Prepared for EPA-600/7-80-157
Sept. 1980
U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
Washington, D.C. 204060
EPA Contract Number 68-02-2607
Technical Directive No. 35
FABRIC FILTRATION ANALYSES
FOR THREE UTILITY BOILER FLYASHES
Final Report
May 1980
Prepared by
Hans A. Klemm
John A. Dirgo
Richard Dennis
GCA CORPORATION
CCA/TECHNOLOGY DIVISION
Bedford, Massachusetts
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DISCLAIMER
This Final Report was furnished to the U.S. Environmental Protection
Agency by GCA Corporation, GCA/Technology Division, Bedford, Massachusetts
in fulfillment of Contract No. 68-02-2607, Technical Directive No. 35. The
opinions, findings, and conclusions expressed are those of the authors and not
necessarily those of the Environmental Protection Agency or of cooperating
agencies. Mention of company or product names is not to be considered as an
endorsement by the Environmental Protection Agency.
/I
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ABSTRACT
A major objective of this program was to augment the present data base
for modeling fabric filter systems designed for the control of inhalable par-
ticulate (IP) emissions from coal-fired boilers. Emphasis was placed on the
determination of K2, the flyash specific resistance coefficient and ac, a
parameter describing fabric cleanability. Fabric filter design, operating,
and performance data were analyzed with the assistance of utility personnel
from Harrington and Monticello Stations in Texas and Kramer Station in Nebraska.
Supplementary laboratory determinations of K2 were made for flyashes produced
by the above facilities because K2 values could not be estimated from field
data alone. Based on laboratory tests it was determined that flyash surface
deposits underwent negligible porosity changes for fabric pressure losses
<2000 N/m2. Additionally, a simple field procedure was developed to measure
K2 directly with the aid of heat resistant membrane filters and a Method 17
in-situ sampling probe. Detailed analyses and modeling trials indicated that
K2 and ac estimates developed froir. routine compliance or acceptance tests
were too rough for dependable modeling although providing useful guidelines.
Estimated K2 values ranged from 0.89 to 3.79 N-min/g-m while ac values varied
from 0.01 to 0.52. Special pilot tests and equipment is the recommended
approach to obtain "modeling quality" data inputs.
iii
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CONTENTS
Abstract iii
Figures vi
Tables viii
English and Metric Equivalencies for Key Filtration Parameters .... x
Acknowledgments xi
1. Executive Summary 1
Background and Statement of Purpose. . . 1
Program Results 2
Conclusions and Recommendations 4
2. Introduction 7
Background 7
Present Modeling Capabilities 7
Critical Modeling Parameters 9
Program Objectives 10
Scope of Work 11
Utility Boilers Studied in Model Validations 11
3. Laboratory Program: Equipment, Technical Procedures, and Test
Results 19
Equipment and Technical Procedures 19
Experimental Results . 23
Significance of Findings 31
4. Analyses of Operating Data 42
Estimation of Fabric Filter System Performance 42
Availability and Assessment of Operating Data, Harrington
Station, Southwestern Public Service Company 44
Review of Operating Data ' 45
Selection of Data ' 48
Preliminary Analysis of K2 and ac 50
Estimation of ac from SPS Operating Data 55
Availability and Assessment of Operating Data, Kramer
Station, Nebraska Public Power District . 60
Availability and Selection of Operating Data, Monticello
Station, Texas Utilities Generating Company 72
References 75
Appendices
A. Supporting data for laboratory measurements 78
B. Sample printout sheets from computer modeling of fabric
filter performance 84
iv
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FIGURES
Number Page
1 Cleaned area fraction versus filter dust loading or interfacial
adhesive force. Coal flyash (MMD = 4.2 ym, og = 2.44) with
woven glass (Sunbury type) fabric 8
2 Boiler and control equipment configuration for Harrington
Station, Southwestern Public Service Company, Amarillo,
Texas 12
3 Boiler and control equipment configuration for Kramer Station,
Nebraska Public Power District, Bellevue, Nebraska 15
4 Boiler and control equipment configuration for Monticello
Station, Texas Utilities Generating Co., Mount Pleasant,
Texas 17
5 Fabric filter test assembly 21
6 Drag versus average dust loading for woven glass fabric panel
and HA membrane filters with Southwestern Public Service
resuspended flyash at approximately 0.61 m/rain face velocity
(see Figure A-l) 25
7 Drag versus average dust loading for woven glass fabric panel
and HA membrane filters with Southwestern Public Service
resuspended flyash at approximately 0.61 m/min face velocity
(see Figure A-4) 26
8 Drag versus average dust loading for woven glass fabric panel
and HA membrane filters with Southwestern Public Service
resuspended flyash at approximately 1.04 m/min face velocity
(see Figure A-l) 27
9 Drag versus average dust loading for woven glass fabric panel
and HA membrane filters with Texas Utilities resuspended
flyash at approximately 0.64 m/min face velocity (see
Figure A-2) 28
10 Drag versus average dust loading for woven glass fabric panel
and HA membrane filter with Nebraska Public Power District
resuspended flyash at approximately 0.64 m/min face velocity
(see Figure A-3) 29
v
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FIGURES (continued)
Number Page
11 Effect of filtration velocity on specific resistance coefficient
(K2). Southwestern Public service resuspended flyash with
woven glass fabric panel and HA membrane filter 30
12 Particle size distribution for Nebraska Public Power District
resuspended flyash, Andersen Mark III impactor measurement
(see Figure 5) 32
13 Particle size distribution for Southwestern Public Service
resuspended flyash, Andersen Mark III impactor measurements
(see Figure 5) .... 33
14 Particle size distribution for Texas Utilities resuspended
flyash, Andersen Mark III impactor measurements (see
Figure 5) 34
15 Specific resistance coefficient (K2) versus specific surface
parameters (Sq)', from Andersen impactor sizing, for various
flyashes 39
16 Boiler firing rate and East baghouse operating parameters for
indicated time interval, Harrington No. 2 Boiler (SPS) .... 49
17 Relationship between accuracy of pressure loss predictions
and ac 70
vi
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TABLES
Number Page
1 Measured and Predicted Performance for Woven Glass Bags with
Coal Flyash 8
2 Laboratory Determinations of K2, Se» Sr, and Wr for Three
Utility Flyashes Using Glass Fabric and Membrane Filters. . 23
3 Specific Resistance Coefficient (K2) and Specific Surface
Parameter (S02) for Test Dusts Filtered at 0.6 m/min Face
Velocity 40
4 Effect of Changing Relative Humidity on Flyash-Membrane
Filter K2 41
5 Measured and Predicted Uncontrolled Flyash Concentrations,
Harrington No. 2 Boiler, Southwestern Public Service, GCA
and SPS Tests 45
6 Flue Gas Statistics for Harrington No. 2 Boiler (SPS) Based
on GCA Stack Measurements, SPS Instrumentation and Fuel
Burning Rates 47
7 Steady-State Operating Parameters, Harrington No. 2 Boiler
(SPS) at 40 Percent and Approximately Full Load Operation . 51
8 Experimental Values Used in Preliminary Estimates of ac and
Kt, Harrington No. 2 Boiler (SPS) 53
9 Paired Values for K2 and ac Satisfying Observed Pressure
Losses at Indicated Boiler Load Levels, Harrington No. 2
Boiler (SPS) 54
10 Summary of Filtration Parameters for SPS Flyash Based on
Laboratory Tests at 25°C 55
11 Input Parameters for Model Validation, Harrington No. 2
Boiler, SPS with Slightly Used Fabric 57
12 Performance Predictions for SPS, Harrington No. 2 BoileT
with Slightly Used Fabric 57
13 Estimation of Model Error in Predicting Pressure Loss When
ac Values are Less Than 0.1 58
v 1 i
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TABLES (continued)
Number Page
14 Calculated Operating and Performance Parameters for Harrington
No. 2 Boiler (SPS) for an S£ Value of 300 N-min/m3 59
15 Data Availability and Cumulative Baghouse Service Periods ... 61
16 Available Operating and Performance Data for Kramer Station . . 62
17 Best Estimates of Inlet Flyash Concentrations, Kramer Station . 63
18 Flange to Flange (Overall) Pressure Losses Versus Individual
Compartment Pressure Losses 64
19 Summary of Cleaning Cycles Used at Kramer Station 65
20 Summary of Kramer Station Operating Data Reduced for Modeling
Analyses 66
21 Estimated ac Values for the Kramer Station Baghouses 68
22 Model Validation Tests Based on Kramer Station Data 71
23 Design and Operating Parameters for Boilers 1 and 2,
Monticello Station, Single Boiler Statistics 72
24 Summary of Design and Operating Parameters Used for Estimation
of ac and Computer Model Analyses, Monticello Station .... 73
25 Comparison of Measured and Predicted Filter System Performance
for Monticello Station 74
viii
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ENGLISH
AND METRIC
EQUIVALENCIES FOR
KEY FTI.TRATION PARAMETERS
Units
Metric
English
Equivalency
Filter resistance
N/m2
in. H2O
249 N/m2 - 1 in. water
Filter drag
N min/m3
in. H2O min/ft.
817 N min/m3 = 1 in. water min/ft
Velocity
m/rain
fpm
0.305 m/m.in = 1 fpm
Volume flow
m3/tnin
cfm
0.0283 m'Vmin = 1 cfm
Fabric area
m2
ft2
0.093 m2 = 1 ft2
Areal density
K/m2
lb/ft7
4882 g/m2 = 1 lb/ft?
Specific resistance
coaf f i cient
N min/g-m
in. H2O min ft/lb
0.167 N min/g-m = 1 in. H20 min ft/lb
Dust concentration
g/m3
grains/ft3
2.29 g/m3 = 1 grain/ft3
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ACKNOWLEDGMENTS
The authors wish to express their appreciation for the able support of
Dr. Jair.es H. Turner, EPA Task Officer, throughout this program and to Mr.
Richard L. Chambers of Southwestern Public Service Company, Mr. Larry McSpadden
of Texas Utilities Generating Company, and Mr. Robert J. Beaton of Nebraska
Public Power District for their assistance in supplying and interpreting
filter system operating and performance data.
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SECTION 1
EXECUTIVE SUMMARY
BACKGROUND AND STATEMENT OF PURPOSE
The expectation that the control of particulate emissions from the combus-
tion of coal in utility, industrial, and commercial boiler applications will
entail progressively stricter emissions regulations suggests that fabric _
filter systems will assume a more pronounced role in the future. For those
situations where fabric failure as the result of thermal stressing, chemical
corrosion, or moisture condensation cannot be avoided, electrostatic precipi-
tation and/or wet scrubbing may provide acceptable alternatives in certain -
applications.
The ease with which a new fabric filter system can be brought on-line
often depends more upon good luck than the application of solid design and
operating principles. There are many reasons for the occurence, and frequently
the persistence, of field shakedown problems although lack of information
certainly plays a key role. In some cases, there may not be a full understand-
ing of the process to be controlled or exactly what takes place during the
operation of a large multi-chambered fabric filter system. Furthermore, even
when the system designer is properly informed from the technical perspective,
there may be an unfortunate lack of solid quantitative data relating to the
key parameters determining the overall filter system performance.
With the present availability of experimental modeling techniques for
predicting filter system operation, there exists a developing capability to
eliminate much of the guess work in filter design by augmenting the data and
experience inventories of the reputable fabric filter vendors and designers.
On the other hand, the surface has barely been scratched in two areas dealing
with fabric pressure losses encountered with many dust fabric combinations
(defined by the specific resistance coefficient of the dust, K2, and the ease
with which a dust may be removed from the fabric during its cleaning). In
current modeling approaches, the degree of cleaning has been defined by the
dimensionless term, ac, that specifies the fraction of the total fabric sur-
face from which the superficial or dislodgable dust layer has been removed.
The critical problem at present is that numerical values for K2 and ac
have been measured for relatively few dust/fabric combinations and the capa-
bility to calculate accurately K? and ac based solely upon theoretical consi-
derations is non-existent. Direct measurement of the above terms is advocated,
preferably by well controlled laboratory experiments and, given the opportunity,
by specially designed field tests on full scale equipment. A study now in
1
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progress, EPA Contract No. 68-02-3151, is intended (a) to develop useful rela-
tionships between coal assays and the filterability of their flyash emissions
and (b) to increase the data base for typical K2 and ac values for U.S. coal
flyashes.
The primary purpose of the present program is to examine alternative
approaches for obtaining improved or new estimates of K2 and ac values typify-
ing real field situations. It has been proposed that for selected field oper-
ating conditions and with prior estimates either for K2 or ac, the steady-state
filtration parameters such as air-to-cloth ratio, inlet dust concentration,
baghouse temperature, total number of compartments, number of compartments
cleaned at one time, cleaning frequency and cleaning duration can be used to
estimate either ac or K2. If the available data do not suffice to make indivi-
dual estimates of K2 and ac, various compatible [K2~ac] pairs for these param-
eters may be inferred from the steady-state field operating and performance
parameters. The above approach is of little value, however, unless supporting
evidence can be obtained to narrow the range of the resultant pairs.
It was recognized at the outset of this study that the use of raw field
data without the advantage of special equipment modifications or controlled
changes in operating mode could not be expected to produce other than interim
working values serving as temporary guidelines until more sophisticated mea-
surements could be performed. It was also suspected and later demonstrated
that certain groupings of field data that inititally proved promising were not
axenable to analysis. On'the other hand, it was believed that if the deter-
mination or assumption of rational values for K2 and ac based upon laboratory
tests or comparable field measurements led to predicted pressure loss values
in fair agreement with field observations, the viability of supporting model-
ing procedures would have been validated. It was recognized that the labora-
tory estimates for K2 based upon the re-dispersion of dust hopper flyash
samples followed by the development of drag-fabric loading curves suffer from
the particle size simulation problems always present when a bulk dust sample
is re-aerosolized. Hence, the laboratory estimates of K2 may differ from the
values associated with the freshly deposited flyash.
In the presentation of technical data, we have adhered to metric units
with their still commonly used English counterparts shown in parenthesis.
However, raw field data have been given in their "as received" English form
for convenient reference to the original sources. Additionally certain for-
mulas appear in the text that are designed to compute the values of selected
variables in metric units.
PROGRAM RESULTS
Laboratory Measurements
The laboratory phase of this program involved the determination of K2
values at typical field filtration velocities for coal flyash samples supplied
by the baghouse operators of three co-operating utility groups, Southwestern
Public Service Company (SPS) , Harrington Station; Texas Utilities Generating
Group (TU), Monticello Station; and the Nebraska Public Power District,
Kramer Station. Flyash samples were filtered on used but cleaned woven glass
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fabrics such as those commonly used in the field while observing the changes
in pressure loss as the dust accumulated (mainly upon the fabric surface) to
areal densities up to ~800 g/m2. Average K2 values for the re-aerosolized
flyash were 2.75, 0.89 and 3.79 N-min/g-m, respectively for SPS, TU and Kramer
Stations. Limited tests at two velocities showed that K2 values for the SPS
flyash were dependent upon filtration velocity but to a lesser extent than
estimated in earlier studies for a cyclone boiler flyash.
A very significant outgrowth of the laboratory test program were the
results of concurrent K2 measurements in which membrane filters (HA Millipore)
were used as the substrate for the deposited flyash layer. It was observed
that the slopes of the pressure loss/fabric loading curves were almost com-
pletely linear from their origins (zero dust loading) to the maximum dust
loading. First, the characteristic concave-down form normally found with
woven glass fabrics during the early fabric loading period was no longer pre-
sent because there is no preliminary pore filling phase such as found with
most woven media. What is measured as an overall pressure loss for the flyash
membrane filter combination is the simple algebraic sum of two series-connected
resistances to gas flow. Second, a frequently observed slightly upward curva-
ture noted previously with some flyash/glass fabric combinations was not seen
with the membrane f.ilter substrate. Because of the linear slope, it appears
that the flyash layers per se undergo no compression due to increased pressure
gradient over nominal ranges, up to 1500 N/m2. Conversely, the observed curva-
ture is probably related mainly to the compression of the less resilient fabric
substrate.
Field Data Analyses and Modeling
The results of the analysis of field performance data from the co-operating
power stations indicated that because essentially continuous cleaning was re-
quired at all plants, no meaningful field estimates of K2 were possible. Only
in those instances where extended filtration intervals without cleaning allow
for the development of a uniformly distributed dust layer can K2 be infered
directly from field operating data. Accordingly, no determination of the
cleaning parameter ac was possible from the field data alone because the esti-
mation of ac requires that K2 be known unless the unlikely situation exists
where a direct measurement of the fraction of the surface dust dislodged (ac)
has been made. Therefore, it was necessary to use the laboratory generated K2
values not only to characterize their field counterparts (with their recognized
limitations), but also to determine the cleaning parameter ac.
The above technique was applied to selected data sets that appeared to
represent the steady-state filtration conditions for which the GCA fabric fil-
ter model has been designed. By treating the above values of K2 and ac as
data inputs in conjunction with design, operating, and cleaning parameters
customarily used in the modeling process, predicted values were generated for
average pressure loss and dust penetration properties for the field systems.
In view of the assumptions involved, the relatively good agreement between
observed and predicted pressure losses (roughly a 10 to 40 percent error)
appears to justify the analytical approach.
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The level of agreement is somewhat deceptive, however, because the initial
calculation of ac is based upon the field operating parameters, including pres-
sure loss, as well as an independent K2 measurement. It is emphasized that the
primary objective of this program was to derive field estimates of ac (and pos-
sibly K2) for dust/fabric combinations not previously studied in detail at the
pilot plant level. Hence, the extent to which a confirming prediction of
pressure loss agrees with the actual field measurement indicates the reasonable
ness of the ac value.
However, in applying the modeling relationship for filter system design
or diagnostic purposes, it must be realized that casual estimates of either
K2 or ac at the ±50 percent level can lead to large variations in predicted
performance and/or estimated air/cloth requirements. Because of the mathema-
tical role played by ac in predictive modeling, predicted pressure losses are
highly sensitive to small changes in ac, particularly when a£ is in the 0.1
range.
A second observation arising from the field analyses was that the com-
puted values of ac in some cases fell below the 0.1 value constituting the
lower limit for model application. (Actually the model will function with ac
entries of less than 0.1, but will treat them mathematically as if they were
0.1). Although this problem was solvable by long-hand approximation techniques
it is recommended that the model application be broadened by reducing the
lower limit for ac.
The unique cleaning approach used by Kramer Station, which often results
in variable cleaning and filtration intervals, represents a practical advance
in adjusting the available filtration capacity to variable boiler load and
variable inlet concentrations. However, the present model structure is not
directly amenable to handling the above operating mode unless the system
variability can be established beforehand.
CONCLUSIONS AND RECOMMENDATIONS
Laboratory Measurements
In the following section, conclusions and recommendations pertaining to
the laboratory measurements program are presented.
1. The non-linearity observed with pressure loss versus fabric
loading curves with many glass fabrics results from compres-
sion of the fabric and not the dust cake over the typical
ranges of pressure loss <2000 N/m2 (8 in. water) encountered
in the field. Although the degree of curvature involved does
not lead to serious computational error for most flyashes,
the capability to distinguish between substrate compression
and dust compression will facilitate the modeling of other
dust/fabric combinations.
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2. The technique of using a membrane filter as the dust collec-
ting substrate provides a simple, economical means for direct
field measurement of Kj. A filter circle consisting of
Teflon or other appropriate membrane material mounted in an
in-stack filter holder with provisions to measure pressure
loss across the filter over a 30 to 60 minute sampling per-
iod and to determine the resulting flyash weight gain by
subsequent removal of the filter from the holder will enable
simultaneous estimates of both K2 and local mass concen-
tration. In contrast to similar measurements with woven
fabrics or other substrates where the initial curve path
is always curvilinear, the membrane approach requires
only two pressure measurements, initial and final, and a
net dust weight to establish the slope (and K2) for the
pressure-fabric loading curve.
Field Data Analyses and Modeling
The attempts to estimate ac and/or K2 values for various flyash/fabric
combinations based upon the analyses of steady-state field performance data
and the use of computer modeling techniques has led to the following conclu-
sions and recommendations:
1. K2 values could not be determined from the field data
provided by the co-operating utilities because continu-
ous cleaning was required to keep system pressure loss
within pre-set bounds.
2. The need to use laboratory estimates of field K2 values
introduces errors relating to probable differences in
particle size parameters. Use of the field K2 technique
involving Teflon membrane filters and in-stack collection
of the flyash as a conventional testing procedure would
greatly improve the accuracy of K2 measurements and hence
the reliability of modeling predictions. It is recommended
that this technique be used for future measurements.
3. . The estimation of ac values from a combination of laboratory
K.2 measurements and typical field measurements associated
with compliance test data supplemented by inlet (uncontrolled
effluent) concentrations depends not only upon the representa-
tiveness of the K2 value but also upon the accuracy of measured
field operating parameters, such as pressure loss, air flow,
inlet concentration, and adherence to indicated cleaning
parameters.
4. Except for rough estimates of the probable behavior of a
given flyash/fabric combination, the results of the cur-
rent analyses demonstrate the need for specialized measure-
ments programs based upon laboratory or field pilot scale
testing to determine accurately the values for the K2 and
5
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ac parameters. It is not recommended that these terms be
computed from theoretical considerations except for guide-
line purposes until the dust permeability and adhesion
phenomena can be described in terms of practically and
easily measured parameters,
5. The apparent occurrence of ac values less than the present
lower limit of 0.1 set for the GCA filtration model suggests
minor changes in the model structure. It is recommended
that these changes be implemented, based on future field tests.
6. Those dust fabric/combinations, which, in conjunction with
certain filtering and cleaning parameters cause small ac
values, will produce the greatest errors in predictive
modeling because of the inherent sensitivity of pressure
loss to small changes in aQ in the low, ^0.1, ac range.
7. The present model structure is not designed to predict
variable system behavior where, due to rapid load shifts
and possibly concurrent changes in in]et loading, the
system never achieves a steady-state condition. The
model can be used on a step by step basis to predict
moderate variability in system behavior when sufficient
time is allowed for near steady state to be established
and the nature of the system variability is known beforehand.
6
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SECTION 2
INTRODUCTION
BACKGROUND
Fabric filtration appears as a logical candidate for control of particu-
late emissions from both utility and industrial coal-fired boilers in those
situations where ash properties preclude cost competitive applications of
electrostatic precipitation. However, the present data bases are limited and
those systems recently installed are still undergoing major shakedowns with
the likelihood that some changes will be made in both design and operating
parameters. In addition, the proposed installation of large scale filter
systems for .>250 Kw (elec) boilers, requires that extreme caution be used in
choosing design and operating conditions. The capability to perform predic-
tive modeling, which has seen only limited field validation, can reduce signi-
ficantly the guesswork involved in constructing filter systems.
PRESENT MODELING CAPABILITIES
At the present time, field measurements performed at three utilities:
Bow, New Hampshire; Nucla, Colorado; and Sunbury, Pennsylvania*>^^ appear to
be predicted within reasonable levels by the GCA fabric filtration model for
collapse and reverse flow and mechanically shaken systems.4>5>6»7»® A compari-
son of estimates of the fabric cleaning parameter, ac, by laboratory and field
measurements showed good agreement in view of the technical difficulties
involved in developing these data.7 Note that ac values for the power sta-
tions cited above tend to lie close to the laboratory-based experimental
curve, Figure 1. Similarly, mass penetration and fabric resistance proper-
ties for Nucla, Colorado and Sunbury, Pennsylvania coal-fired utility boilers
were also predicted with acceptable accuracy according to the measured and
predicted values shown in Table l.4*
Additionally, use of the model to predict operating losses to be expec-
ted at the Amarillo Station of the Southwestern Public Service Company (SPS)
has indicated high pressure losses, ~10 to 12 in. water, (2.5 to 3.0 kPa)
which were consistent with field observations. Because these computations
were based upon a combination of pilot tests performed in the field plus esti-
mates of certain parameters where there were doubts as to their accuracy or
representativeness, the excellent agreement between predicted and observed
pressure losses has been accepted with due caution.
Actually, the data base for determining the values for two parameters
essential to the modeling procedure, ac (the fraction of filter surface
- 7
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10°
<
uJ
CL
°,NUCLA ") FIELD
o 2 SUNBURN > OAT A
0 3 BOW J
oc»«.5lilO*8 W2-*
^ i PILOT ©lAnT
~ VSTCOHS Wl-M
A I SINGLE 9A:$
A J
10
AVERAGE FA9R C LOADl\rG.(W)g/m2
J
Figure 1. Cleaned area fraction versus filter dust loading or interfacial
adhesive force. Coal flyash (MMD = 4.2 pm, og = 2.44) with
woven glass (Sunbury type) fabric.7
TABLE 1. MEASURED AND PREDICTED PERFORMANCE
FOR WOVEN GLASS BAGS WITH COAL
FLYASH4
Percent
penetration
Measured'"
Prcd ic ted3
Nucit, Colorado
0.21
0.19 .
(1.52)b
Sunbury, Pennsylvania
0.15
0.20
Re sis
tanse-kPa
Measured
Fred tc ted
Nur.la, Colorado
Average, clearing and filtering
1 .03
0.97
During cleaning only
1.7
1 .52
Maximum -"est before cleaninz
1.16
1.16
Xinitnum just after cleaning
0.85
0.72
Sunbury, Pennsylvania
Average, cleaning anc filtering
C.'64
0.62
During cleaning on"y
0.71
0.66
Maximum just before cleaning
0.71
0.66
Minimum just after cleaning
0.56
0.57
3
Averaged ever cleaning and filtering cycles.
During cleaning cycle only.
