or extremely useful for designing a dry-collecting electro-
static precipitator, for evaluating the quality of coal in an
unopened seam or field, and for blending coals to produce a de-
sired effect.
The electrical resistivity of fly ash is dependent on several
physical and chemical characteristics of the particulate and
the flue gas. Physically, the particle size distribution, specific
surface and ash layer porosity are important. Chemically impor-
tant are the alkali metals, alkaline earths and iron with respect
to the fly ash and the water and sulfur trioxide concentrations
in the flue gas. Since the technique for predicting resistivity
does not anticipate physical parameters, a large number of fly
ash samples were evaluated in this research to minimize variations
due to physical effects. The effects of fly ash chemical composi-
tion, ash layer field strength, and the water and sulfur trioxide
concentrations in the test environment were evaluated with respect
to electrical resistivity in the laboratory. Correlations were
established between resistivity and the evaluated parameters
for the entire temperature spectrum of interest. The research
became especially difficult when it was discovered that conven-
tional resistivity test apparatus and procedures were not appli-
cable to investigating the effect of sulfur trioxide on resis-
tivity. Suitable equipment and techniques were developed to
obtain the required data.
It was previously observed and reconfirmed in this work
that the chemical composition of fly ash and coal ash are similar
if the fly ash has a relatively low concentration of combustibles
and the coal ash has been ignited in air at a sufficiently high
temperature, J"1050°C. The coal ash chemical composition and
the flue gas analysis calculated from the stoichiometric combus-
tion of the coal were used to predict resistivity using the
aforementioned correlations.
111
-------
Predicted resistivity as a function of temperature was favor-
ably proof tested using data acquired from previous field evalua-
tions of precipitators at six power generating stations. The
proof test involved a comparison of predicted resistivity, labora-
tory measured resistivity, resistivity measured _in situ, precipi-
tator efficiency, and current density of the precipitator outlet
fields.
IV
-------
CONTENTS
Abstract iii
Figures. vi
Tables viii
Acknowledgements ix
SECTIONS
1. Introduction 1
2. Conclusions 3
3. Recommendations 4
4. Investigative Scope and Approach 6
5. Experimental Procedures 7
Fly Ash and Coal Characterization 7
Experimental Equipment and Procedures for
Resistivity Determination 7
6. Results 10
Fly Ash Characterization 10
Resistivity Data 10
Effect of Fly Ash Composition 10
Effect of Environmental Water Concentration.. 27
Effect of Applied Electrical Stress 32
Effect of Sulfur Trioxide 36
General Observations 36
Comments on the Sulfuric Acid
Conduction Mechanism 42
Incorporation of the Environmental
Sulfur Trioxide Concentration into
the Resistivity Prediction 47
7. Resistivity Prediction Method 53
Required Input Data 53
Calculation of Resistivity. 54
Calculation of Volume Resistivity, pv 56
Calculation of Surface Resistivity, ps 56
Calculation of Combined Volume and Surface
Resistivities, p^s 59
Calculation of Acid Resistivity, pa 59
Calculation of Combined Volume, Surface, and
Acid Resistivities, pvsa.... 61
8. Computer Program for Predicting Resistivity 62
9. Predicted Resistivity Proof Test.. 87
References 102
v
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FIGURES
Number Page
1 Typical Resistivity-Temperature Data, Ash 105 12
2 Resistivity versus Lithium + Sodium, Baseline
Conditions, 84°C 15
3 Resistivity versus Lithium + Sodium, Baseline
Conditions, 112°C 16
4 Resistivity versus Lithium + Sodium, Baseline
Conditions, 144°C 17
5 Resistivity versus Lithium + Sodium, Baseline
Conditions, 182°C 18
6 Resistivity versus Lithium + Sodium, Baseline
Conditions, 227°C 19
7 Resistivity versus Lithium + Sodium, Baseline
Conditions, 352°C 20
8 Second Iteration of Figure 7 Resistivity Data
Normalized to 0.4% Lithium + Sodium and 2.5%
Magnesium + Calcium 23
9 Second Iteration of Figure 7 Resistivity Data
Normalized to 0.4% Lithium + Sodium and
1.0% Iron 24
10 Resistivity versus Lithium + Sodium, Baseline Con-
ditions, 352°C. Data Normalized to 1.0% Iron and
2.5% Magnesium + Calcium 25
11 Predicted Resistivity for Baseline Conditions
at 352°C 26
12 Resistivity as a Function of Water Concentration,
Ash 105 28
13 Resistivity as a Function of Water Concentration,
at Various Temperatures, Ash 105 30
14 Effect of Temperature on the Resistivity-Water
Concentration Relationship, All Ashes Tested 31
15 Relative Resistivity Values as a Function of
Applied Ash Layer Voltage Gradient 33
VI
-------
16 Resistivity as a Function of Field Strength for
Ash Layers of Two Thicknesses 35
17 Photographs of a Resistivity Test Cell after
Dielectric Failure 37
18 Photographs of the Upper and Lower Electrodes from
the Test Cell Shown in Figure 17 38
19 Schematic Cross-Section of Cavities Occurring in
Ash Layers Having Experienced Dielectric
Failure 39
20 Resistivity-Time after Injection of 9 ppm of
Sulfur Trioxide in an Environment of Air
Containing 9% Water 41
21 Resistivity-Temperature Relationship with and
without Sulfur Trioxide Injection 43
22 The Effect of Sulfur Trioxide at 1000/T(°K) = 2.37
in an Environment of Air Containing 9% Water 48
23 Resistivity versus Reciprocal .Absolute Temperature
in an Environment of Air Containing «r 9 ppm
Sulfur Trioxide and 9% Water 50
24 Predicted Resistivity as a Function of
Temperature 57
25 Multiple-Card Layout Form 79
26 Example Data Input Cards 80
27 Predicted Resistivity for the Fictive Coal and Coal
Ash used to Illustrate the Computer Program 86
28 Predicted, In Situ, and Laboratory Measured
Resistivity Data for Station 1 W 93
29 Predicted, ^n Situ, and Laboratory Measured
Resistivity Data for Station 3 E 94
30 Predicted, Jin Situ, and Laboratory Measured
Resistivity Data for Station 4 E. .. 95
31 Predicted, Iri Situ, and Laboratory Measured
Resistivity Data for Station 5 W 96
32 Predicted, ^n Situ, and Laboratory Measured
Resistivity Data for Station 7 E 97
33 Predicted, In Situ, and Laboratory Measured
Resistivity Data for Station 13 W 98
VII
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TABLES
Number Page
I. Chemical and Physical Characterization of Fly Ashes... 11
II. Chemical, Physical and Electrical Characteristics of
Fly Ashes 14
III. Chemical Analysis of Ash Specimens Used in the Chemical
Transference Experiment 45
IV. Illustrative Example of the Calculation of the Atomic
Concentration of Cations in Coal Ash 55
V. FORTRAN Computer Program for Predicting Resistivity... 63
VI. BASIC Computer Program for Predicting Resistivity 71
VII. Resistivity Prediction Printout from FORTRAN
Program 82
VIII. Resistivity Prediction Printout from BASIC Program.... 84
IX. Predicted Resistivity Proof Check; General Information
and Coal Analyses for Six Power Stations 89
X. Predicted Resistivity Proof Check; Fly Ash, Coal Ash
and Flue Gas Compositions for Six Power Stations.... 90
XI. Predicted Resistivity Proof Check; Temperature, Resis-
tivity, and Performance Data for Six Power
Stations 92
XII. Comparison of Predicted Resistivity Values with those
Measured in the Laboratory and Iji Situ 100
Vlll
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ACKNOWLEDGEMENTS
The research was financially supported by the Environmental
Protection Agency under Contract No. 68-02-2114. This support
and the time extensions allowed so that unforeseen problems could
be overcome were greatly appreciated.
The experimental approach required the cooperation of many
members of the electric utility industry. The assistance pro-
vided by supplying data and coal and ash specimens is gratefully
acknowledged.
The writer wishes to thank Miss Ann A. Henry of the Southern
Research Institute staff for translating the results of this
research into the computer program appearing in the report.
The laboratory work was executed by Mr. Charles A. Reed,
Engineering Research Technician. Also the helpful support of
the analytical chemistry personnel, the Institute's machine shop
and the art department is appreciated.
IX
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SECTION 1
INTRODUCTION
In the design of an electrostatic precipitator for the dry
collection of fly ash, the electrical resistivity of the ash
is one of several important factors to be considered. Since
resistivity inversely influences the allowable electrical operat-
ing parameters, high resistivity necessitates the design of large
precipitators for a given collection efficiency. The direct
relationship between the size and performance of the precipitator
and the cost makes the knowledge about resistivity mandatory.
When a precipitator is being sized to collect ash produced
from a well known coal of uniform character, performance data
and/or in situ resistivity data are available, and minimum design
difficulty is encountered. However, ash produced from coals
of highly variable character or from coals that have not been
previously commercially burned present a problem. If a trial
burn of a coal of unknown quality at a commercial installation
to obtain design data is not possible, one must acquire this
information in some other manner.
Precipitator manufacturers have proprietary techniques for
estimating fly ash resistivity and precipitator design functions.
Often these techniques, developed from extensive experience,
are based on a correlation in which certain coal, coal ash or
fly ash characteristics are related to previous success or fail-
ure in the precipitator design. Usually these procedures are
not publically available and often are not generally applicable.
An alternate approach1 is to burn small quantities of pulverized
coal in small furnaces and measure the properties of the resultant
fly ash. Although time consuming and expensive, this technique
should give excellent results if the fly ash and the flue gas
duplicate those commercially produced. Using this method, one
can examine the physical, chemical, and electrical characteris-
tics of the fly ash.
Several years ago relationships were developed2'3'" between
fly ash resistivity and certain parameters that are based on
the chemical composition of fly ash. With these relationships
one can predict the resistivity of fly ash for specific condi-
tions or types of ash knowing the chemical composition of the
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fly ash or coal ash. Resistivity predictions obtained in this
manner have been used with a substantial degree of success.
These ash composition-resistivity correlations have some
inherent weaknesses. The data used to establish the correlations
are obtained from laboratory resistivity tests conducted under
a limited number of conditions. Generally these conditions in-
volve low ash layer field strength, invariant environmental water
concentration, and the absence of sulfur trioxide from the test
environment. Furthermore, disagreement was often noted between
laboratory resistivity determinations and ir» situ values; how-
ever, one cannot assume that all in situ data are infallible.
In spite of the shortcomings, these predictive techniques are
reasonably effective when applied to ashes of low-sulfur coals,
because they take into consideration the temperature and the
concentration of sodium in the ash. These two factors exercise
the principal control over ash resistivity values when the sul-
furic acid vapor in the flue gas is insignificant.
There has been an intense motivation to be able to predict
fly ash resistivity quickly, cheaply, and accurately in the abso-
lute sense from the most basic of input data. This ability would
allow one to:
• supply input data for sizing precipitators with respect
to one or many design coals,
• topographically define the resistivity for entire unopened
coal fields or seams from core bore samples,
• troubleshoot poorly performing precipitators without in
situ resistivity measurements,
• develop an in-line monitor for stockpiled coal feed,
• blend coals to obtain superior precipitation characteristics,
• evaluate the merits of hot-side or cold-side operations,
• evaluate and/or select dosages of conditioning agents.
Encouraged by laboratory resistivity measurements that pro-
duce data in better agreement with i_n situ values and by the
observation that in most cases fly ash composition and concomitant
coal ash composition are similar, additional research was proposed
to develop an improved technique for predicting the resistivity
of fly ash. The objective of the research was to produce a pre-
dictive technique that requires as input information the as-received,
ultimate coal analysis and the chemical composition of the respec-
tive coal ash. The output information is resistivity as a func-
tion of temperature for a given coal ash analysis in an environ-
ment stoichiometrically calculated from the coal analysis. This
report describes the results of this research.
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SECTION 2
CONCLUSIONS
As a result of this research, a technique for predicting
the electrical resistivity of fly ash from an as-received, ulti-
mate coal analysis and a chemical composition of the coal ash
was developed. Resistivity predicted as a function of tempera-
ture was favorably proof tested by comparing predicted resis-
tivity values with those acquired by in situ and laboratory
measurements.
A prerequisite step to the accomplishment of the task objec-
tive was the design of equipment and a test procedure to quanti-
tatively evaluate the effect of environmental sulfur trioxide
on the electrical resistivity of fly ash. This was successfully
performed, and additional information related to the conduction
mechanism involving sorbed sulfuric acid vapor was obtained.
It was concluded that the effect of sorbed sulfuric acid vapor
was observable only while the agent was being continuously in-
jected and that the conduction process functioned independently
of other surface conduction mechanisms.
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SECTION 3
RECOMMENDATIONS
The effort to develop the method for quantitatively evaluat-
ing the effect of environmental sulfuric acid vapor on resistivity
required a large amount of contract time. As a consequence,
the amount of data taken after the perfection of this experimental
procedure was held to the minimum that would still permit the
development of the resistivity predictive technique. Therefore,
it is suggested that additional experimentation should be con-
ducted to perfect that portion of the predictive technique re-
lated to environmental sulfur trioxide. Specifically, more data
are needed with respect to: (1) the variation of sulfur trioxide
concentration, (2) the combined effect of variations in water
and sulfur trioxide concentrations, and (3) the relationship
between the effectiveness of sulfur trioxide and the fly ash
composition.
Additional effort should be made to evaluate the predictive
technique with respect to: (1) cleaned coal, (2) the effect
of conditioning agents, and (3) the effect of coal containing
large amounts of ash and moisture thereby yielding a stoichio-
metrically high concentration of sulfur trioxide for a relatively
low concentration of sulfur in the coal. This effort would re-
quire a combined field testing - laboratory experimentation task.
In this report a simple coal ashing technique was used that
was selected based on a few trial and error experiments. It
is recommended that a technique be developed to objectively
select the temperature at which a given coal should be ignited
to produce the coal ash required for the prediction of fly ash
resistivity.
The technique for predicting fly ash resistivity described
in this report utilizes a sulfur trioxide concentration calculated
as a percentage (0.4%) of the sulfur dioxide concentration ob-
tained from the stoichiometric combustion of the coal. Further-
more, it is assumed that the fly ash is in equilibrium with the
concentration of the sulfur trioxide that is measured at the
precipitator inlet and that this is also true of the fly ash
layer under laboratory test when exposed to a given sulfur tri-
oxide concentration for a long period of time, typically 18 hours.
A task combining field evaluation and laboratory experimentation
is required to justify the above approach. Typical of some of
-------
the data required would be in situ resistivity and flue gas analyses
taken at about 350°C and 150°C. This information would be coupled
with coal and fly ash analyses and laboratory resistivity data
obtained under conditions simulating the jji situ conditions.
-------
SECTION 4
INVESTIGATIVE SCOPE AND APPROACH
A large number of commercially produced fly ashes were chemi-
cally and physically characterized for this work. It was hoped
that all ranks of coal would be represented. Resistivity as
a function of temperature for a given set of electrical and en-
vironmental conditions was determined using all the available
fly ash specimens. From these data one can relate fly ash resis-
tivity as a function of temperature to fly ash chemical analysis
for one set of experimental conditions.
From the original group, sixteen ashes were selected to
investigate the effect of the variation in environmental water
concentration and ash layer field strength on resistivity. Eight
of these ashes were further utilized in experiments to determine
the effect of sulfur trioxide on resistivity. By combining the
expressions defining the effects of these three factors on resis-
tivity with the basic expression for resistivity as a function
of ash composition, resistivity can be predicted as a function
of temperature knowing the ash composition, water and sulfur
trioxide concentrations, and the ash layer field strength.
Six coal and fly ash specimens were obtained during field
test programs in which in situ resistivity and precipitator elec-
trical characteristics were monitored. Experiments were conducted
to establish an ash ignition temperature that produced coal ashes
that were chemically similar to their respective fly ashes.
From these coal ash analyses and the water and sulfur trioxide
concentrations estimated from stoichiometric combustion calcula-
tions, resistivity was predicted. This predicted resistivity
value was compared to the resistivity values determined in the
laboratory, the in situ resistivity data, and the precipitator
electrical operating conditions.
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SECTION 5
EXPERIMENTAL PROCEDURES
FLY ASH AND COAL CHARACTERIZATION
The fly ashes were received from commercial steam generating
power plants. An organization supplying fly ash samples also
submitted a data sheet listing the available information regard-
ing coal identification and analysis, flue gas analysis, precipi-
tator temperature, source of ash sample, etc. After the ashes
were put through an 80 mesh screen to remove debris, they were
quartered into 25-gram specimens to be used for resistivity and
characterization studies.
The chemical composition, helium pycnometer density and
particle size distribution were determined for each fly ash.
Helium pycnometer density was determined using a Micromeritics
Instrument Corporation, Model 1302 helium-air pycnometer using
the manufacturer's suggested procedures. A number 6000 Bahco
Micro Particle Classifier was used to determine the particle
size distribution using the technique outlined by the manufac-
turer. Chemical analyses were conducted for the elements com-
monly reported for fly ash. In addition, soluble sulfate and
loss on ignition were determined. The chemical analyses were
made using ash specimens that had been ignited for loss on igni-
tion determination. A general description5 of the analysis pro-
cedure for fly ash and the gaseous environments used is availr
able.
Representative coal specimens were sent to a subcontractor
to have total sulfur, proximate analysis, ultimate analysis,
and forms of sulfur determined. Respectively, the ASTM desig-
nated procedures used for these determinations were: D3117,
D3172, D3176, and D2492. In addition, the subcontractor ashed
one-pound samples of coal using the ASTM procedure D3174 (700-
750°C). These coal ash samples provided the starting material
for the ignition experiments which will be subsequently discussed.
EXPERIMENTAL EQUIPMENT AND PROCEDURES FOR RESISTIVITY DETERMINATION
This research required the determination of resistivity
using simulated flue gas environments. Major experimental prob-
lems were encountered when using sulfur oxides. These difficul-
-------
ties included the technique of environmental chemical analysis,
the inadvertent generation of sulfur trioxide and the need to
develop a resistivity test procedure involving sulfur trioxide.
A significant effort was required to overcome these problems,
ultimately a new test procedure and resistivity test cell were
developed to evaluate the effect of sulfur trioxide on fly ash
resistivity. Since the equipment and test procedures used repre-
sent a departure from the commonly employed techniques, a sepa-
rate report6 regarding this facet of the research was written.
Consequently only a brief description of the apparatus and pro-
cedures used to measure resistivity will be given here.
The initial apparatus consisted of four ASME, PTC-287 test
cells housed in a stainless steel environmental chamber which
was installed in a high temperature laboratory oven. A negative,
direct-current high voltage was supplied in common to the cup
style electrodes. Each current measuring circuit and guard ring
circuit terminated at a female phone jack. A male phone jack
was used to complete the circuit under test. Except when the
effect of ash layer field strength was examined, the applied
voltage was 1330 volts (2 kV/cm). The standard baseline environ-
men in addition to nitrogen contained by volume 5% oxygen,
13% carbon dioxide, 9% water, and 500 ppm sulfur dioxide. The
simulated flue gas environment was maintained under slight posi-
tive pressure in the chamber.
The resistivity as a function of temperature was determined
using the above conditions for each fly ash used in the project.
The ash under test was allowed to thermally equilibrate overnight
at 460°C in a dry nitrogen environment. After determining the
resistivity under this condition, the environment was changed
to the above described baseline mixture. Approximately thirty
minutes later the oven was turned off and allowed to cool natural-
ly. Resistivity and temperature were recorded periodically as
the test cells cooled to 85°C. After removing the test cell
from the chamber, the ash layer thickness was determined, and
resistivity was calculated in the usual manner.
Using the apparatus and procedure briefly described, tests
were repeated on sixteen of the ashes to examine the effect of
water concentration and field strength on resistivity. In addi-
tion to the baseline value of 9%, water concentrations of 5%
and 14% were used. When the effect of field strength was being
determined, the test procedure was slightly altered in that the
oven cooling process was arrested at 162°C. At this temperature
the effect of field strength was measured by increasing the ap-
plied voltage in increments of 1330 volts until dielectric break-
down occurred or the capacity of the voltage supply (6000 volts)
was reached.
-------
The apparatus and procedure used to determine the effect
of temperature, ash composition, water concentration and field
strength on resistivity was unsatisfactory for experiments in-
volving sulfur trioxide. A second test apparatus was constructed
principally of glass that could accommodate one test cell. In
the case of the modified resistivity test cell, two circular,
concentric electrodes 1-mm thick were pressed into the surface
of an ash layer to a depth of 1 mm. Voltage was applied across
a 6-mm gap between the electrodes, and the current was measured.
This thin layer of ash contiguous with the test environment was
capable of equilibrating with the sulfuric acid vapor in a reason-
able amount of time.
The standard test environment was changed from a simulated
flue gas to air containing 9% water. The effect of sulfur trioxide
on resistivity was determined for concentrations of about 5 and 10 ppm
using the air-water environment.
The test procedure was altered significantly also. Isothermal
tests were usually conducted at 138, 147, and 166°C. The ash
was equilibrated in dry air at the temperature of interest for
three hours. After determining dry resistivity, the nine percent
moisture was introduced. Current was measured every five minutes
(voltage applied one minute), and when the value failed to increase,
the sulfur trioxide was introduced. An overnight equilibration
was required for the resistivity to asymptotically approach a
minimum value. The environmental moisture concentration and
sulfur trioxide concentration were determined after the first
hour of the test and during the final hour. Resistivity was
calculated using the expression derived for a radial flow (concen-
tric electrodes) test cell, and the soluble sulfate concentration
for the ash before and after test was recorded.
The equipment and procedures described in reference 6 for
making laboratory resistivity determinations in an environment
containing sulfuric acid vapor represent a noteworthy technical
advancement. At present it is the only available technique for
making this measurement. Later in this report and in subsequent
papers, it will be demonstrated that reasonably good agreement
is obtained between laboratory and _in situ measurements made
with known quantities of sulfuric acid vapor present in the test
environment.
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SECTION 6
RESULTS
FLY ASH CHARACTERIZATION
The results of the physical and chemical characterization
are shown in Table I. The elemental chemical analysis results
are expressed in weight percent as oxides. The loss on ignition
value is listed separate from the total chemical analysis,
because the analysis was conducted using an ignited specimen.
Helium pycnometer density values are shown in grams/cc and are
used to calculate resistivity specimen porosity. Bahco particle
classifier results are shown as mass-median-diameter in microns.
This value and the ash layer porosity can be used to calculate
a crude value that is proportional to specific surface. The
last column shows the location from which the ash sample was
obtained.
Most of the elements determined in the chemical analysis
show a wide variation in concentration among all the ashes.
This reflects the attempt to acquire ashes produced from all
ranks of coal acquired from all major coal producing areas in
North America and some other regions. Density and mean particle
size also varied greatly among the ash samples. It was hoped
that this situation might eliminate data bias that could occur
using ashes produced from coals of a restricted area or of limited
characteristics.
RESISTIVITY DATA
Effect of Fly Ash Composition
For all the fly ashes described in Table I/ the resistivity
was determined between 80°C and 460°C using the baseline condi-
tions and test procedure previously detailed. Baseline conditions
included an ash layer voltage gradient of 2 kV/cm and 9 volume
percent water vapor in the simulated flue gas.
The resistivity data were plotted on semi-logarithmic graph
paper versus the reciprocal of the absolute temperature. Fig-
ure 1 illustrates the data obtained for ash number 105. The
curve shown in this figure has the characteristic inverted V-
shape. At the higher temperatures, the curve is linear in agree-
10
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Table I. Chemical and Physical Characterization of F
Chemical Analysis In Weight Percent As Oxides
Ash No.
