United States
Environmental Protection
Agency
Municipal Environmental Research
Laboratory
Cincinnati OH 45268
EPA-600/2-80-131
August 1980
Research and Development
Control
Strategies for the
Activated Sludge
Process
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
gories were established to facilitate further deveJopment and application of en-
vironmental technology. Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The nine series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
6. Scientific and Technical Assessment Reports (STAR)
7. Interagency Energy-Environment Research and Development
8. "Special" Reports
9. Miscellaneous Reports
This report has been assigned to the ENVIRONMENTAL PROTECTION TECH-
NOLOGY series. This series describes research performed to develop and dem-
onstrate instrumentation, equipment, and methodology to repair or prevent en-
vironmental degradation from point and non-point sources of pollution. This work
provides the new or improved technology required for the control and treatment
of pollution-sources to meet environmental quality standards.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
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CONTROL STRATEGIES -
FOR THE
ACTIVATED SLUDGE PROCESS
by
Thomas K. Keinath and Bryan S. Cashion
Environmental Systems Engineering
Clemson University
Clemson, South Carolina 29631
Grant No. R864357-01-0
Project Officer
Walter W. Schuk
Wastewater Research Division
Municipal Environmental Research Laboratory
Cincinnati, Ohio 45268
MUNICIPAL ENVIRONMENTAL RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
CINCINNATI, OHIO 45268
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DISCLAIMER
This report has been reviewed by the Municipal Environmental Research
Laboratory, U.S. Environmental Protection Agency, and approved for publica-
tion. Approval does not signify that the contents necessarily reflect the
views and policies of the U.S. Environmental'Protection Agency, nor does
mention of trade names or commercial products constitute endorsement or
recommendation for use.
n
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FOREWORD
The Environmental Protection Agency was created because of Increasing
public and government concern about the dangers of pollution to the health
and we.lfare of the American people. Noxious air, foulj water, and spoiled
land are tragic testimony to the deterioration of pur natural environment.
The complexity of that .environment and the interplay between its components
require a concentrated and integrated attack on'the problem. "
Research and development is that necessary first step in problem
solution and it involves defining the problem, measuring its impact, and
searching for solutions. The Municipal Environmental Research Laboratory
develops new and improved technology and systems for the prevention, treatment,
and management of wastewater and solid and hazardous waste pollutant discharges
from municipal and community sources, for the preservation and treatment of
public drinking water supplies, and to minimize the adverse economic, social,
health, and aesthetic effects of pollution. This publication is one of the
products of that research; a most vital communications link between the
researcher and the user community.
\
The automation of wastewater treatment plants has been considered for
many years. Yet the state of the art in this area is today still in its
infancy. Only very rudimentary control strategies have been implemented in
wastewater treatment plants to date. The research reported herein'focused
on evaluating the performance benefits that can be achieved through the
implementation of a process-level control strategy for the activated sludge
process.
Francis T. Mayo, Director
Municipal Environmental Research
Laboratory
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ABSTRACT
Strategies that are proposed for control of the activated sludge process
usually are designed to control either the mean solids retention time (MSRT)
or the food-to-microorganism ratio (F/M), or both. The focus of this re-
search centers on the last of the three alternatives. Therein, MSRT is used
to control the solids wasting and F/M is used -to control the solids inventory
distribution to match the organic loading to the aerator so as to maintain
a constant F/M level throughout the diurnal cycle.
Generally, three solids inventory control modes are possible. These
include: (1) simple control of the recycle flow rate; (2) control of the
recycle flow rate when provision has been made for a constant volume storage
chamber; and (3) control of the recycle flow rate when provision has been
made for a variable volume storage chamber. The first strategy is not
suitable means for controlling the large diurnal flow variations experienced
in most treatment plants. The last two strategies were simulated using a
structured model. The second strategy was also evaluated through a pilot
study conducted at the Blue Plains Pilot Waste Treatment Facility.
The pilot plant investigation was conducted in two phases. The first
was an uncontrolled study to establish base-line conditions. The second
phase was the actual application of the control strategy. Extensive data
collection allowed comparison of the two studies and evaluation of the
utility of the control strategy.
Based on the results of the computer simulations and pilot plant studies,
the following general conclusions can be made:
(1) Suspended solids that pass over the weirs of secondary clarifiers
accounted for a major portion of the total carbonaceous material
present in the effluent of the activated sludge process.
(2) Reductions in soluble organic material that were obtained by solids
inventory control tended to be offset by increases in suspended
solids passing over the weirs of the clarifier.
(3) F/M control had no overall net benefits for the range of process
operational conditions studied.
This report was submitted in fulfillment of grant #R864357-01-0 by
Clemson University under partial sponsorship of the U.S. Environmental
Protection Agency. This report covers an experimental period from October
1975 to June 1977.
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CONTENTS
Foreword , • • • • "iii
Abstract iv
Figures : V1'
Tables • ix
Acknowledgements . ,. x
1. Introduction • 1
2. Conclusions 2
3. Recommendations • 4
4. Control Strategies . 5
5. Dynamic Mathematical Model 9
6. Model Simulations 11
Control case A • H
Control case B 17
7. Pilot-Scale Studies 32
Base-Case study 33
PLI control study . 38
Comparison of controlled and uncontrolled studies .... 42
References . . . . ' 48
Appendices
A. Program Listing of Dynamic Mathematical Model . . . 49
B. Raw Data for Base-Case Pilot Study 60
C. Raw Data for Instantaneous F/M Controlled Pilot Study .... . 95
D. Raw Data for Constant Loading Pilo.t Study -." 132
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FIGURES
Number
Schematic diagram of the conventional activated sludge process
Page
6
1
2 Schematic diagram for an F/M controlled activated sludge
process ......:................ 6
3 Schematic diagram for an F/M controlled activated sludge
process with a variable volume storage basin .......... 7
4 Schematic of the structured dynamic model . 9
5 Influent total organic carbon vs. time (profile) used for
simulations 12
6 Simulated actual MLVSS and desired MLVSS vs. time; storage
volume = 10% of the aeration volume 13
7 Simulated actual MLVSS and desired MLVSS vs. time; storage
volume = 50% of aerator volume 13
8 Simulated actual MLVSS and desired MLVSS vs. 'time; storage
volume = aerator volume 14
9 Simulated process loading intensity vs. time; storage
volume = 10% of the aerator volume 14
10 Simulated process loading intensity vs. time; storage
volume = 50% of aerator volume .". . 16
11 Simulated process loading intensity vs. time; storage i
volume = aerator volume , 16
12 Simulated total BODU in the effluent vs. time; storage "••
volume = 10% of aerator volume ...... 18
13 Simulated total BODU in the effluent vs. -time; storage
volume = 50% of aerator volume ...;... 18
14 Simulated total BODU in the effluent vs. time; storage
volume = aerator volume . ..*..... 19
VI
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FIGURES (Continued)
Number page
15 Simulated soluble BODU in the effluent vs. time; storage
volume = 10% of aerator volume . 19
16 Simulated soluble BODU in the effluent vs. time; storage
vol ume = 50% of aerator vol ume 20
17 Simulated soluble BODU in the effluent vs. time; storage
volume = aerator volume 20
18 Simulated suspended solids in the effluent vs. time; storage
volume = 10% of aerator volume 21
19 Simulated suspended solids in the effluent vs. time; storage
volume = 50% of aerator volume 21
20 Simulated suspended solids in the effluent vs. time; storage
volume = aerator volume 22
21 Simulated actual MLVSS and desired MLVSS vs. time; storage
volume = 10% of aerator volume . . . .... . . . . . -.. .... 24
22 Simulated actual MLVSS and desired MLVSS vs. time; storage
volume = 40% of aerator volume . ........ ...• . ... .. . . . . 24
23 Simulated actual MLVSS and desired MLVSS vs. time; storage
volume = aerator volume . . . . , . . ... . ... ., ....... 25
24 Simulated process loading intensity vs. time; storage
volume = 10% of aerator volume... .... . . . ... . . . . . . 25
-• \ ' . .,
25 Simulated process loading intensity vs. time; storage
volume - 40% of aerator volume ............ 26
26 Simulated process loading intensity vs. time; storage
volume - aerator volume . . . . . . . . . . . . ........ 26
27 Simulated total BODU in the effluent vs. time; storage
volume = 10% of aerator volume ................. 27
28 Simulated total BODU in the effluent vs. time; storage
volume =40% of aerator volume ... .\ ... 27
29 Simulated total BODU in the effluent vs. time; storage
volume = aerator volume . , .... . . ...... 28 ;
30 Simulated soluble BODU in the effluent vs. time; storage
volume = 10% of aerator volume 28
vii
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FIGURES (Continued)
Number
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
Page
Simulated soluble BODu in the effluent vs. time; storage
volume = 40% of aerator volume 29
i
Simulated soluble BODU in the effluent vs. time; storage
volume = aerator volume ..... 29
Simulated suspended solids in the effluent vs. time; storage
volume = 10% of aerator volume
Simulated suspended solids in the effluent vs. time; storage
volume = 40% of aerator volume . • • •
30
30
Simulated suspended solids in the effluent vs. time; storage
volume = aerator volume ............. 31
Influent TOC vs. time for base-case pilot study with no
PLI control 34
Effluent TOC vs. time for base-case pilot study wi.th no
PLI control 34
Effluent turbidity vs. time for base-case pilot study with
no PLI control • • • 35
Effluent suspended solids vs. time for base-case pilot study
with no PLI control 35
Efflueat.volatile suspended solids vs. time for base-case . ,
pilot study with no PLI control 36
Laboratory measured'effluent TOC vs. time for base-case
pilot study with no PLI control 36
Laboratory measured effluent soluble TOC vs. time for base-
case pilot study with no PLI control ........ 37
Influent TOC vs. time for PLI controlled pilot study . . 37
Effluent TOC vs. time for PLI controlled pilot study . ., 39
Effluent turbidity vs. time for PLI controlled pilot study .... 39
Effluent suspended solids vs. time for PLI controlled pilot
study •. . . .
Effluent volatile suspended solids vs. time for PLI controlled
pilot study
40
40
vm
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FIGURES (Continued)
Number
Page
48 Laboratory measured effluent TOC vs. time for PLI controlled
pilot study . ........ . ..... , ......... "• .• 41
49 Laboratory measured effluent soluble TOC vs. time for PLI
controlled pilot study .................... • 41
50 Logarithmic frequency distribution domain for effluent TOC
for base-case and PLI controlled pilot studies ......... 43
51 Logarithmic frequency distribution domain for effluent TOC
(laboratory) for base-case and PLI controlled pilot studies . . 43
52 Logarithmic frequency distribution domain for effluent TOC
(soluble laboratory) for base-case and PLI controlled
pilot studies ................ • • • • ..... 44
53 Logarithmic frequency distribution domain for effluent
(laboratory) for base-case and PLI controlled pilot studies . . 44
54 Logarithmic frequency distribution domain for effluent BODs
(soluble laboratory) for base-case and PLI controlled
pilot studies ..... ; .......... . -x ...... • • 45
55 Logarithmic frequency distribution domain for effluent suspended
solids (laboratory) for base-case and PLI controlled pilot
studies ...... ....... ............... 45
56 Logarithmic frequency distribution domain for effluent volatile
suspended solids (laboratory) for base-case and PLI controlled
pilot studies . . . . ..... .......... ...... 46
TABLES
Number . . Pag
1 Design and Operational Parameters for Pilot Studies ....... 32
2 Statistical Comparison of Two Experimental Studies . . ..... 47
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ACKNOWLEDGEMENTS
The assistance and cooperation of the operating staff of the EPA-DC
Pilot Plant is gratefully acknowledged. Mr. Walter W. Schuk of the U.S.
Environmental Protection Agency is especially recognized for his contributions
to the experimental phase of this study.