8
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cleaned) and K2 (the specific resistance coefficient of the dust of interest)
is very limited. Furthermore, the immediate prospects for providing improved
estimates of these variables, short of direct measurements, are contingent
upon the results of continued laboratory and field research such as the EPA
sponsored study now in progress at GCA/Technology Division, "Development
and Evaluation of Improved Fine Particulate Filter Systems," EPA Contract
So. 68-02-3151.
Therefore, an important facet of the present program is to examine field
and laboratory data from as many sources as possible to provide improved esti-
mates for the modeling parameters.
CRITICAL MODELING PARAMETERS
The core model proposed by Dennis and Kleram for predicting system "pres-
sure drag across fabric filters used to control flyash emissions from coal-
fired boilers is represented in Equation l5
S =, I f£ + |ui...ful
\i=l Sc Suj Su^
(1)
vhere S and A refer to overall drag and filter area, respectively, i desig-
nates the ick fractional area and its associated properties, n is the total
number of elemental areas making up the whole surface, and the subscripts c
and u refer to the cleaned and uncleaned filter areas, respectively. Equa-
tion 1 describes the behavior of a large, multicompartmented baghouse that
undergoes sequential chamber cleaning in accordance with a fixed time cycle
or pre-set limiting pressure loss. As a result, although the pressure losses
are essentially the same across each compartment, the local gas flow through
each compartment is dictated by the instantaneous dust holding (which depends
upon when the compartment was last cleaned). The drag through any section of
the filter surface over which the fabric dust loading is uniformly distributed
is
S - SE + K2W (2)
where S is the total filter drag, S£ the effective residual drag, K2 the spe-
cific resistance coefficient for the dust, and W the fabric dust loading in
mass per unit area.
Specific Resistance Coefficient
The K2 value for any dust is readily determined on an experimental basis
provided that the fabric dust loading, W, is uniform. However, W is often
not uniform because of frequent cleaning in many field applications. Thus,
routine field testing used to assess baghouse performance may not provide
sufficient data for correct estimates of K2.
9
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If one attempts to calculate K2 based upon theoretical considerations
by way of various modifications of the classical Kozeny-Carman relationship;
i.e. :
K2 ¦ 1.6 jjSq2 (l-e)/ppe3 (3)
where y is the gas viscosity, e the cake porosity, pp the discrete particle
density, and S0 the specific surface parameter for tne size distribution, the
results will at best be only within ±50 percent of actual measured values;5
hence, the advisability of determining K2 by direct measurement whenever
possible.
Cleaning Parameter, an
Except for special testing procedures involving direct weighing of filter
bags immediately before and after cleaning, the cleaning parameter ac must be
determined by indirect means for filter systems using bag collapse and low
velocity reverse flow <1.5 m/min for dust removal. Furthermore, there are
not sufficient data to determine dust release properties based upon the funda-
mental adhesion relationship between the overlying dust layer and the fabric
substrate.
If the K2 value for a specific dust can be established, it is possible
tc use the data deriving from routine acceptance, compliance or performance
tests to make a practical estimate of the cleaning parameter,
WD - AW - WR
ac <= 1 - — (metric units) (A)
Up - WR
In the above case, Wp is the estimated (uniformly distributed) fabric loading
corresponding to the resistance P^; i.e., the overall system maximum pressure
signaling the start of cleaning,
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SCOPE OF WORK
To realize the full value of current modeling capabilities, regardless of
the filter system type, certain controlling parameters were investigated in
the field and/or laboratory because there were no accurate means to predict
these parameters from theoretical considerations alone.
Dust deposit resistance to gas flow as defined by K2 and the degree of
cleaning, ac, as defined by the relationship between dust adhesion and separa-
ting forces were computed on a basis of direct measurement, a combination of
laboratory and field measurements, or by trial and error approaches.
Documentation of overall boiler and filter system operations including
relevant input parameters was carried out to provide a rational basis for
assessing system performance as well as flagging specific problems detracting
from system effectiveness.
UTILITY BOILERS STUDIED IN MODEL VALIDATIONS
Southwestern Public Service Company (SPS) — Harrington Station
Boiler No. 2, Amarillo, Texas9,10,11,12
Boiler and Fuel Parameters—
Harrington Station is a pulverized coal burning installation with two
350 Mwe boilers now on line and a third unit under construction. A combina-
tion of electrostatic precipitation and scrubbing is used with Boiler No. 1
whereas a baghouse is the control device for Harrington No, 2 boiler. The
present fuel consists of a Wyoming coal with the following properties: 0.3
to 0.4 percent sulfur, 5 to 7 percent ash and a heating value (as received)
of 8425 Btu/lb. The boiler functions as a peak loaded unit that cycles through
out the day in accordance with the electrical demand. Best estimates of fabric
filter system availability since it became operational on Boiler No, 2 in June
1979 are roughly 90 percent. It is expected that a significant improvement in
availability will be observed once selections of filter fabrics and key
operating parameters are decided.
Flyash Control Equipment—
The Boiler No. 2 baghouse was designed and constructed tci operate with a
fabric pressure loss of roughly 4 in. water and a flange-to-flange loss of
5 in. water. The flyash control system consists of two identical baghouses,
designated as the East and West units, each containing 14 compartments; see
Figure 2. Each compartment contains 204 bags, 30 ft 8 in. long and 11.5 in.
in diameter, manufactured from a glass twill. The original bags were desig-
nated as W.W. Criswell 445-04, a 10.5 oz/yd2 twill with a silicone-graphite
coating. A different Criswell weave, 442-57 DC2 with a Teflon B coating was
used in later tests. At the design air-to-cloth ratio of 3.4 afpm, total
gas flow for the Harrington No. 2 baghouse is a nominal 1.6 * 10° acfm at
baghouse temperatures ranging from 320° to 380°F.
Although the original operating plan called for the pressure actuated,
sequential cleaning of all compartments in groups of two, with varying per-
iods when all compartments would remain on-line, unexpectedly high fabric
-------
1.6 x lO^octrn
J STACK L
FAN
14-COMPARTMENT
EAST BAGHOUSE
14- COMPARTMENT
WEST BAGHOUSE
AIR
HEATER
HEATER
BOILER
NO.2
350 MW
Figure 2. Boiler and control equipment configuration for Harrington,
Station, Southwestern Public Service Company, Amarillo, Texas.
12
-------
pressure losses prevented the latter operating mode. Consequently, the actual
cleaning reginen typifies a tine-controlled system wherein the sequential
cleaning of compartments is constantly repeated. Thus, the steady-state pres-
sure loss conditions will depend upon inlet concentration, air-to-cloth ratio
and the fabric cleanability as influenced by any changes in flyash properties.
During normal operation, 2 minutes are required for the concurrent cleaning
of one West and one East baghouse compartment such that the overall cleaning
cycle takes 28 minutes. The actual data inputs representing the essential
information used in the model validation analyses are listed in Section 4 for
selected operating periods.
During the first year of field operation, the observed SPS pressure losses
ranged from 8 to 10 and 10 to 12 in. water, respectively, for the fabric and
flange-to-flange resistance parameters. In fact, the continuous monitoring
system shoved occasional pressure losses even higher than the levels cited
above. Insofar as particulate emissions were concerned, the discharges were
well below the compliance level; i.e., 0.035 versus 0.1 lb/10e Btu. Excessive
pressures and bag replacement problems experienced during shakedown were attri-
buted to (a) cleaning procedures, (b) a finer ash than anticipated, (c) elec-
trostatic charge effects, (d) variations in mass loadings and coal ash charac-
teristics, and (e) the glass fabric properties.
Several steps were taken (with measurable improvements noted) to solve
the excess pressure loss problem. These included the substitution of differ-
ent fabrics, careful attention to bag tensioning, changes in the mechanical
shaking parameters and installation of a flow control on the deflation system.
Although the multifaceted program to improve both system performance and avail-
ability is proving effective, it has led to data outputs that make difficult
the analysis of some baghouse data for modeling purposes. In subsequent sec-
tions of this report, we have indicated that the number of periods depicting
steady-state operation with the same bag type used in all compartments are
quite limited.
Kramer Station, Bellevue, Nebraska1 3 »1 **»1 5 >1 6
Boiler and Fuel Parameters—
Kramer Station consists of four pulverized coal, peaking boilers, three
designed for ^25 Mwe operation and a single 37.5 Mwe unit. Prior to installa-
tion of the present baghouse, the particulate control equipment consisted of
mechanical, cyclonic-type collectors designed to remove approximately 83 per-
cent of the flyash at a maximum pressure loss of 3.3 in. water. Several types
of coal have been burned with the most recent supply a Kemmerer, Wyoming coal
having a heating value of 10,000 Btu/lb and with sulfur and ash contents of
0.5 to 0.8 percent and 3.2 to A.2 percent (as received). Although several
control options had been considered, such as electrostatic precipitators, scrub-
bers, filters or combinations of the above, it was elected to burn a low sul-
fur coal, thus minimizing the S0X emission problem followed by the selection
of fabric filtration for flyash removal because of the recognized difficulties
in capturing flyash from low sulfur coals with electrostatic precipitators.
It was also decided to use the existing mechanical collectors in a standby,
parallel-flow configuration, should the need for emergency repair and/or plant
turndown arise. The above approach also assures a broad (unfractionated range
'13
-------
in particle size for the flyash depositing on the fabric as opposed to the
narrower size spectrum afforded by an upstream, series-connected cyclone. In
many cases, the removal of the coarser particles appears to increase dust cake
resistance to gas flow. The only noted difference in- the operation of the four
boilers is that the use of a dolomitic 1inestone-precoat with Baghouse (Boiler)
No. 1 has led to a consistently higher fabric pressure loss. The possibility
of moisture pick-up on the limestone was considered by Kramer personnel to
explain the higher operating pressure loss. Flyash was used to pre-coat sys-
tems 2, 3, and 4 prior to fire-up procedures.
Flyash Control Equipment—
The baghouses for Boiler Nos. 1, 2, and 3 are similar, each designed to
handle 122,000 acfm at design flow with a total of 720 Teflon coated fiber-
glass bags* housed in 10 sequentially-cleaned (collapse and reverse flow) com-
partments. The filter unit for Boiler No. 4 is basically the same except that
it consists of 1152 bags housed in 16 compartments and filters a flue gas
flow of 192,000 acfm at temperatures in excess of 325°F. The reverse flow
rate per compartment is 14,400 acfm in all cases. The schematic arrange-
ment for the Kramer bahouses is shown in Figure 3. Although the basic bag
designs were very similar to those used by SPS and Texas Utilities, 4 anti-
deflation rings were sewn inside each bag, starting 6 ft from the top and 5
ft apart. No cleaning augmentation by mechanical shaking is provided for the
Kramer systems.
A unique bag cleaning approach is used whereby the normal cleaning cycle
is interrupted if baghouse pressure loss exceeds the preset level of 5 to 6 in.
water following the cleaning of one compartment. The normal cleaning cycle
allows for approximately 9 minutes of filtration between cessation of one
compartment's cleaning and the inititation of the next compartment's cleaning.
If the preset pressure loss is exceeded after any compartment has been cleaned,
this 9 minute interval is reduced to zero and the baghouse cleans constantly
until the pressure loss is reduced below the preset limit. It should also be
noted that once the pressure loss has been decreased to a point below the
allowable maximum, the system will operate with all compartments on line for
a 9 minute period before corrective cleaning is initiated. Therefore, in the
event cf very sudden increases or decreases in concentration, greater than
average excursions from average pressure loss conditions will take place.
Following the usual gamut cf shakedown problems, many of which were pri-
marily of a mechanical or electrical nature — electrical circuitry, solenoid
valves, current limiting switches — the system has evolved to a relatively
maintanance free operation. Specific details for the design and operating
parameters persisting during the modeling intervals are given in Section 4.
Texas Utilities, Monticello Station, Units 1 and 217
Boiler and Fuel Parameters—
Two boilers rated at 575 Mwe (Units 1 and 2) and one 750 Mwe bailer
(No. 3) constitute the Monticello Station equipment. Units 1 and 2 are con-
trolled by a combination of electrostatic precipitators and fabric filters
^Fabric Filters, Inc., 25 ft, 4 in. long, 12 in. diameter.
14
-------
STACK
STACK
DAMPERS
DAMPERS
BOOSTER
BOOSTER
BOOSTER
BOOSTER
i 300° F
* 300°F
300° F
LU
in
< =>
a. o
3 i
O «
o <
. m
Jo
i »
MECH.
COLL.
MECH.
COLL.
MECH.
COLL.
MECH.
COLL.
DAMPERS
DAMPERS
DAMPERS
DAMPERS
FAN
FAN
FAN
FAN
122,000 aclm
@ ? 3 2 5° F
192 ,000 acfm
@ ? 32 5°F
AIR
HEATER
AIR
HEATER
HEATER
HEATER
BOILER
NO. I
BOILER
NO.2
BOILER
NO. 3
BOILER
NO. 4
25 MW
25 MW
25 MW
37.5 MW
Figure 3, Boiler and control equipment configurations for Kramer Station,
Nebraska Public Power District, Bellevue, Nebraska.
-------
operating in parallel while Unit 3 uses a series-connected ESP and scrubbing
system. All boilers are designed for base-loaded operations with the firing
of pulverized Texas lignites having the following analyses: heating values of
5400 to 6450 Btu/lb, sulfur contents ranging from 0.75 to 1.3 percent, and
very high ash contents, 16 to 28 percent (as received basis).
During early shakedown operations, baghouse availability was less than
90 percent and visible emissions in excess of 30 percent opacity suggested a
possible need for boiler derating. Fabric pressure losses in excess of design
levels plus inadequate collection of the fine particles contributing to exces-
sive opacities by the electrostatic precipitators operating in parallel with
glass fabric filters appeared to be the major problem. Note that the Texas
Air Control Board (TACB) limits plume opacity to 30 percent.
Flyash Control Equipment—
The fabric filters currently installed on Boilers 1 and 2 are retrofit
systems whose major role is to greatly reduce the gas flow through the origi-
nal precipitators such that the ESP treated fraction will produce a reduced
effluent concentration. The physical arrangement for the combined fabric fil-
tor-ESP systems is shown in Figure 4. The remaining flue gas that passes
through the filter (initially expected to be 80 percent of the total flue gas
emissions) after re-combining with the ESP effluent, was expected to provide
a resultant emission with concentrations well below the 0.3 lb/106 Btu level
set by the Texas Air Control Board (TACB). Two baghouses operating in parallel,
each consisting of 18 individual compartments with 204 bags, 30.5 ft long
and 11.5 in. in diameter constituted the filtration equipment. Because of
high operating pressure losses, both A and B Baghouses are cleaned simultane-
ously such that two out of a total of 36 compartments are always in the clean-
ing mode.
During preliminary testing, the glass bags were identified as W.W.
Criswell 445-04, 3*1 twill with a weight of 10.5 oz/yd2 and a silicone-graphite
surface treatment. However, several types of bags were tested and, at the
present time, the boiler No. 1 filter system uses a Criswell bag described as
No. 442-57 DC2 with a 10 percent Teflon B surface treatment. Bags are installed
with the warp side out (or on the clean side) which means that the dust should
be less readily dislodged from the interior (filtering) surface. The actual
fabrics in use when field data were used for modeling analyses are indicated
in Section 4 of this report. The nominal flue gas rate for both boilers 1 and
2 is 2.3 x 106 acfm at 380°F. With ~80 percent of the total gas flow
passing through the baghouses, the design air-to-cloth ratio is 2.74 afpm
with 36 compartments on line and 3.08 afpm with 32 compartments on line
(2 out for cleaning and 2 on standby to allow rapid maintenance with minimal
pressure loss fluctuations). Although the design flange-to-flange operating
pressure loss was 7 to 8 in. water, the actual values were nearer to 11 to 12
in. water when 80 percent of the gas flow was directed through the baghouse.
Some reduction in pressure loss occured when only 61 percent of the flow was
handled by the baghouse although the result of this compromise led to exces-
sive plume opacity (>30 percent according to TACB measurements). Pressure loss
problems were believed to result in part from unexpectedly high K2 values for
the dust although electrostatic charge phenomena were also suspected. After
extensive shakedown tests with different fabrics, the boiler now operates at
.16
-------
BOILER
NO. I
NO. 2
575 MWe
AIR
PREHEATER
*
o
o
ID
m
@1
E
tr>
o
o
a>
to
@
E
tr>
o
ISOLATION
DAMPER
ELECTROSTATIC
PRECIPITATOR
0.35-0.45 * I06 oclm (28 -36%)
0.0-0.9 k I06ac(m (64-72%)
AIR
PREHE ATER
(8-COMPARTMENT
BAGHOUSE
0.8-0.9 * I06ac»m (64-72%)
18-COMPARTMENT
BAGHOUSE
ISOLATION
DAMPER
ELECTROSTATIC
PRECIPITATOR
10 FAN B
BOOSTER
FAN B
STACK
BOOSTER
FAN A
0.35-0.45 * I06acfm (28-36%)
10 FAN A
Figure 4.
Boiler and control equipment configuration for Monticello Station,
Texas Utilities Generating Co., Mount Pleasant, Texas.
-------
rated load with roughly 72 percent of the flow through the baghouses as origi-
nally planned. Concurrently, the TACB 30 percent opacity limit is usually met.
It is pointed out that the opacity problem arises from the fraction of the flue
gas flow that passes through the electrostatic precipitators before rejoining
the baghouse effluent whose opacity is far below the allowable level.
Operating and design parameters relating to the modeling analyses are
provided in Section 4.
.18
-------
SECTION 3
LABORATORY PROGRAM: EQUIPMENT,
TECHNICAL PROCEDURES, AND TEST RESULTS
EQUIPMENT AND TECHNICAL PROCEDURES
Bench Scale nitration Equipment
The laboratory program was designed so that filter performance tests
involving fabric resistance characteristics and particle size properties
could be carried out on a bench scale system. This system is fully described
in a previous report.^ While it is recognized that dimensional or dynamic
similarity cannot always be satisfactorily attained, the bench scale approach
offers such advantages as higher measurement precision and reduced testing
time.
The test assembly used in this program operates with a filtration area of
approximately 345 cm2 (15 cm * 23 cm). A rigid, steel picture frame assembly
functions as the actual filter holder, enabling the filter panel to be removed
for weighing and subsequent replacement. The framed filter panel is held in
a vertical position between inlet and exit manifolds (as shown in Figure 5)
with no physical support or backing behind the fabric. The flat inlet distri-
bution manifold- section ensures a vertical air flow, parallel to the filter-
ing surface, as is the case in a typical field installation. By reducing the
depth of the manifold to approximately 2.5 cm, a vertical velocity sufficient
to support flyash particles of 30 ym aerodynamic diameter is attained (based
on an air-to-cloth ratio of 0.61 m/min, or 2 fpm).
Flyash enters the system through an inlet pipe that discharges into a
hopper section below the inlet manifold. The inlet pipe diameter enlarges
prior to entering the hopper to minimize particle impaction losses on the
opposite hopper wall. Samples of the upstream aerosol for particle size
analysis and for alternative K2 measurement (see below) are withdrawn through
the top of the inlet manifold. The probe opening is located opposite the
center of the fabric panel. On the clean air side of the system, the entire
fabric filter effluent is passed through a glass fiber filter prior to flow
measurement, so that fabric collection efficiency can be determined.
Both the filtration system and the dust generation system (described
below) are electrically grounded (to the extent expected in the field) to
reduce the possibility of electrostatic particle losses and to minimize the
potential impact of electrical charge on dust cake structure.
19
-------
NJ
o
MEMBRANE
FILTER OR CASCADE
IMPACTOR
INLET MANIFOLD
FROM DUST
GENERATOR
VIEW PORTS
TO WASTE
TEST AEROSOL LOOP
^inletI
STATIC PRESSURE
TAPS
EXIT MANIFOLD
\7
fallout jar
7 \
v *". * T •
FABRIC SANDWICH
DUST HOPPER
HOPPER STORAGE
OUTLET SAMPLER
ILTER
•¦TO FLOW METER
AND PUMP
Figure 5.
Fabric filter test assembly.5
-------
Dust Generation Apparatus
Test aerosols are generated with an NBS dust feeder,10 a device that pro-
vides a regulated dust feed over a delivery range of approximately 0.1 to 2
grams/tnin. After discharging from a small storage hopper onto a slowly rotat-
ing spur Rear, the dust (or flyash) is transported to an aspirating tube lead-
ing to a compressed air ejector. A clean, dried compressed air supply of
about 0.11 rr. /rain (4 acfm) at 276 kPa (40 psig) first entrains and then redis-
perses the dry dust by the high velocity (sonic) shearing action in the nozzle.
The well dispersed dust is injected into an aerosol test loop resulting in a
combined air flow, compressed plus entrained air, of 0.23 m3/min (8 acfm).
Excess air from the test loop is vented to a waste gas treatment system.
The aerosol sample for the test equipment is extracted by means of a probe
attached to the filter system inlet pipe. By varying the probe diameter, it
is possible to extract an isokinetic sample (±10 percent) from the test loop
for fabric air-to-cloth ratios ranging from 0.45 to 1-70 m/min (1.5 to 5.6
fpm). The above procedure ensures that flyash size properties will be
unaffected by the extraction flow rate over the range of experimental filtra-
tion velocities used in filter testing. A schematic drawing of the filter test
assembly is shown in Figure 5.
Test Aerosols
Flyash samples from the baghouse hoppers were obtained from each of the
three utility fabric filter users assisting in the study — Nebraska Public
Power District, Kramer Station, Bellevue, Nebraska; Texas Utilities Generating
Company, Monticello Station, Mt. Pleasant, Texas; and Southwestern Public
Service Company, Harrington Station, Amarillo, Texas.
Prior to analysis, flyash samples were mixed and sieved through an ASTM
120 mesh (125 "jm pore size) sieve to remove any coarse material present. This
step was followed by storage in a 100 C drying oven prior to use. The condi-
tioned flyashes were then redispersed by the NBS dust generator described
previously.
Filtration Media and K? Measurement
Two types of filtration media were used in the laboratory program. The
15 cm x 23 cm fabric panel consisted of a new, unused section of Menardi-
Southern 601 TUFLEX woven glass fabric with 10 percent Teflon B coating. Air
was drawn through the fabric panel with a rotary vane sampling pump. Instan-
taneous air flow was monitored with an orifice meter while the total volume
filtered was measured by a dry test meter, corrected to pressure-temperature
conditions at the fabric surface.
Static pressure taps on both the inlet and outlet manifolds allowed for
determination of pressure loss across the fabric at frequent intervals. The
fabric panel and frame were periodically removed from the test assembly and
weighed to determine the mass of flyash accumulated. This procedure was
carried out without serious disruption of the dust cake surface. By assuming
21
-------
a constant dust feeder output and inlet loading, and by using the frequent
pressure loss readings, intermediate points (between actual panel weighings)
on the drag versus dust loading curve were obtained.
At least one K2 measurement was carried out at the air-to-cloth ratio
expected in the field for each of the three flyash samples.9»15»17 The air-to-
cloth ratios at Kramer Station and Monticello Station were similar 0.6
m/min), while the air-to-cloth ratio for Harrington Station was higher (i> 1.0
m/min). To facilitate a velocity-independent comparison of all three flyash
samples, K2 for the Harrington Station flyash was determined at the lower air-
to-cloth ratio as well.
Upon completion of each test, the fabric panel was cleaned by a two-stage
process. First, the dust cake was removed by rapping the panel frame on a
flat surface, with the filtering side of the panel facing downward. Next,
the panel and frame were shaken by hand about 20 times at two cycles per
second to remove any additional loosely deposited flyash. This cleaning pro-
cess produced residual dust loadings ranging from 20 to 56 grams/m2, with an
average value of 39 graais/m2. The above values were in good agreement with
previously determined residual dust holdings. Insofar as could be seen by
direct observation, complete removal of the superficial or dislodgable dust
layer was accomplished.
During each fabric filter test, flyash was also collected on a membrane
filter (Millipore Corporation, type HA, 0.45 ym pore size, effective area
9.62 cm2), by extracting the aerosol sample from a point opposite the center
of the fabric panel. Flow through the membrane filter was held constant by
means of a calibrated critical flow orifice having a diameter that provided
a face velocity essentially the same as that for the woven glass fabric panel.
Static pressure taps on either side of the membrane filter holder were
also provided to record pressure loss during the test. The initial pressure
loss across the clean membrane filter ranged from 920 to 1920 N/n2 (3.7 to 7.7
inches H2O), depending on the filtration velocity. This initial reading was
subtracted from all subsequent readings to obtain values for incremental pres-
sure loss, which were used to construct a drag versus dust loading curve.
Because of the fragility of the membrane filter and its dust cake, it was
not possible to remove the filter from its holder for weighing at intermediate
points during the testing. To obtain intermediate points on the drag versus
dust loading curve, it was necessary to assume that the rate of dust accumu-
lation on the membrane filter was proportional to that of the fabric panel.
In this way, the final dust loading on the membrane filter could be apportioned
over each of the test intervals.
Particle Size Measurement
The particle size properties of each flyash were measured with an Ander-
sen Mark III cascade impactor using glass fiber collection substrates. The
impactor inlet was modified by attaching a straight, 25 cm long, 0.8 cm i.d.
probe to the inlet cone. With this arrangement, the impactor could be mounted
in a vertical position above the inlet manifold, as shown in Figure 5.
22
-------
Samples of the inlet aerosol were extracted from a location opposite the cen-
ter of the fabric test panel.
Impactor flow rates were kept at approximately 0.020 m^/min (0.7 acfm),
and instantaneous and cumulative flow measurements were made with a calibrated
orifice meter and dry test meter, respectively. To maintain similar size
properties between the aerosol extracted from the test loop for particle size
analysis and that extracted for K2 measurement, a total flow of 0.023 m3/nin
CO.81 acfn) was sampled, with the excess air passing through the fabric panel.
The total flow corresponds to the required extraction for K2 measurement at
0.64 ir./min (2.1 ft/min), the filtration velocity at which most tests were
conducted.