101
103
104
105
106
107
109
110
111
112
113
114
115
116
117
118
121
123
124
125
126
127
128
129'
131
133
134
135
137
138
139
140
141
142
143
Li2O
0.04
0.04
0.04
0.05
0.05
0.02
0.01
0.01
0.01
0.05
0.01
0.02
0.03
0.02
0.01
0.02
0.03
0.03
0.04
0.06
0.02
0.05
0.01
0.02
0.04
0.02
0.04
0.07
0.04
0.06
0.02
0.04
0.02
0.02
0.01
Na2O
0.38
0.53
0.35
0.66
0.48
0.30
0.46
3.20
0.29
0.34
1.85
2.02
1.85
9.70
2.27
0.29
1.38
0.47
0.22
0.32
0.33
0.43
8.52
1.58
0.55
1.67
0.29
0.29
0.45
0.24
4.67
0.26
0.36
0.67
1.13
K20
4.4
3.1
3.8
2.9
2.8
0.8
1.6
0.7
0.7
0.5
0.6
1.4
1.4
0.6
2.8
1.8
1.1
2.7
2.7
3.6
2.7
3.9
1.0
0.2
1.7
0.8
2.7
2.4
3.1
2.2
0.8
2.7
0.9
1.2
0.7
MgO
1.1
1.2
1.6
1.2
1.1
2.2
2.9
1.2
1.8
6.8
1.9
2.8
3.0
3.7
1.1
3.6
0.9
1.0
0.8
1.3
0.8
1.5
5.9
8.9
1.2
1.9
1.0
1.0
2.1
0.8
1.6
0.3
1.1
1.7
4.0
CaO
1.9
2.2
1.5
3.1
2.1
9.6
14.5
15.6
12.8
19.6
9.1
13.0
13.7
17.3
2.6
8.6
5.2
4.7
0.4
1.2
1.5
1.4
23.3
32.2
4.3
11.8
1.8
1.6
4.6
1.2
11.5
0.3
0.8
7.0
22.7
Fe2O3
13.1
9.6
11.1
10.5
11.4
3.9
7.8
5.2
4.3
4.7
5.4
10.2
9.8
8.7
19.2
5.9
4.3
19.3
4.8
8.8
23.6
10.3
10.6
12.6
5.1
5.9
15.3
11.0
8.2
11.7
5.9
0.7
7.3
4.5
4.8
A1203
24.0
25.1
25.9
24.1
28.2
17.1
18.5
22.9
22.5
21.4
23.4
18.5
17.3
19.3
18.3
23.7
23.4
19.5
31.5
27.6
19.9
27.9
10.0
12.3
23.7
23.2
22.1
26.1
26.0
30.0
20.1
27.6
26.3
21.5
21.6
SiO2
52.2
54.2
51.6
51.4
51.0
61.5
51.0
45.9
55.0
43.8
51.2
47.7
47.2
28.9
52.0
51.9
58.5
50.4
54.5
54.0
46.2
51.7
27.6
22.6
59.7
51.2
50.7
55.3
52.9
50.9
52.7
63.4
58.3
59.3
38.8
TiO2
2.1
2.3
1.7
2.7
2.5
2.5
1.4
1.4
1.1
1.6
5.5
1.4
1.4
1.9
1.9
1.3
1.7
1.6
2.8
2.3
1.9
2.3
0.7
0.7
2.0
1.8
2.1
1.9
2.2
1.5
0.7
2.1
1.9
1.1
1.9
P2O5
0.3
0.1
0.3
0.3
0.5
1.2
0.5
0.2
0.1
0.3
0.8
0.4
0.3
1.0
0.4
0.4
0.3
0.3
0.1
0.5
0.4
0.7
0.1
0.3
0.3
0.2
0.3
0.3
0.2
0.4
0.4
0.1
0.1
1.0
1.4
SO 3
0.6
0.5
0.3
1.2
0.6
1.2
1.9
1.3
0.3
1.9
0.4
4.2
3.2
5.7
1.0
1.3
0.7
1.5
0.2
0.3
0.8
0.8
11.0
7.9
0.8
1.6
0.5
0.2
0.5
0.4
0.6
0.3
0.2
0.4
1.7
Total
100.1
98.9
98.2
98.1
100.7
100.3
100.4
97.6
98.8
101.0
100.2
101.6
99.2
96.8
101.3
98.8
97.5
101.5
98.0
100.0
98.2
101.0
98.7
99.3
99.4
100.1
96.8
100.2
100.3
99.4
99.0
97.7
97.3
98.3
98.7
S0n =
0.33
0.22
0.24
0.62
0.45
O.SO
0.50
0.34
0.26
0.19
0.37
1.80
1.14
5.65
0.55
0.71
0.30
0.58
0.20
0.29
0.42
0.50
8.93
2.81
0.45
0.69
0.35
0.25
0.50
0.28
0.41
0.19
0.12
0.24
0.83
LOI
1.1
1.8
4.0
2.3
2.7
0.3
0.8
0.4
1.0
0.3
0.3
1.0
1.1
0.7
6.1
0.8
1.6
1.2
3.2
1.9
4.7
3.2
1.0
1.0
5.0
1.7
1.1
3.0
0.4
3.1
0.3
3.2
4.9
2.0
0.1
ly Ashes
Helium
Pycnometer
Density
qms/cc
2.39
2.04
2.73
2.32
2.41-
2.48
2.28
2.19
2.54
2.52
2.03
2.50
2.43
2.79
2.67
2.50
2.15
2.63
2.38
2.59
2.76
2.71
2.99
2.91
2.65
2.37
2.58
2.31
2.49
2.78
ND
2.43
2.26
2.27
2.54
Mass-
Median
Diameter
Microns
26
15
7
13
13
24
50
10
20
11
35
10
10
12
14
3 .
38
16
14
6
16
4
6
12
11
15
12
13
19
4
13
8
13
. 80
7
Source of
Ash Sample
Storage silo
Inlet, hopper
Inlet, cyclone
Inlet, hopper
Inlet, hopper
Inlet, hopper
Inlet, hopper
Proportionate blend,
Mechanical collector
Proportionate blend.
Inlet, hopper
Unknown
Unknown
Hopper
Hopper
Proportionate blend.
Storage silo
Proportionate blend.
Unknown
Unknown
Inlet, cyclone
Unknown
Hopper
Hopper
Unknown
Unknown
Unknown
Inlet, hopper
Inlet, cyclone
Proportionate blend.
Proportionate blend.
Proportionate blend.
Inlet, hopper
Unknown
Unknown
hoppers
hoppe rs
hoppers
hoppers
hopppi-s
hoppers
hoppers
-------
10"
10"
o
i
X
o
K
>
V)
LU
cc
109
I
I
108
1000/T(°K) 3.2 3.0
°C 40 60
°F 103 141
I
I
I
I
I
I
I
I
2.8
84
183
26
112
233
2.4
144
291
2.2
182
359
2.0
227
441
1.8
283
541
1.6
352
666
1.4
441
826
1.2
560
1041
TEMPERATURE
Figure 1. Typical resistivity-temperature data.
Ash 105, baseline conditions.
12
-------
ment with the Arrhenius equation for resistivity. From this
part of the curve the experimental activation energy for volume
or thermally controlled conduction can be calculated. As lower
temperatures are approached, the curve departs from linearity
due to the effect of surface conduction. After passing through
a maximum, resistivity decreases rapidly with lower temperatures
and concomitantly greater relative humidity.
After the data were plotted for each fly ash in this fashion,
the resistivity values at specific reciprocal temperatures were
selected, and the experimental activation energy was calculated.
The resistivity data were compiled for 1000/T (°K) at 1.4, 1.6,
1.8, 2.0,2.2, 2.4, 2.6, and 2.8. The experimental activation
energy was calculated from the slope of the linear part of the
resistivity curve using the logarithmic form of the Arrhenius
equation:
log p = log p o + [(0/k)log e] (1/T) CD
where
pv = volume resistivity,
pv = a complex material parameter including the number
0 of mobile charge carriers,
0 = experimental activation energy in electron volts,
k = Boltzmann constant, and
T = absolute temperature.
This information has been tabulated in Table II. In addition,
the atomic percentages of lithium plus sodium, magnesium plus
calcium, and iron are listed. These values were calculated from
the compositional data in Table I. The weight percent values
were normalized to 100 percent and converted to molecular percen-
tages. The atomic percentage of cation was calculated by multi-
plying the molecular percentage of oxide by the decimal fraction
of cation present in the oxide.
To examine the effect of ash composition on resistivity
and to develop compositional information for the resistivity
predictive procedure, the resistivity values listed in Table
II were plotted versus the combined atomic concentrations of
lithium and sodium. This was done, because it has been shown8'9
that in the absence of sulfuric acid vapor the lithium and sodium
ions are the principal charge carriers. Functioning as mobile
ions, not oxide molecules, the number of charge carriers is pro-
portional to the atomic concentration of these ions. Since the
resistivity should be inversely proportional to the number of
mobile charge carriers, log-log graph paper was used for these
relationships.
Figures 2 through 7 show the measured fly ash resistivity
values plotted as a function of the respective lithium plus
sodium concentrations for the various reciprocal temperatures
13
-------
Table II. Chemical, Physical and Electrical Characteristics of Fly Ashes
Measured Resistivity in ohm-cm at Various Temperatures
Experimental
Ash
NO.
101
103
104
105
106
107
109
110
111
112
113
114
115
116
117
118
121
123
124
125
126
127
128
129
131
133
134
135
137
138
139
140
141
142
143
Atomic percentage
Mg+Ca
2.3
2.5
2.5
3.2
2.4
7.5
11.2
10.8
9.3
16.8
7.3
10.3
11.0
14.4
2.7
8.4
4.0
4.1
1.0
2.0
1.9
2.3
19.0
26.3
3.7
8.9
2.2
2.0
3.8
1.6
8.4
0.5
1.5
5.8
17.1
Fe
2.5
1.8
2.1
2.0
2.1
0.6
1.3
0.9
0.7
0.8
0.9
1.7
1.7
1.6
3.6
1.0
0.8
3.6
0.9
1.6
4.8
1.9
1.8
2.1
0.9
1.0
3.0
2.0
1.5
2.2
1.0
0.1
1.3
0.8
0.8
Li-HJa
0.37
0.49
0.35
0.62
0.47
0.24
0.35
2.43
0.23
0.31
1.40
1.52
1.43
7.53
1.84
0.25
1.10
0.43
0.24
0.35
0.33
0.42
6.20
1.16
0.48
1.27
0.31
0.34
0.41
0.30
3.47
0.26
0.32
0.53
0.84
1000/T(°K) - 2.8
°C - 84
°F - 183
6.0 x
3.4 x
8.8 x
2.2 x
3.0 x
1.3 x
3.4 x
1.7 x
2.2 x
3.2 x
2.0 x
2.7 x
4.5 x
1.0 x
3.3 x
8.0 x
7.5 x
5.0 x
2.0 x
8.0 x
3.8 x
3.7 x
1.4 x
2.2 x
2.2 x
2.6 x
3.8 x
4.0 x
1.4 x
1.6 x
7.0 x
2.4 x
1.8 x
4.4 x
1.1 x
1010
1010
109
10'°
1010
10"
1010
109
10"
10' °
109
109
10'
10 "
109
10"
109
10'°
10"
1010
10"
10"
10"
109
1010
10'°
10'°
1011
10"
10"
10e
10"
10"
1010
1010
6.2 x
4.2 x
1.5 x
2.5 x
3.5 x
1.3 x
2.6 x
1.2 x
1.8 x
2.8 x
1.5 x
1.8 x
3.4 x
6.5 x
3.2 x
7.6 x
6.0 x
6.5 x
3.0 x
9.2 x
5.0 x
3.8 x
1.0 x
1.2 x
2.6 x
2.2 x
4.2 x
2.2 x
1.3 x
1.8 x
4.8 x
3.4 x
1.4 x
6.0 x
9.0 x
2.6
112
233
10"
10"
10"
10"
10"
1012
10"
10'°
1010
10"
10l°
1010
1010
10"
1010
10"
10'°
10"
1012
10"
10"
10"
109
10"
10"
10"
10"
1012
10"
1012
109
1012
1012
10"
10"
1.0 x
9.0 x
4.0 x
5.0 x
6.5 x
2.3 x
7.4 x
2.3 x
3.3 x
8.0 x
3.9 x
4.0 x
9.0 x
1.4 x
4.6 x
1.4 x
8.4 x
1.2 x
5.3 x
1.8 x
9.2 x
9.0 x
1.6 x
2.8 x
6.8 x
4.5 x
7.6 x
2.9 x
3.2 x
3.0 x
9.4 x
6.7 x
2.5 x
1.3 x
2.5 x
2.4
144
291
1012
10"
10"
10"
10"
1012
10"
10"
1012
10"
10"
10"
10"
109
10"
1012
10"
1012
1012
1012
10"
10"
109
10"
10"
10"
10"
1012
10"
1012
109
1012
1012
1012
10"
6.0
5.8
4.0
3.5
4.5
1.9
8.5
2.8
2.7
1.2
4.6
4.6
9.6
1.8
2.2
1.1
5.5
5.5
3.2
9.5
4.6
5.8
2.0
3.9
5.2
4.5
4.4
1.2
2.9
1.8
9.5
3.9
1.0
8.0
3.1
x
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
2.2
182
359
10"
10"
10"
10"
10"
1012
10"
10"
1012
1012
10"
10"
10"
10'
10"
1012
10"
10"
1012
10"
10"
10"
109
10"
10"
10"
10"
1012
10"
1012
109
1012
1012
10"
10"
1.4 x
1.4 x
1.5 x
1.3 x
1.4 x
1.0 x
4.8 x
2.2 x
1.1 x
1.0 x
3.0 x
3.0 x
6.5 x
1.7 x
4.5 x
5.2 x
1.8 x
1.3 x
6.8 x
2.3 x
1.1 x
1.9 x
2.0 x
2.8 x
1.9 x
3.4 x
1.1 x
2.8 x
1.1 x
4.9 x
5.8 x
8.5 x
2.5 x
2.9 x
2.2 x
2.0
227
441
10"
10"
10 "
10"
10"
1012
10"
10"
1012
1012
10"
10"
1010
109
109
10"
1010
10"
10"
10"
10"
10"
109
10'°
10"
10"
10"
10"
10"
10"
10"
10"
10"
10"
1010
2.9 x
2.6 x
3.6 x
2.5 x
2.6 x
5.2 x
2.4 x
3.5 x
5.0 x
1.1 x
1.8 x
2.2 x
4.7 x
9.0 x
8.0 x
1.5 x
5.1 x
2.2 x
9.5 x
3.8 x
2.0 x
2.7 x
1.0 x
2.8 x
3.2 x
3.4 x
1.8 x
4.0 x
3.1 x
6.4 x
4.3 x
1.3 x
4.7 x
5.8 x
3.0 x
1.6
352
666
109
109
109
109
109
10"
10"
109
10"
10"
109
109
109
10 7
107
10"
10"
109
10'
10'
10'
10'
10 "
109
10'
10'
109
10'
109
109
10'
10"
109
109
10"
ACCJ.VdUl.UIl
Energy in
Electron
Volts
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
1.
0.
0.
0.
0.
0.
0.
0.
0.
1.
0.
0.
0.
0.
0.
0.
0.
0.
0.
90
90
79
86
90
86
79
83
83
83
66
68
74
10
86
95
79
90
90
95
90
95
32
86
83
76
79
90
86
90
.60
90
0.83
0.
,86
0.79
Ash Layer
Porosity
in %
54
50
69
59
59
47
44
60
54
59
55
64
60
67
58
70
53
63
67
65
56
81
78
68
76
54
56
67
53
68
ND
75
66
61
64
-------
I
o
oo
evi
n
o Z
§g
t- H
I- O
< Z
CO
UJ <
oc m
o
E
o
UJ
_i
UJ
Q
ill
OC
3
to
y = e • X
In y = a + b In x
where:
a = 22.6416
b = -Z0618
R = -0.94
108
0.1 1.0 10.0
LITHIUM + SODIUM CONCENTRATION IN ATOMIC PERCENT
Figure 2. Resistivity versus lithium + sodium.
Baseline conditions at 84°C.
15
-------
1013
a = 24.8070
b = -2.2334
R = -0.95
0.1 1.0 10.0
LITHIUM + SODIUM CONCENTRATION IN ATOMIC PERCENT
Figure 3. Resistivity versus lithium + sodium.
Baseline conditions at 112°C.
16
-------
a = 25.5104
b = -2.2314
R =-0.97
0.1 1.0 10.0
LITHIUM + SODIUM CONCENTRATION IN ATOMIC PERCENT
Figure 4. Resistivity versus lithium + sodium.
Baseline conditions at 144°C.
17
-------
5
o
5
I
o
0>J
csi
n
5
O
o
o
o
>
CO
CO
LLJ
CC
_l
<
0
HI
_l
lit
Q
LU
CC
D
CO
a = 25.3572
b = -2.0267
R = -0.97
0.1 1.0 10.0
LITHIUM + SODIUM CONCENTRATION IN ATOMIC PERCENT
Figure 5. Resistivity versus lithium + sodium.
Baseline conditions at 182°C.
18
-------
1013
o
•
i
O
q
CN
II
2
o
1012
10
11
CO
to
Ul
tc.
o
oc
H
u
UJ
UJ
Q
UJ
cc
CO
1010
109
y = ea . xb
Iny = a + b In x
where:
a = 24.6023
b = -1.6938
R = -0.93
41'
27 Op 31
O43
015
010
210
ASH NO. 139-Wo 39
017
I
0.1 1.0 10.0
LITHIUM + SODIUM CONCENTRATION IN ATOMIC PERCENT
Figure 6. Resistivity versus lithium + sodium.
Baseline conditions at 227°C.
19
-------
a = 21.3680
b = -1.2630
R = -0.73
0.1 1.0 10.0
LITHIUM + SODIUM CONCENTRATION IN ATOMIC PERCENT
Figure 7. Resistivity versus lithium + sodium.
Baseline conditions at 3529C.
20
-------
of interest. A linear regression analysis was performed on each
group of data, and the resultant line was superimposed on the
data. On each graph the expression for the straight line is
repeated, and the intercept and slope values are shown as well
as the coefficient of correlation, R. This value is a measure
of the degree with which the data fit the regression analysis,
and a value of -1.00 would define perfect correlation between
the two factors.
At the lower temperatures, 1000/T(°K) = 2.2 to 2.8 (359°F
to 183°F), the plots typically show a negative slope of about 2.1
and a R value of -0.96. This indicates that under the prevailing
test conditions the resistivity decreases two orders of magnitude
for each order of magnitude increase in the combined concentra-
tion of lithium and sodium. The value of R suggests that a good
correlation exists between these two factors.
In the simplest case, one can graphically predict resistivity
from plots such as Figure 4 for 1000/T(°K) = 2.4 (144°C, 291°F)
or calculate the value from the given equation. If the combined
lithium plus sodium atomic percentage of an ash is 1.0 percent,
the resistivity is 1.2 x 10'l ohm cm. This value, of course,
is dependent on the quality of the laboratory measurement, is
restricted to an environment containing 9 volume percent water
and no sulfur trioxide, and relates to an ash under an applied
voltage gradient of 2 kV/cm. Subsequently, it will be shown
how the above predicted resistivity value can be changed to re-
flect other field strength levels and environmental conditions.
It would be convenient if the exercise just described could
be repeated to predict the resistivity at all temperatures using
the Figures 2 through 7. However, it is apparent that at the
higher temperatures, where 1000/T(°K) = 2.0 or particularly 1.6,
the relationship between resistivity and the combined atomic
concentration of lithium and sodium degrades. This is apparent
from the decrease in R values and the significant change in slope
of the regression analysis curves.
These observations suggest that in the higher temperature
range other ash compositional factors may influence the measured
resistivity values. Previously investigators have shown that
for certain ash types the concentration of iron10 and the alkaline
earth elements11 (magnesium and calcium) affect resistivity.
The measured resistivity data for 1000/T(°K) = 1.6 were examined
with respect to these two compositional factors.
The as-measured resistivity data shown in Figure 7 were
normalized to the values that would be expected if all ashes
contained 0.4 atomic percent lithium plus sodium. This was done
using an arbitrarily selected slope of -2.0, because the low
21
-------
temperature data indicated that the final slope would be approxi-
mately -2; see Figure 2. The Figure 7 resistivity values normalized
to 0.4 atomic percent lithium plus sodium were plotted as a func-
tion of atomic percent iron to establish a correlation between
resistivity and iron concentration for those ashes having a very
limited range of magnesium plus calcium (1.9 to 2.7 atomic per-
cent) . Using this resistivity-iron correlation, the remaining
Figure 7 resistivity values normalized to 0.4 atomic percent
lithium plus sodium were also normalized to 1.0 atomic percent
iron and then plotted to establish a correlation between resis-
tivity and the atomic percentage of magnesium plus calcium.
The correlations established between resistivity and iron con-
centration and between resistivity and the combined concentra-
tions of magnesium and calcium allowed a secondary correlation
to be established between resistivity and the combined lithium and
sodium concentration for ashes normalized to constant values
of 1.0 atomic percent iron and 2.5 atomic percent magnesium plus
calcium.
This entire procedure was then reiterated to include the
data normalized with respect to the alkaline earths for those
ashes used to develop the initial resistivity-iron correlation.
This extended the number of ashes that could be utilized in the
correlation. Figure 8 shows the second iteration of the resis-
tivity-iron correlation using those ashes having relatively low
magnesium-calcium concentrations that are generally similar to
ashes produced from coals of the Eastern United States. The
linear regression analysis yielded a slope of -0.9696 and a coef-
ficient of correlation of -0.88. Figure 9 shows the second itera-
tion of the resistivity-calcium+magnesium correlation using those
ashes that are generally similar to ashes produced from coals
of the Western United States. The linear regression analysis
yielded a slope of +1.2370 and a coefficient of correlation of
+0.78.
Using the correlations shown in Figures 8 and 9, the resis-
tivity data were normalized to 2.5 atomic percent magnesium plus
calcium and 1.0 atomic percent iron. These data were then plotted
as a function of lithium plus sodium concentration using a nega-
tive slope of about 1.7 obtained from the first iteration. The
results are shown in Figure 10. Comparison of Figure 10 with
Figure 7 shows the dramatic decrease in data scatter; R changed
from -0.73 to -0.95, and the slope increased from -1.2630 to
-1.8916. This indicates that the data scatter and seemingly
lesser effect of lithium and sodium on resistivity at high tempera-
tures as implied by Figure 7 was due to the wide variation in
iron and alkaline earth concentrations. Furthermore, it is ap-
parent that iron and the alkaline earths affect high tempera-
ture resistivity.
The linear regression analyses shown in Figures 8, 9, and
10 have been reproduced without the data points in Figure 11.
The important characteristics of each curve are given. This
22
-------
10"
O40
10
"
o
z
<
>
LU
oc
Q
Ul
N
108
I
y = ea • x*1
Iny = a + b In x
a = 22.5963
b = -0.9696
R =-0.88
240
O38
0.1
1.0
IRON CONCENTRATION IN ATOMIC PERCENT
10.0
Figure 8. Second iteration of Figure 7 resistivity data.
Normalized to 0.4% Li + Na and 2.5% Mg + Ca.
23
-------
10"
o
o
<
<
LU
DC
O
LU
N
OC
O
109
108
029
O28
O 18
41 O
310
O 21-
ASH NO. 121
y = ea • xb
In y = a + b In x
where:
a = 20.9236
b = 1.2370
R = 0.78
1.0 10.0
MAGNESIUM + CALCIUM CONCENTRATION IN ATOMIC PERCENT
100.0
Figure 9. Second iteration of Figure 7 resistivity data.