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SECTION 1
INTRODUCTION
The activated sludge process has become one of the most widely used
methods of wastewater treatment. Automation of this process may provide bene-
fits m the form of enhanced treatment performance. This facet, of course, has
particular relevance considering the performance constraints that have been
imposed through PL 92-500. If, for example, the performance of an existing
treatment plant could be upgraded and made more reliable through the imple-
mentation of process control strategies, to the extent that future performance
constraints can be met without installing additional treatment capacity, then
rather dramatic monetary savirigs would be realized. It is specifically this
concept that is the focus of the research reported herein.
Most control strategies that have been proposed for the activated sludge
process can be grouped under the general category of controlling the food-to-
microorganism ratio dynamically through biosolids inventory control while
maintaining the mean cell residence time relatively constant. To control the
F/M ratio one must be able to obtain information on the process status that
is timely and sufficiently specific to permit the initiation of automatic
control. Information required includes an index of the concentration of
organics present in the influent stream and an indicator of the concentration
of microorganisms. The COD, TOC, and TOD analytical procedures have been
used as indexes for the former while primarily only the volatile suspended
solids test has been used to provide an estimate of the latter, although ATP,
DNA and dehydrogenase activity have been proposed as surrogates. Andrews and
coworkers (1, 2) have proposed an interesting alternative control approach
wherein the specific oxygen utilization rate is calculated on-line and used
as an indicator of sludge activity in the initiation of automatic control.
This study was initiated to establish the performance benefits that can
be attained through the implementation of various PLI control strategies. The
study was two-fold in scope: (1) to mathematically simulate the performance
of an activated sludge wastewater treatment plant controlled by various PLI
control strategies; and (2) to experimentally evaluate one such PLI control
strategy on a pilot-scale.
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SECTION 2
CONCLUSIONS'
Based on the results of two pilot-scale studies the following general
conclusions can be made:
(1) Suspended solids that pass over the weirs of secondary clarifiers
account for the majority of carbonaceous material (as indexed by
BOD) present in the effluent of the activated sludge treatment
system.
(2) Suspended solids that pass over the weirs of secondary clarifiers
vary in direct proportion to the organic loading to the aerator.
(3) Because PLI control imposes hydraulic transients on the activated
sludge system, control itself serves to slightly degrade the efflu-
ent with respect to particulates even though slight benefits are
obtained with respect to soluble organic materials.
(4) PLI control appears to have no net benefits for the range of
process operational conditions investigated.
Moreover, the following additional conclusions can be made on the basis
of the mathematical simulations conducted as part of this research:
(1) The extent of PLI control that can be achieved in an activated
sludge system-that does not have provision for external storage of
biological solids is negligible. Meaningful PLI control can be
achieved only when provision is made for the external storage of
biological solids.
12) When a constant volume chamber is provided for external storage of
biological solids an optimum size of storage chamber exists. If
the storage chamber is too small, the extent of PLI control is
constrained by the lower limitation on recycle pumping rate.
Conversely, if the storage chamber is too large, then the extent of
control is constrained by the upper limitation on recycle pumping
rate.
(3) For the case in which a variable volume storage chamber is employed
for external storage of biological solids a minimum threshold
storage volume exists. All volume supplied in excess of the thresh-
hold value has no net control capability benefits
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(4) With respect to system performance the mathematical simulations
showed that, although the variability of effluent quality decreased
as the PLI was controlled more precisely at the set point level,
virtually no net benefits were noted relative to the total mass of
organics discharged from the treatment system.
(5) In general, the mathematical simulations compared favorably with
the experimental results obtained.
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SECTION 3
RECOMMENDATIONS
Considering the foregoing conclusions, the objectives of controlling an
activated sludge facility treating municipal wastewaters should be: (1) to
minimize the mass of suspended solids transported over the weir of the sec-
ondary clarifier and into the effluent, and (2) to produce a biomass that
thickens well such that solids inventory control options can be implemented.
To meet these objectives all control strategies should be designed to control
those biological and/or physical factors that influence clarification and
thickening. Only then can one expect to observe improved system performance
and stability as a result of implementing control strategies.
Before meaningful control strategies can be designed, however, it is
necessary first to define the causal relationships between the various bio-
logical and physical parameters arid their effect on clarification and thick-
ening. Only then can the master control variables be defined such that
effective control strategies can be properly designed for new plants or
implemented at existing plants for the purpose of upgrading performance.
Studies should be initiated, therefore, to establish the functional
effects of the following parameters on clarification and thickening: (1) mean
cell residence time, (2) hydraulic residence time, (3) aerator dissolved oxy- '
gen tension, (4) aerator dissolved oxygen profiles, (5) aerator hydraulic
regime, (6) contacting patterns, (7) dynamical characteristics of the influ-
ent, (8) clarifier overflow rates, (9) aerator shear intensity, (10) clari-
fier turbulence (bulk circulation). In addition to the usual measured
response variables, the following parameters should be measured to establish
the system performance causal relationships: (1)
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SECTION: 4 ;
CONTROL STRATEGIES
Biological solids inventory control is the objective of F/M control.
Generally, three solids inventory control modes are possible. These include:
(1) simple control of the recycle flow from the secondary clarifier to .the .
aerator, Figure 1; (2) control of the recycle -flow from,the clarifier to the,
aerator when provision has been made in the system for a'. zon&tant volume, •
biological solids storage chamber, Figure 2; and (3) control of the recycle
flow from the clarifier to the aerator when provision has been made in the
system for a valuable.'vohwe. biological solids storage chamber, ..Figure;3.,.-
In the descriptive discussion of the three control strategies that follows,
it has been assumed that both the aerator and storage basin have completely
mixed hydraulic regimes. This, of course, is not a requisite assumption.
In the first of the three solids inventory control strategies, the; : .;-;
clarifier is employed for the storage of biological solids. During periods s
of low diurnal organic loading, the recycle pump is controlled to decrease
the return flow to the extent that the clarifier is forced into a temporarily
overloaded condition. This results in a net transfer of biological solids
from the aerator to the clarifier which;is manifested in a decreasing MLSS
concentration in the .aerator and a rising "solids, blanket" in ,the clarifier.
Conversely, during periods of high organic loading,, the control algorithm .;.
calls for an increased recycle pumping rate which results in a drawdown of
the solids blanket in the-clarifier and transfer of the solids:to the aera-,
tor. ' • •• • -• ,. - , . ,;: . • ••. , ': .--.•.••..• : • • , . .
The .extent of F/M control available through application of-this control
strategy is relatively small. This is due to the fact that there are certain
physical .and biologi.cal limitations (e.g. denitrification.and sludge'settle-
ability) on the mass of biological solids that can be stored in and withdrawn
from the clarifier. It is important to recognize, furthermore, that it is
impossible to achieve any degree of F/M control if the clarifier is continu-
ously underloaded. Control can be achieved only when the clarifier is
transiently overloaded and underloaded through recycle rate control.
When provision is made for separate storage of biological solids, F/M
control can be achieved to a much greater extent than for the case when the
clarifier alone is employed for solids storage. If the solids storage basin
is of a constant volume, Figure 2, then F/M control is achieved through
control of the return flow, FR, using the control algorithm:
-------
F-F..
rw
Figure 1. Schematic diagram of the conventional
activated sludge process.
F-F.
W
F
So
•
Aeration
Basin
MFR
S
V
c
1 xe
' — E
Clarifier
^
fR
XS
Storage
Basin
R
^
E
fw
/^\^1
*o ^r^ V "R
R T T^ "•
1 1
Figure 2.
Recycle
Pump
Control
Schematic diagram for an F/M controlled activated
sludge process with a constant.
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Aeration
Basin
f+f
S
X
Clarifier
s
*s
V_^
Figure 3- Schematic diagram for an F/M controlled activated
sludge process with a variable volume storage basin,
dX
where,
XS - XD
and:
V- (Setpolnt F/M)
F = influent flowrate
FR = recycle flowrate
XD = desired MLVSS
Xs = storage VSS
V = aerator volume
t = time
SQ.= influent concentration of organics
S = effluent soluble concentration of organics
7
(1)
(2)
-------
For this control strategy the minimum allowable FK would be constrained such
that the clarifier would always be in an underloaded condition. The maximum
FR obtainable would be limited, of course, to the maximum available pumping
capacity. In this case, the total mass of biological solids in the storage
chamber would decrease through dilution as the solids concentration in the
aerator increases and vice versa.
Even more precise F/M control can be achieved when a variable volume
storage basin is employed in lieu of a constant volume basin, Figure 3. For
this control strategy FR. is set constant at a level sufficiently high to
ensure that the clarifier is continuously in an underloaded condition, while
FS is controlled using the algorithm given by Equation 1 with F$ substituted
for FR. Because FR and F$ are not equal, the volume of the basin used for
storage of biological solids varies throughout the diurnal cycle; increasing
during periods of low organic loading to the aerator and decreasing during
high organic loading periods. The concentration of biological solids in the
storage basin also varies; increasing during peirods of high organic loading
and inversely. The magnitude of the variation in concentration, however, is
significantly less than for the case in which F/M.control is achieved through
the storage of biological solids in a constant volume chamber.
Either of the two control strategies that make use of independent stor- ,
age of biological solids can be approximated by use of the step-feed modifi-
cation of the activated sludge process. In this case solids are stored near
the inlet end of the aeration basin and control is achieved by shifting the
influent feed point along the length of the aeration chamber in response to
organic loading.
Because the control algorithm given by Equations 1 and 2 was found to be.
unstable, Equation 2 was modified to .
v _ ,
AD V-Csetpoint PL I)
(3)
such that control is predicated on the basis of Process Loading Intensity
(PLI). All mathematical simulations and pilots-plant control procedures were
conducted using Equation 3.
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SECTION 5
DYNAMIC MATHEMATICAL MODEL
The basic dynamic mathematical model of the activated sludge process
that was employed for the current simulations was developed originally by
Bryant (3) and subsequently modified in succession by Busby (4), Stenstrom
(5), and Cashion (6). Since a complete and comprehensive description of the
model is given elsewhere (5), only a brief overview will be provided herein.
A complete listing of the computer program is given in Appendix A.
Generally, the model is structured such thctt any hydraulic and/or dis-
persion regime can be accomodated; from a completely mixed system to the
classic plug flow case.. -In addition, the dynamic model was formulated such
that any modification of the activated sludge process could be simulated.
For example, the conventional, step feed, or biosorption modifications of the
activated sludge process can be simulated by making only minor changes to the
basic model..
Aqueous-phase as well as organism mass balances were written for both
the aerator and the storage chamber, when applicable. Balances for the
aqueous phase were struck""for carbonaceous material expressed as ultimate
biochemical oxygen demand (BQDU), ammonia, nitrate, nitrite, and dissolved
oxygen.. Similarly, organism mass balances were written for the hererotrophic
population and the nitrifier organisms including Nitrosomonas and Nitrobacter.
It is important to note, furthermore, that the model was structured to include
four different solids fractions as shown in Figure 4. These include stored
mass (which accounts for both the internal and external storage products),
active mass, inert volatile mass, and inert inorganic mass..
Figure k. Schematic of the structured dynamic model
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All bio-kinetic growth expressions were fashioned after the developments
of Monod (7). The endogenous respiration phase of bacterial growth was
modeled according to a first-order decay relationship.
Mass balances written for the solids contained within the clarifier con-
sidered the thickening and clarification functions of the clarifier. Both
the gravitational sedimentation and bulk transport velocity components were
considered with-respect to the thickening function. Since no suitable math-
ematical development describing the clarification function is available, a
stochastic regression developed by Pflanz ;(8} was employed. This relation-
ship, based on data obtained at a single treatment plant, is of the form:
SS(out) = 4'5 + 7'5
* OR)/10
where,
SS, .N = concentration of suspended solids in the effluent (overflow),
1 ' mg/1
MLSS = concentration of suspended solids in the aerator, mg/1
OR = clarifier overflow rate, 1/hr-m
All performance predictions relative to particulate BODU can be made only
within the constraints of the empirical Pflanz relationship
It should be noted, moreover, that the dynamic model is limited to the
extent that it does not account for changes in thickening and clarification
characteristics that can be attributed to changes in certain biological and
physical parameters.