Because the concentration of the inlet aerosol averaged U grams/m^, short
sampling times (of the order of one minute) were required. Duplicate measure-
ments were made for each flyash sample. Standard procedures^ for impactor
clean-up were followed. Substrates and filters were weighed on a Mettler
balance to 0.01 mg and constant weights (to within 0.1 mg) were recorded to
0.1 mg for calculations. The manufacturer's calibration data for the inertial
impaction parameter (>/"¥" ) and stage jet diameters were used to calculate
individual stage cut diameters by an iterative procedure.20
EXPERIMENTAL RESULTS
Filtration Parameters
Experimentally determined filtration parameters for the three field fly-
ash samples are presented in Table 2. For the Menardi-Southern glass fabric
panel, residual drag (SR) and dust loading (Wr) were determined from the
cleaned panel pressure loss and weight at the start of each test. Residual
dust loadings were sufficiently small such that the initital pressure losses
were generally less than 25 N/m2 (0.1 inch H2O).
TABLE 2. LABORATORY DETERMINATIONS OF K2, Sg, SR, AND WR FOR THREE UTILITY
FLYASHES USING GLASS FABRIC AND MEMBRANE FILTERS
Fabric filter^
Membrane filter0
Testa
dust
Face
velocity
(r,/min)
*2
1N-nin'
\ 8-ro
\ . SE ,
1 (N-nir./n3)
SR
(N—nir./r:^)
WR
(g/m2)
Face K2
velocity /N-aiinv
(r/min) 1 g-m 1
SPS
SPS
SPS
TU
N'PPD
0.61
0.62
1.02
0.6 4
0.63
2.82
2.30
3.12
C.89
3.79
5^
84
64
SI
-68
29
32
17
31
40
36
46
20
37
56
0.62 2.85
0.63 2.76
1.08 3.27
0.67 1.12
0.62 3.77
a
SPS = Southwestern Public Service Company, Harrington Station.
TU = Texas Utilities Generating Company, Montlcello Station.
N"?PD » Nebraska Public Power District, Kramer Station.
3
Menardi-Southern Division of United States Filter Corporation, Style 601
TUFT,FX woven glass fabric with 10% Teflon B coating.
C.Millipore Corporation, Type HA 0.45 gn pore size, 47 nm diameter.
23
-------
Filter drag versus dust loading curves (Figures 6 through 10) were con-
structed for each of the filtration tests. The raw data from which the smooth
curves in the text were constructed appear in Appendix A, Figures A1 through
A4. These data are the basis for the characteristic curvilinear form of the
drag/filter loading curves when a cleaned fabric is returned to service. The
flyash-fabric specific resistance coefficient (K2) for each curve was obtained
from the slope of a line that was fitted (by the method of least squares) to
the test interval endpoints and the estimated point at which drag increase
becomes essentially linear with areal density. Extrapolation of this line to
a zero dust' loading provided an estimate of effective residual drag, Sg.
At the common filtration velocity of approximately 0.6 n/min (2.0 fpm),
flyash-fabric K2 levels varied over a four-fold range; 0.89 N-min/g-m for the
Texas Utilities, Monticello Station (TU) sample to 3.79 N-min/g-m for the
Nebraska Public Power, Kramer Station (NPPD) sample. The only flyash evalua-
ted at more than one filtration velocity was the sample from Southwestern
Public Service, Harrington Station (SPS). Filtration velocity exerted only a
moderate effect on K2. For a 67 percent increase in filtration velocity .(from
0.6L m/min to 1.02 m/min), there was an 11 percent increase in K2 (from 2.82
N-min/g-m to 3.12 N-min/g-m). The velocity-^ relationship is indicated in
Figure 11 for filtration velocities of 0.61 and 1.02 m/min.
Effective residual drag (Sg) values, with one exception, were in the
range of 50 to 100 N min/m3. The one value which fell outside this range,
-68 N nin/ni3, has no physical meaning except to provide a reference point for
determination of curve slope. It is possible that the negative Sg value nay
have resulted from incomplete fabric cleaning. A higher residual dust load-
ing, Wr, would have shifted the drag versus dust loading curve to the right,
thereby further decreasing Sg.
Figures 6 through 10 also provide incremental drag versus dust loading
curves for the simultaneously run Millipore HA membrane filter measurements.
In order to show more clearly the relationship between the woven glass fabric
and membrane filter curves, the axes of the membrane filter curves were dis-
placed. This was accomplished by adding the fabric Sr and Wr values to each
point on the membrane filter curve, thus creating a common origin.
The flyash-membrane filter specific resistance coefficients (K2) shown in
Table 2 were again obtained from the slopes of linear regression lines based
on the method of least squares fit. For each test, the data points consisted
of the measured initital and final drag and the dust loading, supplemented by
the calculated intermediate points at the end of each test interval.
The flyash-membrane filter K2 values were generally in good agreement
with the flyash-fabric K2 values. A greater than three-fold range in K2 was'
observed among the three field flyash samples; 1.12 N-min/g-m for the TU sam-
ple to 3.77 N-min/g-m for the NPPD sample.
As shown in Figure 11, the moderate velocity-!^ relationship noted for
the SPS flyash with woven glass fabric as the substrate was also noted for
the membrane filter tests. A 74 percent increase in filtration velocity
24
-------
2500
~ MEMBRANE FILTER, 0.62m/min
NOTE = DATA POINTS INDICATE WHERE TEST PANEL
WAS WEIGHED TO DETERMINE LOADING
2000
I 500
1000
500
0
200
0
300
400
500
600
700
800
100
AVERAGE OUST LOADING, (w) g/m2
Figure 6. Drag versus average dust loading for woven glass fabric panel and HA
membrane filter with Southwestern Public Service resuspended flyash
at approximately 0.61 m/min face velocity. (See Figure A-l.)
-------
2500
O FABRIC PANEL. 0.62m/min
~ MEMBRANE FILTER, 0.63m/min
NOTE : SEE FIG. 6
2000
c
E
z
1500
to
o
<
CE
Q
000
cc
Ld
I-
-I
500
0
100
200
300
400
500
600
700
800
AVERAGE OUST LOADING, (W) g/m2
Figure 7. Drag versus average dust loading for woven glass fabric panel and HA
membrane filter with Southwestern Public Service resuspended flyash
at approximately 0.61 m/min face velocity. (See Figure A-4.)
-------
2500
O FABRIC PANEL, l.02m/min
~ MEMBRANE FILTER, I.O0m/min
NOTE : SEE FIG. 6
2000
ro
c
E
z
I 500
to
o
<
sr.
o
1000
IT
UJ
_l
Ll
500
0
100
200
300
400
500
600
700
800
AVERAGE DUST LOADING. (W) g/m2
Figure 8. Drag versus average dust loading for woven glass fabric panel and HA
membrane filter with Southwestern Public Service resuspended flyash
at approximately 1.04 m/min face velocity. (Sec Figure A-l.)
-------
2500
O FABRIC PANEL , 0.64 m/min
~ MEMBRANE FILTER , 0.67 m/min
NOTE • SEE FIG. 6
2000
e
6
z
1500
-------
2500
O FABRIC PANEL, 0.63m/min
~ MEMBRANE FILTER, 0.62m/min
NOTE s SEE FIG. 6
2000
500
1000
500
100
200
300
400
500
600
700
600
0
AVERAGE OUST LOADING. (W) g/m2
Figure 10. Drag versus average dust loading for woven glass fabric panel and HA
filters with Nebraska Public Power District resuspended flyash at
approximately 0.64 m/min face velocity. (See Figure A-3.)
-------
Kp , N min/q-m
O FABRIC PANEL, 0.6lm/min 2.B2
~ FABRIC PANEL, l.02m/min 3.12
O MEMBRANE FILTER. 0.62m/min 2.85
A MEMBRANE FILTER, l.08m/min 3.27
NOTE = SEE FIG. 6
100
200
300
400
500
600
700
800
AVERAGE OUST LOADING, (W) g/m2
Figure 11. Effect of filtration velocity on specific resistance coefficient (K2).
SouLhwesterm Public Service flyash with woven glass fabric panel and
HA membrane filter.
-------
(from 0.62 m/min to 1.08 m/min) caused only a 15 percent increase in K2 (from
2.85 K-nin/g-n to 3.27 N-min/g-m).
Particle Size Properties
Cumulative particle size distributions were plotted on log-probability
paper for the two impactor sizings performed for each sampling of the resus-
pended flyash. Samples were collected immediately before the fabric test
panels, Figure 5. A straight line was fitted by eye to each plot and values
for aerodynamic mass median diameter (aMKD) and geometric standard deviation
(og) were obtained from the curve. The cumulative size distributions for the
three flyash samples are shown in Figures 12 through 14. Aerodynamic mass
median diameters ranged from 5.9 um (NPPD sample) to 9.7 ym (TU sample), with
the geometric standard deviation falling between 2.3 and 2.8. The observed
aMMD and 0g values fall within the range expected for redispersed flyash
from pulverized coal-fired utility boilers.
SIGNIFICANCE OF FINDINGS
Comparison of K? Measurements on Woven Glass Fabric and Membrane
Filter Media
An examination of the filter drag versus dust loading curves for the
woven glass fabric and membrane filter media (Figures 6 through 10) reveals
the following differences and similarities:
• absence of an intermediate zone of cake formation for
membrane filter flyash deposits
• a linear drag versus dust loading curve for membrane
filter media versus a curvilinear relationship for the
woven glass fabric
» comparable K2 values for flyashes deposited on the two
types of media in each of the five tests.
Although the laboratory program was not aimed directly at investigating
the preceding phenomena, the end results are important from both the theoreti-
cal and practical viewpoints.
Early Cake Formation—
The initial nonlinear portions of the drag versus dust loading curves,
characterized by sharp increases in drag for small increments of dust accumu-
lation, are often observed for woven fabrics, particularly those without
heavily napped surfaces. The surface of a new fabric is characterized by
depressed regions at the junctures of the warp and fill yarns with an overlay
of projecting fibers in areas where bulked or staple yarns are present such
as evidenced by the Menardi-Southern glass fabric.*
*The Menardi-Southern glass fabric media used for testing consists of multi-
filiment warp yarns with bulked fill yarns.
31
-------
V)
ac
ui
t-
UJ
2
O
tr
o
tr
UJ
t-
u
2
<
u
2
<.
z
>
a
o
a.
Ui
<
0.5
SYMBOL
TEST
10
a MMD = 5.9^tm
cr g = 2.3
1
20
40
60
80 90
PERCENTAGE OF MASS LESS THAN OR EQUAL
STATED SIZE
95 98
TO
Figure 12.
Particle size distribution for Nebraska Public
Power District resuspended flyash, Andersen
Mark III impactor measurements. (See Figure 5).
32
-------
CO
20
cr
LlI
SYMBOL
TEST
——
t-
0
/
LlI
ISA
5
O
tr
10
~
18 B
u
2
/Q
tr
Id
L.
5
ym
—
r-
UJ
CD
s
<
o
2
Q£f
o
2
<
z
1.0
oMMD = 7.3^im
>
-------
CO
IT
UJ
I-
Ul
2
O
tr
u
cr
UJ
H
Ul
2
<
o
2
<
z
V
Q
o
(X
UJ
<
20
SYMBOL
0
~
TEST
13 A
13 B
.0 -
0.5 —
o o
o
20
o ~
40
a MMD =9.7^m
-------
At the start of filtration, dust deposits within and upon this loose yarn
substrate. The higher pore velocities and greater dust cake thickness per
unit mass of deposited dust at the inception of filtration are largely respon-
sible for the inititally concave downward shape of the drag versus dust load-
ing curve. After the fabric depressions have been completely filled and a
pronounced surface dust deposit formed, the drag versus dust loading curve in
most cases assumes a near linear path.
For fabrics composed entirely of tightly woven multifilament yarns, the
zone of early cake formation is much less pronounced, probably because of
shallower surface depressions. The membrane filters used in the testing repre-
sent an even more extreme situation. The membrane filter is essentially a
sieving or screening device for the preponderance of particles in the approach-
ing flyash aerosol. Because of the small pore diameter (^0.45 pm for the
Millipore HA filters), particles are collected almost entirely upon the mem-
brane surface, such that a sharp line of demarkation exists between the filter
and the dust layer with little evidence of an intermediate pore-filling region.
Hence no zone of early cake formation was seen in any of the membrane filter
performance curves generated during current testing.
Form of Drag Versus Dust Loading Curves—
In addition to lacking a zone of early cake formation, membrane filter
performance curves differ from their fabric counterparts in another important
aspect. What is referred to in the literature as the region of homogeneous
cake filtration (i.e., the linear or near linear portion of a drag-loading
curve) was shown to be almost completely linear with a membrane filter sub-
strate. Conversely, a slight but consistent concave upward curve form was
exhibited for flyash deposits on the woven glass medium, Figures 6 through 10.
The repetitious nature of the above phenomena precludes the liklihood of
experimental error.
The woven glass fabric curves, which were developed from several measured
drag and dust loading points, displayed a constantly increasing slope from pointj
to point following the transient zone of early cake formation. Additionally,
the estimated intermediate points, based on an assumption of constant inlet
loading (as shown in Figures Al through A4 in Appendix A), also show a concave
upward trend. While the assumption of constant inlet loading may be question-
able because of the inherent variability of any dust dispersing apparatus, it
is improbable that dust feed deviations would always follow a pattern such as
to generate the curve forms discussed here.
As previously noted, weighing of the membrane filters and sample holder at
intermediate points during a test was not possible because of cake fracture
problems. As a result, all intermediate points are based on the assumption
of constant inlet loading plus the additional assumption of proportional dust
accumulation on the two types of filter media. However, all five curves
constructed on the basis of these assumptions show a striking adherence to a
linear form (minimum coefficient of correlation, r = 0.999). Erroneous or
invalid assumptions would not be expected to produce such a consistent
relationship.
35
-------
The phenomenon of a nonlinear filtration curve for woven fabrics may have
gone unrecognized or unreported for a number of reasons. Difficult to control
dust feeders in conjunction with limited pressure loss measurements for any
one dust-fabric combination might conceal nonlinearity. Failure to carry
filtration to a sufficiently high fabric dust loading can also obscure the
tendency for curvature. Most important, unless the curvature is extremely
pronounced, the construction of a linear "best fit" is convenient from the
computational viewpoint, and probably well within the error boundaries for
measurements of this type. The linearizing approach has been applied to sever-
al filtration curves for woven glass fabrics found in the literature.21'22.
Since systematic error is probably not a valid explanation for the observed
curvature of the fabric pressure loss or drag versus dust loading curves, some
other mechanism must be found. Dust cake compaction has been suggested as a
cause of nonlinearity with some dusts.23 As the dust cake builds up, incoming
particles may slip past previously deposited particles or force them further
into the dust cake. In view of the large void volume, greater than 70 percent
for most dust cakes, such an explanation is not unreasonable. The result of
cake compaction or compression is a gradual decrease in porosity accompanied
by a resultant increase in pressure loss for equal increments of dust deposit.
If such a phenomenon were solely responsible for the observed nonlinearity
in the glass fabric curves, one should expect a similar nonlinearity in the
membrane filter curves, since both filters were loaded simultaneously under
nearly identical conditions. The extreme linearity of the membrane filter
curves suggests that cake compaction is not the explanation. While the possi-
bility of some cake compaction is acknowledged, no visual evidence is shown
for the membrane filter results.
Hence, a more likely explanation for the fabric nonlinearity, given the
linearity of the membrane filter curves, is the probable compression of the
fabric substrate, in particular the bulked fill yarns with their residual dust
holdings. Even when dust deposition has progressed such that the entire fabric
surface is covered, up to surface loadings of 800 g/m2, occasional fibers from
the fill yarns can be found projecting through the dust cake. It is suggested,
therefore, that the fiber presence may tend to increase slightly the dust cake
porosity during the early stages of filtration until overcome by cake compres-
sion as the pressure loss increases. This would explain the slightly lower
slopes (or incremental K2 levels) at low to moderate surface loadings. How-
ever, once the cake compresses to the porosity found on the membrane filter,
any further rise in apparent K2 levels must be related to compression within
the fabric substrate itself. The final concave (up shape of the nonlinear
pressure) loss-fabric loading curves is attributed mainly to substrate
compression.
Although the drag versus dust loading relationship for woven glass fabric
was consistently curvilinear, the extent of concavity was small enough to
enable a reasonable straight-line approximation for K2. In fact, the minimum
correlation coefficient (r) obtained from the linear regression method used
to estimate Kj was 0.99.
36
-------
Similarity of Calculated K2 Values on Fabric and Membrane Filters—
Despite the basic differences in form between the woven glass fabric and
membrane filter performance curves, the K2 values calculated for the two media
by linear approximation were in good agreement (Table 2). The K2 values for
the surface deposit on the two substrates agreed to within 5 percent for three
of the five filtration tests. For the remaining two tests, flyash-membrane fil-
ter K2 values ranged from 20 to 26 percent higher. One of these tests (20 per-
cent) however, was terminated while the substrate dust loading was still rela-
tively low, 270 g/m2 (see Figure 7). Had the filtration cycle been extended,
it is expected that the upward concavity of the fabric curve would have contin-
ued while the membrane curve would have maintained an essentially linear path.
Calculated K2 values for the two media might then have shown better agreement.
Inspection of Figures 6 through 10 shows that the slopes (i.e., K2 values)
of the filtration curves for the two media are not radically different over the
dust loading range of 300 to 600 g/tn2. The significance of this finding is
that field fabric loadings generally center about this range. Hence, the use
of an appropriate membrane filter is suggested as a convenient method for mak-
ing field K2 determinations.
One of the problems in working with simulated dust clouds generated by
redispersion of bulk samples is that conditions — temperature, size properties,
electrostatic charge, etc. — for the field aerosol never can be reproduced
exactly in the laboratory. For this reason, the applicability of laboratory-
determined parameters, such as K£, is always open to question. A technique
for field determination of K2 values based upon in-stack collection of flyash
on high-temperature membrane filters (Method 17 approach), coupled with con-
current measurement of pressure loss across the filter, should provide improved
estimates of K^> thereby enhancing the value of the fabric filter predictive
models.
A high correlation was observed between K2 values determined on membrane
filters and on the type of Menardi-Southern woven glass fabric used in the
present tests. Measured K2 values for the same flyash collected on two com-
monly used woven glass fabrics were identical in previous bench scale tests.5
In addition, the K2 values developed from flyash collection upon other fabrics
(i.e., cotton and Dacron) were approximately the same.5 Since most woven glass
fabrics used for flyash collection are structurally very similar, it appears
that membrane filters should afford a convenient means for K2 determinations
in the field.
Effect of Velocity on K?
Previous investigators have observed a moderate dependence of K2 on fil-
tration velocity. While the actual relationship between K2 and filtration
velocity in field installations may depend upon many factors, bench and pilot
scale studies have generally shown that K2 is proportional to filtration velo-
city raised to a fractional power ranging from 0 to 1.0,5>23,2l+ with the 0 to
0.5 range best describing more recent measurements.5'23
37
-------
Results from the current testing, fall within 0 to 0.5 range, although
only one of the flyash samples (SPS) was filtered at more than one velocity.
A comparison of K2 values for the first and third SPS tests in Table 2* indi-
cates a proportionality to velocity raised to the 0.20 and 0.25 powers, for
woven glas-s fabric and membrane filter media, respectively.
Effect of Particle Size on K2
The Kozeny-Carman theory predicts an inverse square relationship between
K2 and the particle diameter characterizing the ratio of surface area to unit
volume;24 i.e.,
K2 . l/d|v
This relationship can also be expressed in terms of a specific surface param-
eter, S0, which relates to the surface to volume ratio for the solids contained
in a given volume.
S02 <* 1/d2
sv
For a polydisperse aerosol, the specific surface parameter can be calcu-
lated from the equation
SQ = 6_dJ
where ds and dv are the diameters of average surface and average volume,
respectively. For a log-normal distribution of known mass median diameter and
geometric standard deviation, both dg and dv are readily computed by the Hatch-
Choate equations.25
S0 values were calculated for each of the three field flyash samples,
using the MKD and Cg values from Figures 12 through 14 (a discrete particle
density of 2.0 g/cm^ was assumed in converting aMKD to HMD). Table 3 shows
flyash-fabric K2 values for each flyash filtered at ^0.6 m/min, along with
calculated SD2 values for each flyash.
The S02 values shown in Table 3 were plotted on a graph showing earlier
flyash measurements used to explore the K2~S02 relationship, Figure 15.5 The
results demonstrate that particle size distribution plays a very large role
in determining Kj despite the possibility of variations in other flyash pro-
perties that bear upon K2 estimation; e.g., shape, individual particle density,
and electrical charge. Although the data are limited, the K2~S02 relationship
for the present flyashes follows the trend observed for the earlier measurements.
Note that the size parameters for the N.H. Public Service flyash vary in accor-
dance with the dust generating characteristics of each experimental system.
*As discussed above, the flyash-fabric K2 value for the second SPS test is
considered artificially low because of the low fabric loading.
38
-------
10
E
o»
CO
X
o
UJ
cr
Z)
CO
<
10^
10
-I
P AND F REFER TO PILOT AND FIELD TESTS.
_ ALL OTHER TESTS ARE BENCH SCALE.
A
SYMBOL DUST
O COAL FLYASH
N.H. PUBLIC
SERVICE CO.
O COAL FLYASH
COLORADO-UTE
NUCLA STATION
V LIGNITE FLYASH
TEXAS UTILITIES
GENERATING CO.
A LIGNITE FLYASH
TEXAS UTILITIES
GENERATING CO.
from
REFERENCE
5
COAL FLYASH
SOUTHWESTERN
PUBLIC SERVICE CO.
COAL FLYASH
NEBRASKA PUBLIC
POWER DISTRICT
FROM
¦CURRENT
STUDY
X
10'
7igure 15,
10"
2
-2
SPECIFIC SURFACE PARAMETER (S0) ,cm
Specific resistance coefficient (K2) versus specific
surface parameter (S0)2, from Andersen impactor siz-
ing, for various flyashes.
39
-------
TABLE 3. SPECIFIC RESISTANCE
COEFFICIENT (K2) AND
SPECIFIC SURFACE
PARAMETER (SQ2) FOR
TEST DUSTS FILTERED
AT 0.6 x/min FACE
VELOCITY
K2
Test dust
N-ir.in
g-m
NPPD
TU
SPS
0.89 1.53 x 108
2.82 3.90 x 10®
3.79 4.14 x 10s
Effect of Relatively Humidity on K2
Although relative humidity was not controlled in the five tests reported
here (recorded levels ranged from 25 to 53 percent*), no conclusive effect of
relative humidity on K2 was observed. Two of the five tests were carried out
over three day periods. For one test (Test No. 11, Appendix A), relative
humidity increased from 41 to 53 percent over the test intervals. For the
second test (Test No. 14, Appendix A), a decrease in relative humidity from
52 to 32 percent was recorded. Flyash-fabric K2 increased with successive
test intervals during both tests. This observation is better explained by a
gradually decreasing fabric substrate-dust cake interaction and fabric compres-
sion, as postulated above, than by the effects of changing relative humidity.
Because of their linear form, the membrane filter drag curves provide a
better indication of humidity effects. Table 4 shows the calculated K2 values
for the dust cakes accumulated during four separate time intervals for two
tests. During each interval, SPS flyash was filtered for 90 to 100 minutes
at a filtration velocity of 0.62 or 0.63 m/min (approximately 2.05 fpm).
K2 values varied by only 5 percent (2.76 to 2.90 N-min/g-m) over a more than
two-fold range of relative humidity (25 to 53 percent).
In any earlier study, Dennis et al.5 reported that no perceptible changes
in K2 and flyash penetration were noted during filtration with Dacron fabrics
over the relative humidity range 16 to 42 percent. Poor and good electrical
grounding did not alter the results. Therefore, it is difficult to reconcile
2 6
the above .findings with those of Durham and Harrington and Ariman and
Helf ritch"'' who report significant reductions in Kj as relative humidity in-
creases, In the first case,26 K2 was not determined on the basis of a uniform
dust deposit, while changes in airborne particulate size caused by differential
^Relative humidity data are presented in Table Al, Appendix A.
40
-------
settling may have magnified the K2 changes described by Ariman and Helfritch
It is also important to note that humidity and electrical charge effects can
be readily confused with respect to their possible effects on dust deposits.
Since prelixinary model validation tests had suggested that electrical charg
and humidity effects may play sufficiently similar roles in many field situa
tions to allow them to be grouped with more readily measured parameters, the
conflicting data appearing in the literature emphasize the need for rigidly
controlled tests to clarify the roles of charge and humidity.
TABLE 4. EFFECT OF CHANG-
ING RELATIVE
HUMIDITY ON
FLYASH-MEMBRANE
FILTER K2a
Test % relative
number humidity
IN-mln\
[ g-m J
11A 41 2.87
1 IB 43 2.90
11C 53 2.79
17 A 25 2.76
aResults for SPS flyash at
a filtration velocity of
0.62-0.63 m/min.
Experimentally Derived S^, and Values
Experimentally derived values for residual drag (Sr) , residual dust load
ing (Wr), and effective residual drag (Sg) are all based upon a completely
cleaned, new fabric surface with less than 100 hours use. As will be dis-
cussed later in this report, new fabric values for these parameters do not
describe the state of well-used fabrics where Wg, Sjr, and Sr values are much
higher.
41
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SECTION 4
ANALYSES OF OPERATING DATA
ESTIMATION OF FABRIC FILTER SYSTEM PERFORMANCE
A complete description of fabric filter performance requires that the
following parameters be defined unless K2 and/or ac have been previously
determined.