• Normalized to 0.4% Li + Na and 1.0% Fe.
24
-------
o
(O
r-
II
O_
I-
^
>
O
£
u
iu
o
LU
N
OC
O
a = 20.5926
b = -1.8916
R =-0.95
0.1 1.0 10.0
LITHIUM + SODIUM CONCENTRATION IN ATOMIC PERCENT
Figure 10. Resistivity versus lithium + sodium; baseline
conditions at 352°C. Data normalized to
1.0% iron and 2.5% calcium + magnesium.
25
-------
1012
10
11
u
5
I
o
I
§
CO
HI
3 X
V
/ 1
\
\
\
\
\
\
= ea
= a +
/
/
N
^
\
\
• X
b In
/
/
•v
\
y
\
\
>
b
X
/
f
{
\
\
\
f
f
f
\
f^
\
—
/
/
,**
\
12
f
f
f
^
\
\
.0
t
t
f
<
\
\
K
/
/
/
/>6
'
Ll^
>.• ro
a =
b =
~ LINE f
FOR- 1
*" a = 20.
- b = -1.1
/
/
/
L
F
a
NE
OR:
= 2
= 1
IE B
R: Fe
22.5963
-0.9696
k
.i + N
5926
3916
«
/
C
M(
0.9
.23
/
} +
23
70
/
C
5
/
/
a " -
0.1 1.0 10.0
CONCENTRATION IN ATOMIC PERCENT FOR Li + Na. Fe, OR Mg + Ca
100.0
Figure 11. Predicted resistivity under baseline test conditions at 352°C
as a function of the atomic percentage of lithium + sodium,
iron and magnesium + calcium.
26
-------
figure can be used to graphically determine the predicted resis-
tivity for a reciprocal absolute temperature of (1000/°K) = 1.6
(352°C) and the previously described baseline test conditions.
An example of this prediction is shown in the figure. The fic-
tive fly ash example contains in atomic percentage: 0.5% lithium
plus sodium, 1.9% iron and 12.0% magnesium plus calcium. Fig-
ure 11 is entered at point 1 using the atomic concentration of
lithium plus sodium. At point 2, on Line A, it is indicated
that a resistivity of 3.2 x 109 ohm cm would be expected if the
fly ash contained 1.0 atomic percent iron and 2.5 atomic percent
magnesium plus calcium. The resistivity value is translated
laterally to point 3, 1.0 atomic percent iron. By moving from
point 3 in a direction parallel to Line B to the assigned iron
concentration at point 4, one finds the resistivity value, 1.7
x 109 ohm cm, for the fictive ash excluding the alkaline earth
effect. By repeating the previous step, however, with respect
to the combined concentration of magnesium and calcium (Line
C), one arrives at point 6, 1.2 x 1010 ohm cm, the predicted
resistivity for the ash composition and test conditions stated.
It will be subsequently shown how this predicted value is adjusted
for greater field strength and other temperatures.
Effect of Environmental Water Concentration
Sixteen ashes were selected from the large group available
to examine the effect of water concentration on resistivity.
The selection was made to have the widest possible variation
in ash chemical composition. Each ash was evaluated with the
previously described baseline resistivity test utilizing approxi-
mately 5, 9, and 14 volume percent water vapor in the environ-
ment. An example of the data acquired is shown in Figure 12
for ash #105.
For this particular ash, the effect of water vapor on resis-
tivity was detected first at about 275°C and showed a maximum
effect at the lowest test temperature. As the concentration
of water increased, the maximum resistivity decreased and shifted
to higher temperatures. These observations are similar to those
made by other investigators.12'13 For the example chosen, the
high temperature data reproduced almost perfectly for the three
tests. Because of the differences in porosity among tests of
a single ash and the normal variation due to the precision of
the resistivity measurement, this was not true for each set of
three tests for all sixteen ashes examined. When data scatter
occurred, the entire resistivity-temperature curve was shifted
so that the three curves were superimposed in the high tempera-
ture region, where 1000/T(°K) = 1.6 to 1.4. The superimposed
position was the average value for the three tests.
When the resistivity data presented in Figure 12 are plotted
as a function of water concentration for various isotherms, a
series of more-or-less straight lines result. Water concentra-
27
-------
1012
x
o
E 10"
—
V)
UJ
cc
§
oc
I-
u
oc
CO
108
14.1 °
I
I
I
I
I
I
I
I
1000/T(°K)
°C
°F
3.2
40
103
3.0
60
141
2.8
84
183
2.6
112
233
2,4
144
291
2.2
182
359
2.0
227
441
1.8
283
541
1.6
352
066
1.4
441
826
1.2
560
1041
TEMPERATURE
Figure 12. Resistivity as a function of water concentration for Ash No. 105.
28
-------
tion can be expressed as relative humidity, partial pressure,
or volume percentage as in the case of Figure 13. This figure
shows the pronounced effect that environmental water concentration
can have on fly ash resistivity especially at the lower, cold-
side temperatures. At constant temperature and in an environment
containing no sulfuric acid vapor, the surface conductivity of
a specific fly ash is directly dependent on the interaction be-
tween the ash surface and the water vapor. Therefore, the linear
relationship shown in Figure 13 is expected. Sixteen sets of
data similar to those shown in Figure 13 were accumulated for
the sixteen ashes used in this part of the investigation.
The slopes, Sw, of the curves such as those shown in Fig-
ure 13 were determined for each temperature of interest for each
of the sixteen ashes utilized. From these data the average,
maximum, and minimum slopes were plotted as a function of_recip-
rocal absolute temperature as shown in Figure 14. Since Sw is
a parameter defining the effect of environmental water concentra-
tion on resistivity, it is not surprising to find a linear re-
lationship when this value is plotted on a logarithmic scale
versus reciprocal absolute temperature. This relationship holds
because a similar one exists for the relative humidity of a given
absolute water concentration as a function of temperature. As
the relative partial pressure of water vapor increases, the
residence time of a water molecule on the ash surface increases.
The variation in
at temperatures lower
perature the effect of
consideration, and the
values increases. In
effect seems sensitive
tion for water vapor.
temperature was zero.
Sw among ashes was not particularly great
than about 180°C (355°F). Above this tern-
water vapor on resistivity becomes a minor
variation between maximum and minimum
the high temperature region, the small
to the affinity of a specific ash composi-
The minimum value of S at the highest
w J
The use of Sw is illustrated by the expression
log p = log
S
(Cw - Cb>Sw
(2)
where
log p = the logarithm of the surface resistivity for
s a specific lithium plus sodium concentration
and water concentration, C,,;
Yt
log p^ = the logarithm of the baseline surface resis-
tivity for a specific lithium plus sodium con-
centration and a water concentration of 9
volume percent (values obtained from Figures
2-6);
C = the volume percent water concentration to
w
which the resistivity is to be adjusted;
29
-------
1012
EV
«x 1011
cc i
D I-
co to
<"
109
I I
I I I
1000
T°K
_ • 2.2
V 2.4
• 2.6
A 2.8
I I I I
I I I I
5 10
VOLUME PERCENT WATER CONCENTRATION
15
Figure 13. Resistivity as a function of environmental water
concentration for various test temperatures, ash 105.
30
-------
o
CM
X
s?
10-n
I
I
I
I
I
I
T
T
In Sw = a + bx
a = -8.0442
b = 2.3033
R = 0.998
x = 1000/T(°K)
I
1000/T(°K) •
°C
°F
3.2
40
-103
3.0
60
141
2.8
84
183
Z6
112
233
Z4
144
291
2.2
182
359
2.0
227
441
1.8
283
541
1.6
352
666
1.4
441
826
1.2
560
1041
TEMPERATURE
Figure 14. Effect of temperature on the resistivity-water concentration
relationship, all ashes.
31
-------
C = the water concentration used in establishing
Figures 2-6, 9 volume percent; and
S = A log ps/A%H20; for example, -0.0808 for
1000/T(°K) = 2.4 and water concentrations
between 5% and 15%.
After determining the resistivity for a given atomic per-
centage of lithium plus sodium in an environment containing 9%
water vapor from Figures 2-6, the resistivity values for other
water concentrations can be calculated from Equation 2, using
values of Sw taken from Figure 14. If desired, a series of
curves relating resistivity, water concentration, and temperature
can be generated. The computer program for resistivity predic-
tion described later in this report utilizes the expression
shown in Figure 14.
Effect of Applied Electrical Stress
Since electrostatic precipitators are often operated at
or near the point of dielectric breakdown of the ash layer, it
is desirable to predict and/or measure fly ash resistivity at
this electrical stress level. The ASME, PTC-28 suggests measur-
ing laboratory resistivity at 90% of breakdown stress, and some
iri situ resistivity measurements are reported at about this
point. However, a research program involving many fly ash speci-
mens and a multiplicity of test conditions cannot readily comply
with this procedure.
Resistivity as a function of applied electrical stress was
determined for the selected sixteen fly ashes at one temperature
(160°C) and one set of environmental conditions (9 volume percent
water). Using an ash layer thickness of 6 mm, the applied voltage
was increased until electrical failure occurred or a voltage
gradient of 10 kV/cm was reached. Figure 15 shows the minimum,
average, and maximum effect of increased voltage gradient on
resistivity for the sixteen ashes tested. The data are expressed
as relative resistivity plotted on a logarithmic scale versus
applied voltage gradient. Relative resistivity was calculated
as the ratio of the resistivity measured at some field strength,
E, to the value obtained at 2 kV/cm, the baseline voltage gradient
used in this work. Similar response of resistivity to applied
voltage gradients has been found by others.1"
The following algebraic expression was used to adjust resis-
tivity values taken at conventional stress levels in the labora-
tory to reflect the effect of higher voltage gradients:
log p = log p + (E - E, )S (3)
tL EZ be
32
-------
I-
>
V)
UJ O
u
_i o
UJ Z
oc oc
10.0
1.0
0.1
2 4 6 8 10
ASH LAYER FIELD STRENGTH, E, in kV/cm
Figure 15. Relative resistivity values as a function of applied
ash layer voltage gradient.
33
-------
where
log PE = the logarithm of resistivity adjusted to some
field strength, E;
log p = the logarithm of resistivity with E = 2 kV/cm;
£2
E = the applied voltage gradient to which log
PE is to be adjusted;
E, = the applied voltage gradient used in estab-
lishing the base line data, 2 kV/cm; and
S = A log p/AE = -0.030 (the average value for
e sixteen test ashes at 160°C and an applied
voltage gradient range of 2 to 10 kV/cm).
Until additional information is available, the technique for
predicting resistivity described in Section 7 will utilize the
average Se at all temperatures and test conditions and for all
ash compositions. Unless otherwise noted, resistivity is pre-
dicted for E = 10 kV/cm only. That is, after the resistivity
is predicted as a function of ash composition and water concen-
tration at a voltage gradient of 2 kV/cm, it is adjusted to the
value expected at 10 kV/cm. It is believed that in most cases
this adjusted value will be equivalent to that determined at
dielectric breakdown.
In the course of establishing a means of adjusting resis-
tivity data taken at low stress levels to levels associated with
precipitator operation, several interesting observations have
been made. They are related below because they may affect thoughts
pertaining to electrical breakdown. In the laboratory using
ash layers about 6 mm thick, dielectric failure usually occurred
at voltage gradients of 4 to 12 kV/cm. Iri situ field test deter-
minations with a point-plane probe using the parallel plate mode
of operation show dielectric failure generally happens between
8 and 20 kV/cm. The higher values found with the point-plane
device probably are due to the relatively thin ash layer under
test, typically 1 mm.
The observation that dielectric strength increases with
decreasing specimen thickness is commonly noted with regard to
glasses and ceramic dielectrics.15 In this laboratory it has
been shown that the ash layer field strength at dielectric failure
increases significantly as the ash layer thickness is decreased.
Figure 16 shows resistivity as a function of ash layer field
strength for two identical ash specimens tested simultaneously.
The only difference between the two tests was that one cell had
an ash layer thickness of 0.70 cm while the other was 0.24 cm.
The applied voltage to each cell was identical. Although the
34
-------
o
5
o
h;
>
I-
W
111
oc
109
10s
I
I
I
I
ASH LAYER
THICKNESS
O 0.70 cm
Q 0.24 cm
4 8 12 16
ASH LAYER FIELD STRENGTH, E, in kV/cm
Figure 16. Resistivity as a function of field strength for ash
layers of two thicknesses.
20
35
-------
layers were of two significantly different thicknesses, dielectric
failure occurred at the same applied voltage, 4.65 kV. Conse-
quently it was recorded that the "spark", "arcing", or dielectric
failure occurred at an average stress of 6.7 kV/cm and 19.6 kV/cm
for the otherwise identical thick and thin specimens, respectively.
These data reaffirm the general observation that greater
average electrical stress across an ash layer decreases the
resistivity. This is probably a result of the increased number
and/or the increased mobility of charge carrying ions. It is
also suggested that average field strength has little effect
on dielectric failure since the thick and thin specimens failed
at the same voltage. Failure may have occurred at some location
in the ash layer on the basis of a "weakest link" that is common
to thick or thin specimens. Arguments can be presented that
the failure is related to the fly ash itself or to the gas phase
in the ash interstices.
Also it is interesting to note several manifestations of
an ash layer dielectric failure during resistivity determina-
tions. Figure 17A shows a resistivity test cell in the environ-
mental test chamber with the upper electrode removed after a
failure had occurred. The B view of this figure shows the lower,
negative, cup electrode. Figure 18 shows the upper and lower
electrodes after the removal of the ash. The evidence of arcing
between these two electrodes is obvious and in proper register
with the damaged ash layer.
Detailed examination of failure regions occurring during
tests at 160°C provided the information schematically shown in
Figure 19. Illustration number one shows the observed situation
that suggests an explosion took place leaving a clean cavity.
Illustration two, a cavity with fused ash at the surface, and
illustration three, a column of fused ash, show the effect of
a thermal excursion probably in excess of 1000°C. The mechanism
of dielectric failure has not been studied in this investigation.
However, the observations suggest that ohmic heating at particle
interfaces may play a role.
Some of these observations suggest that the dielectric fail-
ure of fly ash layers is imperfectly understood and that additional
research is desirable. A list of experimental parameters would
include: ash particle size distribution, ash layer porosity,
ash layer thickness, environmental composition and pressure,
temperature, ash composition including combustibles, and test
procedures.
Effect of Sulfur Trioxide
General Observations—
Experimental problems encountered in attempting to quanti-
tatively determine the effect of sulfur trioxide on the resis-
tivity of fly ash in the laboratory severely delayed the completion
36
-------
D
Figure 17. Photographs of a resistivity test cell after dielectric failure.
37
-------
IMCTRIC i| 2
liiiifiiiimnlii
Figure 18. Photographs of the upper and lower electrodes
from the test cell shown in Figure 17.
38
-------
PLANE OF
UPPER ELECTRODE
1. OPEN CAVITY WITH "DRY" WALLS
2. OPEN CAVITY WITH "FUSED" WALLS
3. SOLID COLUMN OF "FUSED" PARTICLES
Figure 19. Schematic cross-section of cavities occurring in
ash layers having experienced dielectric failure.
PLANE OF
LOWER ELECTRODE
39
-------
of this research project. The solution of the experimental dif-
ficulties has been previously discussed in Reference 6, in which
the test equipment and procedure used with sulfur trioxide in-
cluded in the environment is described. Because the time schedule
was already significantly extended, only a few ashes were investi-
gated with respect to the sulfur trioxide-resistivity relation-
ship. The results were very interesting and demonstrated the
pronounced effect the environmental sulfur trioxide concentration
can have on the resistivity of fly ash. At this time it is ob-
vious that the data base is small, and one should therefore use
the quantitative information with cautious reserve. Under an
Environmental Protection Agency grant, additional research will
be conducted to expand this data base.
Experimentation using sulfur trioxide was somewhat different
from the baseline work. In these experiments the fly ash under
test was thermally equilibrated three hours in dry air at the
temperature of interest. Resistivity was determined, water vapor
was added to the environment, and resistivity was determined
again. After the ash had equilibrated with the air-water environ-
ment, the desired concentration of sulfur trioxide was injected,
and resistivity as a function of time was determined. Using
the asymptotic approach of the resistivity to a minimum value
as the end point, about an eighteen-hour exposure was required
to equilibrate the ash volume under test with the sulfuric acid
vapor in the environment.
Figure 20 shows a typical record of resistivity versus time
of exposure to an environment consisting of air, 9 volume percent
water, and 9 ppm of sulfur trioxide at 147°C. At time equal
zero hours, the resistivity was 2 x 1013 ohm cm, and the water
vapor was introduced. Within ten minutes the resistivity had
decreased to 4 x 1010 ohm cm as the water vapor equilibrated
with the ash. At time equal 0.5 hours the sulfur trioxide injec-
tion was started, and after about 1.5 to 2.0 hours, the resis-
tivity started to decrease. After 16 to 18 hours of exposure,
the resistivity asymptotically approached a minimum value of
2 x 109 ohm cm. It apparently took this length of time for
the sulfuric acid vapor to penetrate the ash layer (1 mm) and
reach an "equilibrium" with the ash volume under test. At time
equal nineteen hours the sulfur trioxide injection was stopped.
The effect of the sulfuric acid immediately started to disappear
and had essentially ceased within 2 to 3 hours after the injec-
tion was discontinued. The time required to eliminate the effect
of the sulfuric acid is not related to the time required to re-
move the agent from the environment, because this apparatus
allows for a 99% dilution of an environment in six minutes.
The very rapid disappearance of the effect of sulfur trioxide
when injection is stopped circumstantially suggests that the
adsorbed sulfuric acid participates directly in the surface
40
-------
10
11
V 1010
5
o
>*
H
>
—
Ul -
oc 109
SO3
ON
108
S03
OFF
I
10 12 14
TIME, hours
16
18
20
22
24
Figure 20. Resistivity-time after injection of 9 ppm sulfur trixoide
in an environment of air containing 9% water.
41
-------
conduction process. Since there is no lasting effect, one cannot
equilibrate an ash with sulfuric acid vapor, stop the injection,
and then measure the effect. Neither can one expect to measure
the effect of adsorbed acid after removing an ash from a com-
mercial facility for subsequent testing in a conventional labora-
tory device. Resistivity as a function of time for various levels
of sulfur trioxide concentration has been previously demonstrated.16
Information such as that shown in Figure 20 was obtained
for several fly ashes from eastern and western coals using three
sulfur trioxide concentrations, three water concentrations, and
several test temperatures. Typical data are shown in Figure
21 for ash #143. The upper curve for the entire test temperature
spectrum (circular symbols) was obtained using a simulated flue
gas containing 9 volume percent water and no sulfur trioxide.
The four data points indicated by hexagonal symbols were taken
from curves similar to that in Figure 20 and represent the mini-
mum resistivity at four different temperatures using an environ-
ment containing air, 9 volume percent water, and 9 ppm sulfur
trioxide. A dashed curve is drawn to link the data acquired
in the presence of sulfur trioxide with the high temperature
data obtained without this agent. The low temperature portion
of the resistivity-temperature curve shows the dramatic effect
adsorbed sulfuric acid has on fly ash resistivity. This ash
was the only one examined at four temperatures for a given set
of environmental conditions. These data suggest that, under
the influence of sulfuric acid vapor, the logarithm of resis-
tivity is a linear function of absolute reciprocal temperature.
This observation is reasonable when sulfuric acid vapor provides
the principal conduction mechanism and the temperature is above
the acid vapor dew point. Under these conditions, the resis-
tivity will be dependent on the amount of acid vapor adsorbed
by the fly ash. For a specific fly ash, the amount of acid vapor
adsorbed is a function of the ratio of the given acid vapor
pressure to the saturated acid vapor pressure for a specific
temperature. The logarithm of this ratio is also a linear func-
tion of reciprocal absolute temperature. Therefore with increas-
ing reciprocal absolute temperature, the logarithm of the acid
vapor pressure ratio increases linearly and the logarithm of
the resistivity decreases linearly.
Comments on the Sulfuric Acid Conduction Mechanism—
In order to better interpret experimental observations re-
garding the effect of sulfuric acid vapor on fly ash resistivity,
a chemical transference experiment was conducted in an environ-
ment including sulfuric acid vapor. The objective of this experi-
ment was to determine whether the migration of any chemical
species under the influence of an applied electrical stress could
be detected. The detection of a mass transfer would offer help
in developing an explanation of the electrical conduction mechan-
ism.
42
-------
1012
11
10
o
*
I
t 1010
109
108
i i i i i n I i i r
ASH NO. 143
O AIR+ 9% WATER
O AIR + 9% WATER +
9 ppm SULFUR TRIOXIDE
I
I
I
I
I
I
I
I
1000/T(°K) •
°C
°F
3.2
40
•103
3.0
60
141
2.8
84
183
2.6
112
233
2.4
144
291
2.2
182
359
2.0
227
441
1.8
283
541
1.6
352
666
1.4
441
826
1.2
560
1041
TEMPERATURE
Figure 21. Resistivity-temperature relationship with and without
sulfur trioxide injection.
43
-------
A sample of ash was equilibrated in an air environment con-
taining 9 volume percent water and 9 ppm sulfur trioxide at 140-
150°C. Under these conditions, the specimen had a resistivity
value of 1 x 108 ohm cm. A direct current voltage was contin-
uously applied, and current was recorded as a function of time.
After approximately 38 coulombs of electricity had been passed,
the test was discontinued, and the volume of ash that had been
under electrical stress was divided into thirds-- the volumes
contiguous to the anode and cathode, respectively, and the center
volume. These specimens, as well as a specimen that had not
been under test, were chemically analyzed. This information
is shown in Table III.
The data reported as sodium oxide suggest that sodium ions
migrate from the region of the anode to the volume of ash con-
tiguous with the cathode. This qualitatively indicates that
sodium participated in the conduction process as a charge carrier.
Knowing the amount of electrical energy conducted during the
experiment, 38 coulombs, and estimating the mass of ash involved,
one can calculate the approximate concentration of sodium oxide
that should be found in the ash volume contiguous with the cathode
if only sodium were the charge-carrying species. This value
is about 13% sodium oxide.
Since it was experimentally found that the sodium oxide
concentration at the cathode was increased from about 3.2 to
3.8% instead of the calculated 13%, it can be concluded that
sodium was only a minor participant in the conduction process.
No other cation included in the chemical analysis showed evidence
of migration.
It can be assumed that the sulfuric acid vapor adsorbed
on the surface of the fly ash directly participated in the con-
duction process. The mechanism by which this occurs is_not clear.
It would seen unlikely that the large sulfate anion, S0\, would
be capable of migration. In fact, the data in Table III do not
reflect an excess of SO^ at the anode. This, however, does not
preclude the participation of hydrogen ions in the charge trans-
fer process. The mechanism of the charge transfer and means
of maintaining electrostatic balance are unclear.
If the adsorbed acid vapor principally functioned by increas-
ing the interparticle contact by capillary condensation, one
would expect an enhanced mass transfer of the normal charge carry-
ing species, sodium, and an attenuation of current with increased
time of continuously applied voltage. Neither of these occurred.
Furthermore, one would not expect the almost instantaneous degrada-
tion of current carrying capacity when the sulfur trioxide injec-
tion is discontinued.
44
-------
Table III.