10
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SECTION 6
MODEL SIMULATIONS
Using the dynamic model described above, simulations were conducted for
the two solids inventory control strategies that make use of independent
storage of biological solids.^ No simulations were conducted for the case of
simple control of the recycle flow from the clarifier to the aerator where
biological solids are stored in the clarifier. System interactions between
the aerator and clarifier for this case have been described by Keinath, et a!.
(9). As noted above, the extent of PLI control that can be achieved through
application of this control strategy is relatively small unless the clarifier
is extremely overdesigned from a clarification viewpoint.
All simulations were conducted for the physical pilot-scale system that
was employed in the experimental phase of this study. The system consisted
of a 10992 liter (2904 gallon) completely mixed aerator coupled to a 5.48
square meter (59 square foot) circular clarifier which had a water depth of
3.35,meters (eleven feet). The flow to the system was assumed to be con-
stant at a rate of 75.7 liters per minute (20 gallons per minute). This was
selected since the pilot-scale studies were conducted at a flow rate which
was maintained constant at 75.7 1pm (20 gpm) to eliminate hydraulic trans-
ients as a system variable. The concentration of organics (as indexed by
TOC) in the influent to the system was assumed to vary as shown in Figure 5.
Sludge recycle pumping constraints were imposed at 10 and 200 percent of the
influent flowrate. It was assumed, furthermore, that the mean cell residence
time was maintained constant at 8 days based on the total mass of biosolids
in the system and that the PLI control set point was 1.0 mg TOC/mg MLVSS/day
based on the mass of solids in the aeration basin alone. The total or maxi-
mum volume of the biological solids storage chamber was changed for various
simulations to establish the effect of storage volume on control capability.
The storage chamber was also assumed to be completely mixed.
CONTROL CASE A ("Constant Volume Storage Chamber)
The output for simulations conducted for control case "A" is given in
Figures 6-20 for the situations in which the biological solids storage
chamber was considered to hava a total volume equal to either 10 percent
(1099 liters, 290.4 gallons), 50 percent (5496 liters, 1452 gallons),. or
100 percent (10,992 liters, 2904 gallons) of the volume of the aerator.
Figures 6, 7, and 8 give the time dependent traces for (a) the volatile
mixed liquor suspended solids that should be maintained in the aerator if -.
perfect PLI control is to be achieved and (b) for the actual value of
11
-------
c-1-
CT
LU
=3
U.
257
lib 60 80 100 120 lllO
TIME (hours)
Figure 5. Influent total organic carbon vs. time
(profile) used for simulations.
Tso
12
-------
20 «0 M W 100
TIME (hours)
Figure 6. Simulated actual MLVSS and
time; storage volume = 10%
volume.
120
1UO
180
desired MLVSS vs,
of the aeration
C fii
en
CO
< o
I- 9-
CO
CO
« zo 56 eS e5I5o iio IHoiko
TIME (hours)
Figure 7. Simulated actual MLVSS and desired MLVSS vs.
time; storage volume = 50% of aerator volume.
13
-------
E *•
CO
LU g-
LU
o:
in
co
«&
Figure 8.
120
"Ho ieo
J5«G ~li 3>TEo"
TIME (hours)
Simulated actual MLVSS and desired MLVSS vs,
time; storage volume = aerator volume.
CO
•o
CO
•z.
LU
CO
CO
LU
O
O
0=
D.
SO
*0
120
iko
100
Figure 9.
•5 w loo
TIME (hours)
Simulated process loading intensity vs. -time;
storage volume = 10% of the aerator volume.
14
-------
volatile mixed liquor suspended solids that can be maintained when the con-
trol algorithm is implemented for the specific physical system considered.
Figures 9, 10, and 11 give the corresponding actual PL! values that are
attained. Of course, the intent of the control algorithm is to maintain this
value constant throughout time. Performance indexes for the simulations are
given in Figures 12, 13, and 14;- 15, 16, and 17; and 18, 19, and 20 for
total BODU, soluble BODU and the concentration of suspended solids discharged
with the effluent, respectively. ' .
Analysis of the output of the simulations for the three storage volume
capacities shows the following:
(1) For the system in which the biological solids storage chamber had a
volume of the aeration basin (Figure 6) the control system could
respond appropriately only when the algorithm called for an increased
mass (concentration) of biological solids in the aeration basin. The
control system failed to provide adequate control during periods of low
organic loadino when biological solids should have been transferred from
the aeration basin to the storage chamber. This is due to the fact that
the sludge recycle pump reached its lower physical constraint (10 per-
cent of the .influent flowrate) thereby limiting the extent to which
solids could be transferred from the aerator to the storage chamber.
This is manifested in the form of a lower-bound plateau on the curve
which gives the time dependent trace of the actual volatile mixed liquor
suspended solids that can be achieved.
(2) Figure 9 shows the corresponding PLI values for the case described above.
One can observe, as expected, that the PLI was maintained relatively con-
stant at 1..0 mg TOC/mg MLVSS/day during periods of high organic loading,
but that the value decreased during periods of low organic loading due
to the sludge recycle pumping limitation which constrained the transport
of biological solids from the aeration basin to the storage chamber.
Since more solids than desired remained in the aeration basin during
these periods, the PLI correspondingly decreased.
(3) If the volume of the biological solids storage chamber were increased to
,50 percent of the volume of the aeration basin (Figure 7), then the sys-
tem can properly respond to the control algorithm to maintain the de-
sired mass of biological organisms in the aerator to, in turn, maintain
a relatively constant PLI (Figure 10).
(4) If the volume of the storage chamber were increased even further, to 100
percent of the volume of the aerator ("Figure 8), then the control system
encounters the upper physical constraint of the sludge recycle pumping
rate. That is, during,periods of high organic loading to the aerator
when the control algorithm calls for the transfer of biological solids
from the storage chamber to the aerator as encountered during the last
day of the simulation (136 to 160. hours), it is apparent that only a
portion of the bioloaical solids that should have been transferred were
transferred on account of the recycle pumping limitation. This is mani-
fested in the form of an upper-bound plateau on the curve giving the
time dependent profile of the actual volatile mixed liquor suspended
15
-------
It)
-O
CO
LU
fe 3
Q -
S
co -y
to
O
O
^«S s5 i£ISoilo HoAo
TIME (hours)
Figure 10. Simulated process loading intensity vs. time;
storage volume = 50% of aerator volume.
ro
-o
-------
solids that can be achieved.: The corresponding PLI trace (Figure 11) is
seen to increase during the period when the recycle pumping rate was
constrained by the upper limit.
(5) With respect to system performance, it is apparent that although the
variability of effluent quality, as indexed by total BODU, decreased as
the PLI was controlled more precisely at the set point level, virtually
no benefits were noted relative to the total mass of organics discharged
from the treatment system (refer to Figures 12, 13, and 14). This,
rather suprising observation can be explained through an analysis of the
soluble and particulate components of the total effluent BODg. Imple-
mentation of PLI control serves to decrease the variability in and total
discharge of soluble carbonaceous material in the effluent (Figures 15,
16, and 17) while increasing the variability in and total discharge of
particulate (suspended solids) carbonaceous material in the effluent
(Figures 18, 19, and 20). The two effects counteract one another. The
net result is that the effluent quality does not change materially as a
function of the precision of PLI control even though the overall varia-
bility of effluent quality is decreased.
Considering the results of the simulations for the control system de-
scribed above, it is apparent that an optimum size for the storage chamber
exists. If the biological solids storage chamber is small,,then the solids
stored therein are relatively concentrated since the total mass of biological
solids that must be stored in the chamber is relatively independent of its
volume. This condition, of course, can only be achieved when the secondary
clarifier/thickener is operated at small recycle flow rates. When the control
algorithm is implemented, consequently, control often is constrained by the
lower limitation on the pumping rate..
Conversely, if the constant volume storage chamber is large, then the
biological solids stored therein are relatively dilute. This condition is
achieved when the recycle pumping rate is relatively large. Accordingly, when
the control algorithm is implemented, control is often constrained by the
upper limitation on the pumping rate.
CONTROL CASE B (Variable Volume Storage Chamber) ,
Simulations were conducted for control case "B" for three different maxi-
mum storage volumes — 10, 40, and 100 percent of the volume of the aeration
basin. Since the storage chamber is of variable volume in the dynamic^sense,
it is important to recognize that these volumes represent only the maximum
possible volume of the storage chamber. For these simulations the .sludge re-
cycle pumping rate from the clarifier to the biological solids storage chamber
was maintained constant at 15.14 liters per •minute (4 gallons per minute, 20
percent of the influent flowrate). Of course, the recycle pumping rate from
the solids storage chamber to the aeration basin.was manipulated so as to
maintain a constant PLI.
The output for these simulations is given in Figures 21-35 for the cases
in which the biological solids storage chamber was considered to have a maxi-
17
-------
Si
D)
o
o
CO JJ
u.
U-
UJ
tlT
120
180
W' N iO 100
TIME (hours)
Figure 12. Simulated total BODU in the effluent vs. time;
storage volume = 10% of aerator volume.
m
I-
o
20 «D M> W 100
TIME (hours)
Figure 13. Simulated total BODU in
storage volume = 50« of
tYo
iko
the effluent vs.1 time;
aerator volume.
18
-------
O)
o
o
o
•v^
Figure
tSo
ito
w so w ibo
TIME (hours)
Simulated total BODU in the effluent vs. time;
storage volume = aerator volume.
O)
E
O
o
CO
O
in
20
ISO
ilw
iko
Figure 15.
w so ab ibo
TIME (hours)
Simulated soluble BODU in the effluent vs,
storage volume = 10% of aerator volume.
t i me;
19
-------
O)
o
o
CQ s-
LU
=3
u.
U.
LU
LU
_l
ca
o
CO
55 sb iEo~
TIME (hours)
"155
Figure 16.
Simulated soluble BODU in the effluent vs. time;
storage volume = 50% of aerator volume.
o
CQ
LU
_]
CQ
O
10
1ST
T51T
Figure 17-
ifie5so'100
TIME (hours)
Simulated soluble BODU in the effluent vs. time;
' storage volume = aerator volume.
20
-------
- Bl
D)
O
00 u>.
O
LU
O
LU 3-
co
3
CO
to
LU
180
Jif "Koo 20 «5 eb*SB iS liF ido
TIME (hours)
Figure 18. Simulated suspended solids in the effluent vs.
time; storage volume - 10% of aerator volume.
^ 81
o>
to,
O
O
to
Q
LU
Q
•z.
LU
t
LU
ito
1*0
ifco
Figure 19-
to ob eb too
TIME (hours)
Simulated suspended solids in the effluent vs,
time; storage volume = 50% of aerator volume.
21
-------
in
o
o
00
LU
Q- 2-
10
to
I-
z w
LU
LU «ff•
Figure 20.
ISO
ivo
180
W 6080 100
TIME (hours)
Simulated suspended solids in the effluent vs
time; storage volume = aerator volume.
22
-------
mum volume of either 10, 40, or 100 percent of the volume of the aeration
basin. The time-dependent output variables plotted are identical to those
plotted for Control Case A.
Analysis of the output of the simulations for the three cases shows
the following:
(1) For the case in which the storage volume was assumed equal to 10 per-
cent of the aeration basin volume, the simulations showed that the
control system responded appropriately only when the control algorithm
called for an increased mass (concentration) of biological solids in
the aerator (Figure 21). This is identical to the response observed for
for the case of a constant volume storage chamber of identical volume.
