Q
%
o
PARTICULATE
CONTROL
HIGHLIGHTS
PARTICULATE
TECHNOLOGY
BRANCH
U.S. Environmental Protection Agency
Office of Research and Development
Industrial Environmental Research Laboratory
Research Triangle Park, North Carolina 27711
EPA-600/8-77-020b
January 1978
AN ELECTROSTATIC
PRECIPITATOR
PERFORMANCE MODEL
©
Divide Panicle Concentration Distribution
into M Segments. Start with smallest
Particle Size.
Calculate Electric Field Values. Volta
Current Densities, etc. for a chi
Calculate Particle Charge for
Particle Size and Electric Fi
Are there Non Ideal effect
considered? .
T
Calculate correction factor
non ideal effects e.g.. Rap
gas sneakage.
Calculate migration veloci
TO be mclu<
!tors gerwrated above
e migration velocm
Calculate collection efficie
segment of the precipitato
size. Subtract off the ai
collected from the total
entering this segment
I Is this the largest particjj?
T
Increment particle size to next largest
-------
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
environmental 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)
7. Interagency Energy-Environment Research and Development
8. "Special" Reports
9. Miscellaneous Reports
This report has been assigned to the SPECIAL REPORTS series. This series is
reserved for reports which are intended to meet the technical information needs
of specifically targeted user groups. Reports in this series include Problem Orient-
ed Reports, Research Application Reports, and Executive Summary Documents.
Typical of these reports include state-of-the-art analyses, technology assess-
ments, reports on the results of major research and development efforts, design
manuals, and user manuals.
EPA REVIEW NOTICE
This report has been reviewed by the U.S. Environmental Protection Agency, and
approved for publication. Approval does not signify that the contents necessarily
reflect the views and policy of the Agency, nor does mention of trade names or
commercial products constitute endorsement or recommendation for use.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
-------
EPA-600/8-77-020b
December 1977
PARTICULATE CONTROL HIGHLIGHTS:
AN ELECTROSTATIC PRECIPITATOR
PERFORMANCE MODEL
by
J. McDonald and L. Felix
Southern Research Institute
2000 Ninth Avenue, South
Birmingham, Alabama 35205
Contract No. 68-02-2114
Program Element No. EHE624
EPA Project Officer: Dennis C. Drehmel
Industrial Environmental Research Laboratory
Office of Energy, Minerals, and Industry
Research Triangle Park, N.C. 27711
Prepared for
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Research and Development
Washington, D.C. 20460
-------
ABSTRACT
Electrostatic precipitators are widely used for controlling emissions of fly ash and other dusts
from industrial sources. Research on the process of electrostatic precipitation has resulted in a
computerized mathematical model that can be used for estimating collection efficiency for pre-
cipitators of different designs operating under various conditions. Mathematical expressions
based on theory are used for calculating electric fields and dust particle charging rates. Empirical
corrections are made for non-ideal effects such as a non-uniform gas velocity distribution. The
model is expected to aid in improving precipitator design and in selecting optimum operating
conditions.
THE COVER:
The EPA has sponsored research to develop
a computer model to predict electrostatic
precipitator performance. The model is
available to industry and the public upon
request. A reference to the computer
model is given at the end of this report.
-------
CONTENTS
Abstract ii
Modeling a Precipitator 3
Validating the Precipitator Model 6
Applications 9
FIGURES
Figure 1. Schematic diagram of an electrostatic precipitator collecting dust 2
Figure 2. Particle charge vs. electric field strength for laboratory aerosols
of four different diameters 4
Figure 3. Particle charge vs. diameter for three values of electric field 5
Figure 4. Particle charge vs. Not for three values of electric field 5
Figure 5. Average current density at the collection plate vs. corona voltage 5
Figure 6. Electric potential vs. position between the corona wire and
collection plate 6
Figure 7. Electric field of the collection plate vs. position 6
Figure 8. Simplified flow chart of the computer program to calculate
precipitator performance.