Chemical Analysis of Ash Specimens
Used in the
Chemical Transference Experiment
Specimen
Not Tested
0.01 *
3.2
0.7
1.2
15.1
5.0
1.0
Test
Specimen
Contiguous
with Anode
0.01
2.9
0.8
1.2
14.6
5.0
1.0
Test
Specimen
Center
Section
0.01
3.3
0.7
1.1
15.1
5.0
1.1
Test
Specimen
Contiguous
with Cathode
0.01
3.8
0.8
1.1
14.7
5.1
1.1
Oxide
Li20
Na2O
K20
MgO
CaO
Fe203
Ti02
Soluble Sulfate
SCU 0.34
4.0
5.4
4.9
*Expressed as weight percent of total sample.
45
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In the transference experiment, the magnitude of current
resulting from the applied voltage remained uniform from the
beginning to the end of the test. This observation is consistent
with the lack of evidence for significant chemical migration
or transfer. If the principal source of conduction is a contin-
uously supplied source of adsorbed sulfuric acid, one would not
expect an attenuation of current with time as in the case when
conduction is dependent on a finite concentration of mobile cations
such as sodium ions. Under conditions involving simulated flue
gas containing no sulfur oxides at both 150°C and 350°C when
alkali metal ions are the principal charge carriers, the trans-
ference experiment current decreases with time, asymptotically
approaching some minimum level. This decrease in current is
caused by the depletion of carrier ions at the anode and exces-
sive buildup of these ions at the cathode.
The results from the above-described chemical transference
test offer strong evidence that the adsorption of sulfuric acid
vapor on fly ash provides a separate and distinct conduction
mechanism. The observations suggest that this mechanism is in-
dependent of fly ash composition, except with respect to the
acid vapor-fly ash surface affinity. Certain other circumstan-
tial evidence also supports the view that the adsorbed acid pro-
vides a separate mode of conduction. One such observation is
the transient effectiveness of the sulfuric acid vapor illus-
trated in Figure 20. Even though the electrical stress was only
applied intermittently, the effect of the acid vapor ceased
quickly after injection was stopped, and the conduction process
reverted to that provided by the mobile alkali metal ions. It
has also been observed that the injection of 9 ppm sulfur trioxide
resulted in resistivities of 1-5 x 108 ohm cm for two fly ashes
having, respectively, resistivity values of 1 x 1010 ohm cm and
1 x 1012 ohm cm before injection. This indicates that the effect
of the acid vapor adsorbed on the ash provides a conduction mode
independent of that related to the interaction of water vapor
and fly ash composition.
From the foregoing, it is visualized that under cold-side
precipitator conditions two parallel conduction mechanisms are
available. At very low concentrations of sulfuric acid vapor
the electrical conduction in fly ash is principally influenced
by the charge-carrying ability of the alkali metal ions as af-
fected by the interaction of water vapor and the ash surface.
At high concentrations of sulfuric acid vapor, perhaps 10 ppm
in equilibrium with the ash, the conduction process is princi-
pally controlled by the adsorbed acid. At intermediate concen-
trations of acid vapor, both mechanisms contribute to the con-
duction process. Subsequently, the effect of environmental
sulfur trioxide concentration on the predicted fly ash resis-
tivity is incorporated by using the expression for calculating
46
-------
the resultant resistance for two or more parallel resistances.
This allows the effect of both conduction modes to be appreciated.
Incorporation of the Environmental Sulfur Trioxide Concentration
into the Resistivity Prediction—
Tests illustrating the effect of sulfur trioxide concentra-
tion on resistivity were principally conducted at 148-149°C
(1000/T(°K) = 2.37) using an environment of air containing 9
volume percent water. The concentrations of sulfur trioxide
injected were nominally 5 and 10 ppm. The data acquired under
these conditions, using several fly ashes from eastern and western
coals, are shown in Figure 22. The data points represent minimum
resistivity values taken from curves such as the one shown in
Figure 20 plotted against the measured concentration of condens-
able sulfuric acid vapor (expressed as sulfur trioxide in ppm)
found in the test environment at the chamber outlet after the
ash under test had been exposed for about eighteen hours.
Examination of Figure 22 shows the very pronounced effect
sulfuric acid vapor has on resistivity and that fly ashes pro-
duced from western coals are affected to a greater degree than
ashes from eastern coals for a given sulfur trioxide concentration.
This observation can be justified on the basis of the generally
more alkaline ashes from western coals having a greater affinity
for the acid vapor.
An average value was calculated for each of the four data
clusters, and straight lines were constructed connecting the
data clusters for the eastern and western ashes, respectively.
The following algebraic expressions define the constructed lines:
for eastern ash; where Ca + Mg ^ 3.5% or K ^ 1.0%,
log Pa IOOO/T('K) = 2.37 = 12.9676 - (0.3075 x ppm S03) (4)
and for western ash; where Ca + Mg > 3.5% and K < 1.0%,
Io9 Pa iooo/T(°K> = 2.37 = 12.1612 - (0.3712 x ppm S03).(5)
There are obviously weaknesses in this proposition. It is pos-
sible that some of the resistivity values at the 5 ppm sulfur
trioxide level are influenced by the inherent conduction related
to the alkali metal ions. Also, one would expect the intercepts
at zero sulfur trioxide to be the same value for each line in
Figure 22. Acknowledging these shortcomings, it is believed
that for an initial effort, these expressions can be used to
predict the resistivity of fly ash as a function of the calculated
concentration of sulfur trioxide in the environment.
47
-------
1012
I I I I
EASTERN ASH: where,
Ca + Mgl3.5% or K > 1.0%
g 10
11
o
o
o
<
5 1010
u
§
I
O
£ io9
WESTERN ASH: where,
Ca + Mg > 3.5 % and K<1.0%
EQUATION 5'
108
I
I
I
4567
SULFUR TRIOXIDE IN PPM
10
Figure 22. The effect of sulfur trioxide on resistivity at 1000/T(°K) = 2.37
in an air - 9% water environment.
48
-------
Figure 22 and the expressions (4) and (5) are used to deter-
mine the resistivity of fly ash as a function of sulfur trioxide
concentration at one temperature (1000/T(°K) = 2.37) and one
water concentration (9 volume percent). To be able to predict
resistivity based on the combined conduction modes due to the
water vapor-ash composition interaction and due to the presence
of adsorbed sulfuric acid vapor, one needs to know the effect
on resistivity of the sulfuric acid vapor as a function of tem-
perature. A few isothermal resistivity tests were conducted
at several temperatures using a constant environment consisting
of air, 9 volume percent water, and 9 ppm sulfur trioxide. These
data are presented in Figure 23.
It is again apparent that for a given set of conditions
the resistivity as influenced by the adsorption of sulfuric acid
vapor is attenuated to a greater degree for ashes from western
coals. Since several of the western and eastern ashes were very
similar with respect to physical characteristics, it is suggested
that this effect is related to the greater chemical affinity
of the more alkaline western ashes for the acid vapor.
Figure 23 exhibits the very pronounced dependency of the
sulfuric acid conduction mode on temperature. It was previously
suggested that the observed linear positive relationship between
resistivity and temperature is a reflection of the linear, nega-
tive relationship between the relative partial pressure of sulfuric
acid vapor and temperature. With respect to the sulfuric acid
conduction mode, the resistivities of the eastern ashes are par-
ticularly sensitive to temperature. This sensitivity is great
enough that temperature gradients commonly found within a pre-
cipitator can cause one region to perform satisfactorily while
another region demonstrates poor performance.
The difference in the slope of log p versus 1000/T(°K) curves
shown in Figure 23 could be related to differences in adsorp-
tion energy as a function of variation in ash composition or
to the position of the acid vapor dew point. For the test condi-
tions used, the dew point was about 1000/T(°K) = 2.45 (270°F).
At the dew point, homogeneous condensation occurs and other
factors are no longer of great influence. One would expect
resistivity to dramatically decrease as the dew point is reached.
In Figure 23, it appears that the curves are converging at the
dew point.
In a few experiments involving sulfur trioxide, water con-
centration was the variable. Ashes from both eastern and western
coals were subjected to tests in which the injected concentration
of sulfur trioxide, as well as all other factors, were constant
while the water concentration was varied: 5, 9, and 15 volume
percent. Although water concentration influences the relative
49
-------
1012
10"
o
£ 101°
t-
—
w
LU
cc
109
108
EASTERN ASH: where,
Ca + Mgi3.5% or K > 1.0%
I
I
I
I
WESTERN ASH: where,
Ca + Mg > 3.5% and K < 1.0%
I
I
1000/T(°K)
°C
°F
3.2
40
103
3.0
60
141
2.8
84
183
2.6
112
233
Z4
144
291
2.2
182
359
2.0
227
441
1.8
283
541
1.6
352
666
TEMPERATURE
Figure 23. Resistivity versus reciprocal absolute temperature in an
environment of air containing*' 9 ppm sulfur trioxide
and 9% water.
50
-------
partial pressure of the sulfuric acid vapor, increasing the water
concentration had no effect on resistivity. The value was ap-
parently dependent only on the concentration of sulfur trioxide.
As water concentration increases, the relative partial pressure
of sulfuric acid vapor increases. This should cause an increase
in adsorption and a decrease in resistivity. It is possible
that for the specific experimental conditions used, the amount
of vapor adsorbed as a function of relative partial pressure
lies on a plateau of the adsorption-relative partial pressure
curve. This possibility has been explicitly defined in sorption
studies18 involving fly ash and sulfur trioxide.
With respect to the principal objective of this research,
the prediction of resistivity, both slopes shown in Figure 23
are utilized. After determining the resistivity at 1000/T(°K) =
2.37 for the specific sulfur trioxide concentration of interest
using Equations (4) and (5) , the line defining resistivity as
a function of temperature is established using the following
expression :
log Pa iOQO/T = Io9a 1000/T = 2.37 + [S (2.37 - 1000/T)] (6)
a
where
log pa 1000/T = logarithm of resistivity for a specific
sulfur trioxide concentration and a
selected value of 1000/T(°K) ;
log p = value calculated from Equation (4) or
a looo/T = 2.37
(5) for a specific suifur trioxide con
centration, ash composition, and a
reciprocal absolute temperature of
1000/T(°K) = 2.37; and
S = slope of log pa versus 1000/T (°K) =
10.1048 for ashes in which Ca + Mg ^
3.5% or K ^ 1.0% and 5.6673 for ashes
in which Ca + Mg > 3.5% and K < 1.0%.
T = temperature in degrees Kelvin
Expression (6) yields a curve of predicted resistivity as
a function of temperature based on the estimated sulfur trioxide
concentration in the flue gas and the chemically defined type
of fly ash. It has been previously pointed out that the evidence
suggests that conduction due to adsorbed sulfuric acid vapor
is totally independent of other mechanisms. Also, in the absence
of sulfur trioxide, it is known that conduction is dependent
on the charge-carrying capability of the alkali metal ions and
is controlled by the interaction of water vapor and the fly ash
surface. Obviously, under certain conditions both conduction
mechanisms can be operative. The combined effect of the two
51
-------
mechanisms is established by determining the resultant resis-
tivity using the equation for parallel resistances. In the fol-
lowing section the mechanics of combining the effects of the
principal factors controlling the resistivity of fly ash will
be given. The result is a prediction of resistivity as a func-
tion of temperature for a given coal and coal ash composition.
52
-------
SECTION 7
RESISTIVITY PREDICTION METHOD
The resistivity of a collected layer of fly ash is affected
by certain physical, chemical, and electrical factors. It is
known that the ash layer porosity and the available conducting
surface resulting from the microplacement of a given particle
size distribution have a significant effect on resistivity.
However, since there is presently no way of anticipating these
factors from core bore samples, an attempt was made to circumvent
this problem by incorporating into the study a large number of
fly ash specimens having a wide range of properties. Hopefully,
this technique has minimized the influence of the physical charac-
teristics of specific ashes. The chemical factors include the
chemical composition of the fly ash and the concentrations of
water vapor and sulfur trioxide in the flue gas. The influence
of these factors has been quantitatively defined in a preceding
section. The effect of electrical stress on resistivity was
also discussed previously.
The predictive method attempts to accomodate the most general
case; that is, the prediction of fly ash resistivity from a core
bore sample of a coal that has never been commercially fired.
The various steps used in the prediction of resistivity are dis-
cussed below so that one can calculate resistivity as a function
of temperature from the expressions and graphs previously given
or one can use the computer program that is given in the next
section for this purpose.
REQUIRED INPUT DATA
The required input data are obtained from the as-received,
ultimate coal analysis and the chemical analysis of the coal
ash. Since the predicted resistivity is sensitive to the chemical
factors involved, it is emphasized that one should use the best
available coal and ash specimens and that accurate quantitative
analyses are available.
For this research program, the ASTM D3176 procedure was
used to determine the ultimate coal analysis. From this informa-
tion, a stoichiometric combustion calculation to determine the
flue gas composition based on 30% excess air is made. The 30%
53
-------
excess air value was selected by evaluating the precipitator
inlet flue gas analyses submitted by the forty utility operators
that assisted in this program by supplying ash samples and useful
data. The combustion calculation will not be reproduced here,
because it is a familiar step to the concerned industry. The
output of the computer program that follows shows the general
form of the calculation. Two factors from the computed flue
gas analysis are used in the resistivity prediction. These are
the water concentration in volume percent and the sulfur dioxide
concentration as the dry, volume fraction in parts per million.
For the example calculation that follows, the water concentration
equals 9.9% and the sulfur dioxide concentration equals 1350
ppm.
The coal ash was produced by first ashing according to the
ASTM D3174 procedure and then reigniting a specimen at 1050°C ±
10°C in still air for 10 to 12 hours (overnight). This ignition
schedule was found to be optimum for the several coals used in
this study. The good agreement between the fly ash and coal
ash chemical compositions will be shown later in this report
in the section describing the testing of the predictive technique.
When other research19 is examined, the ignition temperature
established in this work by trial and error seems reasonable.
It is hoped that in the future an objective technique will be
established to determine the optimum ignition temperature for
each specific coal sample prior to chemical analysis.
The coal ash is chemically analyzed, and the data are re-
ported as oxides in weight percent. After normalizing the weight
percentages to sum 100%, each oxide percentage is divided by
the respective molecular weight to obtain the mole fraction.
Each mole fraction is divided by the sum of the mole fractions
and multiplied by 100 to get the molecular percentage as oxides.
Each molecular percentage is multiplied by the decimal fraction
of cations in the given oxide to obtain the atomic concentration.
An example of the calculation is shown in Table IV. The follow-
ing atomic concentrations taken from Table IV are of interest
for the resistivity prediction: (a) the sum of lithium and
sodium, 0.36, (b) the sum of magnesium and calcium, 10.7, (c)
iron, 1.3, and (d) potassium, 0.65.
CALCULATION OF RESISTIVITY
Using the aforementioned input data, resistivity can be
calculated as a function of the usual temperature spectrum ex-
perienced by both cold-side and hot-side precipitators. The
entire resistivity-reciprocal absolute temperature curve is pro-
duced from the combination of three separately calculated curves.
These three resistivity-temperature relationships reflect the
influence of: (a) ash composition, pv, (b) ash composition-water
concentration, ps, and (c) concentration of sulfuric acid vapor, pa,
54
-------
Table IV.
Illustrative Example of the Calculation of the Atomic Concentration of Cations
in Coal Ash.
01
Oxide
Li20
Na20
K20
MgO
CaO
Fe203
A1203
Si02
Ti02
P205
SO 3
Sum
Determined
Wt %
0.01
0.46
1.30
2.82
13.10
7. 46
18.40
49.60
0.64
0.57
2.50
96.86
Normalized
Wt %
0.01
0.47
1.34
2.91
13.52
7.70
19.00
51.22
0.66
0.59
2.58
100.00
Molecular
Weight
29.88
61.98
94.20
40.31
56.08
159.70
101.96
60.09
79.90
141.94
80.06
———
Mole
Fraction
0.00033
0.00758
0.01423
0.07219
0.24108
0.04822
0.18635
0.85239
0.00826
0.00416
0.03223
1.46702
Molecular
Percentage
0.022
0.517
0.970
4.921
16.433
3.287
12.703
58.103
0.563
0.284
2.197
100.000
Cationic
Fraction
0.67
0.67
0.67
0.50
0.50
0.40
0.40
0.33
0.33
0.29
0.25
Atomic
Concentration
of Cation
0.015
0.346
0.650
2.461
8.217
1.315
5.081
19.174
0.186
0.082
0.549
38.076
-------
Calculation of Volume Resistivity, pv
This value at a reciprocal absolute temperature of 1000/T(°K) =
1.6 can be obtained graphically from Figure 11 or can be computed
from:
log p = 8.9434 - [1.8916 log x] - [0.9696 log y] +
V , 1«6
[1.2370 (log z - log 2.5)], (7)
where x, y, and z are the atomic concentrations of Li + Na, Fe,
and Mg + Ca, respectively.
Expression (7) was derived by summing the three curves shown
in Figure 11 and converting to base 10 logarithms. Substituting
the concentrations from Table IV for x, y, and z into Equation (7),
the value of log pv becomes 10.4533. Using Equation (3),
' 1*6
this value for log pv/ 1>6 which is based on the experimental
voltage gradient of 2 kV/cm can be adjusted to the arbitrarily
selected gradient of 10 kV/cm used in this predictive technique.
Then the value of log pv at 1000/T(°K) = 1.6 and E = 10 kV/cm
equals 10.2133, and pv = 1.6 x 1010 ohm cm.
By inserting this corrected value of log Pv,i.6 in Equation
(1) and letting 9 equal 0.86 electron volts, the average value
for this study, the preexponential term of Equation (1) is calcu-
lated. Knowing this term, values of pv at all temperatures of
interest can be calculated. In this manner log pv at 1000/T(°K) =
1.4 was calculated as 9.3464 (pv/ t ^ = 2.2 x 109 ohm cm), and
curve number one in Figure 24 was constructed.
Calculation of Surface Resistivity, PS
The values of log ps at reciprocal absolute temperatures
of 1000/T(°K) =2.8 and 2.6 for E = 2 kV/cm and a 9.0% water
concentration can be graphically interpreted or calculated using
the expressions shown in Figures 2 and 3, respectively. These
values then can be adjusted to an E value of 10 kV/cm and to
the example environmental water concentration of 9.9% using Equa-
tions (3) and (2), respectively. After these corrections are
applied, the values of log ps are 10.3255 and 11.4095 for recip-
rocal absolute temperature of 1000/T(°K) = 2.8 and 2.6, respec-
tively and ps/ and ps/ are 2.1 x 1010 ohm cm and 2.6 x
1011 ohm cm, respectively.
If this technique for calculating ps is used at higher tem-
peratures and the values of ps are combined with the previously
calculated pv values using the parallel resistance expression,
56
-------
10
15
10
14
O
t 1012
CO
UJ
10"
1010
109
I
I
1
I
I
I
I
I
I
I
1000/T(0K) —- 3.2 3.0 2.8 2.6 2.4 2.2 2.0 1.8 1.6 1.4 1.2
°C—-40 60 84 112 144 182 227 283 352 441 560
°F—~103 141 183 233 291 359 441 541 666 826 1041
TEMPERATURE
CURVE
NUMBER
1
2
3
4
5
6
RESISTIVITY
DESIGNATION
Pv
PS
PS
Pvs
Pa
Pvsa
EQUATION
NUMBER
1
FIGURES 2 & 3
8
12
14
15
SYMBOL
O
V
O
D
A
O
Figure 24. Predicted resistivity as a function of temperature.
57
-------
a discontinuity can develop in the resultant resistivity versus
reciprocal absolute temperature curve. This can occur because
of the significant effect of the alkaline earth elements on the
high temperature resistivity, pv. If one were interested in
calculating the predicted resistivity at a single cold-side pre-
cipitator temperature, for example 1000/T(°K) = 2.4 (291°F),
the above procedure used to calculate the values at 1000/T(°K)
2.8 and 2.6 would be adequate.20
However, to extend the ps versus reciprocal absolute tem-
perature curve to some limiting value such as 1000/T(°K) = 1.4
from the value computed at 1000/T(°K) = 2.6, an expression21'13'22
previously rationalized and found useful was used:
p = p
^ M
-W Kn e
K,/T
(8)
Expressed in logarithmic form this equation is:
log p = log p - [log e K0 exp (Kt/T)] W (9)
S SO
where
p = surface resistivity influenced principally by
s temperature, ash composition, water vapor
concentration and specific surface,
p = maximum surface resistivity as the effect of
0 water vapor approaches zero at high temperatures,
W = water vapor concentration in volume percent,
T = absolute temperature, °K,
K0 and
= parameters related to the physical and chemical
properties of the water vapor having the
dimensions I/volume percent water and degrees
Kelvin, respectively.
The quantity shown in brackets in Equation (9) defines the
change in the logarithm of resistivity as a function of water
concentration at a given temperature. This value was previously
defined as S in Equation (2) ; that is,
w
S = log e K0 exp (Kt/T) and
Wf
log
= log (K0log e) +
e (1/T) .
(10)
(11)
Figure 14 graphically illustrated Equation (11). Using
the numerical values for the intercept and slope calculated from
the regression analysis of the data shown in Figure 14, the values
for K0 and Kj were determined, respectively, as 7.3895 x 10" "*
and 2.3033 x 103.
58
-------
Knowing K0, Kt, the water concentration, and ps^ , the
value of pso was calculated from Equation (8) . After determining
pso, the values of ps at 1000/T(°K) = 2.4, 2.2, 2.0, 1.8, 1.6,
and 1.4 were computed. The curve showing these values for surface
resistivity, Ps, as a function of temperature are shown in Fig-
ure 24, curve numbered 3.
Calculation of Combined Volume and Surface Resistivities, pvs
Although in the absence of significant sulfuric acid vapor
the surface and volume conduction mechanisms are both dependent
on alkali metal ions for charge carriers, the two processes af-
ford separate conduction paths through the ash layer. Resis-
tivity as a function of temperature for the combined effect of
surface (ps) and volume (pv) resistivities can be calculated
using the expression for the sum of parallel resistances stated
in terms of resistivity:
It becomes apparent that when pv»ps then pvs ~ pg and when
ps»pv then pvs ~ pv. Curve number 4 in Figure 24 shows the
resultant pvs.
Calculation of Acid Resistivity, Pa
In previous discussion it was concluded that surface conduc-
tion resulting from the adsorption of sulfuric acid vapor occurs
by a mechanism unrelated to that occurring due to the interaction
of the ash surface and water vapor. Consequently the surface
resistivity resulting from the adsorption of sulfuric acid vapor,
pa, is calculated separately in a manner analogous to those used
to calculate ps and pv. Finally, the effect of adsorbed acid
on the complete resistivity-temperature relationship is incor-
porated by combining pa with pvs using the expression for parallel
resistances .
Present knowledge suggests that the effect of adsorbed acid
on resistivity is a function of fly ash composition in that certain
compositions have greater affinity for the acid. Because of
this, two separate calculations are used to define pa as a function
of environmental sulfur trioxide concentration and temperature.
If the combined atomic concentration of magnesium and calcium
^ 3.5% or the potassium concentration is ^ 1.0%, then:
log p = [12.9676 - (0.3075 C )] +
^ a so3
[10.1048 (2.37 - 1000/T) ] . (13)
59
-------
If the combined atomic concentration of magnesium and calcium
is > 3.5% and the potassium atomic concentration is < 1.0%, then:
log P = [12.1612 - (0.3712 C )] +
cl S O ^
where
[5.6673 (2.37 - 1000/T)]. 14
= concentration of sulfur trioxide in dry volume
S° and
T = absolute temperature in °K.