In this case, however, control was constrained by the maximum volume of
the storage chamber instead of the lower limit on the recycle pumping
rate. That.is, during periods of low organic loading to the aerator the
•control algorithm calls for the transfer"of biological solids from the
aeration basin to the storage chamber.. This is accomplished by de-
creasing the recycle pumping rate (storage chamber to aeration basin)
such that the storage chamber fills. When the storage chamber is com-
pletely filled, the recycle pumping rate from the storage chamber to the
aerator then must equal the recycle pumping rate from the clarifier to
the storage chamber. No further transfer of biological solids can then
be accomodated within the biological solids storage chamber. As before,
this results in a lower-bound plateau on the curve which gives the time
dependent trace of the actual volatile mixed liquor suspended solids that
can be achieved. The corresponding PLI curve (figure 24) shows that the
PLI was maintained relatively constant except for periods of low organic
loading..
When the maximum storage volume is assumed to be 40 percent of the vol-
ume of the aeration basin (Figure 22), then sufficient volume is avail-
able such that the system can respond to the control algorithm to
maintain the desired mass of biological organisms in the aeration basin
to, in turn, maintain a realtively constant PLI (Figure 25).
(3) For the case in which the maximum storage volume is assumed to be equal
to 100 percent of the volume of the aerator ('Figure 23), then no addi-
tional control capability benefits are obtained'as compared to the 40
percent case. This is due to the fact that only a portion of the maxi-
mum storage volume available is utilized for control. All excess stor-
age capacity provides no benefits in control capability and, therefore,
is unnecessary. One can conclude, consequently, that a threshold limit"
for storage volume exists for the control case wherein a variable volume
storage chamber is employed. All volume supplied in excess of the
threshold value has no net control capability benefits.
(4) All observations made and conclusions drawn with respect to system per-
- formance for Control Case A (Constant Volume Storage Chamber) apply
directly for this control algorithm as well. Performance indexes have
been plotted in Figures 27-35.
(2)
23
-------
p &l
2 J
LU
<
to
IO
^_ io «o iS iiSi5o
" TIME (hours)
Figure 21. Simulated actual MLVSS and
time; storage volume = 10%
iko
Teo
desired MLVSS vs.
of aerator volume.
I1
CQ
Xc
LU §•
LU
to
to
20 Ub 60 80 100
TIME (hours)
Figure 22. -Simulated actual MLVSS and
time; storage volume =
120
1UO
180
desired MLVSS vs.
of aerator volume.
24
-------
Q 81
tn
-
< o
03 -
_ *a
LU
<
UJ
33
CO
1ST
Tso
Figure 23.
HO 80 80 100
TIME (hours)
Simulated actual MLVSS and desired MLVSS vs.
time; storage volume = aerator volume.
TO
•p,
CO
CO
LU
O
O
C£
CL,
20 u6 so iS ib
TIME (hours)
"iio iUo
Figure 2k. Simulated process loading intensity vs.
storage volume = 10% of aerator volume.
t ime;
25
-------
ro
to
UJ
o
_1
CO
o
o
(£.
OL.
80
120
Figure 25.
~"35100
TIME (hours)
Simulated process loading intensity vs. time;
storage volume = kO% of aerator volume.
ro
-a
LU
O
<
O
UJ
o
o
20
120
160
TIME (hours)
Figure 26. Simulated process loading intensity vs. time;
storage volume = aerator volume.
26
-------
LU
r>
U-
LL.
LU
_]
<
-------
en
3
O
o
QQ
LU
U.
U.
LU
g
20 l»0 60 80 JOE
TIME (hours)
120
Teo
Figure 29. Simulated total BODU in the effluent vs. time;
storage volume = aerator volume.
O
o
QQ
LU
_
LU
LU
_1
QQ
3
o
CO
20 UO BO 80 100
TIME (hours)
IttO
160
Figure 30. Simulated soluble BODU in the effluent vs. time;
storage volume = 10% of aerator volume.
28
-------
Dl
3
Q
O
CQ
U.
UJ
LU
_l
CQ
O
CO
20ttO 60 80 100 120 1UO 160
TIME (hours)
Figure 31. Simulated soluble BODU in the effluent vs. time;
storage volume = 40% of aerator volume.
D)
Q
O
CO
O
to
=¥
Figure 32.
ilto
180
TIME (hours)
Simulated soluble BODU in the effluent vs. time;
storage volume = aerator volume.
29
-------
O)
CO
a
o
to
a
LU
o
LU
D-
10
Z3
to
LU
LU
i'ao il«r
Teo
Figure 33-
"IS iS 55iSo"
TIME (hours)
Simulated suspended solids in the effluent vs. time;
storage volume = 10% of aerator volume.
Ol
to
o
o
10
o '
LU
LU
0. o.)
CO ""
LU
Lu
LU
no
ilio
~s5 55ibo iSo"
TIME (hours)
Figure 3^- .Simulated suspended solids in the effluent vs. time;
storage volume = kO% of aerator volume.
30
-------
co
a
o
CO
a' 2-
LD
O
Q.
CO
i5 i5 • ibo
TIME (hours)
120
Figure 35- Simulated suspended solids in the effluent vs. time;
storage volume = aerator volume.
31
-------
SECTION 7
PILOT-SCALE STUDIES
To evaluate one of the PLI control strategies proposed above, two inten-
sive pilot-scale studies were conducted during 1976 at the EPA Pilot-Plant
in Washington, DC using primary effluent obtained from the Blue Plains Treat-
ment facility. One of the studies served as a base case for comparison
purposes. No solids inventory .control actions whatsoever were implemented
during this study. The second, four-day study was conducted to evaluate the
PLI control strategy wherein a constant volume chamber was employed for stor-
age of biological solids, Figure 2. Salient process design and operational
parameters for these two studies have been detailed in Table 1. Raw data as
collected by EPA personnel for these two studies has been tabulated in Appen-
dices B and C, respectively.
TABLE 1. :DESIGN,AND.OPERATIONAL.PARAMETERS.FOR PILOT STUDIES
Parameter
No Control Case
Controlled Case
SRT, total mass minus
clarifier mass (days)
SRT, aerator mass (days)
PLI (Ibs TOC/lb MLVSS/day)
Aeration Basin Volume
(gallons)
Storage Chamber Volume
(gallons)
Influent Flow Rate, F (gpm)
Recycle Flow Rate, FR (gpm)
Clarifier,Surface Area,(ft2)
2.3
1,2
0.98 (avg.)
2904
1000
20
10
59
3..0
1,2
0.71
2904
1000
20
Variable
59
32
-------
A third experimental pilot-plant study was conducted by EPA personnel.
This study was similar to the base-case study in which no solids inventory
control actions were implemented. In this study, however, the influent
hydraulic flow-rate was controlled such that the organic loading to the aera-
tion basin was maintained constant.. Since this study did not bear directly
on the scope of this project, it will not be considered further herein. None-
theless, the data gathered during the study has been included in Appendix D
-both in tabular and graphical format for future use and reference.
Construction of the pilot-scale experimental system was begun in Decem-
ber 1975 and completed in January 1976. During the February to mid-April
1976 period the system was seeded and operated under, a specific set of condi-
tions until steady-state operation was attained as confirmed by analyses per-
formed on composite samples. Operation was continued for at least.three ,
solids residence times' before the base case high-intensity study was initiated
in late April 1976. Following the end of each individual one-week, high-
intensity study the system was operated under the previous set of operational
conditions for one week until.the data obtained during the high intensity run
was validated. Subsequently, the operational state of the system was changed
to the new set of operational conditions and allowed to attain steady-state
as described above. This procedure was followed throughout the experimental
program that was terminated in August 1976.,
BASE CASE STUDY (no PLI Control)
Before the sampling, and analysis program for this pilot study was initi-
ated, the system was operated at the conditions listed in Table 1 for a
period in excess of three solids residence times as indicated above. The SRT
was controlled by wasting directly from the aerator on a continuous basis.
Dissolved oxygen was controlled in both, the aerator and the storage chamber
at approximately 2.5 mg/1. After the study was initiated total organic
carbon, suspended solids, dissolved oxygen, air flow rates, temperature, hy~
draulic flow rates, and turbidity were measured continuously at various loca-
tions throughout the system using on-line instrumentation. All other analyti-
cal measurements were done on an intermittent, grab-sample basis. These
included soluble and total COD, soluble and total BODg, soluble TOC, total
phosphorus, volatile suspended solids, and pH. In addition, sludge interface
settling velocities and clarifier solids profiles were determined periodically
to establish dynamic changes in sludge settleability. Furthermore, analytical
determinations of total TOC, suspended solids, dissolved oxygen, and tempera-
ture were performed periodically on grab-samples in the laboratory. These
served as a check for the on-line process instrumentation.
Selected results for this study are shown in Figures 36-42 in which total
influent TOC, total effluent TOC, effluent turbidity, effluent suspended
solids and laboratory values for total and soluble effluent TOC have been
plotted as a function of elapsed time.
Because no PLI control was implemented in this study and because the
influent hydraulic flow rate was maintained constant to eliminate hydraulic
transients as a process variable, the reactor suspended solids concentration
33
-------
0)
O
o
LU
u.
•z.
§•
•
X1
i
x
i
Si
*.*
•
f
X
I
1
X
X
X
V
x
i
i
20 V>Bu80 100 ?20
TIME (hours)
Figure 36. Influent TOC vs. time for base-case pilot study
with no PLI control.
e e
o
• •
o
o
«iW Hr
LU
LU
20 W 80 80 100 120
; TIME (hours)
Figure 37- Effluent TOC vs. time for base-case pilot study
with no PLI control.
34
-------
Q
00
UJ
U_
It/ '•
ee
I *
If®
V 1
20 iiE iE so """100ifeo
TIME (hours)
Figure 38. Effluent turbidity vs. time for base-case pilot
study with no PLI' control (zero values signify
missing data).
(VI
£
CO
O
CO
I*
UJ
Q_
CO
• «a
•ae
e *•
J8080
TIME (hours)
100
ifeo
Figure 39. Effluent suspended solids vs. time for base-case
pilot study with no PLI control Czero values
signify missing data).
35
-------
CO
CO
> 2-
I—
f_
•31
UJ
t »•
UJ
e
e
e
O QD 9 O
earae e ee ate»
QOOB so a
•e e e ee
o eoo c o e e e e eo ® e
GO S O O O Q O O
o e oe OB e
o o o o
U SO 110 60 60 100 120
TIME (hours)
Figure AO. Effluent volatile suspended sol ids vs. time
for base-case pilot study with no PLI control
(zero values signify missing data).
o>
li »
o «
o
CO
o
o
o
LL.
IX
UO 60 80
TIME (hours)
100
Figure 41. Laboratory measured effluent TOC vs. time for
base-case pilot study with no PLI control
(zero values signify missing data).
36
-------
CD
O
o
LU
LU _•
OQ
O
C/1
°ff—
Figure 42.
100
120
!D UO 60 80
TIME .(hours)
Laboratory measured effluent soluble TOC vs.
time for base-case pilot study with no PLI
control (zero values signify missing data).
O) "
LU
=3
U, o.
O
o
ft
e e
100
7l20
UO 60 80
TIME (hours)
Figure 43. Influent TOC vs. time for PLI controlled pilot
study (zero values signify missing data).
37
-------
should have remained relatively constant throughout the study. Within the
limitation of the on-line process .suspended solids meter that was employed
for this study one can generally conclude that the suspended solids level in
the aerator remained relatively constant. Consequently, the PLI varied
approximately in direct proportion to the organic loading, shown in Figure 36.
Total effluent TOC measurements taken continuously using an automatic
analyzer, showed a total variability ranging from 6 to 14.5 mg/1. Compar-
able laboratory TOC measurements confirmed the results obtained using the
continuous, on-line process instrumentation. Eight laboratory BODs meas-
urements performed on aliquots taken from the effluent process stream aver-
aged 19.0 and 4.6 for total and soluble 8005, respectively. Although the
effluent can be judged to be of a very high quality regardless of the per-
formance index chosen, it is clear that.the vast majority of the carbonaceous
material present in the effluent is present in the particulate form. Con-
tinuous effluent turibidty measurements, Figure 33, showed a diurrtal varia-
bility which was generally in-phase with the organic loading to the aerator.