7
Figure 9. Experimental and predicted migration velocities for a laboratory
precipitator [[[ 8
Figure 10. Experimental and predicted collection efficiency vs. particle
diameter for a laboratory scale precipitator ................................................. 8
Figure 1 1. Experimental and predicted migration velocity vs. particle diameter for
a full scale precipitator [[[ 9
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IV
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AN ELECTROSTATIC PRECIPITATOR PERFORMANCE MODEL
The availability of high speed digital comput-
ers makes it possible for the engineer to examine
complex industrial processes by constructing
mathematical models of them which can be used,
for example, to show the effect that a variation
in a process parameter such as temperature or
pressure will have on the rate or direction of the
process. An example of the use of this tech-
nique is the modeling of the process of electro-
static precipitation which is used for removing
dust and ash from industrial exhaust gases.
Paniculate air pollution is produced by many
industrial processes, such as metallurgical smelt-
ers, iron and steel furnaces, incinerators, electric
power generating plants, and cement kilns. Elec-
trostatic prccipitators, sometimes called precipi-
tators, are used in all of these industries to con-
trol air pollution.
Well designed electrostatic precipitators typical-
ly remove better than 98% of the dust in the
exhaust gas they treat. The collected dust can
be re-introduced into the manufacturing process,
sold to other industries for raw material, or
disposed of, for example, in a landfill.
One of the largest sources of industrial air
pollution that must be controlled is the fly ash
produced in coaf fired electrical power plants.
Electrostatic precipitators are widely used in the
power industry and in 1976 they were used to
remove an estimated 40 million tons of fly ash
from coal fired boiler stack gases in the United
States.
The widespread use of precipitators provided
the impetus for research by the Environmental
Protection Agency into the operating mechanisms
of these control devices to obtain information
that can be used in the design of more efficient
equipment. As part of this effort, a mathemati-
cal model of the electrostatic precipitation pro-
cess has been developed.
Figure 1 shows a schematic drawing of an elec-
trostatic precipitator. The precipitator shown is
typical of those which are used to collect fly ash
The dust laden flue gas enters the precipitator
from the left and flows between negatively
charged wire electrodes and nearby grounded
plate electrodes. The wire electrode is charged
to a high potential (20-40 kV) by an unfiltered
dc power supply outside the precipitator housing
The applied voltage is high enough to produce a
visible corona discharge in the gas immediately
surrounding the wire electrodes. Electrons set
free in the discharge collide with gas molecules
producing gas ions that in turn collide with dust
particles and give them negative charges. In the
strong electric field between the wire and plate
electrodes the electrically charged dust particles
migrate to the plates where they are deposited
giving up their charge. Eventually a thick layer'
of dust builds up on the plates. With vertically
mounted wire and plate electrodes the accumu-
lated dust layer can be conveniently removed
from the plate by periodically rapping it by
means of an automatic hammer. The dislodged
dust layer falls into hoppers in the bottom of
the precipitator housing, from which it is re-
moved for disposal. The plates continue to col-
lect dust until they are rapped again.
Most industrial precipitators are quite large
because large volumes of paniculate laden flue
gases must be treated. A large electric utility
power boiler burning coal may require several
precipitators, each of which will typically con-
tain over 500 collection plates 10 meters high
and 3 meters wide. Each precipitator will treat
a million cubic meters of flue gas per hour re-
cover several tons of fly ash during that time,
and cost perhaps $5 million. On such a scale,
the need for accurate design predictions of the
and geometry of precipitator components is
apparent. Also, as precipitators are applied to
various industrial processes, the scaling rules dis-
covered by precipitator manufacturers for one
application may not work in another.
-------
HIGH-VOLTAGE
SUPPLY
PLATE
RAPPING
SYSTEM
DUST
LADEN
AIR
CORONA WIRES
GROUNDED
COLLECTION
ELECTRODES
CLEANED
AIR
DUST COLLECTION
HOPPERS
Figure 1. Schematic diagram of an electrostatic precipitator collecting dust.
-------
MODELING A PRECIPITATOR
Most of the models that one sees are physical
entities - a miniature representation of some air-
craft or ship, for example. The quality of the
model is in direct proportion with the accuracy
which the original design is minutely reproduced.