Tiu> chemical limitations applied to Equations (13) and (14)
generally define what is commonly referred to as eastern and
western ash, respectively. Equations (13) and (14) were obtained
by respectively substituting Equations (4) and (5) into Equation
(6) utilizing the appropriate slope value. In either case above,
the calculated value of pa is that concomitant with an E value
of 2 kV/cm. As in the case of the calculations of pv and ps,
the pa values at 2 kV/cm are adjusted to 10 kV/cm using Equation
(3).
In the example problem being considered, the stoichiometri-
cally calculated concentration of sulfur dioxide was 1350 ppm,
dry volume. The concentration of sulfur trioxide used in the
prediction of resistivity, CSO3 , is taken as 0.4% of the computed
Cso2 value. In this case, CSO3 equals 5.4 ppm. This method
of computing the CS03 concentration is based on the review of
information from seventeen field tests in which both sulfur
dioxide and sulfur trioxide determinations were made using speci-
mens taken at the inlet to the precipitator . It is assumed that
the degree of equilibrium between the fly ash and sulfuric acid
vapor at the inlet to a precipitator is similar to that existing
at the surface of an ash layer after long-time exposure to a
laboratory test environment.
In the example problem, the ash analysis indicates that
Equation (14) should be used to compute pa with CsO3 equal to
5.4 ppm. After correcting to E = 10 kV/cm using Equation (3),
values of pa for several values of 1000/T(°K) were plotted in
Figure 24, curve number 5. No data are computed for values of
1000/T(°K) > 2.4. There are two reasons for this. One, no signi-
ficant experimental data were acquired at temperatures lower
than this point. Two, at the lower temperatures, the acid dew
point is approached. It is not possible to precisely determine
this value, and the effect of condensed acid on resistivity has
not been measured.
60
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Calculation of Combined Volume, Surface, and Acid Resistivities/
Pvsa
The curve for resistivity as a function of temperature is
completed to include the effect of adsorbed sulfuric acid vapor
by combining the values for pa and pvs using the equation for
parallel resistances expressed in terms of resistivity:
P P
- a vs ,-, c>
- - (15>
When pa»Pys' Pvsa ~ Pvs and wnen Pvs>:>Pa' Pysa ~ Pa- Curve
number 6 resulting .from the use of Equation (15) is indicated
in Figure 24. Comparison of the resistivity-temperature relation-
ships pvs and pvsa shows the effectiveness of sulfuric acid vapor
as an agent for attenuating resistivity. The example used to
illustrate the method of predicting resistivity in this section
is also used to illustrate the computer program described next.
61
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SECTION 8
COMPUTER PROGRAM FOR PREDICTING RESISTIVITY
In the preceding section a method was described with which
resistivity as a function of temperature can be calculated.
Using an assumed as-received, ultimate coal analysis and the
concomitant coal ash analysis as input information, the method
was illustrated in detailed steps by computing the resistivity
from the many equations and correlations established earlier
in the report. In this section a computer program is given to
determine resistivity as a function of temperature using the
same illustrative example. The program written in FORTRAN is
shown in documented form as Table V. The program written in
disk BASIC for a TRS-80 microcomputer is shown as Table VI.
The input for the FORTRAN program is shown on a multiple-
card layout form, Figure 25, indicating that a data set of three
punched cards are required. The first card contains two vari-
ables: IEND, an end of data indicator, and ITITLE, the title
or designation information. For each data set of three cards,
IEND should be blank. A card with IEND equal 9 should follow
the last card of the last data set to stop the program. The
second card contains the input data for the variables XIN, S02,
W and E. The third card contains the input data for the variable
XMWPO. Figure 26 illustrates the three cards punched for the
example coal and coal ash.
Input for the BASIC program is from the computer keyboard.
The program prompts the user and provides opportunity for error
corrections. The program also allows the user to change sulfur
trioxide after initial resistivity is predicted. The BASIC
program is essentially a direct translation of the FORTRAN code.
The program can be used in several ways. The principal
mode is to determine ash resistivity at a field strength of 10
kV/cm from a core bore sample of coal in which case the data
for variables XIN and XMWPO are supplied respectively from coal
and coal ash analyses determined in the manner described in the
previous section. In this mode the variables S02, W and E are
left blank.
A fly ash chemical composition can be used for the variable
XMWPO instead of a coal ash analysis. In this case, the loss
on ignition value normally reported for a fly ash analysis is
62
-------
001
002
003
004
005
006
007
008
009
010
Oil
012
013
014
015
016
017
018
OJ9
020
02!
022
023
024
025
026
027
028
029
030
031
032
033
034
035
036
037
038
039
o«o
041
042
043
044
045
046
C
C
C
C
TABLE V .
COMPUTER PROGRAM FOR PREDICTING RESISTIVITY
C***********************************************************************
C*
c*
c*
c*
c*
c*
c*
c*
c*
c**
c
c
c
c**
c*
c*
c*
c*
c*
c*
c*
c*
c*
c*
c*
c*
c*
c*
. c*
c*
c*
c*
c*
c*
c*
c*
THIS PROGRAM IS DESIGNED TO COMPUTE FLY ASH RESISTIVITY AS A
FUMCTTOM OF TfMPFRATURE FROM COAL AND COAL ASH ANALYSES*.
PR*. R. l'. RICKELHAUPT OF SOUTHERN RESEARCH INSTITUTE WAS THE
PPTNCIPAI INVESTIGATOR'. THE RESEARCH WAS SPONSORED BY THE
PAPTTC"LATE TECHNOLOGY BRANCH, INDUSTRIAL ENVIRONMENTAL
RESEARCH LABORATORY OF THE ENVIRONMENTAL PROTECTION AGENCY.
OR'. L . E'. SHARKS. PROJECT OFFICER.
*******************************************************************
D I MEMS TON XIW(7).WTM(6).X02(5>.XOAf5),02m,DAm.WETC5).ORYC5),
* XMoLESC7),ITITLE(75).XMWPotin,WPOLC(in,XM.WO(ll).XMFni).
* XMPOdn,XMPt:fi||),TEMPC8).TKi:B).KT(8).RVSAf8),PEOd1).ICTm,
* Rvr8).KS(B>.RVS(6).RA(8),TFTrB).Sl(2).YCEPTr2).SW(2)
EQUIVALENCE (RR(7).RS26)
*******************************************************************,
DEFINITION OF VARIABLES IN DATA STATEMENT
TEMP RECIPROCAL ABSOLUTE TEMPERATURE • IOOO/T DEGREES K
TK TEMPERATURE DEGREES KELVIN
**
k*
*
*
*
*
*
ICT TEMB£RATURE. DEGREES CFNTIRRADE • INTEGER FORMAT FOR PRINTING*
IFT TFMPERATURE DEGREES FARENHEIT • INTEGER FORMAT FOR PRINTING
KT TEMPERATURE. DEGREES KELVIN - INTEGER FORMAT FOR PRINTING
XO? MOLES OF OXYGEN REQUIRED PER MOLE OF C.H2.02.N2.S
FOR COMBUSTION
XDA MOLES OF nRY AIR REQUIRED PER MOLE OF C.H2,0?,N2.S
FOR COMBUSTION
Sj SI OPE OF LM RHO VS ATOMIC X LITHIUM + SODIUM AT
1000/T OFGPFES K s 2.6 AND 2.8 RESPECTIVELY
YCEP1 INTERCEPT OF LN RHO VS ATOMIC % LITHIUM + SODIUM AT
1090/T DEGREES K s 2.6 AND 2.8 RESPECTIVELY
SW SLOPE OF LOG RHO VS VOLUMF X WATER AT
IOOO/T DEGREES * o 2.6 AND 2.8 RESPECTIVELY
NTM MOLECULAR HEIGHTS FOR c.H?,02,N2,s,H20
PEO . X CATIONS FOR REPORTED ASH OXIDES
XMWQ MOLECULAR WEIGHTS OF REPORTED OXIDES
*
*
*
*
QUA
049
050
051
05?
053
054
055
056
057
058
059
060
DATA TFMP/1.4.!.6,1.8.2.0,2.2,?.4,2.6,?.8/
DATA TK/71 4.0. 625.0. 556.0.5011.0.455.0,417.0. 385.0. 357. O/
DATA ICT/aui.352.283.227.182.144.112,8«/
DATA IFT/8?6.666.541,441.359.291,233,183/
DATA KT/71«,625,556.500.455,417,385,357/
DATA X02/lj.0ft,n.50.«r.00.o'.00f l.OOX
DATA XDA/4,76,2.-*8.-4.76.o'.00,4.76X
DATA S1X-2.233^4.8,-2'.061840X
DATA YCEPT/24.807004,22.641601X
DATA SW/0.t280.0'.2029/
DATA *TM/12.01 ,2'.02. 32.00.28'.01.32'.06» 18'.02X
DATA PEO/3*66.66.2*50'.00.2*40.00.2*33.33.28.57.25'.OOX
63
-------
061
062
063
064
06S
067
068
060
070
071
07?
073
07"
07S
076
077
078
080
081
08?
083
084
08S
087
088
r
C*
r*
r*
r*
r*
r*
c*
c*
c*
c*
c*
c*
c*
c
c*
091
00?
093
094
095
096
097
098
09O
100
101
10?
103
10U
105
106
107
108
10°
1 0
1 1
1 ?
1 3
1 4
1 S
116
117
4 1 A
11"
110
120
r
c*
c
c*
c
r*
c*
c*
c*
c*
c*
c*
c
r*
c
c*
c
c*
r>ATA *M*'0/?9.88, 61.98. 94.20, <»0. 31,56.08,159.70. 101 .96,60.09,
* 70.9,l,141.9u,«o'.06/
FUNCTION ROUNDS TO THF. NEAREST o'.OOl
CONSTANTS
CX
XC
SV
XKO
XK1
T
SF
30% FXCESS AIM FUNCTION
LOG 2.5
S!OPE LOG WHO IN 4RRHFNIUS EQUATION VS RECIPROCAL
APSOI.UTF TEMPFRATURE
CONSTANT
*
*
*
*
*
*
*
*
*
Tf'MPfRATURf = 385.0 DEGPEES K
siDPE LOG RHO vs FIELD STRENGTH
CX = 13n.0/100.0
XC = ALOR10(2.5)
SV s 4'. 3345*10'. 0**3
XKO r 7,3804*10."**(•
XK1 = ?.3033*10.0**3
SF = o'.o3
CARD I END AND DATA IDENTIFICATION
S P-EAO (?.h) lENO.ITITLE
6 FORMAT (I1.7SA1j
IEWD = 9 STOPS THF: PROGRAM
IF (TF;MD ,FQ. 95 GO TO 999
ISKIP IS VARIARLF FOR PRINT SPACING
TSKIP s 0
PEAT, DATA CARD
XIN = AS KECFIVEH ULTIMATE COAL ANALYSIS
so? = PPM 502
b' = VOLUME X WATFR
F s FIFI.O STRENGTH
SOP. W. ANH E ARE OPTIONAL AS TNPUT VARIABLES
THE PROGRAM WILL CALCULATE IF NOT INPUT
HEAD f2,l) XIW.S02.W.E
l FORMAT (
is ASH ANALYSIS
*
*
*
*
A
*
*
READ HATA CAPD -
"FAO (?.l) XMKPO
THF OEFAl'LT VALUE FQR FIELD STRENGTH E IS 10.0
1.5 IF CF '.FO. 0.0> Palo'. 0
PRTWT IDENTIFICATION
WRITF (3.71 ITTTI.F;
7 FOPMAT ('1'f 5X,'RESISTIVITY PREDICTION BASED ON WORK DONE BY'/
* feX.'PH. ROY RICKELHAUPT OF SOUTHERN RESEARCH INSTITUTE'.'/
* «>X.'THE RESfARCH WAS SPONSORED'BY THE PARTICUl.ATE'/
64
-------
121
12?
t23
12"
12S
126
127
12*
129
130
131
132
13=i
136
137
13«
in'. L. F'. SPARKS. PROJECT OFFICER.' /// ix.75Ai//>
IF * ANr SOg ARE GIVEN AS IMPUT DONT CALCULATE - SKIP TO 75
IF Cfw'.NF.O.) '.AMP*. fSOa'.NE.O.n GO To 75
ISKJP = i
SUM rnAl. ANALYSIS
SU''IN a 0.0
no jo Irl.7
SUMNJ s SUMIM + VIN(I)
10 CONTINUE
IF (SUM. IN .EQ. lOO'.O) GO TO JO
lTZE COAL ANALYSIS
On 20. 1=1,7
XIN(T) = XINf I)/SUMIN*100.0
M - loo.o
C.ALC"LATF AND SUM MOLFS - MQLES a X/MQLECUL AR WEIGHT
a 0.0
1U7
1"?
149
150
151
15?
153
15fl
155
15fe
157
158
1S9
160
161
162
163
16«
165
166
167
16B
169
170
171
172
173
\7U
17^
176
177
17P
179
c
c*
so
C
C*
C
C*
r*
Si.'MOLF t
SUMOl E; E
(JO COMTTNUf:
CAI cni.ATE AMD SUM MOLES 02 AND ORY AIR
FOR COMBUSTION AT 100* TOTAL AIR
s 0.0
s 0.0
*
*
TF (1 '.F^.
-------
181 XSUMPA r ROllNDfCX * 9UMOA)
182 C
183 C* CA!C"l ATF F.XCKSS AIR AND EXCESS 02
1B« FxAIR = XSU^OA - SUMDA
185 FX02 = XSUM02 «• SUMQ2
186 C
187 C* PRINT
188 WRITF (3.3) XS'IM02,XSHMOA,FXAlR.eX02
169 3 FORMAT (T3fl,'Pew FOR COMBUSTION'/ T35,'MOL.FS/1 00 IB
190 * T^6.'»30X KXCFSS AIR'/ TJU,ift('-')/ T37,'02',ToU,'DRY AIR'/
191 * T3S.6Cf-'),3X.7('-;)/ ' 0? AND AIR * 130/100 TOTAL'.7X,F6.3,
192 * «X.F6'.i> ' FXCF.SS AlR',T.3.8X,F(S'.3.8X,F6'.3/ ' SUM W£T', UX,F6.3/ ' SUM DRY',
225 C
226 C* TF * AND S02 ARfr. NOT RlVFN AS INPUT faO.O) SET W AND *
2?7 C* SO? fROM PREVIOUS CALCULATIONS *
228 75 TF (w '.fe'Q. 0.) ti = wFT(2>
?29 TF (SO? '.f.O. O'.) SO?BDRYf3)*10000.0
230 C
231 C* S02 = -1.0 ON DATA CARD INDICATES 802 SHOULD BE 0.0 *
?32 TF (So? ,f.n. -1.0) SOP.so'.
233 C
23
239 TF. s E
r
66
-------
c* ROUMO w AND so? TO THP NEAREST .i
w =
2«3 SOI s
244 C
245 C* PRINT *
2<17 11 FORMAT (; H20'.F14'.l/ ' S02».flX.I6/ » 803*. FU. I// ' EMOX.I6)
?«8 r
?«9 C* SUM ASH ANALYSIS *
250 S'JMX a o'.O
251 HO HO isl.ll
252 SL'MX = SUMX + XMWPO(I)
253 80 CONTINUE
25u r
255 C* NORMALIZE AND SUM ASH ANALYSIS *
?5h SUMA = o'. 0
257 00 90 J3i.ll
25ft K'POLC(T) 3 (XMWPntD/SUMX)*lOo'.0
259 SUMA * SUMA * WPnLC(I)
260 00 CONTINUE
261 C .
26? C* CALCULATE 4NO SUM MQLF. FRACTION • XMF *
263 SUM s 0.0
26« PO IPO 1=1.11
265 XMF(T) 3 WPOLrr I
266 SUM - SUM + XMF(T)
267 100 CONTINUE
269 C* CALCULATE MOLEr.ULAR X AS OXITES • XMPO *
270 r* CALCULATE AND SUM ATOMIC CONCENTRATIONS OF CATIONS • XMPF *
271 SUMB s 0.0
272 no 110 1=1.11
273 XMPOm 3 XMF(I)/SUM
27« XMPEfl) a XMPOfl) * PfjOd)
275 SUMB s gUMR + XMPE(I)
?76 HO CONTINUE
277 C
27? C* SL 3 ATOMIC CONCENTRATION LITHIUM .+ SODIUM *
279 C* CM a ATOMIC CONCENTRATION CALCIUM + MAGNESIUM *
280 c* XIRQM = ATOMIC CHMCENTRATION IRON *
281 C* POT = ATOMIC CONCENTRATION POTASSIUM *
282 SL a XMPF. Tl) + XMPE(?5
263 CM 3 yMPF(a) + XMPE(S)
264 XIRON s XMPE(6^
285 POT = XMPE(3)
28fe C
267 C* ROUND St. AND POT TO THE NfARFST 0.01 *
288 n* RQUNO CM AND XTRHM TO THE NEAREST 0.1 *
28" SL s AlNT(SL*100'f^SIGN(o'.5.SL) Vl°°i
290 CM 3 AlNTCCM*10.+SiaN(0.5.CM))/lO.
291 XIPOM s AINT(XlRON*io.+SI6N(0.5.XIRONn/1o'.
292 POT s AINT(POT*100'.+SIGN(0'.5.POT))/100.
3I93 C
29« C* CLASSIFY ASH BASFO OF AFFINITY FOR ACID *
295 T* L s ? CALCIUM * MAGNESIUM > 3'.5 AND POTASSIUM < l'.0 *
29fe C* I. a 1 OTHERWISE *
. . . . . ...
298 IF CfrM.GT.3.51 .AND. f POT.U. 1 .0) ) L"2
299 C
300 IF CTSKIP ,EQ. 1>
67
-------
301 i« FOBHAT ('!')
30? C
303 C* PRINT *
30" WRITE (3.12) (XMwpOf I ) , wPOLC ( I) . XMPE CI) < 1=1 , 1 1 ) ,Sl|MX.SUMA,SUM8
305 12 FORMAT (T23, 'CORRECTED'/ TU, 'ASH' . T26. 'ASH' ,T«0. » ATOMIC '/
306 * TM. 'ANALYSTS', T2«, 'ANALYSIS', T3.6, 'CONCENTRATION'/
307 * Tll.flf '-'},J23, «?('-'). T3&.n(»-')/ ' LI20' ,F! ?'.?,P13.?.F 15. V
30P * • NA20'.F)2'.5.F13.2.F15'.3/ ; «20' , 2F 13.2.F t5'.3> ' Mep»,2F13'.2.
309 * F1S'.3/ ' CAn'.2Fl3.2.F15.S/ ' FE203',F 1 j .2. F13'.2, F15'.3/
310 * ' AL?03',Fli .?fFi3.?.Fi«5.V * SI02' .Fl 2.?.F13.^.F 1 5', 3/ ' TI02',
311 * F1i?.?.F13.2.Fl5'.3/ ' P205' ,F12.2,F1 3.?, F15.3/ ' S03'.2F13.2.
31? * FIS'.S// ' SUM;.2F!3'.?.F15'.3//1
313 C
31 AND 2.B *
3«1 C* f?Srw TS LOG SURFACE RESISTIVITY AS A FUNTTION OF *
3) *
359 DO 119 1*1,6
360 »Sm s RSO nt FXP(-W*XKO*EXprXKl/TK(I)))
68
-------
361 1 19 CONTINUE
362 C
J63 C* RVS IS THE RESISTIVITY RESULTING FROM THE COMBINATION OF *
36U C* VOl iiMf AND SURFACE RESlSTIVlTIFS USING THE EXPRESSION *
36S c* FOR PARALLEL RESISTANCES *
366 DO 1?!) 7 = 1, ft
367 PVS(T1 = RV(I)*RS(I)/(*vm+PSfIM
36« 120 CONTINUE
369 C
370 C* IF SO?. S03 = 0, 00 NOT ADJUST RESISTIVITY *
371 C* FOR FfFECT OF ACID *
37? IF (SO? '.WE. 0*.) GO TO 1202
373 DO 1?01 Ial,B
37
-------
421
422
423
424
425
WRITE (3.13) TFMPCl).KT(n.lCTrn,IFT(I).RVSm,Rv3Am
FORMAT (IX.OPFfl.i ,5X,3(4X,l3),3X,lPE6,l,3X.lPEfl.n
GO TO 130
miTF (3.18) TEMP(l),KT(I),iCTirnf IFTm.RVSm
T (1X.OpFft.1 ,5X,3(4X.I3),SX,1PE8.1,7X.'**')
427
430
431
432
433
034
13
128
"RITE (3.10)
}
-------
Table VI
PRGE i BftSIC PROGRAM FOR RESISTIVITY PREDICTION 27 HUG 1979
19 REH ***** PROGRAH PREDRES *******
BASIC PROGRAM (KITTEN IN TRS-88 DISK BASIC 32K RPH
RESISTIVITY PREDICTION BRSED ON HORK DONE BY
29 RE« ROY B1CKELHAUPT OF SOUTHERN RESEflRCH
38 REH BftSIC PROGRAM BY L. L SPARKS
48 aS:PRMDRESlSTIVITY PREDICTION':POKE 16425,8
56 LPRINT TAB<18)°RES1ST1VITY PREDICTION BASED ON UORK DONE BY1
ffi LPRINT TABU8) 'DR. ROY BICKELHRUPT OF SOUTHERN RESEflRCH INSTITUTE'
76 LPRINT TRBU9) 'BASIC PROGRAM BY DR. LE. SPflRKS PARTIOIATE TECHNOLOGY BRANCH":
LPRINT TABae)" INDUSTRIAL ENVIRONMENTAL RESEARCH LRS RESEARCH TRIANGLE PARK NC EPA*;
C«$(ie);TR8<25);'VERSION i HAY L19791
60 DIH U$(7),AS$(il)
98 DIM XH?),HT(7),XO(5),XD<5),02(7),Dfl(?),K(5),DR(5)
m DIH ffl(7),Xe(ll),HP(ll),XH(ll),»:(ll),»>(il),>I(ll),TE(8)
lie D1H KT(8),R(8),PE(ll),CT(8)>RV(8),RT(8),RS(8),Rfl(8),n(8),Sl<2)
128 DIM YC<2),SH<2)
138 RE« Tk€ FOLLOHIKG TMO FUKCTIONS ROUND TO NEflREST .981 fM) .1
140 DEF FNR3,TK,CT(I),FT(1),KT(I>
219 NEXT 1
228 REM READ MOLES OF 02 (XO) AMD DRY AIR (XD) REQUIRED FOR COMBUSTION OF C,H2,0&N&S IN FUEL
238 FOR 1=1 TO 5
248 READ X0(l),«)(l)
256 NEXT 1
266 REH READ MOLECULAR (EIGHTS UT OF C, K2, C& K2, S, PND H20 FROM DATA STATEHENT
278 FOR 1=1 TO 6
289 HERD HT(1)
298HEXT 1
m REH F£ff)'/. CATIONS FOR REPORTED ASH OXIDES
318 FOR 1=1 TO 11
329 READ PE(I)
339KEXT 1
346 REH READ HOLECU.AR SIGHTS OF REPORTED ASH OXIDES
356 FOR 1=1 TO 11
366 READ XU(1)
378 REH READ STRINGS FOR LABLES ** ALL READS ARE FROM DATA STATEMENTS
388 NEXT I
398 FOR M TO 7:READ U$(1):NEXT 1
m FOR M TO 11:READ AS$(D:tEXT 1
71
-------
Table VI (cont'd)
PftGE 2 BR5IC PROGRFI1 FOR RESISTIVITY PREDICTION 27 RUG 1979
419 SKi)=-2.233348:Si<2)=-2.86184 :VC<1)=24.887864 :VC<2)=22,6416
426 SH<1>=.128:SH<2>= 2829
438 CX=i38/i88:XC=LOG<2.5)/10G<16)
448 SV=4.3345*1888 :XK=7.3894/18888.
458 Xi=2,3833*1888:T=385:SE=. 83
468 53=8. :SO=8. :HR=8.