• inlet and outlet particulate concentrations
• volumetric gas flow
• baghouse pressure loss
• baghouse design parameters
• outlet particle size properties
Particulate concentrations are necessary for the determination of fabric load-
ings (a1), fabric loading rate (W/t), and baghouse particulate collection effi-
ciency. Volumetric gas flow in conjunction with the effective fabric area
determines the operating air-to-cloth ratio of the baghouse, (m3/min/m2).
Continuous pressure loss measurements reflecting pressure changes during fil-
tration and fabric cleaning intervals aid in determining the fraction of fabric
surface cleaned as defined by the cleaning parameter, (ac). However, the
observed change in pressure loss over an extended filtering period (with no
cleaning interruptions) wherein a nearly uniform surface dust loading can be
established, provides the best means to estimate aQ or K2. In actual practice,
the above conditions may not be encountered except for moderate inlet concen-
trations of a dust whose K2 value is relatively low. The baghouse design
parameters necessary for the modeling analyses are the total filtration area,
the number of compartments, and the frequency and intensity of cleaning. The
various procedures used to calculate both K2 and ac are described in detail
in earlier modeling studies. However, in order to appreciate how these con-
cepts relate specifically to the analyses of the present field data,, the key
steps in their computation are reviewed here. It must be noted that the spe-
cific resistance coefficient (K2) can only be estimated with confidence under
the following circumstances.
First, for pressure or time controlled cleaning cycles where lengthy
intervals of filtration exist between cleaning cycles, K2 can be estimated
from the rate of pressure drop increase over the final third (roughly) of the
filtering period after the surface dust loading has again approached a nearly
uniform distribution. The above procedure is considered valid provided that
42
-------
the average fabric loading just before the next cleaning is three to four times
larger than that for a single bag immediately after cleaning. When the filtra-
tion period is not long enough to establish a linear rise; i.e., gross differ-
ences still prevail between surface loading at various points on the fabric,
K-2 must be estimated by other methods.
A second approach for estimating K2 is possible when cleaning is continu-
ous and when ac is known or very large (=70 to 100 percent). The above situ-
ation rarely occurs except with multifilament weaves that display excellent
dust release properties but usually poor efficiency characteristics. Although
K2 may, in theory, be estimated without considering ac in the above situation,
its estimated value is still subject to error since assumptions about the
effective drag, S^, and the form of the drag versus loading curve are required.
Determination of the cleaning level, ac, can be made under circumstances
similar to those described previously with the more reliable estimates asso-
ciated with pressure and time-controlled cleaning systems having lengthy
periods of filtration. The calculation process is reasonably straightforward
since the following quantities are readily determinable:
• The amount of dust removed from the fabric — which equals
that deposited over the complete filtration cycle.
• The amount of dust on the fabric just before cleaning —
which can be computed when K2 and the cycle time are known
and provided that the assumption of uniform dust distribu-
tion over the fabric surface is valid.
If, on the other hand, the length of the filtration period is not suffi-
cient to establish a uniform distribution, the calculation of ac becomes more
difficult. First, K2, whose magnitude must be known to compute ac, cannot be
estimated with confidence. Second, it then becomes necessary to establish
the actual dust loading distribution when a non-uniform distribution exists
so that the fabric dust loading just before cleaning can be calculated. When
cleaning is performed on a continuous basis, a similar approach must be taken
since an uneven load distribution exists throughout the baghouse.
Based upon the preceding discussion, there exists only one set of circum-
stances where both ar and K? can be estimated from operating data alone; i.e.,
pressure- or time-controlled cleaning systems with extended periods of filtra-
tion between cleanings. In all other cases, one of the two parameters must be
known. However, a partial analysis can be performed in which the results
indicate possible sets of K2 and ac values.
The analyses of SPS Harrington Station data fell within the latter cate-
gory, until subsequent laboratory measurements by GCA yielded the drag versus
loading relationship for the dust. The first of two analyses was based on
operating data alone while the second analysis entailed the use of both opera-
ting data and the laboratory-determined drag — loading relationships. Detailed
discussions of the analytical approach and the results of its application are
presented later in this section. Since both methods required the use of opera-
ting field data, a review of the availability and reliability of the data is
presented next.
A3
-------
AVAILABILITY AND ASSESSMENT OF OPERATING DATA, HARRINGTON STATION,
SOUTHWESTERN PUBLIC SERVICE COMPANY
Three sources of operating data were available for the detailed analyses
of the Harrington Station Fabric filter system. The first two were the
results of compliance-type tests performed by GCA12 and SPS29 while the third
consisted of output from a computerized, automated data logging system used
by SPS to monitor selected filter and boiler operating parameters for charac-
terizing system performance.
The performance tests, which were carried out in accordance with EPA
Methods 2 and 5 included measurement of inlet and outlet gas flows, inlet and
outlet particulate loadings, particle size distributions, flue gas analyses,
and associated boiler operating parameters. Aside from providing the informa-
tion necessary to define baghouse performance; e.g., pressure loss and effi-
ciency characteristics, these data may also be used to verify the accuracy of
the automated data monitoring system.
The SPS automated data logging system continuously records S02, N0X, 02
and particulate concentrations, and volumetric gas flows in the inlets and
outlets of the East and West baghouses and in the single stack serving both
collectors. Flue gas temperatures and duct static pressures are also monitored
at the inlets and outlets of the two baghouses. In addition, operating load
levels (Mwe), fuel firing rates, and cleaning mode and frequency are continu-
ously monitored and stored either as direct inputs or derived values based
upon data inputs. The various data inputs are summarized and stored for
retrival on an hourly basis.
The computerized system, which came on-line during September 1978, under-
went debugging and calibration until December 1978. During these months, the
only data considered reliable by SPS were temperature and flow measurements.
Since pressure loss data are necessary for an evaluation of the system, the
data recorded prior to the end of November could not be used to assist in the
filter model validation efforts. As discussed in Section 2, SPS instituted
a bag replacement program in January 1979 as part of an effort to reduce oper-
ating pressure losses while simultaneously providing the required gas handl-
ing capacity and effluent properties. Since several bag types were often
installed in the same or adjacent compartments, there is no way that the
behavior of any single bag type can be determined. Thus, all test data devel-
oped under the above conditions have little value from the modeling perspec-
tive unless applied to a system which replicates the bag arrangements used by
SPS (a highly unlikely situation). A conplete rebagging of both baghouses
was carried out in June of 1979. With the exception of two compartments, the
same bag type was installed in the West baghouse. Thus, by discounting the
effect of two odd compartments, the data collected after June 1979 for the
West baghouse can be used for model assessments. However, because the East
baghouse was rebagged with several test fabrics, data from this source are
not suitable for model development.
Data for the month of November 1979 and the July-August period 1979 were
considered by SPS to be accurate and representative of system behavior. How-
ever, certain entries appearing in the fabric filter system log were, according
44
-------
to SPS, inaccurate with the more serious errors associated with the inlet and
outlet particulate loadings.
REVIEW OF OPERATING DATA
Particulate Concentrations
A summary of particulate concentration data is presented in Table 5
based on stack sampling measurements by GCA and SPS. Note that during GCA
test 6, a mixture of coal and gas was fired and that during SPS Test 3, no
sootblowing was performed. A number of conclusions may be drawn from the
entire test series. First, the particulate concentrations differ between the
East and West side baghouses, but with no consistent pattern. Second, with
regard to the SPS tests, the concentration is higher, as expected, during soot-
bloving. Finally, a comparison of measured and expected (based on 80 percent
carry over of coal ash) concentrations shows that only two tests (SPS 1 and 2)
showed particulate concentrations anywhere near the theoretical levels.
TASLE 5. MEASURED AND PREDICTED UNCONTROLLED FLYASH CONCENTRATIONS
HARRINGTON NO. 2 BOILER, SOUTHWESTERN PUBLIC SERVICE GCa'
AND SPS TESTS
Tes t
number
Inlet concentrations —
East West
baghouse baghouse
grains/Sft3
Weighted
average3
Theoretical*3
GCA/Technologv Division12
1C
1.03
1.57
1.36
2.76
2C
0.99
1.68
1.41
2.44
3C
1.34
1.20
1 .26
2.89
4C
2.21
1.36
1.66
2.94
1 .53
1.02
1.26
2.27
6
1.36
2.36
1.97
2.32
Average, Tests 1-5
1.42
1.37
1.39
2.66
Southwestern Public
Service20
1C
2.28
2.74
2.39
2C
2.04
2.56
2.24
3e
1.67
1.63
2.59
Average, Tests 1-2
2.16
2.65
2.32
Based on East and West concentrations and gas flows in each branch.
^Assumes 80 percent of coal ash appears as flyash (computed by GCA).
CContinuous sootblowing.2^
d
Partial gas firing.
e
No sootblowing.
45
-------
The discrepancy between the measured GCA results and the theoretical con-
centrations may be due to (1) settlement in the air preheater hoppers and
throughout the inlet ducts between the air preheaters and the baghouse, (2)
a loss of ash-forming material in the pulverizer due to rejection of pyrite
and associated material and/or (3) an accidental loss of particulate material
from the sampling trains when removing the probe or changing its location due
to the relatively high negative static pressure in the duct and because of
its vertical alignment.
Although estimates of inlet concentrations were obtainable from the SPS
fabric filter system log (FFSL), program operational problems led to uncertain-
ties in the data outputs. Since the above data as well as those developed
from actual stack sampling did not appear dependable, we elected to estimate
inlet loadings directly based upon current log entries for fuel ash content
(6 percent), firing rate, 80 percent carryover as flyash, and the measured
flue gas flow. Additionally, since the difference in concentration between
East and West cannot be readily determined, the assumption was made that equal
amounts of particulate matter enter each baghouse. In reduced form, the inlet
concentration per section may be calculated as follows:
where C-i
I
Volumetric Gas Flow Rates
A study was performed to determine which data should be used to determine
the actual operating gas flow rates without which estimates of baghouse per-
formance are not possible. Hourly entries for average flow rates given in
the FFSL and estimates based upon GCA flow measurements are summarized in
Table 6. Three procedures were used to generate the gas flow data: (1)
measurements by EPA Method 2, (2) continuous measurement by "anubar" instru-
mentation that were recorded in the SPS log and (3) by mass balance based
upon fuel consumption rate and excess air statistics.
Inspection of computations based upon Method 2 measurements suggests a
maldistribution of flow between the East and West side baghouses. The same
conclusion can be drawn by examining the continuous measurements recorded in
the FFSL. Based on discussions with plant personnel, this phenomenon is real
and not due to measurement errors. The gas flow pattern is cyclonic at the
point where the flow partitions between East and West compartments such that
more flue gas enters the West baghouse. Since the ratio of the outlet flows
as determined by Method 5 performance tests and distribution as reported by
the FFSL also confirm the non-uniform flow, the FFSL data appear reliable.
The GCA measurements also indicate significant flow differences between
the inlets and outlets cf both baghouses. Flow also appears lower through
the East baghouse and higher through the West baghouse. It is suspected that
problems with the sampling locations noted in the original field test report
C. = 12,815 T/Q.
3 1
= inlet concentration, g/m3
= tons/hr of coal fired
» actual gas glow rate through East or West sections, acfm
46
-------
TABLE 6. FLUE CAS STATISTICS FOR HARRINGTON NO. 2 BOILER (SPS) BASED ON CCA STACK
MEASUREMENTS, SPS INSTRUMENTATION AND FUEL BURNING RATES
Test number3
H-2-I H-2-2 U-2-3 H-2-4 H-2-5 H-2-6
Station load, Mwe
Coal r.onKumptinn tons/hr
Coal - higher heating value, Btu/lb
c
Flue gas rate" * 10 3 dscF
GCA,
East
- n d
inlet
GCA,
West
Inlet
GCA,
East
outlet^
CCA,
West
outlet
GCA,
total
¦ 1 d
inlet ,
d
outlet
GCA,
total
SPS,
East
Q
outlet
SPS,
West
outlet
SPS,
total
outlet
Theoretical, total outlet^
% difference, GCA versus theoretical
flow
362.0
361 .
9
362.4
362
196.2
197.
8
199.7
194
?850
8744
8487
8502
263
312
380
290
488
510
475
474
385
391
367
384
411
432
463
428
751
822
855
7 64
796
823
830
812
420
431
428
417
443
448
447
439
863
879
875
856
800
840
743
782
-1
-2
5
4
% difference SPS (Anubar) versus
measures flow (Method 2)
aGCA test designation.^
^Partial gas firing with load variations.
C68°F.
^By GCA, Method 2.12
362.1 301.7
190.3 158b
8594 8709
399 302
396 331
396 331
395 332
864 694
791 663
409 356
428 380
837 736
782 660
1 0g
6 11
0
By SPS, in-line "Anubar" measurement from
FFSL.
^Bascd on fuel firing rate, F factors and
O2 data.
^Actual difference <0.5%.
361 .9
197.8
8744
312
510
391
432
822
823
431
448
879
840
-2
7
362.4
199.7
8487
380
475
367
463
855
830
428
447
875
743
5
5
362.0
194.2
8502
290
474
384
428
7 64
812
417
439
856
782
4
5
-------
may be the cause. For example, flow disturbances were located within one
diameter of the measurement locations for both up and downstream tests and
an obstruction in the West outlet duct prevented a complete velocity traverse.
The last two lines in Table 6 show comparison between (a) measured and
theoretical flows and (b) FFSL printout and measured values. Measured flow
rates were consistently within 5 percent of theoretical levels and the flow
rates recorded by the FFSL were generally within 10 percent of the Method 2
measurements. The FFSL data were used to determine the flow rates in the
modeling analyses.
Baghouse Pressure Loss
The only source of baghouse pressure loss data was the information given
in the FFSL as averaged hourly values for the East and West baghouse.
Baghouse Face Velocity
The filtration velocity, (m/min), is determined from the actual gas
flow, (acfm), and the filtration area, Af; i.e., = Qi/Af where the
average fabric area is about 26,000 ft2 or in reduced form:
V (m/min) = 1.172 x 10"6 Q± (acfm) (5)
SELECTION OF DATA
In the preceding sections, the types of data available and their respec-
tive sources have been discussed. Since the analysis of baghouse data for
modeling applications depends upon measurements representing "steady state"
operation, it is imperative that the proper information be chosen. Thus, a
review of the data with respect to load variations must be made in order to
find periods of "steady state" operation since many boilers are expected to
operate under variable load conditions.
Reference to Figure 16, which indicates the coal firing rate for Harring-
ton Boiler No. 2 for November 21 and 22, 1978, shows that over the tine spans
2200/11/21 through 0600/11/22 and 0900 through 2000/11/22 the boiler firing
rates (and load levels) are fairly constant. It should be noted, however,
that a constant load level firing rate does not necessarily mean that the
baghouse has arrived at steady-state conditions. Although step increases or
decreases in boiler load to a new level will be rapidly followed by corre-
sponding changes in velocity (provided that no significant changes in air-to-
fuel ratio or gas temperature take place), additional time may be required
for the system pressure loss characteristics to reach the new steady state
conditions. In fact, if the periods of constant load are not long enough,
the baghouse may never reach true steady-state. The boiler load variations
shown in Figure 16 for the period 0100, November 21 through 2400, November 22
reflect intervals of both constantly varying load and relatively stable loads.
Except for the hourly trends where some pressure loss changes appear to be
out of phase with boiler load and/or filtration velocities, the velocity and
pressure loss curves follow quite rapidly any change in boiler load level.
48
-------
M3
200
I BO
160
- 140
llJ
i-
<
ae
O 120
COAL
TIRING
RATE
,\
\ INLET
. CONCENTRATION
' PRESSURE
/ LOSS
/
A
J
/
I
/ —- INLET
< < VELOCITY
r
\
3.8
3.6
3.4
3.2
3.0
s.
- 2400
2000
- I6O0
1200
800
U-
JL
_1_
0800 1600
11/21/78
2400
->| <-
0B00 1600
11/22/78
DATE-TIME FRAME
Figure 16. Boiler firing rate and East baghouse operating parameters for indicated
time interval, Harrington No. 2 Boiler (SPS) .
-------
It is comparatively easy to explain why pressure loss changes will either
lag or exceed those reported for changes in load levels. If, for example, the
boiler load level and the arrival rate of the surface dust loading increase,
it will take some finite time for the fabric loading to reach its equilibrium
and maximum cleaning rate for the new load level. Thus, the cleaning would not
be able to keep up with the increase in surface loading for a length of time
determined by the actual fabric dust accumulation rate. Conversely, with a
reduction in boiler load level, fabric cleaning will lead to a more rapid
decrease in pressure loss until the equilibrium fabric surface loading is
reached for the new operating conditions. It should be noted that the slopes
of increasing or decreasing pressure-tine traces are always steeper than those
for the velocity-time curves. This follows from the fact that pressure varies
as the square of the velocity provided that there are no significant differences
in gas temperature or flyash loadings for the periods being compared.
Inspection of the concentration-time curve appears to present some anom-
alies until one takes into account that the actual deviations from mean con-
centration are only about ±10 percent. In cases where small increases in
excess air accompany load reductions, the measured particulate concentrations
at constant gas temperature would be expected to decrease and vice versa. On
the other hand, significant decreases in gas temperature are often associated
with boiler turndown such that the particulate concentration reported at the
lover temperature will actually show an increase. The above interactions are
reflected in the inlet concentration versus time curve shown in Figure 16.
The fact that there exists a very close parallel between velocity and
pressure loss changes on the one hand and boiler load levels.on the other
indicates that changing load conditions can be modeled as well as steady-
state conditions provided that the boiler load versus time relationship is
known beforehand. For many peaking boilers, it appears quite reasonable
that the daily power demands would follow the same pattern and thus, adapt
readily to modeling.
For the purpose of the present study, however, it is preferred to deal
only with those data blocks where boiler load level is constant and indisput-
ably representative of steady-state conditions.
Three such time periods and their related operating conditions are listed
in Table 7 for SPS boiler operation at approximately 40 percent full load.
Two additional data sets are provided for near full load operation although
there are doubts as to how well they describe steady-state conditions. In
the case of the July 1979 tests, several bag types were installed in the East
baghouse whereas W.W. Crisswell (Teflon B) bags were used in all but one
compartment of the West baghouse (the latter contained Menardi Southern 601-T
bags).
PRELIMINARY ANALYSIS OF K? AND a,.
As stated previously, the SPS field testing data did not provide suffi-
cient information for the independent determination of K2 and ac. It is again
emphasized that the field data are in no way deficient because of this limita-
tion. The problem is that the routine measurements used to establish mass
50
-------
TABLE 7. STEADY-STATE OI'ERATINO PARAMETERS, HARRINGTON NO. 2 BOTLKR (SPS) AT 40 PERCENT
AND APPROXIMATELY FULL LOAD OPERATION
Koiler
Time period load
Mwp
East baghouse
West baghouse
1. 11/20/78
(0400-0600)
2. 11/29/78
(0100-0500)
3. 11/30/78
(0100-0500)
Average
(1 through 3)
11/22/7H
(1000-1700)
07/31/79a
(1200-2100)
Velocity
tn/min
158
158
153
156
351
324
0.350
0.359
0.356
0.355
0.795
0.798
Tnlet
concentra
g/m3
Pressure
Inlet
Pressure
Velocity ..
tion loss , , concentration Joss
3.49
3.47
3.36
3.44
2.95
3.05
N/r
670
670
660
667
2270
1530
i/min
0.335
0.371
0.363
0.356
0.800
0.687
fi/m"
3.65
3.36
3.30
3.43
2.93
3.58
N/r
700
750
730
733
21 20
1400
Several bag types installed in East baghnuse. Thus data represent a mix of bags.
-------
emissions, pressure loss and size properties were not designed to furnish the
special inputs needed for model development. Therefore, preliminary analyses
were carried out with the expectation that they would yield several possible
combinations of Kj and ac values, rather than finite solutions. The results
of these exploratory analyses are discussed in the following paragraphs.
The method for estimating ac from the operating data of a continuously
cleaned system is summarized here. Continuous cleaning means that following
the sequential cleaning of all compartments 30 minutes for 14 compartments)
the process is resumed immediately with 1/14 of the total fabric area out of
service at all times. The fractional area cleaned is defined as
a = i _ WP ~ (6)
Wp - WR
AW
which reduces to ar = — (7)
Wp
when W^ is much less than Wp - AW
ac = fractional area cleaned
Wp = fabric dust loading just prior to cleaning
AW - amount of dust removed during cleaning, which is
also the amount added during filtration
WR = residual fabric dust loading
The amount of dust added (and removed) from a compartment (AW) over an entire
cleaning cycle; i.e., the sequential cleaning of all compartments, is the pro-
duct of the inlet dust concentration (C^), the filtration or face velocity
(Vi), and the cleaning cycle time (tc). Thus, the numerator of Equation 7 is
readily defined. The dust loading on a compartment just prior to cleaning,
however, must be estimated. The approach used here is to estimate the first
average loading across the entire baghouse from the average pressure loss and
second the distribution of loadings across the baghouse. This procedure, in
conjunction with the assumption of a linear loading distribution, permits the
development of the following set of equations:
P = PE + K2 (wp - WRJ V-L ny (n-1) (8)
Wp = Wp - (tc/2) n/ (n-1) (9)
where P = average pressure loss
effective pressure los?
number of compartments
p
=
PE
=
n
=
WP
=
k2
=
conditions
Combining Equations 7 through 9 yields
P ¦ Pe + K2 (i C^ tc"»/(n-l)
(10)
52
-------
which, by rearrangement, provides a means to determine ac i_f K2 is known or
vice versa since all other terns in the equation are calculable from available
data.
2K2 CjVi2 tc
3c = 2(P - PE) (n-l)/n + K2 Ci V±2 tc n/(n-l) (11)
Although P£ (or Sg) may not be known, a reasonable estimate of this parameter
may be inferred from other systems for which Sg is known. In general, a rough
S£ estimate will not cause large errors unless the average operating pressure
loss is very low. A summary of the parameters used in conjunction with
Equation 11 in the preliminary analyses is given in Table 8. The operating
parameters (C^, V^ and 7) for the low load conditions are the averages for
the East and West baghouses given in Table 5. The parameters for the medium
load situation are also averages of the East and West values, while the high
load condition refers to the West side only. A value of 300 N-min/m^ was
assumed for Sg based on test data for similar dust/fabric combinations.
Earlier tests at SPS with the Mobile Fabric Filter System yielded an Sg value
of 27 5 N-min/n3.
TABLE 8. EXPERIMENTAL VALUES USED IN
PRELIMINARY ESTIMATES OF ac
AND K2, HARRINGTON NO. 2
BOILER (SPS)
Variable
Boiler load level
Low
Medium
High
3.
44
3.
, 32
2
0.
355
0.
.743
0
700
1465
2120
28
28
28
14
14
14
300
300
300
133
157
165
370
350
390
Ci (g/m3)
V-£ (rn/min)
P (N/m2)
tc (min)
n
Sf (N-min/m3)a
T CO
(S£)t N-itin/m3
aAssumed value at 25°C.
Corrected to operating temperature.
The results of the preliminary analysis of the three data sets are pre-
sented in Table 9. The first column gives the assumed or trial value for Kj
at the operating temperature and velocity of the data set (low, medium or
high load) under investigation. Inspection of Table 9 leads to the follow-
ing conclusions:
• First, ac is approximately linearly related to K2, which
indicates that the second term in the denominator of Equa-
tion 8 is much smaller than the first term.
53
-------
• Second, for identical K2 values, ac levels at the high boiler
loads are less than those at the medium levels, which appears
contrary to previous findings; i.e., higher boiler loads lead
to increased fabric loading and higher ac values, Figure 1.
TABLE 9. PAIRED VALUES FOR K2 AND
ac SATISFYING OBSERVED
PRESSURE LOSSES AT INDI-
CATED BOILER LOAD LEVELS,
HARRINGTON NO. 2 BOILER
(SPS)
Specific
resistance
coefficient
K2 (N-min/g-m)3
Cleaning parameter,
ac (dimensionless)
Low Medium High
load load*3 load
0.5
0.01
0.02
0.01
1.0
0.02
0.04
0.03
2.0
0.04
0.07
0.05
3.0
0.06
0.11
0.07
4.0
0.08
0.14
0.10
5.0
0.09
0.17
0.12
6.0
0.11
0.21
0.14
7.0
0.13
0.24
0.16
8.0
0.15
0.26
0.19
9.0
0.16
0.24
0.21
10.0
0.18
0.32
0.23
At operating temperature and face
velocity.
^Refers to boiler output.
The rationale for an increase in ac with higher loading is that with all
other variables held constant (including the time between bag or compartment
cleanings) a greater fabric loading must accumulate during the filtration
period. Since more dust is present just before cleaning, the separating force
is larger and, in turn, more dust is dislodged from the fabric (hence a larger
ac value).
Generally, this criterion appears to be satisfied when the low and high
boiler load conditions are compared but not for the medium and high values as
stated above. There exists a number of possible explanations for this differ-
ence. During high load operations the type of fabric used was different from
that used during the low and medium load situations. Thus, there could be a
distinct difference between dust-fabric adhesion properties and, hence,
cleanability.
54
-------
Another possibility is that steady-state may not have been reached during
the medium load time period. This would result in a lower pressure loss and,
hence, higher values for ac. Another factor that can influence ac estimation
is the inlet concentration, C^, which along with increasing load level, should
produce greater ac values. Note that the indicated K2 values reflect the oper-
ating conditions at each load situation. Thus, if a velocity effect exists
(as has been noted previously with other dusts) , the ac values on a single
line cannot be compared directly for the low to high load operations. In this
instance, however, even if K2 were to vary as the square root of the face
velocity, the actual increase from medium to high load operations would pro-
duce less than a 10 percent increase. It is concluded, therefore, that velo-
city effects cannot explain the "abnormally" low ac values at high boiler
loads. It is further concluded that there is a tremendous range of potential
values for K2~ac combinations that will satisfy the pressure predicting con-
ditions of Equation 11. Therefore, unless one term or the other is known,
there is little likelihood of estimating the other. In the next section, data
analyses based upon prior information for K2 are discussed.