Another kind of model is the abstract construct.
Thus, a theory, for example, is a model because
it seeks to represent how something in nature
works or acts. Instead of wood or metal, a
theory is a model made up of facts, each fact
pieced together with another fact until some
representation of nature has been made. The
quality of this model is judged by how well it
predicts what nature will do in the situations
that it was designed to model.
Therefore any object or phenomenon can be
modeled. What is important is that the model
can be either a concrete or an abstract structure.
A mathematical model of some process is then
no more than a representation of the process by
mathematical formulae tied together with some
overriding procedure or logic. This report deals
with a mathematical model of electrostatic pre-
cipitation; the model is simply some fundamental
theories of physical processes tied together by
the logic of a computer program.
The idea of modeling the electrostatic precipi-
tation process has great appeal if only because of
economic considerations. On a more fundamen-
tal level, the modeling of any complex process
is useful because it promotes an understanding
which is otherwise only available from a costly
"cut and try" approach.
Modeling the electrostatic precipitation pro-
cess is complicated because a variety of physical
phenomena must be accounted for in order to
predict prectpitator performance. The process
is also sensitive to a number of parameters which
must be accurately measured or estimated. The
efficiency of particle collection for a given par-
ticle size is a function of ash or dust properties
(chemical composition, resistivity, density, parti-
cle size distribution), precipitator operating par-
ameters (applied voltage, temperature, gas com-
position, gas flow rate) and precipitator geometry
(collecting plate area, internal dimensions).
Historically, the first aspect of precipitator
performance to be studied was the effect of var-
ious precipitator operating parameters on collec-
tion efficiency. The first successful electrostatic
precipitators for controlling industrial dust emis-
sions were developed by F. G. Cottrell in 1910.
Shortly afterwards, one of CottrelPs associates,
Evald Anderson, recognized that the efficiency
of dust collection was exponentially related to
such parameters as gas velocity and collecting
plate area. In 1922 the German investigator W.
Deutsch put this relationship into a more com-
prehensive form that incorporated concepts from
electrical theory. The equation developed by
Deutsch predicts precipitator collection efficiency
at a particular particle size for turbulent flow con-
ditions and depends upon three parameters: the
area of the grounded collection electrode, the vol-
ume flow rate of the gas passing through the pre-
cipitator, and the migration velocity of the dust
particle to the collection electrode. The last of
these, the migration velocity, is the net velocity
of the dust particle to the collection electrode
resulting from the opposition of two forces, the
force of electrostatic attraction and the viscous
drag of the gas, which retards movement of the
particle. The migration velocity depends on the
charge on the particle, the electric field near the
collection electrode, the gas viscosity, the parti-
cle diameter, and an empirical correction factor
called the Cunningham or slip correction factor.
The Deutsch equation is idealized in that it
assumes thorough mixing of the gas due to tur-
bulent flow, a uniform concentration of uniform-
ly sized (monodisperse) dust particles, and a con-
stant migration velocity for these particles. Any
comprehensive modeling effort must make allow-
ance for these restrictions. In the computer
modeling scheme which has been developed, the
precipitator was divided into short sections and
the Deutsch equation applied to each section,
over several particle size ranges.
Two other fundamental aspects of precipitator
operation which must be described before any
model is built are particle charging and electric
field estimation, both of which are needed to
find the migration velocity.
Finding the charge acquired by a dust particle
in the presence of free gas ions and an electric
field is a complex calculation. Briefly, there are
two ways in which a dust particle can acquire
charge in a precipitator. If the particle is larger
than one or two microns in diameter then the
applied electric field is responsible for most of
-------
the charge on the particle. This type of charging,
called field charging, depends on an induced elec-
tric field to be set up on the dust particle. Then
ions moving in the electric field set up on the
particle are attracted to it, impact, and give it
charge. The particles continue to acquire charge
until the resident charge on the particle is large
enough to repel the incoming ions. The particle
has then reached a saturation charge and can gain
further charge only by random collisions with
energetic ions. This second process, the diffusion
of ionic charge to dust particles, is the predomi-
nant charging mechanism for particles smaller
than about one micron in diameter. For particles
near one micron in size both charging mechanisms
operate and the particle gains charge by field
charging and diffusion charging.