478 ES=. 83:REHES IS THE CORRECTION FflCTOR FOR E F1ED
488 LPR1NT CHR$(i8), CHR$(18), CHR$(18)
498 1HPUT' N»€ OF PLflNT 'jR$
598 INPUT'NMf Of CORL';B$
518 PRINT1 PLRNT NRME IS ';R$: REM CHECK TO SEE IF OftTfl flRE OK
528 PRINT' COft. NfiME IS ';B$
538 INPUT'lS THIS CORRECT V OR N ";W$
548 IF W$="V THEN 568
558 PRINT'REENTER INCORRECT DflTR':GOTO 498
568LPRINT 'PLRNT NflHE IS ';«;' COflL N»€ IS ";B$
578 PRINT' IMPUT ULT1WTE COfiL ftNfiLVSIS'
588 FOR 1=1 TO 7
598 PRINT U$(I),XI(1);' PRESENT VH.UE Ji'iINPUT XKI)
688 NEXT I
618 PRINT'ULTIMRTE flNfiLVIS'
628 FOR 1=1 TO 7
638 PRINT U$U),XI<1)
648 NEXT I
658 INPUTMS THIS CORRECT V OR N';V$
668 IF V$="N' GOTO 678 ELSE GOTO 698
678 PRINT 'REENTER flNY INCORRECT DflTfTGOTO 588
688 REN THE FOLLOWING DflTR ENTRIES RRE OPTIONRL IF 8 IS ENTERED THE PROGRffl HILL CftLCULftTE
698 INPUT'OPTIONRL INPUT IF INPUT 8 PROGRRH HILL CftLCULflTE
ENTER H20 INGRS/iVHR
788 PRINT'CfTIONffl. INPUT. PRESS ENTER RND PROGRflM HILL CRLCULflTE
ENTER -1 IF DESIRE 8':
INPUT "ENTER 502 IN PPH'i SO
718 INPUT'OPTIONRL INPUT IS 8 INPUT PROGRRH HILL CflLCULflTE S03 RS a 884*502 ENTER PPH 503';S3
728 INPUT'OPTIONRL INPUT IF ENTER 8 PROGRRM HILL CftLCULflTE ENTER ELECTRIC FIELD KW«';E
738 PRINT-ENTER RSH RHRVSIS'
748 FOR 1=1 TO 11
758 PRINT RS$<1),X8<1>;'PRESENT VRLUE':1NPUT X8(I)
766 IF E=a THEN E =18
778 NEXT I
786 FOR 1=1 TO 11
796 PRINT RS$(I>,X8
888 NEXT I
72
-------
Table VI (cont'd)
PAGE 3 BASIC PROGRRH FOR RESISTIVITY PREDICTION 27 RUG 1979
816 INPUT" IS THIS CORRECT RSH RNRLVSIS V OR N1; VI
828 IF V$='N' THEN GOTO 739
838 REH CHECK TO SEE IF PROGRRH IS TO CH.CULRTE R20 RH> SQ2
848 IF HRO8 RND SOO8 GOTO 1118
858 REH SUH COM. RNRLVSIS
868 S=8.
878 FOR 1=1 TO 7
888 S=S+X1(1)
898 NEXT I
988 REM CHECK TO SEE IF SUH OF RSH RNRLVSIS IS 188/i
918 IF S =188 GOTO 978
928 REH NQRHRLIZE RSH RNRLVSIS
938 FOR 1=1 TO 7
948 XI(I)=XI(I)XS*188
958 NEXT I:S=188
960 REH CftLCULRTE RHD SUM HOLES-ROLES =X KOLECULRR HEIGHT
978SU=8.
988 FOR 1= 1 TO 6
998 X«(I)=X1<1)/W(I)
1888 XH(1) -- FNR3(XH(D)
1818 SU=SIHXH(I)
1828 KEXT 1
1838 REH CaOJLftTE RH> SUH HOLES OF 02 FIO DRV RIR REQUIRED FOR COMBUSTION RT 1887. TOTRL RIR
1848 S8=8. :SD=8.
1058 FOR 1= 1 TO 5
1868 IF 1=4 GOTO 1898
1078 02(I)=FKR3(XH(1)*XO(D):DR(I)=FNR3(XH(I)*XD(I))
1888 58=58*02(1):SD=SD+Dfl(I>
1898 NEXT I
1188 REH PRINT COKBUSTION REQUIREHENTS
1118 LPR1NT- REQUIRED FOR COHBUSION'
1128 LPR1NT- HOLES/188LB FUEL1
1138LPR1HT1 RS RECEIVED HOLES PER RT 18BCTOTRL RIR1
1148LPR1NT1 ULTIHRTECORL 188LBS FUEL 02- DRV RIR1
1158 FOR 1= 1 TO 6
1168 LPRM U$(l)iTRB(18);XKl)iTfl8(38)iXH(I)iTRB(58)i02(I).TRB(98)>DR(I)
1178 NEXT 1
1188 LPRINT'RSH ';X1<7)
1198 LPRIHT"SUH 'iS,1 VSU,S8,SD
1288 REH CaOJLRTE HOLES 02 Bft DRV RIR REQUIRED FOR 38K EXCESS RIR
73
-------
Table VI (cont'd)
PftGE 4 BflSIC PROGRflH FOR RESISTIVITY PREDICTION 27 HUG 1979
1216 XS=FNR3(CX*S8)
1228 XD=F«G(CX*SD>
1238 Xft=XD-SD:XO=XS-S8
1246LPR1KT'
1258 LPRIHT" REQUIRED FOR COBUSTION1
1268 LPRIHT' HOLES/186 LB FIB.'
1278 LPRIHT' K8KEXCESS B1R'
1288 LPRIHT' 02 DRV flIR'
1298 LPRIHT'02 flH> flIR*138/ie8 TOTflL '; TflB(35); XS; TflB(45); XD
1388 LPRIHT'EXCESS RIR';Tft8<45);Xfl
1318 LPRIHT'EXCESS 02 ';TftB<35);XO
1328 RD1 CftLCULflTE PRODUCTS OF COCUSTION ****
1338 XM<2)=XM(2)+XH(6>+(XD*29*. 813)/18.
1348 X)1(3)=XH(5):X«(4)=XH(4)+(XD*.79)
1358 XH(5)=XO
1368 REM CflLCULfiTE 7. BV VOLUME - l€T BftSIS
1378 SE=8.
1388 FOR I = 1 TO 5
1398 SE=SE+XM(I)
I486 £XT I
1418 REH CflLCULfflE X BV VOLUME DRV BftSIS
1428 SD =SE-XM(2)
1438 FOR 1 =1 TO 5
1448 WE(I)=FMQ(XM(1)/SE*188)
1459 DR(I)=FNR3(XM(l)/SD*i88)
1468 «XT I
1478 DR(2)=8.
1488LPR1NT1 •
1498 LPRIHT1 ***** PRODUCTS OF COWDSTION
1568 LPRIHT' TOTft.'
1518 LPRIHT' MCLES/188 7. BV VOL X BV VOL'
1528 LPRIHT' FUEL JET BftSIS DRV BftSIS'
1538 LPRIHT'OK •; XM(1); TRB<23>; HE(l)i TftB(44); DR(1):
LPR1NTH28 *;XM(2);TflB(23);«(2)Tfi6(44)iDR(2)
1548 LPRIHT'SOS '; XN(3); TflB(23)l£(3); Tffi(44); DR(3):
LPR1HT'N2 '; XM<4); TfiB(23); HE(4); Tfl8(44)j DR<4)
1558 LPRIHT'02 '; XM(5>; TflB(23); HE(5)i TRB(44); DR<5):
LPRIHT'SUM HET ';SE:LPRIHT'SUM DRV ';SD
1568 REM CflLCULftTE H28, S02,503, RND IHSERT DEFPU.T ELECTRIC FIELD
1578 IF UR =8. TKN Hft =tE(2)
1588 IF S0=8. THEN SO=DR(3)*18888
1590 IF S0=-l THEN 50=8
1680 IF 53=8. THEN 53=8. 884*50
74
-------
Table VI (cont'd)
PAGES BRS1C PROGRfH FOR RESISTIVITY PREDICTION 27 RUG 1979
1618 REH ROM) H20 AND S03 TO NEAREST . i
1629 HA=FNRi,CHR$(19>,CH»<19>
1648 LPR1HT "H20 Mtt1 K"; CHR$<18>; '502 'iSO;' PPN'i CtRf (18);'S03 'iSls' FW
1656 LPR1NT 'ELECTRIC FIELD ';&• KV/W.
1668 SX=8
1679 FOR I = 1 TO 11
1689 SX=SX+X8(D
1698 tEXT I
1768 REH NCRHRLIZE RND SUM flSH flNRLVSIS
1718Sft=8
1729 FOR 1= 1 TO 11
1739 UP(I)=(X9(I)/SX)*189
1748 Sft= Sfl + »>(!)
1758 «XT 1
1768 REK CALCULATE RND SUM HOLE FRACTIOH
1778 SZ=8
1788 FOR I = 1 TO 11
1798 XF(1)=W>(1)/XH(1)
1889 SZ = 52 + XF(I)
1818 KXT 1
1829 REM CflLCORTE flH) SDH flTOHIC CONCEKTRRTIOHS OF CATIONS
1838 SB=8
1848 FOR I = 1 TO 11
1858 ffd^XFUVSZ
1866 ffi(I) = »>(l)«fE(I)
1878 SB=Se^(l)
1889 NEXT I
1898 SL=1HT3.5 fiHD XE(3)<1 L=2
1938 LPRINT CH»(12): IHPUT'PRESS ENTER FOR KEXT PAGE(;W
1949 LPRINT TRB(28)'CORRECTED1
1958 LPRINT TRB(7> 'ASH'iTfiB(32) 'RSH1; TRB(58) 'BTOHIC'
1969 LPRINT Tf6(5)"fm.VSI5%TflB(3e)'flNflLV5IS%Tffi(47)1COHCEHTRATION>
1978 FOR 1=1 TO 11
1988 LPRINT RSI(I);TR8(6);X6(I);TRB(38)iUP(I);TAB(49);XE(I)
1998 NEXT I
2899LPRINT'a»l<;SX,' ',SA,SB
75
-------
Table VI (cont'd)
PflGE 6 BflSIC PROGRftM FOR RESISTIVITY PREDICTION 2? flUG 1973
2816 LPRIOT'SUH OF LITHIUM RND SODIUH RTOM1C CONCENTFflTlONS VSL
262B LPRINT'SUM OF HflGNESlUH RND CflLCIUH CONCENTRflTlONS ';CN
2938 LPR1NTMRON RTOHIC COHCEKTRfiTION "ifctf)
2848 LPRINT'POTRSSIUN RTOM1C COHCEHTRflTlON ';XEG>
2858 R6=8.9434-1.89i6*LOG- 9696*LOG>>
2298 NEXT I
2388 REH RS(I) IS THE COMBINED RESISTIVITY DUE TO PRRRLLEL
COMBINE ION OF SURFRCE RND VOLUME RESISTIVITY
2318 FOR 1=1 TO 8
2328 RS(I)=RV(I)*RT(IV(RT(I)+RV(D)
2338 NEXT I
2348 REH CHECK FOR RFF1N1TY OF RSH FOR RCID
2358 REM CftLCULRTE RESISTIVITY IN FflESENCE OF S03
2368 IF L=2 GOTO 2458
2370 R?=1Z %75-(. 3875*53)
2388 FOR 1 = 1TO 8
2398 RT=R7 +(18.1848*(2.37-TE(I»)
2488 RT=RT- (E-2.8)«ES
76
-------
Table VI (cont'd)
PftGE 7 BRSIC PROGRAM FOR RESISTIVITY PREDICTION 27 flUG 1979
2416 Rftd)=ie.[RT
2429 teXT 1
2438 REH TRANSFER TO CflLCULRTION OF COBIWED RESISTIVITY
2446 GOTO 2538
2456 R7=12.1612-(. 3712*53)
2466 FOR I = 1 TO 8
2478 RT = ft? +(5.6673*<2 37-TEd»)
2486 RT= RT - (E - 2.8)«ES
24S9 Rftd) = ia[RT
25f«WtXT I
2518 RE« CflLCULflTE COffilfED RESISTIVITY OF VOLIK PM) SURFftCE
2528 RG1 RESISTIVITY DUE TO 503 IN PflRHlEL
2538 FOR I = 1 TO 8
2548 Rd)=RSd)*Rfld>/+RRd»
2558 »CXT I
25W REH ROUND RESISTIVITY
2578 FOR 1=1 TO 8
2588 C=INT=FNRKRd>A8tO:Rd>=Rd>*18[C
2629 NEXT I
2638 LPRINT CHR$<10>, CHR$(18)/ '
2648 LPRIHT'TEHP 1888/T(K) DECK DEGC DEGF RHO RHO(S)'
2658LPRIHT' --------------------------------- '
2668 FOR 1= i TO 8:IF I>€ GOTO 2688
2676LPRINT TEd^KTd^CKD.nd);" VRSd);' ';R(I):GOTO 2698
2688LPRlHTTE(I),KT(l),CTd),n(I)i' D;RSd);' «*'
2698 r€XT I
2788 LPR1HT CH»(18)
2718 LPR1KT •
2728 LPR1HT CH»(10)
2738 LPR1HT CtR$(18)' RHO IS RESISTIVITY WITHOUT 503 IH OHH-Cfl BUT HITH B;HR;a X HflTER"
2748 LPRM °RHO(S) IS THE RESISTIVITY WITH '; S3; • PPN OF S03 IN OHH CM1
2758
2768 LPR1NT •«* HOTE !! EXISTING EXPERlKENTflL DftTfl DO NOT JUSTIFY1
2778 LPRINTCOHPUTRTIONS flT TEM>ERflTURES LWtR THflN 144 DEGREE C"
2788 LPRINT "»MM>MM*«m*M*MMMMIMMMMMMM>*»«»'
2798 LPRINT'*** NOTE *** BECfiUSE THE PREDICTED RESISTIVITY VflLUES ARE"
2888 LPRINT' VERY! SENSITIVE TO SEVERftL FLUE GRS RND RSH CtWOSITIONflL'
77
-------
Table VI (concluded)
PflGE 8 BflSIC PROGRRM FOR RESISTIVITY PREDICTION 27 RUG 1979
2810 LFRlNT'FflCTORS ONE MUST EXERCISE (BERT CflRE IN THE SELECTION •
2829 LPR1NT 'RM> PREPftRfiTION OF COflL RH> RSH SfffLES***'
2838 LPR1NT' THE OJRL1TY OF THE QURNTITflTlVE CHEMICM. PWRLYSIS WORK IS'
2848 LPRINT'OF GREftT IMPORTRNCE**. •
2856 LPRINT'IN ESTflBLlSHlRG THIS PROGRflH THE ftS-RECEIVED ULTIHftTE"
2868 LPRINT'CORL fiNRLYSES «RE OBTfllNED USING flSTM D3176'
2870 LPRINT'CORL flSH HRS PRODUCED USING RSTH D271 PROCEDURE'
2888 LPRIHT'FOLLOICD BV ft SECOK) IGNITION RT 1058 DEC C '
2898 LPRINT+OR- 10 DEC C IN STILL filR FOR 10 TO 12 HOURS'
2988
2910 LPR1NT CHR$(12)
2920 INPUT 'ENTER 1 TO CflLCULflTE RESISTIVITY FOR DIFFERENT 503'; X
2938 IF XO1 GOTO 2988
2948 INPUT'NEW 503 COCENTRflTION IN PPH';S3
2958 LPRINT 'RESISTIVITY FOR °;R$;' BURNING ';»;' COH. WITH 503 OF '; S3i ' FW
2960 X=0
2976 GOTO 2360
2988 INPUT" DO YOU HfWT TO CflLCULflTE RESISTIVITV FOR RNOTHER PLflNT Y OR N';V$
2990 IF Y$='Y" RUN
3888 STOP
3SH0DfiTfl 14,714,441,826, 714
3828 OflTfl i 6, 625, 352, 666, 625, 1 8, 556, 283, 541, 556, 2, 588, 227, 44L 598
3838 DfiTR 2. 2, 455, 182, 359, 455, Z 4, 417, 144, 29L 417
3840 DflTfl 2. 6, 385, 112, 233, 385, 2. 8, 357, 84, 183, 357
3858 DflTft i, 4. 76, . 5, 2. 38, -1. , -4. 76, 0. , 0, 1, 4. 76
3860 DftTfl 12. 81, 2. 82, 32, 28. 6L 32. 06, 18. 02
3878 DftTft 66. 66, 66. 66, 66. 66, 58. , 58. , 40, 40, 33. 33, 33. 33, 28. 57, 25
3888 DflTR 29. 88, 61. 98, 94. 2, 48. 3, 56. 88, 159. 7, 181. 96, 60. 89, 79. 9, 141 94, 80. 86
3090 DflTfl 'C', 'K2', "02°, 'N2°, 'Sn, °H20', 'RSH'
3188 DflTfl1I20', 'Nft20', 'K20V 'HGO', 'CRO', 'FE203', 'RL203', '5102', 'T102', 'P205', '503'
78
-------
Figure 25.
MULTIPLE-CARD LAYOUT FORM
IEND
999999
1 2 3 J 5 6
c
999999
1 1 3 4 5 6
ITITLE
999999
7 8 9 10 II 12
H2
999999
7 t 9 10 11 12
999999
13 14 IS 16 17 18
02
999999
1] 14 15 IS 17 IB
999999999
19 JO 21 22 23 24 25 26 27
XIN
N2
999999999
19 20 21 22 23 24 K 26 27
999999999
28 29 30 31 32 33 34 35 36
S H2O
999999999
28 29 30 31 32 13 M 35 38
999999
37 38 39 40 41 42
ASH
999999
37 33 39 W 41 42
999999
43 44 45 46 47 44
SO2
999999
4J 44 IS 46 47 48
999999999999999999
49 bO 51 52 U 54 55 56 57 58 59 60 61 62 63 64 65 66
W E
999999999999999999
49 50 51 52 5J S) 55 56 57 58 59 60 61 62 63 64 65 66
XMWPO
Li2O
999999
1 1 ] « 5 6
999999
123456
999999
123*56
999999
1 2 J « 5 6
Na2O
999999
7 6 9 10 11 12
999999
7 S 9 10 11 12
999999
7 1 9 10 11 12
999999
7 8 9 10 II 1?