ESTIMATION OF ac FROM SPS OPERATING DATA
Various laboratory tests were performed to determine approximate K2 values
for the SPS flyash. The technical procedures used and the interpretation of
these measurenents have been described in Section 3. Because the laboratory
tests involved the redispersion of bulk flyash sampled from the SPS baghouse
hoppers, it is recognized that the estimates of particle size parameters and
K2 are subject to error. Ordinarily, it is expected that such laboratory
measurements will indicate coarser size properties and possibly lower K2 values
because even high pressure compressed air dust generators 90 psig) fail to
provide complete breakup of agglomerated particles. Key properties for the
SPS flyash are summarized in Table 10.
TABLE 10. SUMMARY OF FILTRATION PARAMETERS FOR SPS FLYASH BASED ON
LABORATORY TESTS AT 25°C
Test
Substrate
K2
Se
sR
Wr
(ir./nin) (N-min/g-m) (N-min/ra^) (N-uiin/m2) (g/m^)
11 Glass fiber 0.61
12 Glass fiber • 1.03
11 Membrane filter 0.61
12 Membrane filter 1.08
HA Millioore filter.
2.98
3.13
2.85
3.26
\Toven glass, Menardi-Southern.
b.
25
75
36
20
29
17
Based upon measurements at two face velocities, the laboratory tests on
the SPS dust indicate that K2 was less dependent upon face velocity than had
been determined for other flyashes; i.e., K2 = f(v)0.2-0.2 5 rather than f(V)0,5
as noted for the GCA flyash.^ The above variance is believed to reflect
55
-------
differences in flyash properties and not errors in measuring techniques.
Laboratory measurements also indicated lower values for residual (effective)
drag, S£, because the test medium had seen only brief service. Allowing for
the fact that all filter media experienced a slow but gradual increase in
interstitial dust deposits over their service life, we have elected to assume
a higher and more conservative value for Sj;, ^ 300 K-min/m3. The measurements
presented in Table 10 represent less than two days fabric use such that the
residual dust holding, Sr, and the effective residual dust holding, Sg, are
well below their quasi-steady-state levels. The negative S£ intercept is
merely a niathematical convenience for defining the curve of best fit for the
drag-fabric loading relationships.
The use of HA membrane filters as the flyash substrate revealed that dust
cake properties per se underwent little change over the range of pressure loss
and fabric loading levels studied. Therefore, it appears that it is the com-
pression (and hence, reduced porosity) of the woven glass fabric and not the
dust layer that causes the slightly concave upward shape noted during labora-
tory drag versus loadings measurements (Figures 6 through 10). In actual prac-
tice, whatever the reason for the concavity, it can be readily defined mathe-
matically. However, force fitting to a linear relationship is generally
acceptable for current modeling purposes.
Since (a) the effect of velocity on K2 appeared to be relatively small
for the SPS flyash and (b) the range of average velocities for the field tests
under investigation was encompassed by the laboratory tests, a linear relation-
ship was assumed for the drag versus loading curve. This led to selection of
3.0 N-nin/g-n as the average Kt value at 25 C and 25 N-min/ra3 as the effective
residual drag, SE. Based upon the design and operating parameters given in
Table 11, wherein the K2 values have been corrected to their equivalent levels
at operating baghouse temperatures, the ac values calculated from Equation 11
were 0.07, 0.13 and 0.10 for boiler firing at low, medium, and high load levels,
respectively. Adjusted Sg values were essentially the same, 31 to 33 N-min/m3
regardless of firing rate. The fact that ac values do not continue to increase
with boiler load may be due to the lower dust loading at high load, differences
in fabric, or some parameter change not detected during the test periods of
interest. It has been demonstrated in the past studies that the dust dislodg-
ing forces and ac will increase for a fixed cleaning mode when the thickness
of the dust; i.e., the fabric loading, is increased.
The ac values along with the relevant operating parameters shown in
Table 11 were used in the computer model to calculate the SPS system perfor-
mance characteristics summarized in Table 12. Predicted pressure losses were
between 40 and 75 percent lower than the actual measured values. In the low
load case, low estimates may be due to one of the model's limitations; i.e.,
the model operation is restricted to ac values equal to or greater than 0.1.
Therefore, although the computer program will function for ac entries of less
than 0.1 values, ac will be processed as if it were exactly 0.1. The result
is that the model will automatically predict a lower pressure loss in such
cases. With respect to the medium and high load predicitons, however, the
low ac estimate must be explained by some other mechanisms.
-------
TABLE 11. INPUT PARAMETERS FOR MODEL VALIDATION, HARRINGTON
NO. 2 BOILER, SPS WITH SLIGHTLY USED FABRIC
Low Medium High
Parameter , , • , ,
Number of compartments
14
14
14
Cleaning cycle time (min)
28
28
28
Individual compartment cleaning time (min)
1
.9
1.
9
1,
,9
Reverse flow velocity (m/nin)
1
.54
1.
54
1,
.54
Average face velocity (m/nin)
0
.355
0.
687
0.
KD
00
Gas temperature ( C)
133
157
165
Inlet dust concentration (g/m3)
3
.44
3.
58
2,
.94
Specific cake resistance, K2a (N-rain/g-m)
3
.77
3.
87
3.
98
Effective drag, Sg3 (N-min/m3)
31
32
33
Residual loading, WR (g/m2)
28
28
28
Fractional area cleaned, ac^
0.
. 07c
0.
13
0.
.10
aReported at actual operating temperatures and gas flows.
b
ac computed from Equation 11.
£
Computer program converts this value to 0.10 for subsequent
calculations.
TABLE 12. PERFORMANCE PREDICTIONS FOR
SPS, HARRINGTON NO. 2 BOILER
WITH SLIGHTLY USED FABRIC
Average pressure
Load
loss3 (
N/m2)
Fractional
level
penetration
Predicted
Measured
Low
400°
700
0.0036
Med ium
1000
1400
0.0047
High
1400
2200
0.0058
3ased on Sg values for slightly used
fabrics, 31 tc 33 N-min/m^.
Average penetration by GCA tests,
0.005-0.006.12
Based on computer value of 0.1 for ac.
57
-------
The difference between the predicted ac value for low load operation and
that which would haye resulted had the model been designed to operate over the
range (ac = 0.05 to 1) has been estimated by an equation developed during
earlier model sensitivity studies; i.e.,
K2CjVi2tr. (2n-l) / (2n-2)
K2CjVj tc
Se + KjCiV^tc (l-ac/ac)
"P" =
In 1 +
(12)
in which average pressure loss is related to system design and operating param-
eters. The units for the indicated variables remain as defined previously in
Equations 8 through 11 and Table 8 for actual temperature and flow conditions.
By substitution of the same parameters used to generate the model output sum-
marized in Table 13, in conjunction with the previously calculated ac values
of 0.07 and 0.10, pressure loss data were developed for low boiler operation.
The data presented in Table 13 mny be interpreted as follows: first,
Equation 12 provides a good pressure loss estimate relative to the more sophis-
ticated model solution. For an ac input of 0.1, the Equation 12 value is only
15 percent greater than that deriving from the model. Second, if the cleaning
parameter is actually 0.07 as computed from Equation 11, the pressure loss
based on Equation 12, 666 N/m2, is in reasonable agreement with the measured
value of 7 00 N/m2. Despite the approximations involved, the above analysis
suggests that the model disagreement under low load conditions may be at least
partly due to the lower limit (0.1) set for ac. If further field trials indi-
cate that low cleaning levels, ac<0.1 are very common, the model will be
revised to take this situation into account.
TA3LE 13. ESTIMATION OF KODEL ERROR IN
PREDICTING PRESSURE LOSS WHEN
ac VALUES ARE LESS THAN 0.1
Average pressure loss, N/m2
Cleaning Computed Computed Actual
parameter, ar c I j
^ from by measured
equation model value
0.07 666 400 700
0.10 462 400 700
The preceding analysis cannot be applied to medium and high load condi-
tions because the calculated ac values are already within the 0.1 to 1.0 range.
Predicted pressure losses for the medium and high load cases, respectively,
were roughly 29 and 36 percent lower than the measured values.
-58
-------
Since the model assumes that K2 varies as the square root of the filtra-
tion velocity whereas present tests suggested a lesser exponent; i.e.,
K2 = F (v)0,2~0'25, the velocity effect was suspected as a possible cause of
the low predicitons. However, when the model was actually adjusted so that
the velocity dependency was eliminated altogether; i.e., K2 is constant, the
predicted pressure loss for the medium load level was found to be the same as
that forecast when the velocity exponent was 0.5.
Therefore, the fact that the input parameters in Table 13 included a very
low value for Sg, ^ 31 N-rain/m3, was examined as a possible cause of low model
predictions. Based upon prior laboratory and field measurements, it had been
noted that Sg values in the range of 300 N-min/m3 at 25 C were not uncommon for
fabrics that had been in service from 1 to 2 years. In terms of overall pres-
sure loss across the filter, the difference between 30 and 300 N-min/m3 for Sg
translates to a pressure loss increase of 183 N/m^ (^ 0.75 in. w.c.) for a
filter system with a face velocity of 0.61 m/min (2 ft/min). Thus, although
the high £p selection is conservative, its impact on overall system pressure
is comparatively small, (<10 to 15 percent). New estimates of at were made by
means of Equation 12 for low, medium, and high load conditions assuming the Sg
value to be 300 N/min/ra3, Table 14.
TABLE 14. CALCULATED OPERATING AND PERFORMANCE PARAMETERS
FOR HARRINGTON NO. 2 BOILER (SPS) FOR AN SE
VALUE OF 300 N-min/m3
Average pressure Percent^
Load S£ b loss, N/m2 pressure Fractional
level (N-min/m3) c loss penetration
Predicted Measured0 deviation
Low 370 0.08 580 700 -17 0.0033
Medium 380 0.16 1080 1400 -23 0.0037
High 390 0.11 1600 2200 -27 0.0042
3 1 O
Sr corrected to Table temperature from 300 N-min/m13 at 25 C.
^ac computed from Equation 11.
CFrom Table 12.
^Percent deviation from measured value.
According to Table 14, it appears that the assumption of a higher SE value
(which may be more in line with the estimated service life of the SPS bags)
brings the model pressure loss predictions into closer agreement with the
measured (field test) values. A comparison of the flyash penetration levels
given in Tables 12 and 14 shows relatively small changes in emissions. A
direct relationship, however, is indicated between penetration and ac which
is consistent with increased dust removal from the fabric. It should be noted,
however, that with both ac and S£ undergoing change, the end result could be
either an increase or decrease in flyash penetration.
59
-------
With respect to the effect of increased Sg or pressure loss, basic theory
suggests that if the substrate pressure loss is increased with no change in
the amount (W) and K2 properties of the overlying dust layer, the overall
fabric pressure loss should also increase. However, these effects are not
necessarily directly additive for sequentially cleaned multicompartment
systems as demonstrated in prior model sensitivity studies.
AVAILABILITY AND ASSESSMENT OF OPERATING DATA, KRAMER STATION,
NEBRASKA PUBLIC POWER DISTRICT
A considerable part of the operating data for Kramer Station has been
obtained from plant log sheets and strip charts. These data include coal con-
sumption and steam production rates, baghouse inlet temperatures, pressure
drops across each compartment and overall baghouse pressure drop. As mentioned
earlier in this section, two additional pieces of information are necessary to
appraise baghouse resistance characteristics; gas flow rate and the inlet (or
uncontrolled) particulate concentration. Outlet particulate concentration is
also necessary to define baghouse collection efficiency for the aerosol. The
latter information (flow rate and inlet and outlet concentrations) was provided
for some time periods by several field tests performed at Kramer Station.
Shortly after the baghouses were placed in service, compliance tests were
performed (May 1977) that provided data on gas flow, temperature, and outlet
concentrations. During the same time frame, acceptance tests provided similar
data as well as estimates of inlet particulate concentration. Compliance tests
were performed for each stack rather than for Boilers 1 through A whereas
acceptance tests were performed only on Boilers 1 and 4. The result of these
tests alon^ with all relevant details are described in References 13 through 16.
In addition to the compliance and acceptance tests cited above, special
performance tests were conducted on the Kramer baghouses by MRI* under contract
to the Electric Power Research Institute (EPRI). Partial results for the
October 1977 and May 1978 tests are reported in References 14 through 16. A
final EPRI report is now in preparation that will provide information on bag-
house outlet and inlet concentrations, efficiency, all gas flows and steam
generation rates, and plume opacity.
Finally, operating data were also obtained for more recent time periods,
July 13, 1979 and January 22, 1980, when no concurrent stack measurements
were performed. The July date was chosen since on that date an "urge" test
was performed. During this period the boilers were operated at maximum load
(actually 20 percent over the design level) . One reason for selecting the
January date was that the Boiler 2 load level was reasonably constant through-
out the day. The only information sources for these tests were the plant log
sheets and strip charts.
In general, all the time periods for which data were considered for analy-
sis reflect fairly steady boiler load levels over at least 3 or A hours of
^Meteorological Research, Inc., Altadena, California.
60
-------
operation. Tvo of the acceptance tests, however, were run over a much shorter
(1 hour) period. The data also represent a broad range of operating conditions
and operational exploration. It was observed, for example, as will be dis-
cussed in the following sections, that baghouse operating procedures have
undergone modifications as more field experience accrued. The available data
are included in the time periods listed in Table 15.
TABLE 15. DATA AVAILABILITY AND CUMULA-
TIVE BAGHOUSE SERVICE
PERIODS
Data available Cumulative on-line service
May, 1977
<1
month
October, 1977
5
months
May, 1978
1
year
June, 1979
2
years
A compilation of the operating data extracted from plant log sheets,
strip charts and various reference sources 13 through 16 is presented in
Table 16. With the exception of the tests ending with "avg" all test numbers
were assigned by CCA. Inlet gas flow rates were available only for the compli-
ance and/or acceptance test data. All outlet particulate concentration and
collection efficiency data reported for EPRI tests were used to calculate the
inlet concentration. Two sources of information were available for baghouse
pressure drop as well as the pressure drops through the individual compart-
ments. Baghouse pressure loss is also recorded continuously for each baghouse
on strip chart recorders. The numbers appearing in parentheses under the
flange to flange pressure drop present strip chart data. These values were
essential to determine the reliability of the pressure drops shown on the log
sheets since pressure drop is manually recorded every 3 hours in some cases.
Furthermore, the log sheet values are instantaneous readings that do not neces-
sarily represent the average pressure drop for the time interval of interest.
Finally, steam generation rates were obtained from both the log sheets and
supporting references 14 through 16, whichever appeared the most appropriate
for a given analysis.
Volumetric Gas Flow Rate
When flue gas flow rates were not available for the time periods of inter-
est, they were estimated from other data such as boiler steam rates which were
indicated for nearly all time periods. Since steam flov: is roughly proportion-
al to fue.1 firing rate and fuel firing rate in turn relates almost directly
to flue gas flow, the volumetric gas flow could then be determined from the
boiler steam flow. Although other factors, such as coal heating value, mois-
ture content, and excess air also affect gas flow rate, these factors could
not be taken into account over the short term for modeling purposes. However,
these factors were not considered to detract from the accuracy of the flow rate
estimates any more than the possible error contributed from the need to
61
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TABT.E 16. AVAILAKLK 0PEKAT1NG AND PERFORMANCE DATA FOR KRAMER STATION
Baghou
se inli-t mcuauremenLs
Pressure loss
in.
water
lost
code
Holler Date
F 1 ow
(103 acfm)
Temperature^
CF)
Part fcula tec
concentration
(gr/acf)
Average''
across
compar Linen ts
d
Flange
to
f 1 a np, e
Steam
rate
(103 Ib/hr)
Par t J i n 1 a te
collec tiori
ef f ic iency
(percent)3
?-a vg
1 5/77
133.4
336
0.424
5.7
8.3
240b
98.9
3-avg
1 5/77
127.7
329
1.637
4.8
7.3
214
99-1
C
1 10/77
116.2
0.593
7
(6.5)
210.03
99.85
0
I 10/77
106.5
0.574
5.5
(6.0)
197.0*
99.7 7
E
1 10/77
92.9
0.34 2
5
(4.5)
154 °a
99.66
R
I 7/79
380
4.0
5.5
(5.5)
236b
S
2 7/79
365
2.8
4.8
(4.5)
244*
V
1/80
325
4.2
5.2
163
A
J 10/77
90.9
0.563
4
159.5a
216.0a
99.77
1',
3 10/77
130.9
0.605
6
99.90
1
3 5/78
0.752
2.6
3.4
137a
99.89
2
3 4/78
0.605
5.0
1603
99.86
3
3 5/78
0.656
2083
99.92
4
3 5/78
0. 7 38
2.4
3.3
140a
99.96
5
3 5/78
0.302
2.5
3.5
185a
99.90
6
3 5/78
1 .23
3.8
5.3
2Ub
99.98
T
3 7/79
375
4.3
6.9
(6.6)
257b
5-avp
4 5/77
202.8
37 2
0.278
6.0
7.5
320
98.7
6-avp
4 5//7
213.7
388
1 .002
7.0
8.3
99.0
I1
4 7/79
405
2.7
3.6
(3.6)
362
Note: Data reported In "as recieved" English units,
n
From Reference 3.
'Vrom Kramer Station log sheets.
c
From References 1, 2, and 3. October 1977 and May 197B values calculated from outlet concentration and
ef f icienc y.
d
Numbers not in parentheses are from Kramer Station log sheets; mimhers in parentheses are from baghouse
pressure loss strip charts.
-------
average hourly steam flow rates over 3 to 4 hour periods. The relationship
between steam flow and gas flow was established by plotting the indicated gas
flows versus their associated steam flows for Boilers 1, 2, and 3. The design
flow for the above boilers is 122,000 acfm at 22,000 lb/hr steam (0.55 acfm
per lb steam). For boiler 4 the flow increases to 192,000 acfm at 330,000
lb/hr steam (0.58 acfin per lb steam). Boiler 4 operating data were not
used for flow estimates, however, because the steam rates appeared to differ
from those of the three smaller boilers. The flow estimating relationship
for Boilers 1 through 3 was determined to be:
Q (acfm) = 0.54 x S (lb/hr steam) + 9000 acfm
The actual design rate was used to estimate the required flow data for
Boiler 4, when actual flow data were not available.
Inlet Concentration
Bagnouse inlet concentrations were available only for time periods when
actual performance tests were conducted. The remaining inlet concentrations
were assumed to be the same as those deriving from actual measurements. A
summary of the assigned concentrations is presented in Table 17.
TABLE 17. BEST ESTIMATES OF INLET
FLYASH CONCENTRATIONS,
KRAMER STATION
Inlet
flyash
concentration
, gr/acf
Boiler
number
Date
Assigned
value
Based on
coal ash
content
1
7/79
0.6
(l-37)a
0.70
(1.59)
2
7/79
0.6
(1.37)
0.66
(1.51)
2
1/80
0.6
(1.37)
0.76
(1.74)
3
7/79
0.6
(1.37)
0.67
(1.54)
4
7/79
0.4
(0.92)
0.69
(1.58)
Concentration in g/am^.
^Based on coal firing rate, 3.9 percent
ash and 80 percent carryover.
A value of 0.6 gr/acf was assigned as the inlet concentration for Boilers 1
through 3. However, a lower value was assigned to Boiler 4 since compliance
and acceptance measurements indicated that the inlet concentration to Boiler 4
was about 30 percent lower than that for Boiler 1. According to the estimates
of inlet concentrations based upon coal ash content and an 80 percent carryover,
the assigned inlet concentrations are roughly 80 to 90 percent of the coal ash
derived values for Boilers 1 through 3 and about 60 percent of the ash value
for Boiler 4.
63
-------
Baghouse Pressure Drop
As noted earlier, pressure drop data were provided by plant log sheets and
strip chart recorders. The Kramer log sheets indicate the overall baghouse
pressure drop given by fluid nanometer readings, overall baghouse pressure
drop excerpted from recorder strip chart, and individual compartment pressure
loss based on conventional manometer. Information is usually entered on the
log sheets every 1 to 3 hours, although more frequent entries were made dur-
ing some test periods. Reference to Table 16 shows that the pressure drops
obtained from log sheets and strip chart records are in good agreement. Since
the pressure drops of concern for the modeling analyses should be those across
the bags alone, any losses attributable to ductwork or manifolding effects
should be excluded. Despite the fact that pressure taps for estimation of
overall or flange-to-flange pressure loss do not include much ductwork or mani-
folding, distinct differences are indicated between the former values and the
fabric losses alone, Table 18. In a previous study, similar differences have
been cited for Kramer Station15 as shown in Table 18.
TABLE 18. FLANGE TO FLANGE (OVERALL) PRESSURE LOSSES
VERSUS INDIVIDUAL COMPARTMENT PRESSURE
LOSSES
Pressure loss, inches water
Boiler 1 Boiler 2 Boiler 3 Boiler 4
Flange-to-flange 8.0 6.2 4.8 6.0
Compartment 6.8 5.0 3.9 4.5
Difference (Duct
and manifold 1.2 1.2 0.9 1.5
loss)
Based upon the data appearing in Tables 16 and 18, when overall baghouse pres-
sure loss constitutes the only data input, 1 inch water is subtracted from the
former value to estimate the pressure loss through the dust-laden fabric alone.
Cleaning Cycle
The general aspects of cleaning cycles have been discussed in Section 2
of this report. However, the performance analyses of the Kramer Station bag-
house requires that the exact cleaning cycle used during each test period be
defined since Kramer Station has employed at least four different cleaning
cycles. A summary of the various cleaning cycles is presented in Table 19.
The off-line times shown in Table 19 represent the period when one compart-
ment undergoes cleaning, whereas the on-line time depicts the time when all
compartments are filtering. Since the cleaning cycles for the Kramer Baghouses
are partially controlled by pressure loss (see Section 2), a baghouse may, in
fact, operate with several permutations of off-line/on-line conditions. For
64
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example, if a baghouse is operating under the 11 min. 25 sec. cleaning cycle
and pressure loss exceeds the preset limit, the cleaning cycle will shift to
a "constantly cleaning" mode (the 58 sec. cycle). Since this situation repre-
sents a highly variable cleaning process, it cannot be analyzed via the steady
state approach. The time scale on the pressure drop strip charts was suffi-
ciently resolvable to determine whether or not a variable cleaning rate had
been in effect. It is cautioned that in the application of any test data,
it is important to observe not only the actual test data, but also to deter-
mine whether pressure conditions were such as to drive the system into a con-
stantly cleaning mode.
TABLE 19. SUMMARY OF CLEANING CYCLES USED AT KRAMER STATION
Time per compartment
May 1977 September 1977 October 1977 May 1978
Off-line3
58
sec
1
rain
18 sec
1
min
25 sec
1
min
25 sec
On-line'3
0
sec
2
min
4
min
10
min
Total
58
sec
3
min
18 sec
5
min
25 sec
11
min
25 sec
&
Refers to compartment undergoing cleaning.
^All compartments filtering.
Filtration Velocity
Filtration velocity (metric units) was computed from the volumetric gas
flow (English units) at baghouse inlet conditions and the total filtration
area:
0.02832 0 (acfm)
V (m/min) = j3
where A = 6,706 m2 for Baghouse 1, 2, and 3.
A = 10,745 m2 for Baghouse 4.
Selection and Reduction of Operating Data
Based on inspection of the Table 16 data, most tests present sufficient
information for a steady-state analysis. Test 3 (avg) on Boiler 1 in May 1977
could not be used since the time frame was less than 1 hour. The same logic
applied to a subsequent test on Boiler 4 conducted in May 1977, Test 6 (avg).
The measurement interval for July 13, 1979 for Boiler 1 (Test R) could not be
used since the baghouse cleaning was carried with a combination of the 11 min.
25 sec. cleaning cycle and the 58 sec, cycle. Finally, Test 3 of May 1978 on
Boiler 3 was excluded because of missing pressure loss data, The remaining
test information was reduced by the techniques described in this section to
a form suitable for analysis. The results of the data reductions are summa-
rized in Table 20. Note that the cleaning cycle time shown in Table 20 refers
65
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TABLE 20.
SUMMARY OF KRAMER STATION OPERATING DATA REDUCED FOR MODELING ANALYSES
Test
Code
Boi1er
Date
Inlet
concentrat ion,
(g/am3)
Velocity
V
(am/in i n)
Pressure
1o ss, P,
(N/m2)
Total cycle
time, tc,
(min)
Gas
temperature
(°C)
2-avg
1
5/77
0.97
0.563
1420
9.7
164
C
1
10/77
1.36
0.491
1100
9.7a
166
D
1
10/77
1 .31
0.450
11 20
9.7rf
166
E
1
10/77
0.78
0.392
1000
9.7a .
149
S
2
7/79
1 .37
0.60
700
114.2
185
V
2
1/80
1.37
0.41
670
114.2
163
A
3
10/77
1.29
0.380
750
54.2
149
B
3
1 0/77
1 .39
0.553
1250
9.7a
166
1
3
5/78
1.72
0.351
650
9.7
149
2
3
5/78
1.39
0.401
1000
9.7
149
4
3
5/78
1.09
0.357
600
114 .2
149
6
3
5/78
2.82
0.528
950
114.2
166
T
3
7/79
1 .37
0.63
1075
9.7*
191
5-avg
4
5/77
0.64
0.535
1500
15.5
189
4
4
7/79
0.92
0.560
675
182.7
208
Note: All units expressed in Metric system for data reductions.
aIndicates that the normal cleaning cycle reverted to continuous cleaning and
remained at that level for the entire test period.