Theories which describe particle charging typi-
cally do well in estimating particle charge for
either diffusion charging or field charging condi-
tions, but in the particle size range where both
types of charging occur, a simple sum of the
charging due to each mechanism is incorrect. A
more sophisticated theory is needed. Fortunately,
recent work sponsored by the Environmental
Protection Agency has produced a more compre-
hensive theory of particle charging. This theory
agrees with experiment to within 25%. For par-
ticle sizes and charging times in the range of
interest for precipitator operation, the agreement
with experiment is within 15%.
Figures 2 through 4 show comparisons of
theory and experiment for a variety of experi-
mental charging conditions. Figure 2 shows
particle charge as a function of charging field
strength for four particle sizes. Here the pro-
duct of the charging ion concentration, N0, and
the time that the particle is charged, t, is equal
to 1.0 x 1013 sec/m3. This N0t product is in
the correct range for precipitator operation but
is lower than a more usual value of 4 x 1013
sec/m^. Figure 3 shows particle charge as a
function of particle diameter for three charging
field strengths. The value of 3.6 x 10^ volts/
meter is probably most representative of precip-
itator operation. As in Figure 2 the N0t product
is 1.0 x 1013 sec/m3. Figure 4 shows particle
charge as a function of the N0t product for
several charging field strengths; these data are
for a particle diameter of 0.28 Mm.
One last fundamental aspect of precipitator
operation must be described before a model of
electrostatic precipitation is possible. This is the
500
I
o
o
H
cc
0.
2 4 6
CHARGING FIELD STRENGTH, kV/cm
Figure 2. Particle charge vs. electric field strength
for laboratory aerosols of four different
diameters. N0t = 1 x 7073
calculation of the electric field inside the precipi-
tator as a function of position. A correct value
of the electric field is needed to calculate both
migration velocity and particle charge.
The equations which describe the behavior of
the electric field in a precipitator are well known.
The difficulty is their solution. Their solution
is obtained by numerically solving the appropri-
ate partial differential equations subject to the
wire-plate geometrical configuration of the elec-
trostatic precipitator. A computer program was
written to perform the calculations and yield a
voltage-current relationship for a given wire-plate
geometry. The distribution of voltage, electric
field, and charge density are also calculated by
the computer program for each corona wire
voltage and the associated current to the collec-
tion electrode. The agreement between theory
and experiment is within 15%.
Figures 5 through 7 show how the predictions
of this computer program agree with measure-
ments made of the current density, electric field
-------
and potential values at various places in a wire-
plate electrode system. Figure 5 shows the aver-
age current density at the collecting electrode
(plate) as a function of the voltage applied to the
wire. In this experiment a 1.3 mm wire was used.
Here the agreement between theory and experi-
ment is excellent. Excellent agreement is also
seen in Figure 6, which presents a comparison of
predicted and measured potential as a function
of the distance between the corona wires and
the grounded collection plate. Results for two
wire diameters, 1.016 mm and 0.3048 mm, are
shown. Figure 7 shows the electric field at the
collection plate as a function of displacement.
Corona wires are located directly across from
the points -10, 0, and 10 cm at the plate. Posi-
tions -5 and 5 correspond to positions at
the plate, midway between corona wires. Again,
the agreement with theory is good, and within
8%.
Now a computer model of the electrostatic
precipitation process can be constructed. The
0.4 0.6 0.8 1.0
PARTICLE DIAMETER,
1.4
Figure 3. Particle charge vs. diameter for three
values of electric field.
PARTICLE DIAMETER
* E = 9.0 x 105 V/m
• E = 3.6 x 105 V/m
• E - 3.0 x 104 V/m
.THEORY
0.28
I
I
0.0
1.0
2.0
3.0
4.0
5.0
6.0
N0t, sec/m3 X 1013
Figure 4. Particle charge vs.
of electric field.