K2O
999999
1) 14 IS 16 17 18
999999
13 14 15 16 17 18
999999
1} 14 15 16 17 18
999999
13 11 15 16 17 18
MgO d
999999999
19 20 21 22 23 24 75 26 27
999999999
19 20 21 22 23 24 25 26 27
999999999
19 20 21 22 23 24 25 K 27
999999999
19 20 21 22 23 24 25 26 27
lO Fe2O3
999999999
28 29 M 31 32 33 34 35 3S
999999999
28 29 30 31 32 33 J4 35 36
999999999
28 M 30 31 32 33 34 35 36
999999999
28 29 M 31 32 33 V 35 36
AI203
999999
37 38 N 40 41 42
999999
37 38 39 40 41 42
999999
37 38 39 4041 42
999999
37 38 39 40 41 42
SiO2
999999
43 U 45 46 47 48
TiO2 P2O5 SO3
999999999999999999
49 50 51 52 5J 54 55 56 57 58 59 60 61 62 63 64 65 66
99999999999999
67 68 69 70 71 72 73 74 75 76 77 78 79 80
99999999999999
67 68 69 70 71 72 73 74 75 7» 77 71 71 M
99999999999999
67 68 69 70 71 72 73 74 75 76 77 7» 79 80
99999999999999999999999999999999999999
43 44 45 46 17 48 49 SO 51 52 S3 54 55 56 57 58 53 60 61 62 63 64 65 66 67 68 63 70 71 72 73 74 75 76 77 71 71 80
999999
43 U 45 46 4) «
999999
43 M 45 46 47 48
99999999999999999999999999999999
49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
999999999999999999
49 50 M 52 53 54 55 56 57 58 59 60 61 62 6j 64 65 66
99999999999999
67 U 69 70 71 72 73 71 75 76 77 78 79 BO
-------
"EELCHFIRE UNIT 1 PUMPKIN SWAMP CDAL
0 0 D 0 0 0 S 0 0 0 0 ••! D 0!:; 0 : C 0 D :| 3 D 0 0 0 0 x :i: 0 0 0 0 0 0 0 0 0 0 0 0 0 S G 0 D 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 G 0 0 : : : 3 D 0 0 0 0 0
i i i i s i i i •. i] i' ii:: ,t is ii >i it 11 ii ii i: :i :t :i :i n n n 11 n » u u 11 u ji 11 11 » n a a u u » i: u a a \\ a :i v 11 u 1111 si t; c ti n n n r. n u u it n .; n » •> :; » 'i '< 11
I I I 1 I II I I i II I I 111; II I II I I 1 I 11 I gIII II I ij II II I I I I I I I I 11 I I I I 11 I II I I I I II I II I I I II I I i I 1 II
2 g 2 2 2 2 2 2 2 2 2 2 2 Z 2 2 Z 2 Z 2 2 Z ; is 2 2 2 S 2 2 2 Z Z Z Z Z Z Z Z 2 2 2 2 2 Z Z 2 2 Z Z 2 Z Z Z 2 Z Z Z Z 2 2 2 2 2 2 2 2 2 2 2 Z 2 2 2 2 2 2 2 2 2
3 3 3 * ii 3 3 3 3 3 1 3 3 3 •;! 3 3 3 3 3 2 3 3 3 3 3 3 3 3 3 3 3 3 £ 3 3 S 3 3 3 J 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
44 4 4 4 < 4 4 i 4 4 a 1 ; < ,' 4 4 4 4 f: g 4 •! 4 4 4 4 4 4:? 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 < 4 4 4 4 4 4 4 < 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 '. ! < 4 < J < 4 4 4
5 5 v 5 5 5 S 5 '. S 5 5 ? 5 S S 5 5 i 5 5 5 5 5 5 ?: 5 5 5 b 5 5 5 5 5 5 5 5 5 S 5 5 5 5 5 5 5 S 5 5 ! 5 5 5 5 5 5 5 5 5 5 5 5 5 5 S 5 5 5 5 5 5 5 5 5 5 5 5 5 5
E E D B E t 5: 6 5 S C Ii ii 6 5 ( 6 6 G D S 5 6 6 6 6 6 C':;': 5 "a 6 5 C S 6 6 a 1 5 6 S B 6 5 S 6 6 S 5 E G 6 5 6 6 6 6 6 6 E G 8 t S 6 6 E 6 6 S u 6 i 5 E G £ S 6
1117111J i: J i i J 7) 7 7 7 ;;i) J ii 1717 7171 s 7117 7 7 7 7 7 7 7 7 J 717 7 7 M 71117 717 7 71717 ? i > J i J111117 7 7 [
a B 3 B 8 >: S S : 0 8 B 8 3 3 m 3 S B n G S B 1 ! : C a J B S 8 m 8 3 6 8 3 3 8 H 9 e t t t : 8 9 C I B 8 B 8 8 ; 0 8 I 8 8 S I E E 3 I 3 i B 3 8 8 [
! 9 S 9 9 3 9 ;!':•: 9 S 9 :• 9 9 3 9 0 9 S 3 9 9 :•: 9 9 3 9 9 9 3 9 9 9 9 3 9 9 9 9 5 9 9 9 3 999 9 9 9 5 S ! 9 9 9 9 9 9 3 3 3 3 9 9 0 3 5 9 9 9 2 i 9 9 3 9 9
i i j i : t i i ) •) n i; •] -i •; ••. ', u n i: ;• n n := i; )i IT :i :i u n 33 i! u u is n 11 n *i : 3 3 3 3 3 i| i| 3 3 3 3 3 i|i 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 j 3 J 3 3 3 3 3 3 3 3
4 j .; 4 .; 4 :|. < < 4 44 4 4 4 4 4 J i 44 (4 4 4 4 4 4 < i. t 4 4 4 4 44 M ? t ( 4 4 < 4 4 4 4 J 4 4 ( < < 44 < I 4 i 44 4 < 4 ( < 4 4 4 4 4 4 44 U U
j 5 5 3 5 1 5 f i : 5 5 5 5 5 5 5 5 5 S 5 5 S S 5 5 ':• 5 5 5 5 5 5 3 5 5 5 5 b i S S 5 C- 5 5 5 5 5 5 5 S 5 5 5 5 5 5 5 5 5 5 S 5 5 5 5 5 5 5 5 5 5 5 5 5 S 5 5 5
C 5 C : 6 G 6 G ij S 6 6 6 8 6 S S 0 G 6 S ii 6 t B i 6 6 S E E E G 6 6 6 6 E 6 6 E B 6 6 6 5 i 5 6 6 G S 6 G G G 6 6 C 6 6 S C " '. C S 8 ; G '. 5 t G 6 C £ 5 t 5
j 1 7 1 1 7 7 1 1 1 I 1 1 7 1 7 I 7 7 i 1 1 1 1 7 1 7 17 7 7 7 i 7 i|: •; 7 7 1 J 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 1 7 1 7 7 7 1 7 7 7 7 7 7 1 I 7 1 7 1 7 1 7 7 1 7 7
C :; |i 1 J I 1 :;• 8 t B 8 8 :j: 0 a 8 0 8 i; 3 S 8 ! 8 •: 8 5 8 8 D t \: 8 J a 8 ;!; 8 8 6 C ! 8 8 8 8 i 3 ! C 8 B 3 8 t ! 8 6 C 8 8 B E 3 6 ! C 8 J E E C S 8 8 3 J 8
9 5 9 C 0 9 9 9 1!;.; 3 : J 9 9 9 9 9 3 S 5 S 9 3 9 9 9 3 C 5 9 S 3 9 3 9 9 S C 9 ') 9 9 ?! 0 9 9 9 9 3 9 9 9 3 :5 3 I 1 9 9 5 9 9 0 3 D 9 C 9 ? 1 9 9 9 9 9 9 9
i i ; i i b • . 'i . .-. •-. u -s u u n ;i i! u n 31 :s • :i 11 :i': n i; n ;i is :i n ;; :i u n u .; u u n u n n n i: u : i: :; n n n u
111;;; 11111 ii i •;; 111111 ii 111 ji 11 j; 11111111:? 111 M 111111111111111111111 i i M 11 M 11 M 11111
2 2 2 2 2 2 2 2 2 2 3 2 2 2 2 2 2 2 g 2 2 S 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 ! 1 2 I :| 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
3 i: 3 3 3 3 J :=: 3 3 3 3 31:;:-; 3 3 3 3 :=: 3 3 3 3 3 .•:.•: 3 3 3 3 •: 3 3 3 3 3 3 :|i 3 3 3 3 3 i|! 3 3 3 3 g 3 3 3 3 3 g 3 3 3 3 3 :! 3 3 3 3 3 3 3 3 3 3 3 3 1 3 3 3 1 3
4 t 4 4 4 n < ?: 4 44 I 4 4 ! J 4 M * 4 1 4 4 4 4 q 1 4 4 4 |: 4 4 4 4 44 f. 4 4 j? 4 4 4 4 4 4 4 4 £ < 4 4 4 4 44 4 4 4 4 4 44 4 44 4 4 U 4 4 1 4 44 4
5 5 5 5 5 b b b 5 b b 3 5 5 5 5 5 I ! j 5 S b b 3 S b 5 5 b b 5 5 b b b b b 5 5 5 5 5 b 5 b 5 b 3 5 S 5 5 b S 5 ;•: 5 S 5 5 b g b 5 5 S S 5 J 5 5 5 5 5 } S 5 5 b
6 6 6 6 3 i 5 5 5 g 6 6 6 6 B B B D 5 0 6 6 E 6 5 C 6 C 5 6 6 S 6 :; 5 6 5 6 C B B 6 6 6 6 $: 6 6 6 B :':: 6 6 C 6 6 6 6 E B C G 5 3 J B 6 C 5 i, 6 6 '; 6 6 5 S 5 B 6
j 1 I 7 1 7 1 I I 1 7 7 7 7 7 7 7 7 7 7 7 7 1 7 1 7 7 1 7 7 7 :| 7 7 7 7 7 1 7 7 7 7 7 1 1 7 7 7 7 7 7 7 7 7 7 7 1 7 I; 1 1 1 1 1 1 1 1 1 1 1 1 I 7 7 7 7 1 7 7 7 7
{ 8 j: C S ! J B ji ! : 3 3 t :ij £ 8 B ! E £ >j 5 ': i 3 B :i: 5 8 B 8!; 8 U E 8 g i; 8 3 B B B H B 8 8 8 S S » 8 8 8 g B 3 8 8 8 |: J 8 8 8 B 6 I! B ? i) B 8 8 S I 53 9
! 9 9 3 9 0 5 C 9 S 3 9 : 9 C 'J 9 3 9 9 9 9 3 9 3 9 3 C 1 3 9 3 9 9 9 9 9 9 9 9 9 9 3 S 9 9 9 9 9 3 9 9 9 9 9 9 9 S 2 9 9 S t 9 3 3 9 3 3 9 9 9 9 9 9 J 9 S 9 9
i i l < s r * j . . •• ,: -i -. •'. :i i.' i; r.:; ;i ;i:: is:; 311: j ,.• :i 31 u u /.:;;: u » u n c n n is it u u i: '.i si n 'i '.> '•• '•> '•''-' •* '* t: '• < -; '-• -•i? ll " " " " " '• IJ " "' " ' l:
L_ . 9011
Figure 26. Example Data Input Cards
80
-------
simply omitted from the data input. If one wants the resistivity
predicted for some value of field strength other than 10 kV/cm,
the field strength value desired is punched in for the variable
E instead of leaving it blank. Also, in place of an as-received
coal analysis (variable XIN on the second card), one can introduce
known or assumed sulfur dioxide and environmental water concentra-
tions for the variables S02 and W respectively on the second
card.
Table VII is the data printout for the FORTRAN computer
program for predicting resistivity as a function of temperature.
On the first page, the as-received ultimate coal analysis input
data are shown along with the essential features of the calcula-
tion of combustion products using 30% excess air. At the bottom
of the page, several of the parameters critical to the calcula-
tion of resistivity are tabulated: (1) the environmental water
concentration in volume percent, 9.9%; (2) the sulfur dioxide
concentration in dry volume ppm, 1350 ppm; (3) the sulfur tri-
oxide concentration (sulfur dioxide x 0.004) in dry volume ppm,
5.4 ppm; and the field strength (E) to be used, 10 kV/cm.
Table VIII is the data printout for the BASIC program.
On the top of the second page of Tables VII and VIII, the ash
analysis input data are shown with the resultant values of cationic
atomic concentration. This calculation was demonstrated in the
preceding section. The atomic concentrations critical to the
computation of resistivity are tabulated as: (1) lithium plus
sodium, 0.35%; (2) magnesium plus calcium, 10.7%; (3) iron, 1.3%
and (4) potassium, 0.65%. At the bottom of the page is a tabula-
tion of temperature and resistivity. The resistivity values
with the heading RHO (VS) are those resulting if the effect of
sulfuric acid vapor is excluded, while the data headed RHO (VSA)
are those resulting from the prediction including the effect
of acid vapor.
Figure 27 presents in graphical form the predicted values
of resistivity as a function of temperature with and without
the effect of sulfuric acid vapor taken into account. These
data were generated using a fictive coal and coal ash. Although
the principal purpose of the technique is to predict resistivity
from core bore samples of coal, one can obviously use it to gener-
ate information about the effect that various parameters have
on resistivity.
81
-------
Table VII
PFSISTIVITV putorcTiou RASED ON HORK RONE BY
DP. '•'OY PTTKKIHAUPT OF SOUTHERN RESEARCH INSTITUTE.
Tut RESFARCH WAS SPONSORED RY THE PARTITULATE
TFCHMOLOGY FiHi'ir.H. INDUSTRIAL ENVIRONMENTAL RESEARCH
LABORATORY "F THf. £MVIRONMF.NTAL PROTECTION AGENCY.
DP. L. E'. SPARKS, PRO.IECT OFFICER'.
HEl.CHFTRF U'iTT i PIIMPKIM S^AMP COAL
02
N?
s
AS
ASH
AN:AL
COAL
58.13
4.6°
9.13
1.36
1.50
13.77
11.12
100.00
MOLfS PER
tOO I.B
FUEI.
2.322
0.2B5
0.76'J
0.000
FOR COMBUSTION
MOLFS/100 LB FUEL
AT 1QOX TOTAL AIR
0?
U.««0
1.161
• 0.?85
0.000
0.047
o.ooo
0.000
5.763
DRY ATP
?3'.03«
S',526
-l'.357
o.oon
0,22
-------
Table VII. cont'd.
LI20
NA20
K20
MGQ
CAO
Ffc?03
AL203
SI02
TI02
P205
S03
SUM
ASM
ANALYSIS
0.01
0>6
1.30
11
3.9F+11
7. IE* 10
5.5E*09
**
**
** EXISTING
AT
OATA DO NOT JUSTIFY COMPUTATIONS
THAN J^^j DEGREES C*.
NOTE: RECAMSE THF PRFPICTED PESISTIVITY VALUFS ARE VFRY
SENSITJVF. Tn S.FVERAl FLUE GAS AMD ASH COMPOSITIONAL FACTORS,
ONE MUST F.XF.RCTSF T,RF.AT CARE IN THE SELECTION AND PREPARATION
OF COAl AND ASH SAMPI.F:S. FURTHERMORE. THE QUALITY OF THE
flUANTITATiVf CHEMICAL ANALYSIS WORK IS OF GRFAT IMPORTANCE.
IN ESTAHI ISHIMG THIS P&OGHAM. THF AS-RECEIVER. ULTIMATE COAl.
ANALYSES WFRf PRTAINFO USING ASTM 03176 PROCEDURE, A.MD THE
COAL ASH WAS PRODUCED USING ASTM 0271. PROCEDURE FOLLOWED BY
A SECOND IGNITION AT 1050 DEGREES C * OR . 10 DEGREES C IN
STILL AIR FOR 10 TO i? HOURS'.
83
-------
Table VIII
PftGE 9 BflSIC PROGRAM FOR RESISTIVITY PREDICTION 27 RUG 1979
RESISTIVITY PREDICTION BRSED ON HORK DONE BV
DR. ROY B1CKELHAUPT OF SOUTtON RESEARCH INSTITUTE
BASIC PROGRAM BY DR. L E. SPARKS PART10JLATE TECHNOLOGY BRANCH
INDUSTRIE ENVIRONMENTAL RESEARCH LAB RESEARCH TRIANGLE PflRK HC EPfl
VERSION! NAY 1,1979
PLANT NAME IS BELCHFIRE 1 OH. NAME IS PUMPKIN SHAMP
REQUIRED FOR COHBUSION
HOLES/188LB FUEL
C
H2
02
N2
S
H28
ftSH
SUM
AS RECEIVED
ULTIMATE COAL
58.13
4.69
9.13
136
15
1177
1142
188
MOLES PER
18BLBSFUEL
4.84
2322
.285
.849
.847
.764
8.387
AT 188KTOT
02
4.84
1161
-.285
8
.847
8
5.763
RL AIR
DRY AIR
23.838
5.526
-1357
8
.224
8
27.431
REQUIRED FOR COHBUSTION
HOLES/188 LB FUEL
ttSXXCESS AIR
02 DRY AIR
02 WD R1R*138/188 TOTAL 7.492 35.66
EXCESS AIR 8.229
EXCESS 02 1729
PRODUCTS OF COffiUSTlON *****
TOTAL
HOLES/188 7. BY VOL X BY VOL
FUEL WET BASIS DRY BASIS
C02 4.84 12516 13.894
K28 3.83288 9.912 8
S02 .847 .122 .135
N2 28.2284 72.979 81888
02 1.729 4.471 4.963
SUM WET 38.6693
SUM DRY 34.8364
H20 9.9 •/.
S02 1358 PPM
S03 5.4 PPM
ELECTRIC FIELD 18 KVrtM
84
-------
Table VIII (cont'd)
CORRECTED
RSH RTOMIC
RNRLYS1S CONCENTRflTIOH
.8163242 .8156999
.474912 .248163
L 34214 .65
2,91142 2 46221
13.5247 a 21948
7.78184 13
18.9965 5.87995
512879 19.3689
. 668748 . . 18788
.588478 .8887485
2.58165 .549383
188 38.2668
SDH OF L1TH1LH RID SODIUM RTOH1C CONCENTRRT10NS . 36
sun OF MRGNESiurt m> atciun OBCENTRRTIOHS ia?
IRON RTOHIC CONCENTRRTION 1 3
POTASSIUM RTOM1C CONCENTRATION . 65
RSH
RNfLYSIS
LI20 .81
NR20
K20
HGO
CRO
FE203
RL203
SI02
T102
P205
503
SUM
.46
13
282
111
7.46
18.4
49.6
.64
.57
2.5
96.86
TEHP 1808/T(K) DECK
DEGC
DEGF
RHO
RHO(S)
1.4
16
1.8
2
2.2
2.4
26
2.8
714
625
556
588
455
417
385
357
441
352
283
227
182
144
112
84
826
666
541
441
359
291
233
183
22E+89
16E+1B
liE+ii
6.3E+11
12E+12
7.3E+11
26E+11
2.1E+18
22E+89
16E*18
11E+11
3.9E+11
7.1E+18
5.5E+69
*»
*»
RHO IS RESISTIVITY WITHOUT S03 IN OHfKfl BUT WITH 9.9 '!. HRTER
RHO(S) IS THE RESISI^ITV KITH 5.4 PPM OF S03 IN OHH CM
** NOTE !! EXISTING EXPERIMENTS DRTft DO NOT JUSTIFY
COIfUTRTIONS RT TEHPERflTURES LOWER THflN 144 DEGREE C
»Mi«»*»frKMMMMMM>«iMMMi>IMUMMMm*m
*** NOTE *** BECAUSE THE PREDICTED RESISTIVITY VRLUES RRE
VERY! SENSITIVE TO SEVERRL FLUE GfiS RW> RSH COHPOSITIONRL
FRCTORS ONE MUST EXCERCISE GRERT CRRE IN THE SELECTION
RH) PREPRRRTION OF CORL RND RSH SRHPLES***
THE QURLITV OF THE QURNTITRTIVE CHEHICfiL RNRLVSIS WORK IS
OF GRERT 1HPORTRNCE**.
IN ESTRBLISHING THIS PROGRffl THE ftS-RECEIVED ULTIHRTE
CORL RNRLYSES HERE OBTRINED USING RSTH D3176
CORL RSH MRS PRODUCED USING RSTM D271 PROCEDURE
FOLLOKD 6V R SECOND IGNITION RT 1950 DEG C
+OR- 18 DEG C IN STILL RIR FOR 18 TO 12 HOURS
85
-------
SYM
O
A
PRINT
OUT
RHO(vs)
RHOIvsa
1013
10
3
5
c
D
- 1C
>
r>
n
u
c.
10
1
1000
12
11
10
09
m°
-
NAME
BELCH FIRE UNIT 1
PUMPKIN SWAMP CO-
--
-
—
f
\
—
C/P
-
tu-
-
f
4-
\-t-
1
/
/
,f
/
/
\
PR.
-
-
H20
9.9
9.9
°2
5.0
5.0
-/
* k
i »
1
•«
/
^
/
f
SO2
0
1350
S03
0
6.4
i
/
i
(
t
L
\
\
S
s
A
V
- -
t\
P%
-
-
\
\-
\
\
\
\
^
E. kV/cm
10
10
I
\
\
\
\
\—
}
mmd. pm
-
-
1 —
^
—
d. g/cc
-
-
i-
-
K)— -3.2 3.0 2.8 Z6 2.4 2.2 ZO 1.8 1.6 1.4 1.2
°C— 40 60 84 112 144 182 227 283 352 441 560
°F— -103 141 183 233 291 359 441 541 666 826 1041
DATE
-
-
TEMPERATURE
Figure 27. Predicted resistivity for the fictive coal and coal ash used to
illustrate the computer program.
86
-------
SECTION 9
PREDICTED RESISTIVITY PROOF TEST
In the preceding sections experimental data have been pre-
sented to quantitatively relate resistivity to the principal
fly ash and flue gas compositional factors that influence this
property. Finally, these relationships were used to predict
resistivity as a function of temperature utilizing input data
acquired from the ultimate analysis of a coal and the composi-
tional analysis of the respective coal ash.
The accuracy of resistivity predictions made in the above
manner was tested using data mainly acquired from another re-
search project that required significant field testing.2i The
objective of the proof test was to compare predicted resistivity
values with those values determined in the laboratory and in
situ using a point-plane resistivity probe. Furthermore, these
data were compared with mass train efficiency information and
the current density of the outlet field of the precipitator.
During a relatively short time period (several hours) while
the boiler and the precipitator were operating in a normal full-
load manner, the following data and samples were simultaneously
taken: coal sample, fly ash sample, ir\ situ resistivity data,
mass train efficiency data, secondary current and voltage data,
and the flue gas analysis at the precipitator inlet. The coal
sample was used to obtain the as-received ultimate coal analysis
and to produce the coal ash for chemical analysis. The fly ash
sample was subjected to chemical analysis and was used to deter-
mine the laboratory resistivity data. Laboratory resistivity
values were measured in an environment simulating the rn situ
environment with respect to temperature and the concentrations
of water vapor and sulfur trioxide.
The field test data and samples from six power stations
were used. Three stations were burning coals from the western
part of the United States. Two cold-side and one hot-side pre-
cipitators were in use at these stations. A similar situation
existed for the three stations burning coal from the eastern
part of the United States with the exception of the prerequisite
that one of the cold-side units was collecting ash produced from
a "cleaned" coal.
87
-------
For each station, Table IX records the field test date,
the size of the unit tested, the specific collection area of
the precipitator and the analysis of the coal being burned at
the time of interest. The W or E following the station number
indicates whether the station was burning western or eastern
coal respectively. The table conveys the variation in station
and precipitator size and the coal quality.
In Table X the chemical analyses for fly ash and coal ash
for each station are shown. The coal ash was analyzed after
the ashing procedure previously described in detail was executed.
Soluble sulfate (SO,,) and loss on ignition were determined on
separate fly ash specimens. The remainder of the ash from the
loss on ignition test was used to determine the chemical com-
position of fly ash.
Also in Table X, the jji situ flue gas composition is com-
pared with the composition calculated from the stoichiometric
combustion of the coal using 30% excess air. It was previously
stated that the predicted value for sulfur trioxide was arbi-
trarily taken as 0.4% of the sulfur dioxide value. With respect
to the measured flue gas values, the sulfur dioxide and sulfur
trioxide values are usually averages and ranges of values respec-
tively depending on the availability of field test data taken
during a time period of two to eight hours.
Comparison of the chemical compositions of fly ash with
the respective coal ash compositions shows little difference
between the values that are specifically significant in the pre-
diction of resistivity. These of course, include the elements
lithium, sodium, magnesium, calcium and iron. Furthermore, the
entire weight percent analysis of the coal ash is similar enough
to the respective fly ash analysis that one would not find a
significant difference between resistivity data predicted from
fly ash or coal ash for the stations evaluated.
With respect to the prediction of resistivity, the principal
flue gas species are sulfur trioxide and water vapor. The in
situ and predicted values for these environmental factors can
also be compared in Table X. For the six stations examined,
the water concentration was under-predicted three times and over-
predicted three times. The greatest deviation was a predicted
concentration 30% greater than the measured value. On the average,
the predicted concentration was 5% greater than the measured
value. Typically, a predicted value of 9.5 volume percent would
relate to a 9.0 volume percent measured value, an insignificant
difference. Under the usual cold-side precipitator conditions,
a 30% error in water concentration could cause a factor of two
error in predicted resistivity.
88
-------
Table IX. Predicted Resistivity Proof Check
General Information and Coal Analyses for Six Power Stations
STATION NUMBER
oo
vo
TEST DATE
UNIT SIZE,
MW
SCA OF ESP, m2/m3/sec
ftVft'/min
COAL ANALYSIS
AS-RECEIVED
PROXIMATE, wt. %
Moisture
Volatile Matter
Fixed Carbon
Ash
Sulfur
Btu
AS-RECEIVED
ULTIMATE, wt. %
Carbon
Hydrogen
Oxygen
Nitrogen
Sulfur
Moisture
Ash
KW)
7 AUG 75
135
98.8
504
13.94
37.78
43.07
5.21
0.41
10,557
59.41
4.24
15.33
1.46
0.41
13.94
5.21
3(E)
2 MAR 76
122
50.2
256
10.84
33.99
43.94
11.23
2.05
11,050
62.44
3.95
8.27
1.25
2.02
10.84
11.23
4(E)
27 APR 76
271
76.4
390
6.22
30.73
50.20
12.85
0.95
11,903
64.75
4.11
9.42
1.69
0.96
6.22
12.85
5(W)
5 OCT 76
508
117.2
598
19.91
26.48
42.16
11.45
0.43
9,104
52.01
3.53
11.55
1.02
0.53
19.91
11.45
7(E)
17 SEPT
350
33.3
170
11.68
31.06
46 . 36
10.90
0.81
12,011
65.22
3.87
6.21
1.21
0.91
11.68
10.90
13 (W)
21 JULY 77
800
60.2
307
12.34
37.81
40.59
9.27
0.48
10,630
60.58
4.16
11.78
1.39
0.48
12.34
9.27
-------
Table X. Predicted Resistivity Proof Check
Ply Ash, Coal Ash, and Flue Gas Compositions for Six Power Stations
vo
o
STATION NUMBER
ASH COMPOSITION
WEIGHT PERCENT
LizO
Na2O
KiO
MgO
CaO
PejO,
AlzOj
SiOi
TiOj
PiOs
SOi
TOTAL
LOI
SOLUBLE SOLFATE
FLUE GAS
COMPOSITION
C02, VOl %
Oz , VOl »
HjO, vol %
SO 2 ppm
SO 3 ppm
1W
FLY
ASH
0.02
0.29
1.8
3.6
8.6
5.9
23.7
51.9
1.3
0.39
1.2
98.7
0.8
0.7
IN SITU
13
7
8.3
262
<1
COAL
ASH
0.01
0.27
1.0
2.8
7.5
6.0
15.2
65.3
1.2
0.35
0.58
100.2
-
-
PREDICTED
13
5
9.6
440
1.8
3E
FLY
ASH
0.03
0.67
2.1
1.0
5.0
13.1
21.8
50.2
2.0
0.78
2.3
99.0
10. "9
1.6
IN SITU
13
5
8.2
2440
6-9
COAL
ASH
0-.03
0.63
2.1
1.0
4.6
9.0
25.4
53.3
1.6
0.21
0.77
98.6
-
-
PREDICTED
13
5
8.4
1730
6.9
4E
FLY
ASH
0.04
0.43
3.5
1.3
1.1
7.2
28 -.4
53.8
1.8
0.23
0.50
98.3
3.5
0.3
IN SITU
15
5
8.5
755
2-3
COAL
ASH
0.04
0.44
3.2
1.2
1.0
7.4
28.4
53.3
1.9
0.24
0.15
97.3
-
-
PREDICTED
13
5
7.8
800
3.2
5W
FLY
ASH
0.02
1.38
0.54
1.1
5.8
6.1
13.2
70.8
0.9
0.05
0.50
100.4
1.0
0.5
IN SITU
13
6
8.1
480
<1
COAL
ASH
0.02
1.28
0.53
1.8
5.3
2.5
13.7
73.6
1.2
0.13
0.63
100.7
-
-
PREDICTED
13
5
10.5
570
2.3
7E
FLY
ASH
0.05
0.27
2.1
0.9
3.7
7.1
29.3
53.5
1.8
0.20
0.7
99.6
7.5
0.7
IN SITU
ND
ND
9.0
600
3-4
COAL
ASH
0.05
0.31
2.2
0.9
3.2
6.8
29.4
54.4
1.6
0.33
1.6
100.8
-
-
PREDICTED
13
5
8.2
740
3.0
13W
FLY
ASH
0.01
1.42
1.0
1.8
6.7
5.0
25.5
56.3
1.0
0.31
0.71
99.8
2.6
0.5
IN SITU
15
5
9.6
430
<1
COAL
ASH
0.01
1.51
0.9
1.9
7.3
5.7
21.6
57.8
0.5
0.3
3.5
101.0
-
-
PREDICTED
13
5
9.1
429
1.7
About 3% of this ash was > 0.18 mm (+80 mesh) and mostly carbon.