-------
to the time span embracing the sequential cleaning of all 10 or all 16 compart-
ments, respectively. The cleaning times that are footnoted, Table 20, are
"constantly cleaned" cycles which were inititated by high pressure losses on
the dates in question. Had pressure losses not exceeded the pre-set value,
the normal cleaning cycles would have been those shown in Table 19. It is
also emphasized that some of the EPRI tests were purposely forced into a
constantly-cleaned mode for experimental purposes.
Analysis of K? and ar.
Based on the preliminary analyses of Southwestern Public Service (SPS)
data, concurrent development of K2 and ac parameters was not possible for the
Kramer baghouses. Therefore, the value of K2 used in modeling calculations
was that determined by laboratory measurement (see Section 3), 3.7 N-min/g-m
at 25°C and 0.61 m/min. In order to estimate ac, an additional piece of infor-
mation is required; i.e., the effective drag, Sg. Since the laboratory tests
were performed on relatively new fabrics with only minor plugging, Sg values
were estimated from prior measurements with a similar fabric for various ser-
vice lives.5 Typical Sj levels for new, less than 6 months service, and 2
years field use are 60, 115 and 352 N-min/m3 respectively. Based on the above
values the following estimates of S£ were applied to the Kramer baghouses:
Boilers 2, 3, and 4
• approximately 1 month service - 150 N-min/m3
• approximately 6 months service - 350 N-min/m3
Boiler 1
• approximately 1 month service - 550 N-min/m3
• approximately 6 months service - 550 N-min/m3
The reason for the higher S£ value for the Boiler 1 baghouse was the higher
pressure drop reported for this baghouse. Boiler 1 generally operates at a
pressure drop roughly 1 inch water greater than that for the other units at the
same operating conditions.1^ ^t 0.61 m/min face velocity, this translates to
a drag value of about 400 N-min/m3, Although it is recognized that the rela-
tionship between Sp; and overall pressure loss is not linear, 400 N-min/m3 were
added to the Sg value of 150 N-min/m3 corresponding to 1 month of service. It
is suspected by Kramer personnel that the lime precoat on Boiler 1 is respon-
sible for this difference. The same value was also applied to Boiler 1 for
the October 1977 tests (after 6 months service), the assumption here being
that either no flyash has deposited interstitially in the fabric or that any
flyash that has deposited, has in effect, displaced an equilavent amount of
limestone. For Boilers 2, 3, and 4 the values shown for 1 month service were
applied to the May 1977 tests, whereas the 6 month values were applied to all
other tests.
Values of ac, Table 21, were estimated from the data presented in Table 20,
the previously mentioned Kj and Sp values, and Equation 11. The results seem
to indicate that the cleaning cycle time is more important in determining
67
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ac than the boiler load level, neglecting for the moment any concurrent changes
in such variables as inlet concentration and pressure loss. Tor example, for
Tests 2 and A the steam flows were almost identical although the cleaning
cycles were different. Thus, for a time interval of tc ¦ 9.7 minutes, ac was
estimated as O.OL while for 54.2 minutes it appears as 0.07. This argument is
apparently contradicted by Tests 5 and 6. However, the inlet concentration
for Test 6 was about 3 times greater than that for Test 5 and the gas flow was
also somewhat higher. In essence, Tests 5 and 6 demonstrate that the amount
of dust added during a cleaning cycle; i.e., the product of concentration,
velocity and cleaning cycle time is the controlling factor in determining ac.
This is to be expected since ac reflects the amount of dust removed (which
equals the amount added) divided by the total amount on a bag before cleaning.
TABLE 21. ESTIMATED ac VALUES FOR THE KRAMER
STATION BAGHOUSES
„ Steam ° f" Calculated
Boiler Date flow C^C e ac
C° 8 (103 lb/hr) (min) (fractional)
2-avg
1
5/77
24 0
9.7
0.02
C
1
10/77
210
9. 7a
0.01
D
1
10/77
197
9. 7a
0.01
E
1
10/77
154
9. 7a
0.01
S
2
7/79
244
114.2
0.52
V
2
1/80
162
114.2
0.21
A
3
10/77
160
54.2
0.07
B
3
10/77
216
9. 7a
0.02
1
3
5/78
137
9.7
0.02
2
3
5/78
160
9.7
0.01
4
3
5/78
140
114.2
0.20
5
3
5/78
185
114.2
0.17
6
3
5/78
214
114.2
0.47
T
3
7/79
257
9. 7a
0.04
5-avg
4
5/77
320
15.5
0.01
4
4
7/79
362
182.7
0.49
alndicates that the normal cleaning cycle was overridden
by high pressure loss, see Table 19.
This is not meant to imply that the pressure limit aspect of the clean-
ing cycle is unimportant. If the preset pressure limit is exceeded during the
normal cleaning cycle, the system reverts to the "constantly-cleaning" mode
which automatically provides more frequent cleaning. However, for at least
one full cycle, the value of ac would be the same (regardless of the type of
cleaning cycle) since the amount of dust on a bag prior to cleaning will deter-
mine how much dust is removed from the bag in a deflate-reverse flow system.
During subsequent cycles, however, less dust will be removed because the depo-
sit thickness will be less just before cleaning. With continued filtration,
the system will eventually achieve a steady state whereby the amount of dust
added over the period representing a complete cleaning and filtering cycle
68
-------
equals that removed. Since less material accumulates over 10 minutes than
during 54 minutes, less removal is required to maintain steady-state. The ac
values shown in Table 21 are "steady-state" values.
Model Validation
During the analyses of the SPS data discussed in the first part of this
section, it became apparent that ac values of less than 0.1 would require modi-
fications to the existing model to obtain accurate results. In light of the
fact that many of the ac values estimated from the Kramer data were consider-
ably less than 0.1, the need for adjustments was further demonstrated.
Although external corrections were applied to the SPS results when ac values
slightly less than 0.1 were encountered, it is undesirable to apply the same
approach for ac values as low as 0.01 or 0.02. The principal objection is
the high sensitivity to fabric pressure loss in the low ac range. Therefore,
only a selected number of tests results and associated derived data were used
in the Kramer validation study. The actual values used in the modeling analy-
ses are those which were presented in the preceding section, Tables 20 and 21 .
The results of the analyses are presented in Table 22. With the exception of
Test A, all ac values for the tests in Table 22 were greater than 0.1.
Although the ac value for Test A was 0.07, the model automatically treats it
as 0.1. The result is that the predicted pressure loss is lower than that
predicted had the actual value of 0.07 been used in a model capable of opera-
ting at ac = 0.07. Therefore, the difference between predicted and actual
pressure drops is correspondingly greater as shown in Table 22.
With the exception of Test A, predicted pressure losses are in good agree-
ment with the measured values with a minimum deviation of +4 percent for Test U
and a maximum deviation of-22 percent for Test 4. It appears that the greatest
differences between actual and predicted pressure losses occur for the low ac
values as indicated in Figure 17. Although it might be argued that these
differences are due to random errors in the input data, if one assumes that
the operating data have the same accuracy from one test to the next, a real
relationship appears to exist. If so, it must be assumed that the model becomes
less accurate^for low values of ac, a supposition that is confirmed by pre-
vious studies'30 that show pressure drop is more sensitive to ac variations
when ac is small.
The model predictions of penetration are not as accurate as those of
pressure loss for the Kramer Station Baghouses. In fact, the Kramer baghouses
appear to be vastly more efficient than predicted by the model. Although not
analyzed in this study, other tests at Kramer indicated efficiencies of 99.97
to 99.99 percent for Boiler 3 when operating at 50 to 90 percent of full load
with no cleaning.15 The large differences between predicted and actual
penetration have not as yet been resolved.
69
-------
TABLE 22. MODEL VALIDATION TESTS BASED ON KRAMER STATION DATA
Pressure drop, N/m2
Test
code
Boiler Date
Predicted Actual
Actua1
predicted
Penetration, percent
Predicted Actual
s
7/79
74 5
700
0.94
0.61
—
0.52
V
2
1/80
57 0
670
1.18
0.34
0.21
Aa
3
10/77
525
750
1.43
0.39
0.23
0.07
4
3
5/78
A 90
600
1.22
0.29
0.04
0.20
5
3
5/78
545
625
1.15
0.51
0.10
0.17
6
3
5/78
800
950
1.19
0.35
0.02
0.47
U
4
7/79
700
675
0.96
0.60
—
0.49
a
ac
value of
0.07 -
all other
tests had
ar values
greater than
0.1.
-------
1.5
CO
CO 1.4
O
LlI
q:
=>
CO
CO
LJ
CE
CL
a
LJ
i-
o
a
LJ
cr
CL
1.2
<
3
H
U
<
I.I
1.0
0.9
~ M0NTICELL0 STATION
• KRAMER STATION
X HARRINGTON STATION
0.1 0.2 0,3 0.4
FRACTIONAL AREA CLEANED, oc
0.5
Figure 17. Relationship between accuracy of pressure
loss predictions and ac.
71
-------
AVAILABILITY AND SELECTION OF OPERATING DATA, MONTICELLO STATION,
TEXAS UTILITIES GENERATING COMPANY
Design and operating parameters for Boilers 1 and 2 at Monticello Station
were supplied by TU personnel during a GCA plant inspection and in subsequent
telephone communications with the engineers responsible for the direction of
baghouse operations. The information used in the modeling analyses presented
here reflect the most recent reporting of baghouse design, operating, and per-
formance parameters. Table 23 provides a listing of the key data inputs used
to describe current boiler and cleaning system operating characteristics.
TABLE 23. DESIGN AND OPERATING PARAMETERS FOR BOILERS 1 AND 2,
MONTICELLO STATION, SINGLE BOILER STATISTICS
Range
Average
Lignite firing rate
411-496 tons/hour
454 tons/hour
Coal ash content
16-28 percent
22 percent
Amount of coal ash
appearing as flyash
—
65 percent
Total gas flow, ESP plus
filter
—
2.3 x 106 acfm
Total baghouse flow,
Sections A and 3
—
1.7 x 106 acfm
Total filtration area
—
6.7 x 105 ft2
Filtration velocity
2.39-2.69 afpm
2.54 afpm
Baghouse pressure loss
Boiler No. 1
Boiler No. 2
10-12 in H20
10.5-11 in H20
11 in H20
10.8 in H20
Reduction of Operating Data
In reducing the design and operating data for the baghouse system, the
average values for coal firing rate (454 tons/hr), coal ash content (22 percent),
ash carryover (65 percent), and volumetric gas flow rate at baghouse tempera-
ture (2.3 x 106 acfn) were used to computer the resultant flyash particulate
loading (6.6 gr/acf or 15.1 g/am3) in the gas streams entering the two sections
of each boiler baghouse system. The average filtration velocity was estimated
as 2.54 afpm (0.77 am/nin), based upon the average baghouse flow and total
filtration area shown in Table 23. Similarly, an average pressure loss value
of 11 in. water was selected for modeling studies.
The cleaning cycle for the Monticello baghouses is designed to take each
compartment off-line for 2.5 minutes. After returning the just-cleaned com-
partment to the filtration mode, the isolation of the next compartment to be
cleaned is delayed for 1.25 minutes. Thus, a total of 67.5 minutes is required
72
-------
for the sequential cleaning of 18 compartments during which time all compart-
ments are on-line for 22.5 minutes and 17 compartments on-line for the remain-
ing 45 minutes.
As in the case of Kramer Station, insufficient field data were available
for the concurrent determination of K2 and ac. Thus, the value of K2 used in
the present analysis, 1.0 N-Tnin/g-m (at 25°C and 0.65 n/min), was that derived
from the laboratory measurements discussed in Section 3 of this report. An
assumed S£ value of 350 N-min/m3 was chosen as a representative effective
residual fabric drag describing the fabric properties after extended field
service. The bases for this selection were prior GCA laboratory measurements
on related flyash/glass fabric combinations.'
The total filtration capability for each boiler consists of two separate
baghouses, A ar.d B, each containing 18 separate compartments. Furthermore,
the levels of operating pressure loss have been sufficiently high, MO-12 in.
H20, to require continuous or back-to-back cleaning. Since two compartments,
one from Section A and one from Section B are isolated simultaneously, the
baghouse system can be analyzed as if it were made up of 18 sequentially
cleaned compartments. Hence, in the summary of test parameters used for cal-
culating ac levels, the number of separate compartments is effectively 18.
In Table 24, the necessary design and operating parameters needed to compute
ac by means of Equation 11 and also those required to operate the filtration
model have been combined with the specific application designated by the cod-
ings ac and M.
TAELZ 24. SUMMARY OF DESIGN AND OPERATING PARAMETERS USED FOR
ESTIMATION OF ac AND COMPUTER MODEL ANALYSES,
MONTICELLO STATION
Parameter description
2
Application
M ac
Numerical value
Number of compartments
M
ac
18
Cleaning cycle duration
M
ar
67 .5 minutes
Time to clean one compartment
M
2.5 minutes
Reverse flow volume
M
Not used
Cleaning cycle initiation
M
Continuous cleaning
3aghouse temperature
M
ac
177°C
Inlet concentration
M
ac
15.1 g/am3
K2 (25°C and 0.65 m/min)
M
ac
1.0 N-min/g-m
SE (25°C)
M
ac
350 N-min/m^
Kr
M
73 g/m2
Filtration velocity
M
ac
0.77 m/min
Average pressure loss
ar
2750 N/n2
(measured)
^ designation means Model Input.
ac designation means use for ac computation by Equation 11.
73
-------
Since Konticello Station is a baseload plant with only minor variations
in load level, a steady-state analysis can be performed. Furthermore, since
the bags in each section are essentially the same type and all have seen the
same service time, a representative estimate of ac appears possible. The
method used for estimating ac has been presented in preceding sections of this
report dealing with the Harrington and Kramer baghouses. Based upon the data
shown in Table 24, the estimated aQ value calculated by Equation 11 is 0.32
for the Monticello filter system. Despite the limitation of the estimating
procedures, an ac value of 0.32 in conjunction with a corresponding K2 value
of 1.0 appears consistent with similar data reported for the Nucla, Colorado
system; i.e., 0.37 for ac and a value of 0.76 N-min/g-m for K2• By using
the ac value of 0.32 in conjunction with the other parameters required for a
computer model prediction of filter pressure loss and dust penetration charac-
teristics given in Table 24, the following results were obtained (see Table 25).
TABLE 25. COMPARISON OF MEASURED AND
PREDICTED FILTER SYSTEM
PERFORMANCE FOR MONTICELLO
STATION
Predicted Measured
Pressure loss, N/m2^ 1735 2750
Penetration, percent 0.8 No data
aBased on GCA Fabric Filtration Model.®
^Pressure loss across fabric.
According to Table 25, the measured pressure loss is approximately 60
percent greater than one might expect based upon the modeling input information
appearing in Table 24. Several reasons can be offered for the poor agreement
between predicted and measured values. The very limited amount of data used
in these analyses automatically detracts from its statistical significance.
Additionally, the field and laboratory observation of electrical charge effects
not detected with three other flyashes involved in this study represent another
critical unknown quantity. It is suspected, although we have no supporting
evidence, that the charge properties may cause the K2 values estimated in the
laboratory to be erroneously low relative to the field values. Therefore,
there seems to be a critical need to determine K2 values by an in-situ method
such as that proposed in Section 3 of this report. Insofar as attempting to
apply even the most advanced of the current theories for predicting K2 values
from fundamental principles, it is believed that an accuracy of ±50 percent
represents the best that could be expected at the present time.
Samples of the tabular printout from the computer analyses of the
Monticello, Kramer, and Harrington Station data are presented in Appendix B.
74
-------
REFERENCES
1. Ha]1, R.R. and R. Dennis. "Mobile Fabric Filter System." GCA/Technology
Division, Bedford, Massachusetts. Control Systems Laboratory, U.S. Envi-
ronmental Protection Agency, Research Triangle Park, North Carolina.
EPA-600/12-75-013a. August 1975.
2. Bradway, R.M. and R.W. Cass. Fractional Efficiency of a Utility Boiler
Baghouse - Nucla Generating Plant. U.S. Environmental Protection Agency,
Control Systems Laboratory, Research Triangle Park, North Carolina.
EPA-600/12-75-013a (NTIS No. PB-246-64/AS) - August 1975.
3. Cass, R.W. and R.M. Bradway. Fractional Efficiency of a Utility Boiler
Baghouse: Sunbury Steam-Electric Station. U.S. Environmental Protection
Agency, Control Systems Laboratory, Research Triangle Park, North Caro-
lina." EPA-600/2-76-077a (NTIS No". PB-253-943/AS) . March 1976.
4.- Dennis, R. and N.F. Surprenant. Particulate Control Highlights: Research
on Fabric Filtration Technology. U.S. Environmental Protection Agency,
Industrial Environmental Research Laboratory, Research Triangle Park,
North Carolina. E?A-600/8-78-005d. June 1978.
5. Dennis, R., et al. Filtration Model for Coal Fly Ash with Glass Fabrics.
U.S. Environmental Protection Agency, Industrial Environmental Research
Laboratory, Research Triangle Park, North Carolina. EPA-600/7-77-084.
August 1 97 7.
6. Dennis, R., R.W. Cass and R.R. Hall. "Dust dislodgement from woven fabrics
versus filter performance." J. Air Pollution Control Association 28:47.
(1978).
7. Dennis, R. and H.A. Klaitm. "A model for coal flyash filtration." J.
Air Pollution Control Association 29:230 (.1979).
8. Dennis, R. and H.A. Klemm. Fabric Filter Model Format Change. Vol. 1
Detailed Technical Report, Vol. II User's Guide. U.S. Environmental Pro-
tection Agency, Industrial Environmental Research Laboratory, Research
Triangle Park, North Carolina. EPA-600/7-79-043a, EPA-600/7-79-043b.
February 1979.
9. Jones, J.D. and Kenneth L. Ladd, Jr. Selection Criteria for Emission Con-
trol System and Status Report of Fabric Filter Performance Testing.
Presented at Third EPA Symposium on Fabric Filters for Particle Collection.
Tucson, Arizona. December 5, 1977.
75
-------
10. Faulkner, George and Kenneth L. Ladd, Jr. Start-up, Operation and Perform-
ance Testing of Fabric Filter System Harrington Station, Unit No. 2.
EPA-600/7-79-044b. February 1979. (Presented at Symposium on the Trans-
fer and Utilization of Particulate Control Technology. Denver, Colorado.
July 1978).
11. Ladd, Kenneth L., Jr., Richard Chambers, and Sherry Kunka. Installation
of a 3aghouse Fabric Filter System. Paper No. 79-38.2. Presented at
72nd Annual Meeting of APCA. Cincinnati, Ohio. June 24-29, 1979.
12. Schiff, Howard, W. Piispanen, and R.M. Bradway. Baghouse Performance
Test — Southwestern Public Service Company Harrington Station Unit No. 2.
Draft Test Report. Prepared by GCA/Technology Division for Southwestern
Public Service Co. August 1979.
13. Stenby, S.W., L.W.A. Bye, and R.J. Beaton. The Kramer Baghouse. American
Power Conference. Chicago Illinois. April 23-25, 1979.
14. MacRae, Terry. Design, Start-up, and Operating Experience on Western
Pulverized Coal-Fired Boiler Baghouses. Presented at 71st Annual Meeting.
APCA. Houston, Texas. June 25-30, 1979.
15. Stenby, E.W., L.W.A. Bye, and R.J. Beaton. The Kramer Baghouse. Combus-
tion 51:31. October 1979.
16. Beaton, R.J. Continuing Operation and Maintenance Experience of the Four
Reverse Air Fabric Filters at the Kramer Station. 4th International
Fabric Alternatives Forum. Phoenix, Arizona. December 5-6, 1979.
17. Roeck, D.R. Operating Experience at Two Utility-Scale Baghouse Installa-
tions. Memorandum prepared for Utilities Air Regulatory Group, Particu-
late Control Subcommittee. July 1979.
18. Dill, R.S. A Test Method for Air Filters. Trans. Amer. Soc. Heat Vent.
Eng. 44:379 (1936).
19. Cushing, K.K. and W.B. Smith. Procedures Manual for Fabric Filter Evalu-
ation. EPA-600/7-78-113. June 1978.
20. Ragland, J.W., et al. HP-25 Programmable Pocket Calculator Applied to
Air Pollution Measurement Studies: Stationary Sources. EPA-600/7-77-058.
June 1977.
21. Davis, W.T., P.J. LaRosa, and K.E. Noll. The Generation and Evaluation
of Fabric Filter Performance Curves from Pilot Plant Data. Filtration &
Separation. November/December (1976).
22. Koscianowski, J.R., L. Koscianowski, and E. Szczepankiewicz. Filtration
Parameters for Dust Cleaning Fabrics. EPA-600/7-79-031. January 1979.
23. Rudnick, S.N. and M.W. First. Dust Cake Compaction in Fabric Filtration.
(Paper No. 78-62.7, presented at the 71st Annual APCA Meeting. Houston,
Texas. June 25-30, 1979).
76
-------
24. Billings, C.E. and J. Wilder. Handbook of Fabric Filter Technology.
Volume 1: Fabric Filter Systems Study. EPA No. APTD 0690. (NTIS
No. PB-200-648). December 1970.
25. Drinker, T. and T. Hatch. Industrial Dust. 2nd Edition, Chapter 10.
McGraw-Hill Book Company, Inc. (1954).
26. Durham, J.F. and R.E. Harrington. Influence of Relative Humidty on
Filtration Resistance and Efficiency of Fabric Dust Filters. Filtration &
Separation. July/August (1971).
27. Ariman, T. and D.J. Helfritch. How Relative Humidity Cuts Pressure Drop
in Fabric Filters. Filtration & Separation. March/April (1977).
28. Ladd, K.L. Summary Table of Baghouse Performance Tests Conducted by SPS.
Personal Communication. July 1979.
29. Chambers, R. Confirmation of Continuous Sootblowing During GCA Testing
of SPS Filter System. Personal Communication. March 3, 1980-
30. Dennis, R. and H.A. Klenrn. Fabric Filter Model Sensitivity Analysis.
U.S. Environmental Protection Agency, Industrial Environmental Research
Laboratory, Research Triangle Park, North Carolina. EPA-600/7-79-043c.
April 1979.
77
-------
APPENDIX A
SUPPORTING DATA FOR LABORATORY MEASUREMENTS
78
-------
vC
TA3LF. A - 1 .
DATA
Stf>«MARy K)K I.ARDIUTOKY
F .i t. r 1 c
filter
*rlitcnt Z
% rrl.it I ve
li'in Id 1 t y
" CM
nurhfr
-*11 r r
lot
d jst'
Tiif
v. 1 .•». 1 t
(n/mn)
Inl.l
* I'l'nii-nliflt U»ii^
^2r
I \ "ilnl
' K n /
1 1 A
11-ns_7q
il
n.',i
4 32
2.40
1 IP
11-Oh,79
<;p<;
U 1
0.6?
) . 94
? 86
1 IC
11-07-79
SI b
S3
0.61
4 . 3**
3 .00 •
1 ? A
11¦0°- 7 9
5.IS
4i
1 U2
4. i n
2. «M
1 /A
J 1 -0<«- 79
srs
s
I 01
4 .60
^ .40
1.*.
11 -;»-79
tv
. s?
0.64
2.71
CT.68 -
1 '.!»
11-29-79
ii1
*36
0.64
7.80
0. *6
i ur
11- 30-^
i if •
•' 32 ^
0 *><•
- ' 4.27
"f .OS •
1K\
oi-6:-«o
NPPP
•' 30*
0 6)
"4:ij -
lf*B .
0l-of-80
NKKP
30
11.61
I ' 4T74 •* •
,4 .IS
1 /A w
.dl-li-id
?JrS
?s
0 f-7
' • 4
2. 30
filtration
ME A S U R
. Hrane
ti
X Kin(rjtl^n
v c 1 o c I f v
(r/*ln). *
«. nlet •
coticrntratlonk
(*/>X)
(vil
~nr
0.03*
0. 1^
¦ 0.029
0,02)
O.OSA
0.'*?
0 .6?
0.6?
1 .08
1 .08
n.V.7
0.M
0 67
,62/»
62 :
,2.80
.3.07
,-r.o
2/71
\
~
•v <
7.87 •
?. 90
2.79 -
3.2S
J. W*-,
I .IS
I.I).
1 .09
J.7S
3.79
•1
.'I
0.61
„ , 2-H •
<;r<;
it
nf-po
Southv^tfFuMlC Service, Harrington SC«Hof\.»'
Utlllr !e«-Cedent lnr Co»*p»hv. Mont'lfrfl lo Starlonr
P.iKtlf Power District. Kri^er ^rttlon' '
Me,hracf Volume .6f • I r drawn thiougli frhe^filtir.'
Mj t it f j 1 wh lc iff o 115 out ot deposit! prior lu r c«i li Jn(t t he
f 11 ti r yJrfata la de* lcc t ./ Since the pcwbrane (liter-* '•
«. iMi Id b* *vc Iglvai* only at the bcflnnln* and end p( each '
Kor «-.v li test Intcrwil , Kf.le defined by a llrtnr
.ipiicom txat Ion of . t he . dr ig vpjshs dust'load 1ng curve.
,For t hi Intt La 1° f abr lc test Interval'*',' the p'ofAt at
.which the drJR ver»u» du*t loading «u#»«basins to
.level »>f' t tie •
-------
2000
FINAL point-
S -- 2156
w = 733
1500
F
g 1000
or
n
u
a:
CD
500
100
200
100
400
FABRIC LOADING
-------
FINAL POINT
3^ 798
V 7$7
E
Z
o
2 500
a
u
s
m
<
u.
>00
200
300
FABRIC LOADING (W). fl/m
400
500
600
700
Figure A-2. Test No. 14 Texas Utilities Generating Company Flyash,
face velocity = 0.64 m/min.