Not for three values
t-
z
UJ
EC
tr
u
HI
13
tc.
Ul
30 32 34
APPLIED VOLTAGE. kV
36
Figure 5. Average current density at the collec-
tion plate vs. the corona voltage.
-------
computer model is simply a codified procedure
which uses a mathematical description of each
of the fundamental aspects of prccipitator oper-
ation discussed .ibove to predict the behavior of
an actual precipitator. As discussed above, the
method used is to break the precipitator into
many small sections. As the simplified flow
diagram, Figure 8 shows, the particle-size dis-
tribution entering the prccipitator is broken
down into a number of narrow size bands with
a median particle size calculated for each band.
Calculations arc made separately for each size
band as the dust moves through the segmented
precipitator. In each segment of the precipitator,
the electric field, particle charge, migration veloc-
ity, and collection efficiency arc calculated for
40
30
O 20 —
• EXPERIMENTAL
—- THEORETICAL
1.02 mm
WIRE DIAMETER
Figure 6. Electric potential vs. position between
the corona wire and collection plate.
3.0
2.0
I
H
H
O
0
cr.
\-
1.0
, MEASURED
(WITH DISCHARGE)
THEORETICAL
MEASURED
(WITHOUT DISCHARGE)
THEORETICAL
0.0
DISPLACEMENT, cm
Figure 7. Electric field of the collection plate
vs. position. Corona wires are directly
across from positions —10,0, 10,
the median particle si/e and the percent collected
is subtracted from the concentration entering
that segment. This procedure is repeated for the
next and each succeeding segment until the
entire precipitator has been traversed. In this
way each size band passes through the simulated
precipitator and an overall collection efficiency
is found for the various median sizes. The pre-
cipitator has then been modeled. That is, its
collection efficiency has been predicted over the
range of particle sizes which experiment has
shown that it must collect.
VALIDATING THE PRECIPITATOR MODEL
In order to validate a modeling procedure, the
predictions of the model must be compared with
the behavior of actual systems. This precipitator
-------
Read Input Data
\
Divide precipitator into N segments.
Start with first segment.
Divide particle concentration distribution
into M segments. Start with smallest
particle size.
Calculate electric field values, voltages
current densities, etc., for a chosen
segment.
Calculate correction factors to allow for
non ideal effects e.g., rapping losses or
gas sneakage.
Are there non ideal effects to be
considered?
Calculate particle charge for a chosen
particle size and electric field, etc.
Calculate migration velocity. If non-
ideal effects are to be included use
correction factors generated above to
modify the migration velocities.
Calculate collection efficiency for this
segment of the precipitator at this particle
size.
Subtract off the amount of dust
collected from the total concentration
entering this segment.
Is this the last segment of the
precipitator?
Move to next segment of the
precipitator.
Increment particle size to next largest
size.
Is this the largest particle size used?
Print out results; overall efficiency and
other pertinent data.
End of program.
Figure 8. Simplified flow chart of the computer program to
calculate precipitator performance.
-------
model has been compared with measured migra-
tion velocities and collection efficiencies for labo-
ratory scale and full scale electrostatic precipita-
tors. Figure 9 shows the comparison of ideally
calculated migration velocities and collection
efficiencies with experimentally measured values
obtained from a laboratory scale precipitator.
The values obtained in Figure 9 were taken for
three different current densities. The good
agreement with laboratory data indicates that
the model is fundamentally sound. Other
measurements made with the laboratory scale
precipitator indicate that perhaps 8% of the
particulate laden air does not pass through the
charging regions. If this sneakage is taken into
account, even better agreement with theory is
achieved, as is shown in Figure 10.