This correspondence may be observed by comparing Figures 36 and 38.
PLI CONTROL STUDY
As for the base-case study the system was operated for a period in
excess of three SRTbs to ensure proper equilibration. Upon initiating the
study, the recycle flow rate, FR, was controlled as designated by the algo-
rithm given previously. The differential term, V(dXo/dt), was neglected for
this particular study, however. The MLSS, of course, varied throughout the
run in response to the control algorithm. All process operational and per-
formance analyses were identical to those employed during the base-case
study with the exception of continuous, on-line effluent TOC which malfunc-
tioned during a major portion of this study.
Results for .this pilot study are graphically displayed in Figures 43-49
in which total influent TOC, total effluent TOC, effluent turbidity, efflu-
ent suspended solids, effluent volatile suspended solids and laboratory values
for total and soluble effluent TOC have been plotted as a function of elapsed
time.
Eight laboratory total TOC measurements taken on effluent samples aver-
aged 11.3 mg/1 and ranged from 8 to 15 mg/1. Measurements of total and sol-
uble 8005 on the same samples of process effluent quality appears to be
slightly better than that for the base-case study as indexed by BOD, no con-
clusions can be drawn because of the relative magnitude of the values obtained
and the very limited number of BOD values obtained.
The results of this study also showed that suspended solids account for
the majority of the carbonaceous material present in the effluent. Comparing
Figures 43 and 45, it is readily apparent that (1) the diurnal cycle in
effluent turbidity is in-phase with the organic loading cycle to the aerator
and (2) the magnitude of the diurnal excursions in turbidity is proportional
to the magnitude of variation in organic loading to the aerator. These obser-
vations are identical to those made for the base-case study.
38
-------
o. ,
in '
H-
Z
LU
8-
O.
~
03
H
u. o.
~ ib"iffiib"i5 *ibo120
TIME (hours)
Figure 45. Effluent turbidity vs. time for PLI controlled
pilot study (zero values signify missing data),
39
-------
CO
o
— to.
_J
o
CO
o
01
O CM.
01
a.
CO
CO
o
e
OB eo
O OO
o o o
O O OO Od>
(9 O O MDOBO O
O O O O O (BO O
OO O
O
O O O
•V s
Figure 46.
60
80
120
TIME (hours)
Effluent suspended solids vs. time for PLI
controlled pilot study (zero values signify
missing data).
CO
CO
Ol
=3
e
0
o
o
o o o o
O ^D O
O (9 9X9
GDOOQ O (B GXDOB O
QO O OO QDOOO OOO O O
GOO O O O O9BQ0O O O
' QD O O O
O
CV^
Figure
20
I WU v
TIME (hours)
120
Effluent volatile suspended solids vs. time
for PLI controlled pilot study (zero values
signify missing data).
40
-------
CC ID.
o
o
03
< w.
o
o
QJ
LJJ
eg,
Figure 48.
40 60 60
TIME (hours)
100
120
Laboratory measured effluent TOC vs. time for
PL! controlled pilot study (zero values signify
missing 'data) .
D5
E
I-
1-
O
t/5
20
100
120
UO 60^ 80
TIME (hours)
Figure 49. Laboratory measured-effluent,soluble TOC vs.
time for PLI control led pi lot study (zero
values signify missing data).
41
-------
COMPARISON OF CONTROLLED AND UNCONTROLLED STUDIES
Results of the two pilot-scale studies can be compared most conveniently
through the use of frequency distribution plots. Total effluent TOC data
obtained using a continuous, on-line TOC analyzer has been plotted in a fre-
quency distribution format in Figure 50. Similar plots, Figures 51 through
54, have also been developed for data obtained in the laboratory for both the
controlled and uncontrolled studies for total effluent TOC, soluble effluent
TOC, total effluent BODs, and soluble effluent BODs, respectively.
Figure 50 shows that the total effluent TOC for the pilot study in which
the PLI was controlled was higher than it was for the base-case (uncontrolled)
study. This observation is particularly interesting considering the fact
that the total influent TOC was one-third higher for the base-case study as
compared to the PLI controlled study. It is interesting to note* furthermore,
that the slope of the frequency distribution trace for the total effluent TOC
for the controlled study also was greater than that obtained for the base-case)
study. This implies that the variability of the effluent TOC was greater for
the controlled case as well.
• On the basis of the experimental continuous, on-line data obtained it
would appear that PLI control has no net benefits and, indeed, might even be
slightly detrimental to process performance. The corresponding laboratory
measurements (Figures 51 through 54], however, do not confirm and are some-
what in conflict with the measurements made continuously using an on-line TOC
analyzer. Qualitatively, the laboratory results show that: (1) the median
total effluent concentration of organics expressed either as TOC or BOD5 was
lower for the controlled study than it was for the uncontrolled (base-case)
study; (2) the variability in total effluent TOC or BODs was greater for the
controlled than for the uncontrolled study; and (3) no significant differ-
ences existed between the controlled and uncontrolled studies with respect to
soluble effluent TOC or BOD5. Based on the laboratory data it appears that
the particulate solids in the effluent account for the majority of the ob-
served difference in performance between the controlled and uncontrolled
(base-case) studies as well as the relative differences in variability ob-
served between the two process outputs. Laboratory suspended solids and
volatile suspended solids data obtained for the two studies, Figures 55 and
56, respectively, confirm this observation.
Although the laboratory data, in contrast to the continuous, on-line
data, supports the contention that benefits can be obtained by virtue of PLI
control, no such conclusions can be made since the laboratory data was ex-
tremely limited. Only eight analyses were performed in the laboratory for
each of the parameters measured. Moreover, the eight samples analyzed were
collected twice daily at the same clock times (12:00 midnight and 2:00 PM)
throughout the period of the study.
Since the issue of whether PLI control has a beneficial effect_on
process performance could not be resolved on the basis of the conflicting
sets of experimental data, simulations were conducted for the two pilot-scale
systems evaluated experimentally at the EPA Pilot Plant using the dynamic
mathematical model employed previously in this study.
42
-------
1.7
1.6 -
1.5
1.4
1.3
1.1
at
I
1.0
.9
.8
Contro
10 20 50 80 90
Percent of Observations with Values Equal
to or Less Than Stated Value
99
Figure 50. Logarithmic frequency distribution domain for effluent
TOG for base-case and PLI controlled pilot studies.
u
o
.p.
2
o
JQ
a
. ' 4J
§
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
Base Ca
Controlled Case
10
20
50
80
90
99
Percent of Observations with Values
Equal to or iess Than Stated Value
Figure 51. Logarithmic frequency distribution domain for effluent
TOC (laboratory)" for base-case and PLI controlled pilot
studies.
43
-------
~ 1.6
o>
1.2
4J
§
3
-------
- 1.4
Figure 54.
10 20 50 80 90
Percent of Observations with Values
Equal to or Less Than Stated Value
Logarithmic frequency distribution domain for effluent
BOD5 (soluble, laboratory) for base-case and PLI controlled
pilot studies.
•O
•H
i-l
O
1.6
1.4
1.2
1.0
m 0.8
w
4J
3 0.6
*W
«H
W
° 0.4
0.2
T
T
T T
Base Case
Controlled Case
I
10
20
50
80 90
99
Percent of Observations with Values
Eaual tQ pr Less Than Stated Value
Figure S5. Logarithmic frequency distribution domain for eMluent
suspended solids (laboratory) for base-case and PLI
controlled pilot studies.
45
-------
I
§
o
B)
V
1
8
M
ia
tn
Figure 56.
0.8 —
o.e -
0.4 -
0.2
Percent of Observations with Values
Equal to or Less Than Stated Value
Logarithmic frequency distribution domain for effluent
volatile suspended solids (laboratory) for base-case
and PLI controlled pilot studies.
46
-------
TABLE 2: STATISTICAL COMPARISON OF TWO EXPERIMENTAL STUDIES
Type of Analysis
Number of Lower Upper
Determinations 95%-tile Median 95%-tile
*** Continuous, On-Line Measurements ***
Total Effluent TOC (mg/1)
Uncontrolled Study
Controlled Study
Effluent Turbidity (JTU)
Uncontrolled Study
Controlled Study
192
83
147
171
6.8
7.4
15.8
31.6
10.0
15.7
26.6
53.1
*** Laboratory, Off-Line Measurements ***
14.5
33.5
45.2
88.1
Total Effluent TOC (mg/1)
Uncontrolled Study
Controlled Study
Soluble Effluent TOC (mg/1)
Uncontrolled Study
Controlled Study
Total Effluent 6005 (mg/1)
Uncontrolled Study
Controlled Study
Soluble Effluent BOD5 (mg/1)
Uncontrolled Study
Controlled Study
Suspended Solids (mg/1)
Uncontrolled Study
Controlled Study
Volatile Suspended Solids (mg/1)
Uncontrolled Study
Controlled Study
8
8
8
8
8
8
8
8
95
97
95
97
11.3
7,2
6.8
6.1
11.9
1.3
1.2
1.9
4.7
2.8
3.5
.1.8
13.9
11.0
9.6
9.7
19.0
8.7
3.9
3.7
9.2
7.0
6.7
.4.8
18.2
17.0
13.2
' 15.3
31.0
60.0
13.3
7.8
18.0
18.0
13.0
.13.0
Analysis of the simulations showed that the total mass of BODU dis-
charged with the effluent was approximately the same for both simulations,
PLI controlled and uncontrolled (base-case). Nonetheless, the variability of
the BODU for the uncontrolled system was somewhat greater than that simulated
for the controlled system. These specific observations for the simulations
do not compare precisely with the corresponding experimental observations.
The general simulations, however, compare favorably with the experimental
results obtained. This, of course, lends credence to the mathematical
developments.
More specific analysis of the components of the total effluent BODU,
soluble and particulate, shows that implementation of PLI control serves
to decrease the variability in the effluent soluble BODU. Considering both
effects, the controlled and uncontrolled systems appear to be approximately
equivalent in performance.
47
-------
REFERENCES
1. Busby, J. B. and J. F. Andrews, "Dynamic Modeling and Control Strategies
for the Activated Sludge Process." 3. Wat&i ?olt. Con&tol Fe.d. 47,
1055-1080, 1975.
2. Andrews, J. F.5 M. K. Stenstrom, and H. 0. Buhr, "Control Systems for the
Reduction of Effluent Variability from the Activated Sludge Process."
Jin WateA Tech. S, 41-58, 1976.
3. Bryant, J. 0., "Continuous Time Simulation of the Conventional Activated
Sludge Wastewater Renovation System." PhD Dissertation, Clemson Univer-
sity, Clemson, SC, USA, 1977.
4. Busby, 0. B., "Dynamic Modeling and Control Strategies for the Activated
Sludge Process." PhD Dissertation, Clemson University, Clemson, SC,
USA, 1973.
5, Stenstrom, M. K. , "A Dynamic Model for Computer Compatible Control
Strategies for Hastewater Treatment Plants.* PhD Dissertation, Clemson
University, Clemson, SC USA, 1976.
6. Cashion, B. S., "Sludge Inventory Control Strategies for the Activated
Sludge Process." MS Dissertation, Clemson University, Clemson, SC, USA,
1976.
7. Monod, J., "The Growth of Bacterial Cultures."' Ann. Rev. Alto/to. 3, 371.
8. Pflanz, P., "Performance of (Activated Sludge) Secondary Sedimentation
Basins." In Advance* in Wat&i ?ott. ReAe.ax.ch, Proc. 4th International
Conf. 1969, Ed - by S. H. Jenkins, Pergamon Press, New York., 1969.
9. Keinath, T. M. , M. D. Ryckman, C. H. Dana, and D. A. Hofer, "Activated
Sludge - Unified System of Design and Operation." Joannal ol tke. Env&wn-
Vi.vti>jjovi, ASCE, 103, EE5, 829-849, 1977.