-------
2000
1500
B
E
z
1000
-------
1000
500
200
FABRIC LOADING (W), g/m2
Figure A-4. Test No. 17 Southwestern Public Service Flyash,
face velocity = 0.62 m/min.
83
-------
APPENDIX B
SAMPLE PRINTOUT SHEETS FROM COMPUTER
MODELING OF FABRIC FILTER PERFORMANCE
84
-------
TABLE B—1. SOUTHWEST PUBLIC SERVICE SIMULATION - LOW LOAD - SE = 25 N-min/m3
SUMMARY OF INPUT DATA FUR BAGHUUSE ANAIYSIS
SUUTHwEST PUBLIC SENVILE - MEDIUM LOAD DATA
BASIC DESIGN DATA
NUMBER UF CCJMPAHTMtNTS
CUMPAHTMtM [LEANING TIME
f OF F LINh TIME)
CLtANING CYCLt riMt
CONTINUOUSLY CLtANFD SYS IF m
REVERSE FL U*v VtLOCITY
OPf R A T I (VG DATA
AVERAGE FACE VELOCITY
GAS TEMPfKATMRE
INLET DUS1 LUhCtNTRAT1 ON
MEASURED AT
FABRIC AND DUST PWOPERT1ES
SPECIFIL RESISTANCt, «?
MEASURED AT
EFFECTIVE RF.SIOUAL DRAG, Sf
MEASURED A1
RESIDUAL LOADING. wR
1 mjnuTFS
r>H.O MIMUIES
l.-VUKI ^ /Ml N
0 . h 0 / 0 M/MJN
1S7. OEGKE ES C f- I IGHAUh
(./Mi
IS?. DTGREES CFmTIGWADE
^.H7 N-MIfl/(i-M
1 S 7. DEGREES CENTIGRADE
0 . hH 7 0 M/MIN
4?. N-M I N/M"i
1S 7. DFGREES CtNTIGHADk
?b. 0 G/M
-------
TABLE B-l (continued)
CALCULATE^ VALUkS
iNLtT DUST CONCENTRATION J.S6
CUHWtCTFD TO OPEHA1lNG T f MHEK A 1UWK
KAHWIC AND OUST CAKL HWljPt»TIFS COHtfF.CTtD HOW (iAS VISCDSlTr
SPECIFIC C A K. t HtSlSTANCtf K
-------
TABLE B-l (continued)
RESULTS UF BAGHOUSt ANAITS1S
southwest puhiic SERvitt - "-ifdium luap oar a
FUR
?R.OO M1NUTFS OPE RAT]DN > CYCLt MllMHtR I I
AVERAGE Ht'Nt' I H A I PJN =
AVERAGE PRESSURE OHlIP:
AVERAGE SYSTEM F l_Ol\ =
MAX (MUM PE*t 1HAI ION =
MAXIMUM PRESSURE URUP'
,a it - o 3
1026.70 u/M2
0./«JO M/M1M
.S1E-0 i
I 117 . 7H N/M?
OD j
FUR
28.00 M1NUTFS OPERATION, LtCLt fjUMbER
AVERAGt PENE THAT 1 (JM =
AVERAGE PRESSURE DROP:
AVERAGE SYSTEM FLO* =
MAXIMUM PENt THA T If)N =
MAXlWIH PRtSSURE DROP:
U. 78E-03
I 021 .Ob N/M2
0.7M0 M/M1N
-------
TABLE B-2. SOUTHWEST PUBLIC SERVICE - MEDIUM LOAD - SE = 25 N-min/m3
SU^MAKY OF INPUT DAM FOR HAGhUUSF ANALYSIS
SUUlHrtEST PUBLIC SFRVICE- LOW LOAD DA 1A
UASIC DESIGN DA I A
NUMRFk Of- tO^PARTMFNTS
CUMPAR T Mf n 1 CLEANING T I MF
(OFF LTNt TIME)
LLtAMNi; CYt.LF T I mh
C(1N r I NtJtHJSl Y CLEANED SYSTF.M
REVERSE HDn VELOCITY
DREWA TING DATA
AvEWA&f. FACE VELUC I 1 Y
r. AS T E fr'.Pt * a I IJM t
Inlet dust loncfmpatiun
measured at
FABWIC AND OUST PROPERTIES
SPECIFIC RESISTANCE, HP
MEASUWtD A[
EFFECTIVE RESIDUAL DRAG. SF
MEASURED AT
RFSIDIJAL LOADING, WR
1 U
1.9 MIMUTF5
£>^.o MiMiirs
I.SUOO V/MJN
U.5S50 M/MIN
I il. Df GRF ES i:tM 1 GRADE
l.ua G/t"5
I ii. DEGREES CENT TI.HADE
i.l V N-^iN/c.-rv,
1 6i. DFGREFS CFNT IGHADF
O.^bSO M/min
51. N-MIm/m'i
1?3. DEGREES CEM1GRADF.
2A.0 G/M2
SPECIAL PROGRAM INSTRUCTIONS
MAX NUMHER OF CYCLES MODFLED 20
ACCURACY LFVFL 0
TYPF OF RESULTS REQUESTED SUMMARY /
FRACTIONAL AREA CLFAnF.D' AC 0.06
-------
TABLE R-2 (continued)
CALCULATtn VALUES
INLET DUST CUNCF NT RATION l.U
-------
TABLE B-2 (continued)
HFSULTS (JF HAGHQUSE ANALYSIS
SUUIHfttST PUBLIC SERVICE'- I Urt LOAD DATA
F t)w
. () 0 MINUltS ITERATION, CrCLL MUMHEM
\?
AVE w A(|F PE Nt TWA I [ffi =
AVERAGE PRESSURE DRUP =
AVERAGE SYSTEM FLlJwr
MA X IMt/M Vt NE TRA T I(JI\i =
MAXIMUM PRESSURE DROP'
T.h?t-03
^ i? i . 9 1 f*/Wi
U. 7 N/M2
AVERAGE SYSTFM f LlJws 0.4SJ0 M/M1N
MAH JMUM PENFTRMI(JN = S.SIE-03
MaxiMUM PRESSURE DROP* US6.34 N/M2
-------
TABLE B-3. SOUTHWEST PUBLIC SERVICE SIMULATION - HIGH LOAD - SE = 25 N-rain/m3
SU*MAHY UF IN^U! DATA HIH HAGHIJUSE ANALYSIS
SUUTHflEST PUBLIC St«V IC t - HIGH LOAD DATA
HASIC DESIGN DATA
NUMRfcH OF CUMPAHTMENIS
CUMPARTMtM CLEANING TIMF
(CJFF LINE TIME)
CLEANING CYCLE TIME
CONT]NUOUSL Y CLEANED SYSTEM
HfcVEKSE FLO* vILUCHY
OPERATING DATA
AVERAGE FACE VEIOCITY
GAS TEMPERATURE
INLET OUST CONCENTRATION
Mt ASURE D AT
FABRIC and dust PROPERUtS
SPfCIFtC RESISTANCE, K<>
MEASURED AT
tFFECHVF RESIUUAL DRAG, SE
MEASURED A]
RESIDUAL LOADING, wN
I H.O MINUTES
1 . bUOO • M/N IN
0.7960 M/M|N
16S. DtGHFES C h N 1 1 (, K A I) V.
X.9H.O G/M?
SPECIAL PROGRAM INSTRUCTIONS
MA X NUMBER OF CYCLFS MriDFLtD ?0
ACCURACY LEVEL 0
TYPE OF RESULTS REUUESTED SUMMARY /
FRACTIONAL AHEA CLEANED, AC 0.09
-------
TABLE B-3 (continued)
LALCULATtD yflLUIS
lNLtT DUST CUMCtMRAH'JN 2.9U b/Mj
CUHWLCTfD TO UHt HillNt TE*HfcWArUWfc
FflyHlC A NIJ Dusr CAM PkPPEftT I ES CLtWWeCTED h UH UAS VISCOSITY
SPECIFIC CAKE. kLSISTAMCL, k<> 3.4P N-MiN/G-r"
EFFECTIVE DH A(,, SL HO. N-mIU/mJ
F HAC 1 I (> N A L A WE A CLEANtl),
f1 ME JNCHEMENT
SYSTEM CONSTANT w»
0 .09
O.SO
0 . 0
MNUTKS
G/M2
-------
TABLE B-3 (continued)
RESULTS UF HAGHUUSF AMALYSIS
SUUTHrtEST POHI 1C SEKVlCt - MI li H LUAO PA1A
ruw r'M.OI) HlNUItS OPFRATiriM, CYCLE WUMULR 10
AVERAGE PF W T R A I J ONs b.9SE-0i
AVERAGE PHESSURE l)RUP = 1U2H.OV N/M£'
AVERAGE SYSTEM FLCJhs 0.89U0 M/MI N
MAXIMUM PENT THAI [UNl 1.0«E-0f?
MAXIMUM PRESSURE DROP = 1561.23 N/M2
MJW «J8.00 MINUIES UPEHAT10N, CYCLE MJMbtR 11
vo • AVERAGE PENETRATIONS S.BbE-Oi
LaJ
AVERAGE PRESSURE DROP = laOS.Sl N/M2
AVERAGE SYSTEM FLl)w = O.H9UO M/MIN
maximum PF NC TRA T I UMr I.01E.-01
MAXIMUM PRE S 5 U R E [)RUP = lb?
-------
TABLE B-4. SOUTHWEST PUBLIC SERVICE SIMULATION
yu^AWY UF iN^ur DATA Fu^ t) at?M|JUSt ANALYSIS
SMiJlHrtfcbl PUblll SFWvlLt - L> I U ^ L< • a I lul#
BASIC DtSlC.N DATA
f\JUMrtF H UF CUMPAMMFUTS )u
CflMPAr! I>if fgT C I ( ft M 1 IJ U llMf 1.4
(UFF LIMC ll'^n
C L F A M 11 j (, t'YCLL 1J*'F f>a.u
CllNT I NUUUSL Y C L L A N t L) S Y S I t.M
HFVtWSt FLOrt V t L UL I I Y I.SU
OPFWAriMt; DAT ft
A V t ^ A 0 K FALt VtldCllY O.tirf/u
GAS ltvHtWAHJKt IS/.
INLtt DUS1 CUNLtN! HA I 1U>M S.bn
MtASUHtU A I lb/.
FAflwJC A'JO UU S 1 ^WUF'F.n I 11 3
SPtClKIC WFS151ANCL, i.rw
MtASiJKtD Al lb/.
0 . 711
tFFtenvL HtSlDUAL OkAG, Sf It1.
MtA.StJMH) A 1 lb 1.
Kf-SIDUAL L11A L) 1 1-.K r'8.0
SF'tCIAL 1 Mb I KlJt 1 1 UNS
MAX NUMBtW UF lYCLFS M(jL)fcLF.l) tH'
ACCUHACY LFV6L 0
TYPfc I )F frt.bULIS KtUUtSUU Jilji-'NAKY
FKACIIUNAL A k t A CLtANtO, AC:
0 . 1 d
MEDIUM LOAD - NO VELOCITY EFFECT ON K2
M11L S
1; .1.11 K S
K. / M 1 l\J
M / K | to
J11» W fc t ,S LfiiMiaKAul
(../Mi
UtbHtt S CFM ll.KADt
I'J - "1 I >M / G - "1
UtbtfF. fc.5 Lt^'lb^Aut
M / M 1 l\i
(VI - |V< 1 H / M 3
OFGKtES CFMIGKAOF
-------
TABLE B-4 (continued)
1. ftLlULA rtl* VALUES
iNLt! DUST CUNCtNlKAUOM i.SB G ~ Mi
COHKtCTEl) IU OPfcHflllKiU !£MP£»ATURK
~AbrtlL 4 ML) UUS1 CAKt HHOftKlJiS CUWHkUEU ~ 0* MS K ] 5L"US I T Y
SPECIFIC CAKt WfcSlSTAMCL, *2 3.B7 N-rflN/G-.M
EFFECTIVE UW fiG , 5E 1 u U . im-m i /g/w J
FHfiCUUMAL AREA CLtfl'vtU. AC <». 1 i
TIME INCHEMEN1 (J.SO , f'lMJltS
ST SI LM CON31ANT «* (>. ii U/»£
-------
TABLE B-4 (continued)
HtSULIS UF BAliHUUSt ANALYSIS
SUUlHrttST PUBLIC SERVICE - MEDIUM I.OAO UAlA
F UH
«?tt.U0 t*I MUTES uPFWOTIUfJ, CYCLE 1-iUMHEK
1 0
AVERAliF
AVEWAGE
AVtRAlit
A X 1 V||
-I A X ImiH
F>E'Nf I RAT 1 CM =
kktSSljwt liKUf:
SYSIt^' FLO* =
PET.'t 11.' AT li'J =
K " t SS>U >< E l' f-i I > k-' ¦
7. W - 03
10i/ i*i ,>
vO
E UR
28.00 MINUTES ijPEHATIQN, CYCLE NijMbtH
1 1 '
AVERAGE
AVEWAUE
AVE H Af.F
^ A X I '"1 Li M
MAX IM(J*
KENE lK/\ I ItjNs
i'wf.ssuiiF nunc:
.SY S I t K F I. (H. s
F»t NE I HA I l()Us
F'NEiiSUHE UWOP:
7 . iPE-t) 4
1 0 I ft .
0 . / rt SII
I . OPE-OP
1nno. hn
N/M?
'VI/K I fM
EUR
28. 00 MJMIJTE.S LlPERAI lU.v. CYCLF NlMHEw
1 ?
A V E H u bt
A vt^Al.t
AVE*A(,t
MAXl^UN
MAX IMIj*
Nt 1 ^ a T I i !¦< =
HWESbl'Mt l HU-1:
b Y S 1 E^1 FLun =
PE ME 1 KA1 111fsi =
PriESSUHE DK(IH:
, P /E-u i
0.7 HiO
, 0 1 E - U P
11) 7 4 . 9 1
m/^P
.M/MIN
N/NV
-------
TABLE B-5. SOUTHWEST PUBLIC SERVICE SIMULATION - LOW LOAD - Sg = 300 N-mln/m3
suMM«wr of input data foh bAuHuust analysis
SUti T H.its I HU^LIL SlkvlLl- LUw LUAD DATA
bASIC DESIGN Data
— — '¦HIMHfcN OF L THf I b • - 44-
CHWPAwTwitM ILLAMNt I I Ml 1.9 MINUTES
CUFF LIM HMD
CLfc*w*NG OClfc 1 1Mb MJHUIH-&
C(JNf INUUUSL* LLlANll) SYSTEM
WE VfcHSfc F-LUw VlLUtllY l.bUOl) ' M/MIN
UHIWAI1NG l)A I A
A VlH A Gt l-ALfc VtLIJLI !» O.ibSU M/MlN
INLtI DUST CONCENTRATION
MEASURE D AT
i yi,
i.HU
I 31.
—lit &KI £ S-C4-W1 I tw A ufc
G/h J
UEGRfcES CENTIGRADE
FAbrflL ANO DUST PWOMEMItS
S M t F11 H AM t* Ki
MtASU^fcD AT
- 1,3 1
133.
0.3b50
Mi.
^e.o
DEGREES CENT 1 GRADE
M/MJN
W-M1NVG-M
tfriCTlVt HfcSHiUftL UBAI.. St
MlASUWIU A I
his I dual loading, k*m
N-M1N/M3
UtGHtF.S CENT 1 GR A Dfc
G/M*!
3PLC1AL PHUGRAM INSTRUCTIONS
MAX NUMHCW -OF- C*U.£SMOOtLtft
ACCUWALt LtVEL
IYPE UF" HlbUL'S WtUUlSTtD
ZfX
0
SUGARY /
FRACTIONAL AREA CLEANED, AC 0.06
-------
TABLE B-5 (continued)
LALLULMtO MALilLS
t-MLfr-t-BUSI CUME*UMA I Km - - -— - 4/m±
CUHHLttHJ ru U^l K A T 1Nb ItM^tWAFUWt
fitwt AW- tWil tAAt PnuPiWl CUKKlCltU tUMUS
SPtClFIC CAKt KLSISTANCF, K
-------
TABLE B-5 (continued)
iH+t T s UF H*GHtwSf- ***1 y SIS-
SUUTHwFST PUBLIC StWVlCt- LU* LUfll) DATA
r
*u-<
dt».UU MlwtKfctt yPfcHAHU^r— e-KLt^NUMHfc-H-
-H —
AvfcHAGt PtNtIHAUUN =
AVtRAbt Pf8 . 00 M1NU1L3 UPEHATIUN, CrCtt NUMBfcK
1E-03
tiZMZ-
0.4510 M/MIN
3.66L-03
-------
TABLE B-6. SOUTHWEST PUBLIC SERVICE SIMULATION
OF iNPut DATA M)W HAGHCJUSt ANALYSIS
SniJlMrttST HUritlL t> t K V ILL - MIDIU* LUmD DATA
H6S1L DESIGN U A T A
t^PAHtMfc-haS-- —¦ \li--~
LuMPAKlMtM L L t A rj I !j I, llMt 1 .
( U»- f- L I Is-1 11 ML J
bfcR44-Ukt
1 NLt-T IIUSI CUNCtNTHAUUN
MtASUHtl) AT
f-AetHlC and UUS T PrtUPEwTIES
(>. to H 7 0
1^7.
lb/.
!>^fcCiUC Kt.SlSI ANIL, M
MtASUNtU A I
I,til
I *>7.
0.6070
MfASUHfcU A I
Ht S IUIIAL LUAU IhG» nK
1 "37.
-------
TABLE B-6 (continued)
LULCULAItU VALUf-S
fc-l-W A4- f(jw -
ClJWrVtCltU III UHhKAIllvJU IL'iPtKAIUKt
t»/M4
SPECIFIC CAKt WtSISTAHCEr K£ i.bb
--W+AUT-- at- - —aH4>, -
N-M1N/G-M
N-M4N/M^-
—AHfe A- HUHyf AG-
TIMt INCWfcMtr^l
-0.
0 .SO
MINUTES
srliFfcM coms U:\il w«
0. 0
b/M^
-------
TABLE B-6 (continued)
wfriH+t JS t+f hAKm<«jS+ ami YSIS
SUUlHrttar PUHLIC StHVlLE - MtUIUV LUflU U A T A
1-tH M}ivu?t{>-tif4rHfc-fftHyT i *ttfc • 10 ^
AVEHAGL HI Nt T K A I i (JN= *.7^-03
iVLHAl.t PHLS5UWI UHUPs JOUfl.lb N/M2
H-0»»
H MIH4Ilim: S.OiL-O.i
MAXIMUM PRLSSUKh lJtH l)HUP = lUHu.hB N/Mt?
AVLNA(,l SrSIEM HlJh= O.7M0 M/M1N
- . MAXIMUM Wfc-QA -
MAXIMUM PNE3SUWE UHUP = 1JU7.U0 N/MiJ
fUH e!8,00 "MUIES UP t H A 1 I UN. CYCLE NtlMHEH I {
AVE^Al.t HLNLIWAUUIv= i. 77E-03
_ ._ - _ AvEJiAl»i_-HMtS^UHL UKUPi |l>Hj».7h N/MP
A VE H A l»E SYSTEM FLUW= 0,7810 M/M]N
MAXIMUM PENE THATIUN = 5.01E-03
MAXIMUM PHtssuiH- nmips : naa.M N/Mj>
-------
TABLE B-7. SOUTHWEST PUBLIC SERVICE SIMU1.ATION - HIGH LOAD - Sp = 300 N-min/m
SUMMAHY of- input U A T A F OH bftC.HUUSF ANALYSIS
* A*****.*-*-*-*-***-**-**-* •»•*•***.**•* ***»***•• ».•*••***** A * * *« A # *
SUulMrttSI PUbLIL Sfc w W I L t - HII.m LUAU Ij A I A
HASIC DtSlGN DA1A
HUHBfcH Of T*t*IS 14 -
LUMP Ah I Mt N I CLI AMNb I | Mfc l.s
lUFk L I (Mf I 1Mb )
— LkfcA*±*G-fc-*-tLfc n«t <;*.«
CUNTINUUUSLY (.LEANEU SYSTEM
KtVtWSL FLUW vELUCITY l.bUOO
MINUTES
MlWUjtS
M/MIN
L)Pt W A I |NC> OA I A
Avk HAGk V flCt Vk. LUC 1 I Y
t»AS J-t MV4-UA4 UHi
INLET OUSf C LlNC E N T H A T 1 UN
ME ASUHtU A I
f-AHKlC A i\J U IJIJ3 I HWUPtMlES
U./WHO
-iob.
16b.
M/MJN
UH*KfctS fci.-fr4-H.KAUt,
G/M3
OE&ktES CENT ICkADE
ME ASUS t U AT
-fctf tCH-V£—k£31»UAV-Ultiu;» SL
MEASUHtU A I
Hf 5 I DUAL LOAU1MU, «H
I fcb.
o. 7«»ao
1 hS.
?H.O
tti»M jlM /l>M .
DEUHEES CENT1GHADE
M/M1N
N-MIN/Mj
UI G H E E 5 CENT1GWAUE
G/M£
SPECIAL PRUGRAM 1NSTHUCI1UN3
MAX- NI1MBLW Uk- CvriFS MODELED
ACCUKACY LEVEL
1YPF Uh KtSULJS MEUUkSTLD
-20
0
summahy /
FRACTIONAL AULA CLEANtU r AC 0.11
-------
TABLE B-7 (continued)
C«LLuLflIt 0 vtLUk S
lAitf t cum:> mwahww— — -- »>.^« u/m j
LUW^tCH. D lU liPF Wfl I I "Mb 1fMptWATUMf
t ArtH JC AM) tKhS-l—4rA*fe **UJifck4It-it tOMkUItU > UK UAi- Wl —
SPttiHC t A K t HtSlSl ANCt. K 2. i.U6 N-HIN/U-M
fcft-t C + l^e-»WAfcT — - 4*1 ,- -
+-KAG I lUHAt A«trA- -trttAM-U, - AC
TMt INCHEMLNT
SI 'S 11« IIINS I Aim I **
u. n
o.so
u. a
MINUTES
b / M i
-------
TABLE B-7 (continued)
WfcSULis o*~«AtHuyst analysis
SUJTMHtSI PUHLIC StKV ICE - HIGH LUAU DATA
«, At-..
MAXIMUM HtNt'WAT1UN= U.Bot-Ul
maximum ~'KtSSUME UHUH: 17* =
J'tNt l-KA 1 lUJUS—
HWES3UHE DH0f=
16IV.3B N/
0.H«»«0 M / M 1 N
1711.78 N/M2
f UN
dH.OU MlojUItS UHtNAdUN, C*CLt UU*btN
1ENt 1HA I llJNs
AWLHAUt P-KLSSUttl UHUHs
AwtHAtt SYSTEM FLOws
MAXIMUM HENtTHATlUNa
-MAJtlMUM PHESSUWt DHUKS-
U.«?9E-03
—1610.ai H/m _
O.dtUQ M/MIN
«.7«»E-03
UOUiU-M/Ma
-------
TABLE B-8. KRAMER STATION SIMULATION - TEST S
SUMMARY Uf INPUT l»IA ~ UH BAGHUUSfc. ANAIES-IS-
KNAMfcH - UNIT 2 - TfcST
DATfc 7/13/7V
BASIC DESIGN DATA
NUMBEK OF COMPARTMENT 3
GOMWW*+M€*U--€ttAWt~1 l«fc
(UFF LINE I1ME J
CLEANING CYCLE TIME
-SY&TEM-
REVERSt FLUW VELOCITY
10
Ir*
U4.
-------
TABLE B-8 (continued)
CALCllLAl tl> VALutS
INLET DUST CONCENTRATION 1.57
OPERA TINT. tFMPKHATllHP - -
XJf L ^ i | "vJ I, M W 1 v ¦< C
G/MJ
o
vj
KABklC AND DUST CAKfc PNOHtWT I L5> CUHKtC TED FOH UAS VISCOSITY
SPECIFIC CAKE RESISTANCE, K2 5,06
EFFECTIVE DKAG, SE 761.
N-MIN/G-M
N-MIN/Mi
FHACTIUNAL AULA CLtANED, AC
0,52
TIME INCREMENT
QVO T CM rnilOTllNl
2. 85
n A
MINUTES
I1/M3
-------
TABLE B-8 (continued)
»»»*•»»*•*•••*****•••***•»**•* A* «
HtbULTS U* BAGHUUSE ANALYSIS
KRAMfe* - -UN I I i - «_UAIfc-/-/H/-7-9- —
P UH
] I 4 . d(J MjNUTLS UPEHATIUN, tYCLt NUMbEH
-A¥4-KAUfcPfcNtVKA-UUN- -
AVEKAGE PHE S3UKL UHL1P'
AVEKAGE SYSIE.M FLUH*»
MAXIMUM -PL fat I HAT 4 UN*—
MAXIMUM HHt SSUWt OHUf =
6,0 7-£*4J
7416 . bO N/M2
O.toO?1! M/MIN
UQ<*E-0i~ _...