When the precipitator model is compared with
field data and an attempt is made to simulate
the behavior of full scale precipitators, non-ideal
effects must be included or else the agreement
is generally poor. Therefore, the precipitator
model is not complete until these effects are
allowed for. In a real precipitator, the gas ve-
locity across a duct may be very nonuniform,
the flue gas stream can bypass the electrified
regions (sneakage) and particles that are once
collected can be reentrained when the collecting
100.0
o
o
>
g
i-
cc
I
10.0
THEORETICAL
EXPERIMENTAL
1.01—
0.1
1.0
PARTICLE DIAMETER, urn
10.0
Figure 9. Experimental and predicted migration
velocities for a laboratory precipitator.
99.99
99.98
CORRECTED
FOR 8%
SNEAKAGE
90.0
1.0
PARTICLE DIAMETER,
10.0
Figure 10. Experimental and predicted collec-
tion efficiency vs. particle diameter
for a laboratory scale precipitator.
plates are cleaned (rapping reentrainment). All
of these non-ideal effects are to some extent
design related. However, even with careful
design they usually are reduced but not elimi-
nated.
The net result of the non-ideal effects is to
lower the ideal collection efficiency of the pre-
cipitator. Since the mathematical model of the
precipitator is based on an exponential equation
for individual particle sizes, it is convenient to
represent non-ideal effects in the form of correc-
tion factors which apply to the exponential argu-
ment. The correction factors are used to modify
the ideally calculated migration velocities. The
resulting "apparent" migration velocities are
empirical quantities and are no longer related'to
the actual migration velocities in the real precipi-
tator being modeled. The determination of the
correction factors is an involved task which re-
quires the correlation of large amounts of field
-------
information, taken at existing electrostatic pre-
cipitators. These results have also shown that
the current density, applied voltage, and particle
size distribution are the most important variables
in the calculation of overall mass collection effi-
ciency for a given collection electrode area-pre-
cipitator gas flow ratio. The theoretical calcula-
tion of ideal overall collection efficiency of a
typical boiler effluent in an electrostatic pre-
cipitator generally predicts a higher value than
is observed. Corrections to the idealized or theo-
retical collection efficiency to estimate the
effects of non-uniform gas flow, reentrainment
of dust due to rapping, and gas sneakage all
reduce the overall values of calculated efficiency
to the range of values obtained from field
measurements. The calculations suggest that the
theoretical model may be used as a basis for
quantifying performance under field conditions
when sufficient data on the major non-idealities
are available. Considerable effort has been
expended to learn about modeling non-ideal
effects and their inclusion in the precipitator
model. To date the results are promising; how-
ever, much study and evaluation remains to be
done.
Figures 11 and 12 show experimentally
measured and model predicted values of migra-
tion velocity and collection efficiency as a func-
tion of particle diameter for a full scale precipi-
tator. This precipitator collected fly ash from a
coal fired power boiler and operated at an aver-
age temperature of 150°C. These figures il-
lustrate the kind of agreement which is currently
realized. Two curves are shown on each graph.
99.99
28.0
g 24.0
". 20.0
8 16-0
12.0
8.0
4.0
THEORETICAL-
THEORETICAL
CORRECTED
I
I
I
0.1 0.2 0.4 1.0 2.0 4.0
PARTICLE DIAMETER. ;im
10.0
Figure 11. Experimental and predicted migration
velocity vs. particle diameter for a
full scale precipitator.
10.0
PARTICLE DIAMETER, j
Figure 12. Experimental and predicted migration
velocities vs. particle diameter for a
full scale precipitator.
The upper curve is an "ideal" calculation. The
lower curve takes into account a correction for
a non-ideal gas velocity distribution. Other non-
ideal effects were not taken into account; how-
ever, a continuing effort to model these effects
is underway.
The theory has been compared with a broad
range of laboratory and field data. The results
of these comparisons indicate that the mathe-
matical model provides a basis for indicating
performance trends caused by changes in pre-
cipitator geometry, electrical conditions, and
particle-size distribution.
APPLICATIONS
Precipitator size depends on the quantity of
gas flow, the gas composition, the collection effi-
ciency, the electrical properties of the dust, and
the size distribution of the dust. Present practice
is to base the size on that of an existing precipi-
tator collecting dust from a similar source, on
pilot plant tests, or from empirical relationships.