48
-------
APPENDIX A
Program Listing
of
Dynamic Mathematical Model
49
-------
* THIS MACRO CONTAINS THE MASS BALANCES FOR THE J TH STAGE *
MACRO VJDOT,SJ?SNH4JiSN02J,SN03J,XAJ,XIJtXNBJ,XNSJ,XSJ,XTJ=...
STAGE (FOJtFRJfSOJfSNH40J,SN020J,S
-------
MACRO FTL,SL,SNH4L,SN02L,SN03L,XAL,XIL,XNBL,XNSL,XSL=MIX<...
FTK,FK,SK,SNH4K,SN02K,SN03K,XAK,XIK,XNBK,XNSK,XSK,SOK,SNH40K,SN020K,...
SN030K,XAOK,XIOK,XNBOK,XNSOK,XSOK)
NOSORT
FTL=FTK+FK
FX1=FTK/FTL
FX2=FK/FTL , . •
* BYPASS CALCULATIONS IF NO MIXING
IF(FX2> 10,10,20
10 CONTINUE
SL=SK
SNH4L=SNH4K
SN02L=SN02K
SN03L=SN03K
XAL=XAK
XIL=XIK
XNBL=XNBK
XNSL=XNSK
XSL=XSK
GO TO 30
20 CONTINUE
SL=FX1*SK+FX2*SOK
SNH4L=FX1*SNH4K+FX2*SNH40K
SN02L=FX1*SN02K+FX2*SN020K
SN03L=FX1*SN03K+FX2*SN030K
XAL=FX1*XAK+FX2*XAOK
XIL=FX1*XIK*FX2*XIOK
XNBL=FX1*XNBK+FX2*XNBOK
XNSL=FX1*XNSK+FX2*XNSOK
XSL=FX1*XSK+FX2*XSOK
30 CONTINUE
SORT
ENDMACRC
***************************************#*#**#***#********************#**
# THIS MACRO CALCULATES RUNNING MEANS AND RUNNING VARIANCES *
**#*#****#***********#*****#**********************#*********************
MACRO XBARJ,VARJ=STAT(XJ,INDEPJ,TRIGJ)
CALC10=MODINT(O.OtTRIGJ,1.0,XJ)
CALC11=MODINT(0.0,TRIGJ,0.0,(XJ**2))
PROC XBARJ,VARJ=LOGIC(CALC10tCALCll)
IF(INDEPJ) 340,350,340
340 XBARJ=CALC10/INDEPJ
VARJ=(CALC11-{(CALC10)**2)/INOEPJ)/INDEPJ
350 CONTINUE
ENOPRO
ENDMAC
#****#**##**************************************************************
* PARAMETERS AND INITIAL CONDITIONS *
*******#*#**************************************************************
PARAM PLIST=l.,NDEBUG=ltTDEBUG=1000.
PARAM PROPW=8.0 '
PARAM ITYPE=1,TSHFTI=120.,SHFTI=-1
PARAM RTYPE=-2,TSHFTR=120.,SHF'TR=2
PARAM CTYPE=+4,TSHFTC=120.,SHFTC=*4
51
-------
POSITIVEfPLI
POSITIVE(PROPW
POSITIVE(PLI
POSITIVEICON.
PARAM STYPE=-3 ,TSHFTS=120. , SHFTS=-3
*** RTYPE = NEGATIVEtCONSTANT ) ZERO(MASS PROP. )
*** CTYPE = NEGATIVECTOTAL MASS) ZERCH AERATOR MASS)
*** STYPE = NEGATIVEtONE PUMP ) ZEROIMASS PROP. )
*** ITYPE = NEGATIVE(CON. FLOW ) ZEROCPLI FLOW )
PARAM KOEX=1.42,TCHECK=25.,RCHECK=10.,KOES=l.5,EFF=0.0,KTOD=l.
PARAM TODAVG=76.3,TSSAVG=30. ,XDESUP=10000.,XDESLO=100.
PARAM WLO=0.,WUP=5., SLO=. 10, SUP=2.
PARAM RLO=.10,RUP=2.tFVlUP=l.,FVlLO=.01,FV4UP=1.00,FV4LO=1.0
PARAM FTOTAL=28800. , VTOTAL=2904. ,FRAT=.5,FVSTAB=.345, ICFRAC= 1 .
* INITIAL CONDITIONS
PARAM ICS1=2.996,ICS4=10.788
PARAM ICXA1=2085.5,ICXA4=358.04
PARAM ICXS1=33.133,ICXS4=15.193
PARAM ICXI1=1788. 1,10X14=305.09
PARAM ICXNS1=0.,ICXNS4=0.
PARAM ICXTR=5248.6,ICCLAR=161.30
PARAM ICXNB1=0.,ICXNB4=0.
* CARBONACEOUS PARAMETERS
PARAM FSH=0.45,KS=150.,KFS=.2,RXA=0. 30,RT=5. 0,RXI =. 015, Yl=0.5, Y2=0.25
PARAM XAO=0.,XSO=0.
PARAM ICXNV1=00. ,ICXNV4=00.
* NITRIFYING PARAMETERS
PARAM MUHMS=0.020,KSNS=1.0,MUHNB=0.04,KSNB=l.O,KDNS=0.005,KDNB=0.005
PARAM YNS=0.05,YNB=0.02,SCNH4S=0.086
PARAM SNH4IN=30.
PARAM SN020=0.,SN030=0.,XNSO=0.,XNBO=0.
PARAM ISN021=1.12,ISND24=9.00
PARAM ISNH41=7.8, ISNH44=9.00
PARAM ISN03i=9.,ISN034=17.5
PARAM AREA= 59. ,FRACV=0. 79,FRACB=0. 75
PARAM NELEM=10,HCLAR=9.0
INITIAL
*«««#««
* CALCULATION OF CONSTANTS
4c##«4c4
FIXED I,H, JtK,L,M,N,Hl,NELEM, I TYPE, IRANI , IRAN2 .NDEBUG
FIXED RTYPE, CTYPE, STYPE
STORAGE TFLUX(10),SETFLX{10),VS(10)
A=AREA*0,0929
DX=HCLAR*30.48/FLOAT(NELEM)
CLAR=ICCLAR
SNH40=SNH4IN
F=FAVG
FS=FR
FSU=FSC
FAVG=3.78*FTOTAL/24.
FR=FAVG*FRAT
PROPR=FRAT/TODAVG
S4=ICS4
S1=ICS1
HCLARC=HCLAR*30.48
SIN=TODAVG
52
-------
PLISET=PLIST
SAVE1=60000.
SAVE2=9.0E+08
SAVE3=1,3E*06
SAVE4=2,6E+08
SSIN=TSSAVG
THETAA=V4/FAVG
U=(FR+FW)/A*0.1
V1=FVSTAB*V4
V4=VTOTAL*3.78
FWLO=WLO*FAVG
FWUP=WUP*FAVG
FRI_0=RLO*FAVG
FRUP=RUP*FAVG
FSLO=SLO*FAVG
FSUP=SUP*FAVG
V1LO=FV1LO*V1
V1UP=FV1UP*V1
ICV1=ICFRAC*V1UP
Y1P=1.-Y1
Y2P=1.-Y2
XTR=ICXTR
FRC=FRAT*FAVG
FSC=FRC
SO=SIN+FRACV*FRACB*KOEX*TSSAVG
QNEOVR=(Y1*PLISET-RX!*(FVSTAB*ALPHA-H. ))/(FVSTAB*ALPHA+l.)
ALPHA=1.+1./FRAT
SSAGE=1./ONEOVR
SOAVG=SO
XDESC=XT4
X T 1= I CX A l± I OLSJjfclC XJLL
NOSORT .
DO 10 1=1, M
TFLUXt I)=0.
. SETFLX(I)=0. -
ICC(I»=CLAR
10 CONTINUE
ICC(NELEM)=XTR
IF(STYPE»LT.O.AND«RTYPE,LT.O) ICV1=VIUP
SORT
DYNAMIC
NOSORT
IF(TIME.GE.TSHFTI)
IF(TIME^GE.TSHFTR)
IFtTIME.GE.TSHFTS)
IF«TIME.GE.TSHFTC)
ITYPE=SHFTI
RTYPE=SHFTR
STYPE=SHFTS
CTYPE=SHFTC
53
-------
SORT
* TIMER SEGMENT OF MODEL
TRG6=0.5-IMPULS(6.,6.)
TRG24=0.5-IMPULS(24.,24.)
TRG168=0.5-IMPULSt168.,168.)
TRGR=0.5-IMPULS(RTIME,RTIME)
T6=MODINT(0.0, TRG6t1.0,1.0)
T24=MODINT<0.0, TRG24,1.0,1.0)
T168=MODINT(0.0, TRG168,1.Ot1.0)
TR=MODINT(0.0,TRGR,1.0,1.0)
It******************:!
* INPUT SECTION OF MODEL
**********#**#**««*«*#**>
PROCEDURE F,SIN,SSIN,SNH40=INPUT(ITYPE)
IF(ITYPE) 3020,3030,3060
* TIME VARYING INPUTS.FROM ACTUAL DATA
3020 SSIN=TSSAVG*TSS(TIME-TSHFTI)
SIN=VBOD(TIME-TSHFTI)
SNH40=SNH4IN*VSNHMTIME-TSHFTI)
* F=FAVG*FLOW(TIME-TSHFTI)
GO TO 3060
* HYDRAULIC VARIATION TO MAINTAIN CONSTANT MASS LOADING
3030 SSIN=TSSAVG*TSS(TIME-TSHFTI)
SIN=VBOD(TIME-TSHFTI)
SNH40=SNH4IN*VSNH4(TIME-TSHFTI)
F=PLISET*V4*MLVSS/SO/24.
3060 CONTINUE
ENDPRO
* INSERT CONVERSIONS THAT HERE DONE IN PRIMARY
FP=F
SSOUT=SSIN
SPFEED=SIN
XIO=SSOUT*FRACV*(1.-FRACB) '
XNVO=SSOUT*(l.-FRACV)*KOEX
SO=SPJFEED *• FRACV*FRACB*KOEX*SSOUT
BODINF=SPFEED*0.54+SSOUT*FRACV*FRACB*0.54
»***********!
STORAGE STAGE
K*************^
V1DOT,S1,SNH41,SN021,SN031,XA1,XI1,XNB1,XNS1,XS1,XT1=STAGE(...
0.,FR,SO ,SNH40,SN020,SN030,XAO,XIO,XNBO,XNSO,XSO,SR,SNH4R,SN02R,..
SN03R,XAR,XIR,XNBR,XNSR,XSR,ICS1,ISNH41,ISN021,ISN031,ICXA1,ICXI1,,
ICXNBI,ICXNS1,ICXS1,V1LO,V1UP,V1,FS,V1)
DXNV1=(FR*XNVR-FS*XNV1-V1DOT*XMV1)/V1
XNV1=INTGRL(ICXNV1,DXNV1)
NOSORT
ft******
* STORAGE STAGE FLOW CONTROL
.**********$***********:<
IF(STYPE)3070,3080,3090
* ONE PUMP
3070 FS=FR
GO TO 3100
* TWO PUMPS, MASS PROPORTIONAL
54
-------
3080
* TWO
3090
3095
3098
3100
SORT
FS=PROPR*F*SIN
GO TO 3100
PUMPS. PLI CONTROLLED MIXED LIQUOR
IF(TR-RCHECK)3095f3098f3098
XOESU=F*(SO-EFF*S4)*24.*KOEX/{V4*PLISET*KOES)
XDESC=LIMIT(XDESLO,XDESUP,XDESU)
XDDOTS=DERIV(0.,XDESC)
FSU=(XDESC*FP+V4*XDDOTS)/(XT1-XDESC)
FSC=LIMIT06) )
BODU=(S4+COVER*( ( XA4*XS4 )/XT4 ) )
BOD5=BODU*.63
U=(FR+FW)*0.l/A
C=INTGRL(ICC,CDOTt10)
MTT=MODINT(0.0,TRG24»1.0,MT)
XTDGT=MODINT(0.0,TRG24,1.0,XTR)
WTOT1=FW*XTR
WTOT2= ( FT4-FW-FR ) *COVER
WTQTIl=MODINT(0.0,TRG24, 1.0,WTOT1)
WTOTI2=MODINT(0.0,TRG24,1,0,WTOT2)
MTASUM=MODINT(0.»TRG24, l.,MTA)
WTCTI = WTOT!H-WTOT 12
WTOT=KTOT1<-WTOT2
FDGTl=MODINT{O.OtTRG24,l,OtFW)
CCOT,SETFLX, TFLUX fUS t XTR,THETAS, MTS, SAGE 1 f ...