N/M2
O
oo
HUH
Il4,i>0 MINUltS OPERATION, CYCLk NUMBEH
AVtWAGL
-AV£KAUt
AVEKAGE
MAX 1 MUM
MAXIMUM
HtNfcI HA 110N«
HHtSSUKfc QRUP:
SYSIEM FLU* =
HE NE(HAT1UN"
HhhSSUWF l)KUH:
6.07E-0J
7-U6 . Ud
0.607b M/MIN
i .o^E-oi
im.ii n/m2_
.FUK
—U«.
i T I QN«
CYLLE NLMhEH
a _
A VEN AGE PENETRATION"
AVERAGE PHESSUHE UKUP"
AVERAGE BY SILM F LUrtil _
MAXIMUM PENETH AT I(JN»
MAXIMUM PHESSUHE DHUP«
.Q7E-03
746.41
_.U^hJI7b
, Q9E-02
893. 11
N/M
-------
TABLE B-9. KRAMER STATION SIMULATION - TEST V
*U«MAK» UF~ IWUl DA I A i- Uk-BAUWUUSt A^ALJTilS
KWAMEH - UN 1 I d - ILSI
- DATE
BA31C DESIGN DATA
NUMtttH OF CUMPAHIMtNIS
(UFF LlNt HMD
CLEANING OLLt I lMt
V CLiANttf-iVSlfeN—
KEVEH3E FLUW VtLUCl I Y
10
— 1.4
1 1«.2
U,6000
minutes
M/M1N
AVENAOt FACE VELOCITY
GAS TEMPEWATuWt
iNLtr
MtASUHtU AT
f AtiHiC AND- OUST- PKOHttil 1E.S
SPECIFIC HES151ANLE, *2
ME. ASUHhU—A-I
EFFEC T1VE KtSlUUAL UHAG, St
Mt-'AftHHftt AT
KtSlUUAL LUAU1NI,, wH
o . a i o o
lbl.
-4.17—
163.
3.70
..._
O.blOO
3S0.
25„
M/M 1 N
ULGHLES CENT1GHADE
U/tti
DbGkEES CENTlGHAUt
N-MlN/G-M
ULt.Hb.LS CE-ftll 1 ijHADtu-
M/M1N
N-MIN/Ml
b6.0
b/M2
SPECIAL PHUGHAM 1NSTHUCI1UN3
MAX NUMOEH UF LYLLE3 MUUELED «»0
— ACCURAL t LEVEL U
TYPE UF Ht3uLfS NEUUES(tD AVEHAGE /
- F H Af 1 lllislAI AHf- A <1 f AMFnf AT 0.21
-------
TABLE B-9 (continued)
t^LtUL A I t L> V ALtJf b
INLL! OUS1 CUNlfcNIKAfIUN 1.37 U/MJ
CUH«4^TfcU--tU-U^6,MAHMV -LtMftKAJUJit
F AHK it ANU UUbf CAKt Kku^twilts CUKKtCltL) KUH UAS VlSLOSITf
SPtClHL CAKt KtSlSlANCtf 4.B9 N-MlN/G-M
tH-tdlVt UN A L> > St 7 3/, N-MiN/M3
u.«>i
i.B5
0.0
-------
TABLE B-9 (continued)
HtSUllS OF ttAGHUUSt ANALYSIS
KHAKLH --W1I-i - Ifcil - UATfc 1/^/ttO
•¦UK I 11,^U MJ^ulLS UPtHAl1U*, CYLLt NUMtttH |U
- — --- AVfcHAfct PfeNt-T-HAI IONS '
AvtMAGt PNfcSSUHE DWUP» i72.7«l N/H?
AVERAGE SYSTEM H.Uw« 0,4175 M/MJN
— - — - HAX-IMUM-Vfe-fcfc | RA-HfcM*« W
MAXIMUM HXtSSUHt UHU^= 70^,10 H/*2
t UK ll«,t!Q MINUTES UPEHAT 1U*, LYLLt NUMBtK II
AVEHAGE PENETRATIUNb J.J9E-U3
AVfcRAfc4-gKt.S9UHE OH OP* *73.15 N/M^_
AvEHAliE SYSTEM FLUMS O.Ul/b H/MIN
MAXIMUM PtNfclKAI lUNa S,69E-0i
--¦ ^ MAAi'ttyte HWt9SUKt llHU^s 704.42 N/M2
. I-UM- 11U.WU M414UIL& UPfcKAUUW, CJCLt NUMbbK —li
AVEHAUE PENE T H A TION = 3.i<»E-UJ
AVEHAUt PKE33UHE UHUP» *71,Mb N/M2
A*UiAUL-S*SU>l FXO«* : Q.aWS-M/MIM
MAXIMUM PENE THATIUNb 5.69E-03
MAXIMUM PKES3URE OKUP" 703,b
-------
TABLE B-10. KRAMER STATION SIMULATION - TEST A
6UHHAHY OF INPUT DATA FW BAGHUU8E ANAIY6I3—
KH4MEH - UNIT i - Ifc 3 T A - DATt 10/77
BASIC DESIGN DATA
NUMBER OF COMPARTMENTS
COMPARTMENT CLEANING TIME
10
-4-r#-
' MINUTES
(OFF LINE 11Mt)
CLEANING CYCLE TIME
CONUWOUSIY GLEANEO SYSTEM
SU.2
MINUTES
REVERSE FLOW VELOCITY
0,6000
M/MIN
OPERATING OATA
AVERAGE h ACE VELOCITY
GA9 TEMPfcWA T UHE
INLET OUST CQNCENTRATION
MEASURED AT
FABRIC ANQ OUST PROPERTIES
0.J800
1«9.
149.
M/HIN
DEGREES CENTIGRADE
G/Mi
DEGREES CENTIGRADE
SPECIFIC RESISTANCE. *2
MEASURED AT
J.70
N-MIN/G-M
DEGREE3 CENTIGRADE
EFFECTIVE RESIDUAL DRAG* SE
MEASURED - AT
O.blOO
350.
M/MIN
N-MIN/MJ
DEGREES CENTIGRADE
RESIDUAL LOADING, WW
bb.O
G/M2
SPECIAL PROGRAM INSTRUCTIONS
MAX NUMBER OF CYCLES MODELED 20
ACCURACY LEVEL —: fl_
TYPE OF RESULTS REQUESTED AVERAGE /
FRACTIONAL AREA CLEANED, AC Q.«07
-------
TAHT.E B-10 (continued)
CALCULAltU vALUtS
INLET OUST CONCENTRATION
CUHHECTbO TO OFEBAH NG Tt TM-
1.29
G/Mi
FAbHIC AND 0US1 LAKE PKUPEHTIES CUHHEC TEO PUH GAS VISCU3IT*
SPECIFIC CAKE KtSlSTANCt, K2 <4.78
EFFECTIVE DHAG, SE 720.
N-MIN/G-M
N-MlN/MJ
FHACT10NAL aula CLE ANt l)» AC
TIME INCREMENT
8V8TEM CONSTANT W*
0.07
1 .35
-Qi«-
M1NUTE9
6/M,?
LJ
-------
TABLE B-10 (continued)
t MA-44AA4A A * A A AAA A HAA-iAjUM-t iAAlJ 4
t iJAJlAftftl
RESULTS QF BAGHOUSE ANALYSIS
HHANE.R. - ml I 1 - TfcST A PATfc- 10/77-
h UR
54.20 Ml NU (E3 CJPfc RATION, tYCLt NUMBER 11
AVERAGE PRESSURE DROP"
AVERAGE SYSTEM FLOKh
MAXIMUM-
MAXIMUM PRESSURE DRUP =
525.06 N/M2
0•4025 M/MIN
638.01 N/M2
l-UH
54.20 MINUTES OPERAIIJN» LYCLE NUMBER 12
AVERAGE PENETRATION*
AVERAGE SYSTEM FL0n =
MAXIMUM PtNETHATlON"
MAXIMUM PRESSURE DROP*
1.8<>E-0J
S2I,S6 M/M2-
0¦4025 M^MIN
4.66E-03
bii .91 6L/X2—
-FJifi-
-S4„20 MINUTES OPERATION# CYCLE NUMBER IX
AVERAGE PENETRATION*
AVERAGE PRESSURE DROP>
AVERAUt- 3YST-LM FLOWS
MAXIMUM PENETRATIONS
MAXIMUM PRESSURE DROP'
3.88E-03
51H.32 N^M2
0.a025 M/M1N
U.61E-01
627.34 N/M2
-------
TABLE B-ll. KRAMER STATION SIMULATION - TEST 4
SUMMARY Uf INPUT DATAFUR BAGHUUSfc ANALYSIS
KRAMtR - UNIT 1
TEST
- DATS: b/7b
BASIC DESIGN DATA
NUMBER OF COMPARTMENTS 10
fHEW CLEANING TIME—— —1,-M-
{UF F LINE TIMt)
CLEANING CYCLE UME 114,2
GONTmuUUSt* CLEAN£t> S-YST-fcM —
REVERSE FLOW VELOCITY 0,6000
-MINUTE 8
MINUTES
M/MIN
OPERATING DATA
AVERAGE FACL VELOCITY
GAS TEMPERATURE
INLET &U8I CUNCENTKA4I-QN
MEASURED AT
0.Ib90
1«9.
-
1
-------
TABLE B-ll (continued)
C ALC UL A 'tl) VALUES
INLET OUST CONCENTRATION
rnHflFf TP O Tn HP£ RAT
w v i' " u v " l~ v I \J ' J' L"* * .
1 .69
G/M3
MHHIC AND OUST CAKt PHO^EHTIES CUHWECTED K OH GAS VISCOSITY
SPECIFIC CAKt RESISTANCE, K2 U.7B
EFFECTIVE DRAG, SE 720,
N-MIN/G-M
N-MIN/M3
FHACTIUNAL AKEA LLE ANEL) , AC
TIME INCREMENT
SYSTEM CONSTAH-T w«
0.20
2.85
: o.o-
MINUTES
— —
-------
TABLE B-ll (continued)
RESULTS OF HA&HUUSE ANALYSIS
— WMl J i « --GA T &--W/tt - -
EUK
ll_UA-
.NUMMLH U_
AVERAGE PtNE THAT IUN =
AVERAGE PRESSURE OHUP:
-AVERAGE—S-YST EM HQWs
£,B9E-03
<491. 78 N/^
^.Ibbb—M/MIN
MAXIMUM PENETRATION*
MAXIMUM PRESSURE DROP*
5.2/E-03
b 1 6 . f I
N/M?
-------
TABLE B-12. KRAMER STATION SIMULATION - TEST 5
-SUMMAii* -OF-lNPlM- PA-TA --F-UR -BAUHUU3L—AfltAiXS-13
KRAMtR - UNI I 3 - ItSf
- DA[E S/7B
BASIC DESIGN DATA
NUMBER Of COMPARTMENTS
COMPARTMENT CLEANING TlMfe
REVERSE FLOW VELOCITY
10
(OFF LINE TIME)
CLEANING CTCLE TIMt
CONTINUOUSLYGLLAN4P SrSTfe-M
I 1«.2
0.6000
MlNllTfcS
M/MIN
OPERATIMG PAT A
average face vtLOCirr
GAS TEMPERATURE
IMET OUST CUNCfcNTRAHQN
0.4600
1U9.
Q.69—
M/MIN
DEGREES CENTIGRADE
G/M3
MEASURED AT
1«9,
DEGREES CENTIGRADE
FABRICAND DUST PBOPfcRTIfcS
SPECIFIC RESISTANCE. K2
MEASURED AT
3.70
-25^-
N-MIn/G-m
nEGREF.S CFNT1GRADF
EFFECTIVE RESIDUAL DRAG# 3E
.MEAflURED AT
0.6100
350.
2 St
M/MIN
N-MIN/M3
nEGBEf.S CfWTICRADf
RESIDUAL LUADlNG, WR
56.0
G/M2
SPECIAL PROGRAM INSTRUCTIONS
MAX NUMBER OF CYCLES MODELED 20
ACCURACY LtDlL O-- - . -
TYPE OF HESULTS REQUESTED AVERAGE /
FRACTIONAL AHfA CLFANEQ, AC O.U : -
-------
TABLE B-12 (continued)
LAUCULATLl) vflLUtS
INLET DUST CONCENTRATION 0.69 G/M3
EWHKW-16 QPfc«ATI^G+t+tPEWA+yAfc- - — -
FABRIC AND OUST CAKt PROPERTIES CORRECTED FOR GAS VISCOSITY
SPECIFIC CAKE RESISTANCE * *2 «.78 N-M1N/G-M
EFFECTIVE DRAG, SE 720. N-M1N/M3
FRACTIONAL AREA CLtANtD, AC 0.17
TIME INCREMENT 2.85 MINUTES
- -&»8TEH CONSTANT— W - — — 0,0 &/M3
-------
TABLE B-12 (continued)
WESULT3 Of 0ACHOUSE ANALYSIS
*WAMfcM - UNIT3 • TEST—5—- t>ATE-%//ft--
K UM L 14.^0 MINUTES U^EHATION, CYCLE NUMBER 10
: AVWM^- PtWt WAl-lWs 1SE-01
AVERAGE PRESSURE DROP" 549,23 N/M2
AVERAUE SYSTEM FLOW* 0.467S M/M1N
_ _ . —— — HArX1WJM 11OW* —-
MAXIMUM PRESSURE 0RUP« 668.12 N/M2
hUR
11".20 MINUTES OPERATION, CYCLE NUMHER
ro
O
1 1
avera&e
PtNETRATION"
average pblssure PHoei
5.HE-03
547.S9 tUMj
AVERAGE SYSTEM KLOws
MAXIMUM PENETRATION*
-MAXIMUMPRESSURE ORQPS-
0,<467b M/M1N
6.68E-03
t»&S»
-------
TABLE B-l3. KRAMER STATION SIMULATION - TEST 6
SUMMARY OF INPUT DATA EUR BAGHOUSE ANALYSIS
i
KRAMER
UNIT 3 - ItST
- DATE. 5/78
BASIC DESIGN DATA
NUMBER Of- compartments
GUMP4 ATH€NT €itANING TIME
10
-4-*4-
MINUTE8
(OFF LINE TIME)
CLEANING CYCLE TIME 111.2
- GlfcA*€-U SYS44M
REVERSE FLOW VELUCITY 0.6000
MINUTES
M/MIN
operating data
AVERAGE FACE VE.LUC I T Y
GAS TEMPERATURE
MEASURED AT
ANO T IE-4-
0.5280
16b.
ibb.
M/MIN
degrees centigrade
g/ma
DEGREES CENTIGRADE
SPECIFIC RESISTANCE# *2
«tASU«tO-A4
EFFECTIVE RESIDUAL DRAG, SE
MEASURED AT
RESIDUAL LOADING, *R
3.70
-&*w-
0.6100
350.
—as»-
56. 0
N-MIN/G-M
DEftRfcta Cfciil IGHADfc
M/MIN
N-MIN/M3
DECREES CENTIGRADE^
G/M£
SPECIAL PROGRAM INSTRUCTIONS
MAX NUMBEH OF CYCLES MODELED 20
ACCURACY IfeVEl - - -ft ¦ —
TYPE OF RESULTS REQUESTED AVERAGE /
-fc-KAtTiOMAL AREA CLEANED, AC O.a?
-------
TABLE B-13 (continued)
CALCULATED VALlJt^
INLET OUST CONCENTRATION 2,82
MrW*fc«ATU«€~—
C/M3
FABRIC ANO OUST CAKE PKOHtWT ItS CUKHtCTED F-OR U AS VISCOSITY
SPECIFIC CAKE RESISTANCE K2 4.92
EFFECTIVE DRAG, SE 740.
N-MIN/G-M
N-MIN/MJ
FHACT1UNAL AREA CLEANED. AC
TIME INCREMENT
0.«7
2.BS
MINUTES
-------
TABLE B-13 (continued)
HtSULTS UF BAGHOUSE ANALYSIS
KWAMtW—4> - DA I E 5/78 ,
£75?-
VtfcETKATlUfcs i. 514-0 ft ,
PHESSuHE DHOP* 80i.«8 N/M2
SYSTEM FLOi** 0,5455 M/MJN
Ptfvife THAT lUNs 1.07E-02 -
PHESSUWt- DHUP = S79.B7 N/M2
I
PtNE THAT IUN« 5.51E-03 I
PRESSURE0HUP* _ . BO J.iB N/M2
SYSTEM KLUW= 0.5355 M/M1N
PENETMATlUNs 1 .07E-02
PRESSURE- HHJJE= 9 7*-*iil-Ji/M2
EO* _ nu.jn mtmiitps npmtrmM. tYfi t- numher a ..
AVERAGE PENE THAT10N= J.51E-03
AVERAGE PHtSSUHE DHClPs 803.3fc N/M2
A.V.E HACit- SYS^M f LU *t£_ CU5 iSb My.M IN
MAXIMUM P6NE THAT IQN« 1,07002
MAXIMUM PRESSUHE DHUP« 979,56 N/M2
turt wi.20 mimutes upewajiun, cyclt ivumbew b
-- - - AVfcUAWE-
AVEHAGE
AVERAGE
- _ - MAXIMUM
MAX 1M U M
FUW 111.20 MINUTES OPERA TIUN# CYCLE NUMHEW /
to AVERAGE
^ _ -AvERAGE-
AVtWAUE
MAXIMUM
. . ; MAXIMUM
-------
TABLE B-14. KRAMER STATION SIMULATION - TEST U
SOMMAH* OF
. YSJ-5—
KRAMER - UNIT a - TEST
DATE //13/7 AC
-------
TABLE B-14 (continued)
L ALLUL A 1 tLl V fllUl i
INLET OUST CONCENTRATION 0.92 li/MJ
£UH*tG?fcE> T9 OPL+UVMNG- IfcWPfeWATlWt— r
^ A HH L C ANU DUST CAHt HHUPt K T IE S CUHKtC I E D F (JK OAS VISCOSITY
SPECIFIC CAKt RESISTANCE, K«? 5,2« N-MIN/G-M
EFFECTIVE DKAb, 3t 7tJ9. N-MIN/M3
f-KACflUNAL AHEA CLtAf^EU. AC 0.<49
TIME INCREMENT 2.85 mjnoTES
0,0
NJ
<*n
-------
TABLE B-14 (continued)
RESULTS OF BAGHOUSE ANALYSIS
KRAMER - UHi-T » - Tfc61
DATE 7/13/79
FUR 102,70 MINUTES OPERATION# CYCLE NUMBER b
: AVERAGE PfcNfcTRATION*
AVERAGE PRESSURE DROP*
AVERAGE SYSTEM FLOW"
-HA-X4MUM pfeNfcTHAUOft«
MAXIMUM PRtSSUHE ORUP"
fc.O^fc'Oi
704,77 N/M2
0.5646 M/MIN
6.8IE-03
790.71 N/M2
FUR 162.70 MINUTES OPERATION, CYCLL NUMBER
FOR— 182.70 MINUTES OPERATION. CYCLE NUMBER
7
AVENAGt PENETRATION* 6.04E-0i
AVERAGE PRESSURE PRUP* 70*1,71 N/M2
AVLHAlit SYSTEM FLUW® 0.S646 M/MIN
MAXIMUM PENt THAT1UN« 8.B1E-0J
MAXIMUM RRESSURfc DHUV 790.S» H/Mg
—8 : —
AVERAGE PtNETHATlUNs 6.0ME-03
AVERAGE PRESSURE OROP« 7Q4.70 N/M2
AVkRAGfc SYSTEM FLOW* —Q.bbttto M/MIN-
MAXIMUM PENETRATION- 8.B1E-0J
MAXIMUM PRESSURE DROP* 790.53 N/M2
-------
TABLE B-15. TEXAS UTILITIES - MONTICELLO STATION SIMULATION
ttXAS uULllltS - MijN I ILfcLLU blflNurv
BASIC DESIGN i>aTA
NUKbEK UF C UMPA N T MENIS 16
CUf*P-AH tMSw f CLEAHim*- -U^E —— «>.b WJJJU I-ES-—
( Oh V U 1 /.S MNUTES
—¦_—Cun I luuoJ^L i—LLt.6i.tu
kEvtWSt FLU* vtLULHY 0.0 M/M1N
lIPfcHt f INC. UQ Tfl _ _ _ _
UVtKflbL > fiCfc »t LUC 1 I V 0.77IJ0 M/M]N
(,AS I f•-iPtKA t UKt I'/'l. UEbKEES CEMltKAUt
- IiiLfc. 1 UUixJ L UftiC En f Kfl 1 JIUiii U/Mi
MEA3UKEU AT 177. 0EGIREE3 CENTIGRADE
f- AHH 1 C AM) nu.Sl PKIlHt-KHf-S
SHtlJh 1L HtSlSTAiaE,
1»U ASUttLu ft I
EFFECTIVE WtSIOUAL UkAG, SE
MLASUKLil—4J
HtSlDUflL LUAuJuli, rtK
1 .UO
0, t>50U
JSO.
-2h.
bu .0
N-MIN/G-M
M/MlN
N-MIN/M3
JJEGKE t S_££NI l_GfiAQ£_
SPECIAL f«U(ikAM IMSTHUCT IUIMS
^Al imu^oLK Oh CYCLES MuLiELEu til
Af.riihacy i tvf.i u
IrPt l>F HtSULTS HEuiitSlfcU AvENAtE /
-------
TABLE B-15 (continued)
L •• _ i. - I.' ¦ • i .r >
llNiLt.l L»IJS 1 lUlMCfc .v. I tV A I RliM lb. 10 l./Mi
l-t U- I u 1 Jul- I L^UA-1 UKt
hrti»Klt /imi ;;Uj I I.Aft I 11 5 Li.jKkf.Lltu vlSLUbll*
bPhCIML CtKt HLblblAuLt. * k t £ L 1.1 « i'«t i'» ''L 0 , JtT
I 1 "it i iv L N K. v> L iv 1 (J.9li M]MUrt5
-------
TABLE B-15 (r.ont i.nue.d)
'to ill.T 'it- (Ul.nl uoL "I- Yolo
i i i i I i ( ^ - 1 I.J' j I ilCLLU b I - t • ; ¦ 1 ' . ¦ r' :
] Mb . (*>
D . / 7 0 <> m / M i i*j
b. I6t-Ui
1 4 u s . 1 1 f I / " d
LH
ti/.b U |J .'! Il'j • Jt'f h « I J i • -I, •¦Ij-'UtK
/
ii v t u 01 ( i t L 11< ii I [1 M.' ~
AwLKAbt KKLbotiKL
u j t K « L> I- 5 * o I I ! r i i • =
x 1 u ' ~ h lit. if-" I J i.i-s
• A A i i'U - hit bJUnL L.!nUK-
r1 . Utit-il i
1 Mb . 4 1 N/ I
11. / / u u ^ / '"i 1 i
"> . 1 ') t - u i
i 'wb.'jo i /." /¦
Liri
fa/.bU \ii.U 11 b-UF tn a J.4 LhJ, . LiCLL iiL'riCLh
h V f" w M I. K P f i 11 I K (V I 1 I , —
U V t O t. ^ * t- b b I / * t I} ^ I.' -
A V L H A L> L O r b I L •: h L lj n -
•iiU'vi h K i'k- I h 6 I i tjU =
.. 0*JM(jr-i h H t S S> IJ K fc. jfrUH:
^ . >J O t - l» J)
I •' $ H . 11 S
l' . t / UIJ
t! . J t, f. - 4
Mu'j . / I
,/i V
"/"•J
I
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing/
1. REPOR" \0 2.
EPA-600/7-B0-157
3. RECIPIENT'S kCClte&iur* NO.
PB fiO 214182
A TITLE AND SLBTiTLE
Fabric Filtration Analyses for Three Utility Boiler
Flyashes
5. REPORT DATE
Sept. 1980 Issuing Date.
6. PERFORMING ORGANIZATION CODE
7. A U T HO R (S)
H.A.Klemm, J.A.Dirgo, and Richard Dennis
8 PERFORMING ORGANIZATION REPORT NO.
GCA-TR-80-37-G
9. FERFORMING OROAMIZATION NAME AND ADDRESS
GCA/Technology Division
213 Burlington Road
Bedford, Massachusetts 01730
10. PROGRAM ELEMENT NO.
EHE624A
11. CONTRACT/GRANT NO.
68-02-2607, Task 35
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 PE R LOO COVERED
Task Final; 6/79-5/80
14. SPONSORING AGENCY CODE
EPA/600/13
is. supplementary notes Project officer James H. Turner is no longer with the Agency; for
technical details, contact Louis Ho vis, IERL-RTP, Mail Drop 61, 919/541-2^25.
i6. abstractreport gives results of fabric filter analyses of flyash from three util-
ity boilers. A major aim of the program was to augment the present data base for
modeling fabric filter systems designed to control inhalable particulate (IP) emis-
sions from coal-fired boilers. Emphasis was placed on the determination of K sub 2,
the flyash specific resistance coefficient, and a sub c, a parameter describing fab-
ric cleanability. Fabric filter design, operating, and performance data were analy-
zed with the assistance of utility personnel from Harrington and Monticello stations
in Texas and Kramer station in Nebraska. Supplementary laboratory determinations
of K sub 2 were made for flyash produced by the three plants because K sub 2 could
not be estimated from field data alone. Based on laboratory tests, it was determined
that flyash surface deposits underwent negligible porosity changes for fabric pres-
sure losses <2000 N/sq m. Also, a simple field procedure was developed to measure
K sub 2 directly with the aid of heat-resistant membrane filters and a Method 17 in-
situ sampling probe. Detailed analyses and modeling trials indicated that K sub 2 and
a sub c estimates developed from routine compliance or acceptance tests were too
rough for dependable modeling, although providing uselful guidelines. Laboratory-
estimated K sub 2 was 0. 89-3. 79 N-min/g-m; a sub c was 0.01-0. 52.
17. KEY WORDS AMD DOCUMENT ANALYSIS
a DESCRIPTORS
b.IDENTIFIERS/OPEN ENDED TERMS
c. COSATl Field/Group
Pollution Analyzing
Fabrics Mathematical Models
Filtration Sampling
Fly Ash Measurement
Boilers
Utilities
Pollution Control
Stationary Sources
Fabric Filtration
Utility Boilers
13B 14B
11E 12A
07D
21B
13A
13. DISTRIBUTION STATEMENT
/
Release to Public
19. SECURITY CLASS (This Report)
Unclassified
21. NO. OF PAGES
20. SECURITY CLASS (This page j
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
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