It was removed prior to testing.
-------
The predicted values for sulfur trioxide were within the
range of values reported in the field test data for the stations
burning eastern coal. However, the predicted sulfur trioxide
concentration for the stations burning low-sulfur western coals
was about 2 ppm while the in situ value was < 1 ppm. Several pos-
sible explanations can be given for this observation. The iri situ
measurement of sulfur trioxide is not a simple test, is subject
to error, and is less reliable the lower the concentration of
agent present. Also, 2 ppm is near the level of detection.
On the other hand, the ashes from western coals are inherently
more basic than ashes from eastern coals. This greater affinity
for acid vapor coupled with the low available concentrations
of sulfur trioxide could lead to an almost undetectable concen-
tration remaining in the flue gas at the inlet to the precipi-
tator. In the proof test experiments, the sulfur trioxide value
determined from the stoichiometric combustion calculation was
used to predict resistivity, while the in situ value was duplicated
in the experimental environment for the determination of labora-
tory resistivity.
Table XI shows a comparison of ir\ situ resistivity just
prior to dielectric failure, laboratory resistivity just prior
to dielectric failure, and predicted resistivity at a field strength
of 10 kV/cm. The temperature listed refers to the temperature
at which the in situ determination was made and later duplicated
during the laboratory measurement. Precipitator mass train ef-
ficiency and current density for the outlet field are also given
as circumstantial evidence to help evaluate the quality of the
resistivity determinations and prediction.
Figures 28 through 33 show the in_ situ and laboratory resis-
tivity data superimposed on a curve of predicted resistivity
as a function of temperature for each of the stations evaluated.
To illustrate the pronounced effect of sulfuric acid vapor on
resistivity, the data are plotted with and without the effect
of the predicted concentration of sulfur trioxide taken into
account. The predicted resistivity under consideration in all
cases except station 5 is the value obtained by including the
effect of sulfur trioxide. In the case of station 5, the tem-
perature of interest is significantly lower than the lowest
temperature used to develop the predictive parameters involving
sulfur trioxide.
The data illustrated in Figures 28 through 33 visually demon-
strate the generally good agreement obtained between predicted
and measured results. Only in the case of stations 5 W and 4 E
was the deviation significant. In these instances, the in situ
resistivity data were about one order of magnitude greater than
either the predicted or the laboratory measured data.
91
-------
Table XI. Predicted Resistivity Proof Check
Temperature, Resistivity and Performance Data for Six Power Stations
STATION NUMBER
TEMPERATURE, °C
RESISTIVITY, ohm-cm
In Situ Spark
Laboratory, Spark
Predicted, 10 kV/cm
ESP EFFICIENCY, %
CURRENT DENSITY
OUTLET FIELD, nA/cm2
1W
145
3.0 x 1011
5.0 x 10 ll
1.2 x 101 '
99.92
15
3E
158
2.1 x 10 10
2.3 x 1010
7.0 x 1010
99.87
45
4E
332
3.0 x 10 10
4.0 x 109
2.3 x 109
99.65
37
5W 7E
105 163
5.0 x 101 ' 2.7 x 101 '
5.0 x 1010 2.2 x 101 l
1.6 x 10lo(a) 5.0 x 101 '
99.85 NA
23 NA
1.8
2.0
1.4
99
13
13W
350
x 10 9
x 10 9
x 10 9
.22
a Test temperature below that of acquired laboratory data involving sulfur trioxide.
-------
SYM STATION NAME
D
O
A
O
10
10
i
j
£
£
O
^ 1C
>
/>
7i
u
r
1C
1
1W
1W
1W
1W
13 p~i
12
11
10
n9
-
PREDICTED
PREDICTED
IN SITU
LABORATORY
C/P
—
_
-
-
-
i
I
/
/
A
PR.
-
—
-
-
-t
1
t
(
/
H2O
9.6
9.6
8.3
9.0
°2
5
5
7
CO2
13
13
13
AIR
/
/
t
ft
I
^
'
\
••
/
\
*
1
f
»
j
/
r
T
f
t
/
1
s
/
V
^
so2
440
0
262
0
s
«
^
\
1
S03
1.8
0
<1
1.3
i
\
\
^
P%
—
—
-
-
?
>
S
k
\
1
E. kV/cm
10
10
SPARK
SPARK
\
)
-\-
i
\
v
>
\
\
i
\
mmd, um
-
-
-
-
--
1
d. g/cc
-
-
-
-
DATE
-
-
-
-
1000/T(°K)
°C
°F
— 3.2
— - 40
3.0
60
— 103 141
2.8
84
183
2.6
112
233
2.4
144
291
2.2
182
359
2.0
227
441
1.8
283
541
1.6
352
666
1.4
441
826
1.2
560
1041
TEMPERATURE
Figure 28.
Predicted, in
situ.
and labor
awry
measured
resistivity data,
Station 1W.
93
-------
SYM STATION NAME
a
o
A
o
3E
3E
3E
3E
PREDICTED
PREDICTED
IN SITU
LABORATORY
C/P
-
-
-
-
PR.
-
-
-
-
H2O
8.4
8.4
8.2
9.0
°2
5
5
5
C02
13
13
13
AIR
SO2
1730
0
2440
0
so3
6.9
0
(6-9)
8.7
P%
-
-
-
-
E. kV/cm
10
10
SPARK
SPARK
mmd, urn
-
-
-
-
d, g/cc
-
-
-
-
DATE
-
-
-
-
o
o
>
(/)
UJ
DC
IU
10"
ioio
109
108
1000/T(°
<
/
/
/
>
v
/
/
I
f
)
/
/
X
<
t
r
•
1
/
I
'
w
_
*.
/
-JL
f
L\
3
^
1,
1
^
r
s
s
>
S
\
-r
1
>
k
>
\
\
\
I
L
\
\
\
>
\
(
J
\
t
1
I
\
>
\
k
\
r
i
K)— -3.2 3.0 2.8 Z6 Z4 2.2 2.0 1.8 1.6 1.4 1.2
°C— -40 60 84 112 144 182 227 283 352 441 560
°F— -103 141 183 233 291 359 441 541 666 826 1041
TEMPERATURE
Figure 29. Predicted, In situ, and laboratory measured resistivity data.
Station 3E.
94
-------
SYM STATION NAME
a
0
A
o
4E
4E
4E
4E
PREDICTED
PREDICTED
IN SITU
LABORATORY
C/P
-
—
-
-
PR.
-
-
-
-
H2O
7.8
7.8
8.5
9.2
°2
5
5
5
5
CO2
13
13
15
S02
800
0
755
AIR
S03
3.2
0
2.5
3.1
P%
_
_
—
-
E. kV/cm
10
10
SPARK
SPARK
mmd, tiff*
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_
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-
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DATE
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(
1
K) — 3.2 3.0 2.8 2.6 Z4 Z2 ZO 1.8 1.6 1.4 1.2
°C— 40 60 84 112 144 182 227 283 352 441 560
°F — 103 141 183 233 291 359 441 541 666 826 1041
TEMPERATURE
Figure 30. Predicted, iii situ, and laboratory measured resistivity data,
Station AE.
95
-------
SYM
D
O
A
o
STATION NAME
5W
5W
5W
5W
PREDICTED
PREDICTED
IN SITU
LABORATORY
C/P
-
-
-
-
PR.
-
-
-
-
H20
10.5
10.5
8.1
9.0
°2
5
5
6
C02
13
13
13
AIR
S02
570
0
480
0
S03
2.3
0
1
1.0
P%
-
-
-
-
E. kV/cm
10
10
SPARK
SPARK
mmd. urn
-
-
-
-
d. g/cc
-
-
-
-
DATE
-
-
-
-
RESISTIVITY (OHM-CM)
•*
S-» £ 0 0 C
-JO O -» -»
Zl co «o o ->
<
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I
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/
fl
^
r
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K)— "3.2 3.0 2.8 2.6 2.4 2.2 2.0 1.8 1.6 1.4 1.2
°C— 40 60 84 112 144 182 227 283 352 441 560
°F— -103 141 183 233 291 359 441 541 666 826 1041
TEMPERATURE
Figure 31. Predicted, in situ, and laboratory measured resistivity data,
Station 5W.
96
-------
SYM STATION NAME
a
o
A
o
O
+
y
v
RESISTIVITY (OHM-CM)
7E
7E
7E
7E
7E
7E
7E
7E
10"
10™
mS
PREDICTED
PREDICTED
IN SITU
LABORATORY
PREDICTED
IN SITU
PREDICTED
IN SITU
-
-
._
_
-J-<
-
-
-
-
-
-
-
C/P
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-
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—
-
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f
H2O
8.2
8.2
9.0
9.0
8.2
9.0
8.2
9.0
>
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J
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°2
5
5
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5
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5
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T
-
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-
DATE
_
_
_
—
—
1000/T(°K) — 3.2 3.0 2.8 Z6 2.4 2.2 ZO 1.8 1.6 1.4 1.2
°C-~ 40 60 84 112 144 182 227 283 352 441 560
°F — 103 141 183 233 291 359 441 541 666 826 1041
TEMPERATURE
Figure 32. Predicted, iri situ, and laboratory measured resistivity data.
Station 7E.
97
-------
SYM STATION NAME
D
O
A
o
13W
13W
13W
13W
PREDICTED
PREDICTED
IN SITU
LABORATORY
,012 „,.
10"
RESISTIVITY (OHM-CM)
in™
109
C/P
-
-
-
-
r
/
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f
r "
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430
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5
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nramd. um
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-
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-
-
DATE
-
-
-
-
\
J
1000/T(°K) — 3.2 3.0
°C — 40 60
°F—-103 141
2.8
84
183
Z6
112
233
2.4
144
291
2.2
182
359
2.0
227
441
1.8
283
541
1.6
352
666
1.4
441
826
1.2
560
1041
TEMPERATURE
Figure 33. Predicted, in situ, and laboratory measured resistivity data,
Station 13W.
98
-------
Station 4 E is a hot-side unit burning eastern coal. Since
both the _in situ and laboratory measured resistivity values were
in the desirable range, 3.0 x 1010 ohm cm and 4.0 x 109 ohm cm
respectively, it is difficult to assess the accuracy of either.
The efficiency of the precipitator and the outlet field current
density are commensurate with desirable levels of resistivity.
It is noted that only one hot-side in situ resistivity measure-
ment was made during the field test. This value was obtained
with a new high temperature probe in service for the first time.
The other unit that showed a significant deviation was the
cold-side unit burning a western coal, station 5 W. In this
case the high efficiency of the precipitator and the reasonably
high current density in the outlet field (23 nA/cm2) suggest
that for some reason the in_ situ resistivity is inaccurately
high. It is pointed out that the power station in this case
was having pulverizing-mill problems at the time of the field
test, and a high percentage of coarse fly ash was produced.
The point-plane in situ probe is inclined to preferentially col-
lect a particle-size distribution that is coarser than normal.
From the standpoint of specific surface and perhaps ash composi-
tion, this biased collection could lead to ir\ situ resistivity
values that are higher than anticipated. Another minor factor
contributing to this deviation was the fact that the water con-
centration used in the resistivity prediction was over 2 volume
percent greater than that measured _iri situ.
The predicted resistivity also can be evaluated by examining
resistivity ratios in which a perfect correlation yields a ratio
of unity. Three calculated ratios are shown in Table XII: in
situ resistivity/predicted resistivity, laboratory measured re-
sistivity/predicted resistivity, and laboratory measured resistiv-
ity/in_ situ resistivity. When it is considered that consecutive
ir\ situ resistivity measurements involving the point-plane probe
have shown on occasion an order of magnitude variation and that
a series of repeated laboratory determinations can develop a
factor of 3.0 high/low ratio, the agreement among in, situ, labora-
tory and predicted resistivity is excellent. With the exception
of the two cases in which the in situ data are an order of magni-
tude greater than both the predicted and laboratory-measured
data, one could not expect better agreement.
The results pertaining to station 7 E require additional
explanation. This station was burning a coal that had been cleaned
to reduce the ash and sulfur content from 20-25% and 1.5-2.0%
to <12% and <1% respectively. First, it was desired to evaluate
the resistivity prediction for a cleaned coal. These results
were included above; that is, in situ and laboratory measured
resistivity was 2-3 x 1011 ohm cm and predicted resistivity was
5 x 101 * ohm cm.
99
-------
Table XII. Comparison of Predicted Resistivity Values
with those Measured in the Laboratory and In Situ
Resistivity Ratio
In Situ Laboratory Laboratory
Station T, °C Predicted Predicted
1 W 145 2.5 4.2
3 E 158 0.3 0.3
4 E 332 13.0 1.7
5 W 105 31.3 3.1
7 E 163 0.5 0.4
13 W 350 1.3 1.4
100
-------
In anticipation of elevated resistivity due to the lowering
of the coal's sulfur content by cleaning, the utility had available
a commercial sulfur trioxide injection system to condition the
ash. This afforded an opportunity to compare ir\ situ and predicted
resistivity values for sulfur trioxide conditioning.
Two injection concentrations were used, nominally 25 and
15 ppm. These injection rates at the precipitator inlet produced
measured sulfur trioxide concentrations of 11-14 ppm and 7-10
ppm, respectively. Resistivity was predicted for these injection
rates using the coal and coal ash analyses shown in Tables IX
and X, respectively, except that the calculated sulfur trioxide
value of 3 ppm based on the coal's sulfur content was replaced
by the average values measured at the precipitator inlet, namely,
12.5 and 8.5 ppm. These predicted resistivity values and the
resistivity data measured in situ are shown in Figure 32. At
the temperature of interest, the predicted resistivity using
12.5 ppm sulfur trioxide was 3 x 109 ohm cm while the in_ situ
measurement was 9 x 109 ohm cm. The prediction for 8.5 ppm
sulfur trioxide was 3 x 1010 ohm cm and the ir\ situ measurement
was 2 x 1010 ohm cm. These results are very encouraging with
respect to the resistivity prediction technique. One cannot
critically review the variance shown with respect to the method
of prediction. It is obvious that the resistivity is very sensi-
tive to temperature and sulfur trioxide concentrations. Because
of this sensitivity, small deviations in temperature and the
lack of information about the concentration of sulfur trioxide
at the precise time and the exact region of the in situ resis-
tivity probe measurement can cause the resistivity data to agree
or disagree with the predicted value.
101
-------
REFERENCES
1. Wagoner, C.L., et al. Fuel and Ash Evaluation to Predict
Electrostatic Precipitator Performance. Presented at the
ASME/IEEE Joint Power Generation Conference, Long Beach,
California, September 18-21, 1977. 14 pp.
2. Bickelhaupt, R.E. Influence of Fly Ash Compositional Factors
on Electrical Volume Resistivity. EPA-650/2-74-074, U.S.
Environmental Protection Agency, Research Triangle Park,
North Carolina, 1974. 49 pp.
3. Selle, S.J., et al. Western Fly Ash Composition as an
Indicator of Resistivity and Pilot ESP Removal Efficiency.
Paper 75-02.5, 68th Annual Meeting of the Air Pollution
Control Association, Boston, Massachusetts, 1975. 9 pp.
4. Bickelhaupt, R.E. Effect of Chemical Composition on Surface
Resistivity of Fly Ash. EPA-600/2-75-017, U.S. Environmental
Protection Agency, Research Triangle Park, North Carolina,
1975. 50 pp.
5. Dismukes, E.B. Conditioning of Fly Ash with Sulfur Trioxide
and Ammonia. EPA-600/2-75-015, Environmental Protection
Agency, Research Triangle Park, North Carolina and TVA-F75-
PRS-5, Tennessee Valley Authority, Chattanooga, Tennessee,
1975. 169 pp.
6. Bickelhaupt, R.E. Measurement of Fly Ash Resistivity Using
Simulated Flue Gas Environments. EPA-600/7-78-035, Environ-
mental Protection Agency, Research Triangle Park, North
Carolina, 1978. 29 pp.
7. American Society Mechanical Engineers, Power Test Code 28,
Determining the Properties of Fine Particulate Matter.
Section 4.05, Method for Determination of Bulk Electrical
Resistivity. 1965. pp 15-17.
8. Bickelhaupt, R.E. Electrical Volume Conduction in Fly Ash.
APCA Journal 24 (3)-.251-255, 1974.
9. Bickelhaupt, R.E. Surface Resistivity and the Chemical
Composition of Fly Ash. APCA Journal 25 (2)-.148-152, 1975.
102
-------
10. Bickelhaupt, R.E. Volume Resistivity-Fly Ash Composition
Relationship. Environ. Sci. Technol. 9 (4) : 336-342, 1975.
11. Selle, S.J., et al. A Study of the Electrical Resistivity
of Fly Ashes from Low-Sulfur Western Coals Using Various
Methods. Paper 72-107, 65th Annual Meeting of the Air
Pollution Control Association, Miami Beach, Florida, 1972.
32 pp.
12. White, H.J. Chemical and Physical Particle Conductivity
Factors in Electrical Precipitation. Chem. Eng. Prog.
52:244-248. 1956.
13. Maartmann, Sten. The Effect of Gas Temperature and Dew
Point on Dust Resistivity—and Thus the Collecting Efficiency
of Electrostatic Precipitators. Second International Clean
Air Congress of the International Union of Air Pollution
Prevention Association, Washington, D.C. 1970.
14. Baker, J.W., and K.M. Sullivan. Reproducibility of Ash
Resistivity Determinations. Presented at the ASME/IEEE
Joint Power Generation Conference, Long Beach, California,
September 18-21, 1977.
15. Kingery, W.D. Introduction to Ceramics. John Wiley and
Sons, Inc., New York. 1960. pp 732-736.
16. Kanowski, S., and Coughlin, R.W. Catalytic Conditioning
of Fly Ash without Addition of S03 from External Sources.
Environ. Sci. Technol. ll.(l) : 67-70, 1977.
17. Ditl, P., and Coughlin, R.W. Improving Efficiency of Elec-
trostatic Precipitation by Physicochemical Modification
of the Electrical Resistivity of Fly Ash. AIChE Journal
22(4):730-736, 1976.
18. Ditl, P., and Coughlin, R.W. Sorption and Diffusion Inter-
actions with Fly Ash of S02 in Air, S03 in Air, H20 in Air,
S02 + H20 in Air, S03 + H20 in Air. Environ. Sci. Technol.
11(7):701-706, 1977.
19. Wagoner, C.L., and Duzy, A.F. Burning Profiles for Solid
Fuels. ASME Paper No. 67-WA/FU-4. Presented at the Winter
Meeting and Energy Systems Exposition, Pittsburgh, PA.,
November 12-17, 1967. 8 pp.
20. Bickelhaupt, R.E. A Technique for Predicting Fly Ash Resis-
tivity. EPA-600/7-79-044a, pp 395-407, U.S. Environmental
Protection Agency, Research Triangle Park, North Carolina,
1979.
103
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21. Daniels, R.O., Jr. A Study of the Effects of Adsorbed Films
upon the Surface Electrical Conductivity of Powders. Ph.D.
Dissertation, Department of Metallurgical Engineering,
University of Utah, June 1952.
22. McLean, K.J. Factors Affecting the Resistivity of a Particu-
late Layer in Electrostatic Precipitators. APCA Journal
26(9) :866-870, 1976.
23. Gooch, J.P. and Merchant, G.H., Jr. Electrostatic Precipi-
tator Rapping Reentrainment and Computer Model Studies.
EPRI FP-792 Volume 3, Electric Power Research Institute,
Palo Alto, California, 1978.
104
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-600/7-79-204
2.
3. RECIPIENT'S ACCESS I Of* NO.
4. TITLE AND SUBTITLE
A Technique for Predicting Fly Ash Resistivity
5. REPORT DATE
August 1979
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO.
Roy E. Bickelhaupt
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Southern Research Institute
2000 Ninth Avenue, South
Birmingham, Alabama 35205
10. PROGRAM ELEMENT NO.
EHE624
11. CONTRACT/GRANT NO.
68-02-2114
12. SPONSORING AGENCY NAME AND ADDRESS
EPA, Office of Research and Development
Industrial Environmental Research Laboratory
Research Triangle Park, NC 27711
13. TYPE OF REPORT AND PERIOD COVERED
Task Final; 11/75 - 5/79
14. SPONSORING AGENCY CODE
EPA/600/13
15. SUPPLEMENTARY NOTES JERL-RTP project officer is Leslie E. Sparks, Mail Drop 6179197
541-2925.
16. ABSTRACT
The report gives results of research to develop a technique for predicting:
the electrical resistivity of fly ash from an as-received, ultimate coal analysis; and
the chemical composition of the concomitant coal ash produced by simple laboratory
ignition. Important chemical factors are the alkali metals, alkaline earths, and iron
(with respect to the fly ash), and the water and sulfur trioxide concentrations in the
flue gas. Many fly ash samples were evaluated to minimize variations due to physi-
cal effects. The effects of fly ash chemical composition, ash layer field strength,
and the water and sulfur trioxide concentrations in the test environment were evalua-
ted with respect to electrical resistivity and the evaluated parameters for the entire
temperature spectrum of interest. Equipment and techniques were developed to ob-
tain the required data. Predicted sensitivity as a function of temperature was favor-
ably proof-tested using data acquired from previous field evaluations of precipitators
at six power generating stations. The proof test involved a comparison of predicted
resistivity, laboratory measured resistivity, resistivity measured in situ, precipi-
tator efficiency, and current density of the precipitator outlet fields.
7.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.IDENTIFIERS/OPEN ENDED TERMS
c. COSATI Field/Group
Pollution Alkali Metals
Fly Ash Alkaline Earth Com
Electrical Resistivity pounds
Chemical Composition
Forecasting Iron
Coal Electrostatic Pre-
Combustion cioitators
Pollution Control
Stationary Sources
13 B
2 IB
20C
07D
14B
21D
07B
131
8. DISTRIBUTION STATEMENT
Release to Public
19. SECURITY CLASS (ThisReport!
Unclassified
21. NO. OF PAGES
115
20. SECURITY CLASS (Thispage)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
105
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