One of the unknown factors in design is the
allowable current density. Selection of the design
current density involves a prediction of the resis-
tivity of the dust to be collected. If the resistiv-
ity is low then high current densities are possi-
ble. High resistivity dusts are difficult to col-
lect and precipitators must be operated at
reduced current densities. These dusts are often
encountered in flue gas streams from power
boilers burning low sulfur content coals. The
-------
art of precipitator design is based to a great
extend on being able to recognize the relevant
factors influencing resistivity and allowable
current density.
In the electric power industry many types of
empirical relationships have been developed to
permit the selection of design parameters from
coal composition. But none of these relation-
ships are founded in a consistent theory of pre-
cipitator operation. Even these relationships
are not appropriate for some of the high effi-
ciency precipitators currently being installed.
What is needed, and what the Environmental
Protection Agency is attempting to provide with
the mathematical model of electrostatic precipi-
tation is a theoretical base for prediction of
electrostatic precipitator design parameters.
Cost considerations alone suggest that a useful
mathematical model of electrostatic precipita-
tion would benefit both the manufacturer and
the user of these devices. The actual dollar
savings are dependent on precipitator size,
operating temperature, gas volumetric flow rate,
collection plate area and difficulty of erection.
But all of these factors, with the exclusion of
the physical construction, can be estimated with
the help of the precipitator model. Further-
more, savings would be introduced at the design
stage.
Another useful application of the modeling
effort is in troubleshooting problems in existing
precipitators. The remedy to a problem can be
tried out on the computer before money and
time are commited. Once the fix is determined,
costs can be realistically estimated because all
of the needed modifications have been deter-
mined in advance.
With this mathematical model of electrostatic
precipitation, the Environmental Protection
Agency hopes that precipitator design can move
in the direction of a science rather than an art.
It is recognized that the model is not perfect,
especially in a comprehensive estimation of non-
ideal effects. However, a continuing effort of
research and development is underway to im-
prove the model and insure its applicability to
a wide range of gas cleaning situations.*
* A more detailed description of the computer
model is contained in "A Mathematical Model of
of Electrostatic Precipitators", by J. P. Gooch,
J. R. McDonald, and S. Oglesby, Jr. 1975.
NTIS-PB 246188. This report can be ordered
from the National Technical Information
Service, 5285 Port Royal Road, Springfield,
VA 22161.
10
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-600/8-77-020b
2.
3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
5. REPORT DATE
Particulate Control Highlights: An Electrostatic
Precipitator Performance Model
December 1977
6. PERFORMING ORGANIZATION CODE
7. AUTHORIS)
J. McDonald and L. Felix
8. PERFORMING ORGANIZATION REPORT NO.
SORI-EAS-77-675
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Southern Research Institute
200'0 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 A.ND PERIOD COVERED
Task Final; 11/76-11/77
14. SPONSORING AGENCY CODE
EPA/600/13
15. SUPPLEMENTARY NOTES IERL_RTp project officer is Dennis C. Drehmel. Mail Drop 61,
919/541-2925.
16. ABSTRACT
The report describes a computerized mathematical model that can be used
to estimate the collection efficiency of electrostatic precipitators (ESPs) of different
designs, operating under various conditions. (ESPs are widely used to control emis-
sions of fly ash and other dusts from industrial sources.) Mathematical expressions
based on theory are used to calculate electric fields and dust particle charging rates.
Empirical corrections are made for non-ideal effects such as a non-uniform gas
velocity distribution. The model is expected to aid in improving ESP design and in
selecting optimum ESP operating conditions.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS C. COSATI Field/Group
Air Pollution
Electrostatic Precip-
itators
Mathematical Models
Collection
Efficiency
Estimating
Fly Ash
Dust
Air Pollution Control
Stationary Sources
Collection Efficiency
Particulates
13B
12A
14B
21B
11G
18. DISTRIBUTION STATEMENT
Unlimited
19. SECURITY CLASS (ThisReport)
Unclassified
21. NO. OF PAGES
14
20. SECURITY CLASS (This page)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
11
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