SAGE2=THICK(MLSS,FT4,U,COVER)
FLUXIN=(FT4*MLSS-(FT4-FR-FW)*COVER) *0, I/A
55
-------
DO 4000 I=1,NELEM
vsm=svstc(iM
4000 SETFLXU)=C( I)*VS( I )
TFLUX(1)=U*C(1)+AMIN1(SETFLX(1),SETFLX(2))
CDOT(1)=(FLUXIN-TFLUX(1))/OX
DO 4010 I=2tM
TFLUX(I)=U*C(I)+AMINI{SETFLX(I),SETFLX CI +1))
4010 CDOT(I)=(TFLUX(I-l)-TFLUXm)/OX
COOT(NELEM)=(TFLUX(M)-U*C(NELEM))/DX
THETAS=0.
MTS=0.
DO 4030 I=1,NELEM
MTS=MTS+DX*A*10.*C(I)
4030 THETAS=THETAS+DX/(VSm+U)
XTR=C(NELEM)
IF(WTOT) 5005,5005,4990
4990 SAGE1=MTA/(WTOT*24.)
SAGE2=MT/
XNSRP=PIPE(250,ICXNS4,HCLARC,VELA,XNS4,l)
XNVRP=PIPE(250,ICXNV4,HCLARC,VELA,XNV4,1)
MLSSD=XARP-t-XSRP*XIRP-«-XNBRP+XNSRP*XNVRP
XAR=XTR*XARP/MLSSD
XIR=XTR*XIRP/MLSSD
XSR=XTR*XSRP/MLSSD
XNSR=XTR*XNSRP/MLSSD
XNBR=XTR*XNBRP/MLSSD
XNVR=XTR*XNVRP/MLSSD
MWT=INTGRL(0.0,WTOT1)
MSOUT=(FT4-FR-FW)*BODU
MSBAR,MSVAR=STAT(MSOUT,T24,TRG24)
PLI=SO*F*24.*KOEX/(MT4*KOES)
PLIBAR,PLIVAR=STAT(PLI,T24,TRG24»
INTER=INTGRL(0.,PLI)
NOSORT
IF(TIME.EQ.O.) GO TO 5050
56
-------
5050
SORT
PLIMN=INTER/TIME
CONTINUE
SAGEC,SAGEV=STAT(SAGE1,T24,TRG24)
SAGE2C,SAGE2V=STAT(SAGE2,T24,TRG24>
* CONTROLLER SEGMENT *
************************************************************************
NDSORT
IFIT24-TCHECK) 6000,7000,7000
***************************************** *****$****$,)($$$$ * « ******«***#*$
* CONTROLS WASTING FLOW RATE *
****************:
6000 IF(CTYPE) 6001,6002,6003
* PLI CONTROL TOTAL MASS
6001 FWU=(SAVE2/(SSAGE*24.)-SAVE3)/SAVE1
GO TO 7000
* PLI CONTROL AERATOR MASS
6002 FWU=-SAVE3)/SAVE1
7000 TCHECK=T24
FWC=LIMIT(FWLO,FWUP,FWU»
FW=FWC
SAVE1=XTDGT
SAVE2=MTT
SAVE3=WTOTI2
SAVE4=MTASUM
***#*********4
CONTROLS RECYCLE FLOW RATE
I*********:
IF(RTYPE) 5000,5010,5020
* CONSTANT RECYCLE
5000 FR=FAVG*FRAT
GO TO 5035
* MASS PROPORTIONAL RECYCLE
5010 FR=PROPR*F*SIN
GO TO 5035
* PLI CONTROLLED RECYCLE
5020 IFITR-RCHECKJ5025,5030,5030
5025 XDESU=F*lSO-EFF*S4)*24./(V4*PLISET*KTOD)
XDESC=LIMIT(XDESLO,XDESUP,XDESU)
XDDOTR=DERIV(0.,XDESC)
5030 RCHECK=TR
FRU=(XDESC*FP+V4*XDDOTR)/(XT1-XDESC)
FRC=LIMIT(FRLO,FRUP,FRU)
FR=FRC
5035 CONTINUE
CALL DEBUG(NDEBUG,TDEBUG)
TERMINAL
********>
* OUTPUT SECTION
57
-------
METHOD RKSFX
TIMER FINTIN= 168.,OELT=0.01,PRDEL=.1,OUTDEL=L.
PRINT XDESC,MLVSS,XT4,XA4,XS4,XI4,XT1,XAI,XSI,XI1,S1,S4,CLRCN,...
CU-10),FRU,FRC,FSU,FSC,PLI,PLIBAR,SAGEC,SAGE2C,COVER,FW,FR,FS,V1,V4,...
MTA,MTS,MT1,MT,BODU,MSOUT,MSBAR,SSAGE,XNS4,XNS1,XNB4,XNB4,MASS
LABEL GENERAL SIMULATIONS
LABEL CONSTANT VOLUME, VARIABLE RECYCLE
LABEL STORAGE VOLUME!IDS) RECYCLE RATE FOR BASE CASE(20«)
LABEL PLI= 1.0 PER DAY TOTAL MASS SRT =8.0 DAYS
OUTPUT TIME,MLVSS,XDESC
PAGE XYPL3T,WIDTH=8.,HEIGHT=5.,GROUP=<0.0,2000.),MERGE
OUTPUT TIME,COVER
PAGE XYPLOT,WIDTH=8.,HEIGHT=5.,GROUP=<0.0,25.0),MERGE
OUTPUT TIME.S4
PAGE XYPLOT,WIDTH=8.,HEIGHT=5.,GROUP=(0.0,40.),MERGE
OUTPUT TIME,BODU
PAGE XYPLOT,WIDTH=8. ,HEIGHT=5.,GROUP=(0.0,40.).,MERGE
OUTPUT TIME,PL I
PAGE XYPLOT,WIDTH=8.,HEIGHT=5.,GROUP=(0.0,4.),MERGE
OUTPUT TIME,SO
PAGE XYPLOT,WIDTH=8.,HEIGHT=5.,GROUP=(0.0,100.),MERGE
END
STOP
FUNCTION SVS(S)
C THE FUNCTION SVS CONTAINS A POLYNOMIAL FIT OF INITIAL SETTLING
C VELOCITY DATA USED IN THE CLARIFIER MODEL.
C THE REMAINING FUNCTIONS,TSS,FLOW,VBDD,VSNH4, CONTAIN FOURIER
C SERIES COEFFICIENTS FOR THE INPUT VARIABLES TOTAL SUSPENDED
C SOLIDS, INFLUENT FLOW RATE, INFLUENT SUBSTRATE CONCENTRATION,
C AND INFLUENT AMMONIA COMCENTRATION.
DATA A/.521753E-07/,B/.834793E-02/,D/-.103521E-01/,E/.419438E-02/
'C=S/1420.
SVS=SQRT(231.37/(A+B*C+D*C**2+E*C**3))
RETURN
END
FUNCTION TSS(TIME)
DIMENSION A(5),B(5),C<5)
DATA A/-.154903,-6.96097E-2,-.176173,.14660,-9.67005E-02/,
1 B/0. 127113,2. 60089E-02,-. 274343,4. 09673E-02, 2. 49002E--02/,
2 C/l.,2.,7.,14.,2l./,F/3.73999E-02/
TSS=1.
DO 10 1=1,5
THETA=F*C(I)*TIME
10 TSS=TSS*A(I)*COS(THETA)+B
-------
RETURN
END
FUNCTION VBOO(TM)
DIMENSION A(5)tB(5)tC(5)
DATA A/73.28,.4862,-2.646,5.924,-.7770/,
I B/0.,15.63t-6.886,-.0252,1.6797,
2 C/l.,5.,2.,9.,13./
F=6.28319/191
TIME=TM*2.
V80D=0.0
DO 10 1=1,5
THETA=F*TIME*(C(I)-l.)
10 VBOD=VBOD+A( I )*COS *SIN1 THETA)
RETURN
END ,
FUNCTION VSNH4CTIME)
DIMENSION A(3),B(3),C(3)
DATA A/-0.0794,0.0057,-0.0634/,B/-0.2996,-0.059,-0.0976/
DATA C/1.,2.,3./,F/0.26179/
VSNH4=1.0
DO 10 1=1,3
THETA=F*C(I)*TIME
10 VSNH4=VSNH4+A(I)*COS(THETA)*B(I)*SIN(THETA)
RETURN
END
ENDJOB •
59
-------
APPENDIX B
Raw Data for Base-Case Pilot Study
LOCATION: Influent
KEY:
1. Month
2. Day
3. Time
4. Flow Rate (manual), gpm
5. Flow Rate (continuous), gpm
6. Total Organic Carbon (continuous), mg/1
7. Total Organic Carbon (laboratory), mg/1
8. Chemical Oxygen Demand, mg/1
9. Biochemical Oxygen Demand, mg/1
10. Total Phosphorus, mg/1
11. Suspended Solids, mg/1
12. Volatile Suspended Solids
NOTE: A (-1) value designates missing data.
60
-------
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65
-------
LOCATION: Aerator
KEY:
1. Month
2. Day
3. Time
4. Total Flow Rate (continuous)r gpm
5. Dissolved Oxygen (continuous), mg/1
6.' Dissolved Oxygen (process meter) , mg/1
7. Dissolved Oxygen (bench meter), mg/1
8. Air Flow (continuous),. cfm
9. Air Flow (rotameter), cfm
10. Air Pressure, psi
11. Temperature (continuous), C
12. Temperature (manual), °C
13. pH (bench meter)
14. Suspended Solids (continuous), mg/1
15. Suspended Solids (laboratory), mg/1
16. Volatile Suspended Solids (laboratory), mg/1
17. Chemical Oxygen Demand (laboratory), mg/1
NOTE: A (-1) value designates missing data.
66
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ooooooooooooooooooooooooo
VD o**-ooooooocrooooooo*oooooooo
- ^4 r* f^ f~t ft r-j r~l <~4 r-t CVJ »-l «—* ^* «-^ f-t F-4 ^^rH^-*»H^-l'-*^-tr^'^
I I I I I I I I I I I I I I I I I I I I I I I
(TJ OOOOOOOOOOOOOOOOOOOOOOOOO
I I I I I I I
ooomootAiniAoooooooooooooooo
^>«r-^r-r-i~t-^>>ooYr
-------
LOCATION:
KEY:
1.
2.
3.
4.
Clarifier
Month
Day
Time
Blanket Level, ft.
NOTE: A (-1) value designates missing data,
71
-------
-1- -2-
-3-
-4-
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
25.
25.
25.
25.
25.
25.
25.
25,
25.
25.
25.
25.
26.
26.
26.
26.
26.
26.
26.
26.
26,
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
26.
1800.
1830.
1900.
1930.
2000.
2030.
2100.
2130.
2200.
2230.
2300.
2330.
0.
30.
100.
130.
200.
230.
300.
330.
400.
430.
500.
530.
600.
630.
700.
730.
800.
830.
900.
1000.
1030.
1100.
1130.
1200.
1230.
1300.
1330.
1400.
1430.
1500.
1530.
1600.
1630.
1700.
1730.
1800.
1830.
1900.
-1.
-1.
-1.
11.
-1.
11.
-1.
11.
-1.
11.
-1.
11.
-1.
11.
-1.
11.
*"" 1 *
11.
-1,
11.
~~" 1 *
11.
-1.
11.
-1.
11.
*"" 1*
11.
""1 *
10.
-1.
-1.
11.
-1.
11.
-1.
11.
-1.
11.
-1.
11.
-1.
11.
-1.
11.
-1.
11.
-1.
11.
-1.
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
26.
26.
26.
26.
26.
26.
26.
26.
26.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27,
27.
27.
27,
27.
27.
27,
V27.
27.
27.
27.
1930.
2000.
2030.
2100,
2130.
2200.
2230.
2300.
2330.
0.
30.
100.
130,
200.
230.
300.
330.
400.
430.
500.
530.
600.
630.
700.
730,
800.
830.
900,
930.
1000.
1030.
1100,
1130.
1200.
1230.,
1300.
1330,
1400*
1430.
1500.
1530*
1600,
1630,
1700«
1730,
1800*
1830«
1900.
1930,
2000»
11.
-1.
11.
-1.
11.
~*1 .
11.
-1.
11.
' -1.
11.
-i.
11.
-1,
11.
-1.
11.
-1.
11.
-1,
-1.
11,
-1.
11.
-1,
11.
*~1 .
11.
""* * •
11.
-1,
11.
-1.
11,
-1,
11.
-1,
11,
-1,
11.
"" L «
11.
'""* i *
11.
-i.
11.
-i.
ii.
-i.
11.
72
-------
-1- -2-
-3-
-4-
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
27.
27,
27.
27.
27.
27,
27.
28.
28.
28.
28.
28,
28.
28.
28.
28.
28.
28.
28.
28.
28.
28,
28.
28.
28.
28.
28.
28,
28,
28.
28.
28,
28.
28.
28.
28.
28.
28.
28,
28.
28.
28.
28.
28.
28.
28.
28,
28.
28.
28.
2030.
2100.
2130,
2200.
2230,
2300,
2330.
0.
30.
100,
130,
200.
230.
300.
330.
400.
430.
500.
530.
600.
630.
700.
730.
800.
830.
900,
930.
1000.
1030.
1100.
1130.
1200.
1230,
1300.
1330.
1400.
1430,
1500.
1530.
1600.
1630.
1700.
1730.
1800.
1830.
1900.
1930,
2000.
2030.
2100.
-1.
11,
-1.
11.
— 1,
11.
-1.
11,
~~1 •
11.
-1,
11.
-1.
11.
-1.
11,
~~ 1,
-1.
-1.
~ 1,
11.
-1.
11,
*"* A *
11.
-1,
11.
""" A *
11,
-1.
11.
-1,
11.
-1,
11.
-1.
11.
-1.
11.
-i.
11.
-1.
11.
"""" A »
11,
-1,
11,
-1.
11.
-1.
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
28.
28.
28,
28 o
28.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29,
29.
29,
29.
29.
29.
29.
29.
29.
29.
29.
29.
29,
29,
29.
29,
29,
29.
29,
29.
29,
29.
29,
2130.
2200.
2230,
2300.
2330,
0.
30.
100.
130.
200.
230.
300,
330.
400,
430.
500.
530,
600.
630.
700.
730,
800.
830.
900,
930,
1000.
1030,
1100,
1130.
1200,
1230,
1300.
1330,
1400.
1430.
1500,
1530.
1600.
1630,
1700.
1730.
1800*
11.
-1.
11.
-1,
11.
-I.
11,
-1.
11.
-1.
11,
-1.
11.
-1.
11.
-1.
-i.
""" 1.
11.
"""" A •
11,
~~i .
11.
-1,
11,
~~1 ,
11.
~1 .
11,
-1.
11.
»1
ill
-i.
11.
-i,
11.
-i.
11.
-i.
11.
J— * A •
73
-------
LOCATION: Recycle Line
KEY:
1. Month
2. Day
3. Time
4. Recycle Flow Rate, gpm
5. Sludge Wasting Rate, gallons/4 hours
6. Suspended Solids (laboratory), mg/1
7. Volatile Suspended Solids, mg/1
8. Chemical Oxygen Demand, mg/1
NOTE: A (-1) value designates missing data.
74
-------
— 1 —
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
— 2 —
25,
25.
25.
25.
25,
25.
25.
25.
25.
25.
25.
25,
26.
26.
26,
26.
26.
26.
26.
26.
26.
26.
26,
26.
26.
26.
26,
26.
26.
26.
26.
26,
26.
26.
26,
26.
26.
26.
26.
26.
26.
26.
26.
26.
26,
26.
26.
26.
26.
26.
-3-
1800.
1830.
1900,
1930.
2000.
2030.
2100.
2130.
2200,
2230.
2300,
2330.
0.
30,
130.
200.
230.
300.
330.
400,
430.
500,
530.
600.
630.
700.
730.
800.
830.
900.
930.
1000.
1030.
1100.
1130.
1200.
1230,
1300,
1330.
1400.
1430.
1500.
1530.
1600,
1630.
1700.
1730.
1800,
1830.
1900,
_4_
-1.0
9.6
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
9.6
-1,0
-1,0
-1.0
-1.0
-1.0
-1.0
9.6
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
9.6
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
9.6
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1,0
9.6
-1.0
-1.0
-1.0
-1.0
-1.0
-1,0
-1.0
9.6
-1.0
-5-
-1.0
338.1
-1.0
-1.0
-1.0
-1,0
-1.0
-1.0
-1.0
411.6
-1.0
-1.0
-1,0
-1.0
-1.0
-1.0
367.5
-1.0
-1.0
-1.0
-1,0
-1,0
-1.0
-1.0
352,8
-1.0
-1.0
-1,0
-1,0
-1.0
-1.0
-1.0
323.4
-1.0
-1.0
-1.0
-1,0
-1.0
-1.0
-1.0
338. 1
-1.0
-1.0
-.1.0
-1.0
-1.0
-1.0
-1.0
352.8
-1.0
-6-
-1.
-1.
"" ' 1 *
'"" 1 •
2340.
-1.
-1.
-1.
-1.
-1.
-1.
J~" 1 *
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""" 1 •
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2650.
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-1.
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""" i •
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185,0,
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~lo
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— 1 ,
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-1.
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-1.
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75
-------
-1-
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
-2-
26.
26.
26.
26.
26.
26.
26.
26.
26.
27.
27.
27.
27,
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27o
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
27.
-3-
1930.
2000.
2030.
2100.
2130.
2200.
2230.
2300.
2330.
0.
30.
100.
130.
200.
230.
300.
330.
400.
430.
500.
530.
600.
630.
700.
730.
800.
830.
900.
930.
1000.
1030.
1100.
1130.
1200.
1230.
1300.
1330.
1400.
1430.
1500.
1530.
1600.
1630.
1700.
1730.
1800.
1830.
1900.
1930.
2000.
. -4-
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
9.5
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
9.6
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
9.6
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
9.6
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
9.6
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
9.6
-1.0
-1.0
-1.0
-5-
-1.0
-1.0
-i.o
-1.0
-1.0
-1.0
352.8
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
352.8
-1.0
-1.0
-1.0
-1,0
-1.0
-1.0
-1,0
367.5
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
308.7
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
352.8
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
323.4
-1.0
-1.0
-1.0
-6-
-1.
3240.
-1.
-1.
-1.
-1.
-1.
-1,
— 1.
-1.
""" i *
-1.
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""" J» •
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3110.
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3767.
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3767.
76
-------
-1-
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
APRIL
-2-
27.
27,
27*
27.
27.
27.
27.
28.
28.
28,
28,
28.
28,
28,
28.
28.
28.
28.
28,
28.
28.
28.
28.
28.
28.
28.
28.
28.
28.
28.
28.
28.
28.
28.
28.
28.
28,
28,
28.
28.
28.
28.
28.
28.
28.
28.
28.
28.
28.
28.
-3-
2030.
2100,
2130.
2200.
2230.
2300,
2330,
0,
30,
100.
130,
200.
230.
300.
336,
400.
430,
500.
530,
600,
630.
700.
730.
800,
830.
900.
930.
1000,
1030,
1100.
1130.
1200.
1230,
1300,
1330.
1400.
1430,
1500,
1530,
1600.
1630.
1700.
1730.
1800,
1830,
1900.
1930,
2000.
2030.
2100,
-4-
-1,0
-1.0
-1.0
-1,0
9.6
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1,0
9,6
-1.0
-1.0
-1,0
-1.0
-1.0
-1.0
-1.0
9,6
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
9.6
-1.0
-1,0
-1.0
-1,0
-1.0
-1.0
-1.0
9.6
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
9.6
-1.0
-1.0
-1,0
-1.0
-1.0
-5-
-1.0
-1.0
-1.0
-1.0
323.4
-1.0
-1,0
-1.0
-1.0
-1.0
-1.0
-1.0
352.8
-1.0
-1.0
-1.0
-1,0
-1.0
-1,0
-1,0
367.5
-1.0
-1,0
-1.0
-1.0
-1,0
-1.0
-1,0
367.5
-1.0
-1.0
-1.0
-1.0
-1.0
-1,0
-1.0
352.8
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
308.7
-1.0
-1.0
-1.0
-1.0
-1.0
-6-
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-i. •
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-1.
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3430.
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-1.
-1.
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-i.
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3580,
-1,
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-1-
APRIL
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-2-
28.
28.
28.
28.
28.
29.
29,
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
'29.
29.
29.
29.
29.
29.
29.
29.
29.
29.
-3-
2130.
2200.
2230.
2300.
2330.
0.
30.
100.
130.
200.
230.
300.
330.
400.
430.
500.
530.
600.
630.
700.
730.
800.
830.
900.
930.
1000.
1030.
1100.
1130.
1200.
1230.
1300.
1330.
1400.
1430.
1500.
1530.
1600.
1630.
1700.
1730.
1800.
-4-
-1.0
-1.0
9.6
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
•1.0
9.6
-1.0
•1.0
-1.0
-1.0
•1.0
•1.0
•1.0
9.6
•1.0
•1.0
1.0
-1.0
•1.0
1.0
•1.0
9.6
1.0
•1.0
1.0
1.0
•1.0
1.0
1.0
9.6
1.0
•1.0
•1.0
1.0
•1.0
1.0
1.0
-5-
-1.0
-1.0
308.7
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1,0
367.5
-1.0
-1.0
-1.0
-1.0
-1.0
-1.0
-1,0
367.5
-1.0
-1.0
-1.0
-1.0
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-1.0 '
-1.0
252.8
-1,0
-1.0
-1.0
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-1.0
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323.4
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78
-------
LOCATION: Storage Chamber
KEY:
1. Month
2. Day
3. Time
4. Dissolved Oxygen,(continuous), mg/1
5. Dissolved Oxygen (process meter), mg/1
6. Dissolved Oxygen (bench meter), mg/1
7. Air Flow (continuous), cfm
8. Air Flow (rotameter), cfm
9. Air Pressure, psi
10. Suspended Solids (laboratory), mg/1
11. Volatile Suspended Solids, mg/1
12. Chemical Oxygen Demand, mg/1
NOTE: A (-1) value designates missing data.
79
-------
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81
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82
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-------
LOCATIONS Effluent
KEY:
1. Month
2. Day
3. Time
4. Turbidity (continuous), JTU
5. Turbidity (laboratory), JTU
6. TOC (continuous), mg/1
7, TOC (laboratory), mg/1
8. Soluble TOC (laboratory), mg/1
9. COD (laboratory), mg/1
10. Soluble COD (laboratory), mg/1
11. BOD, mg/1
,12. Soluble BOD, mg/1
13. Total Phosphorus, mg/1
14. Suspended Solids (laboratory), mg/1
15. Volatile Suspended Solids (laboratory), mg/1
NOTE; A (-1) value designates missing data.
85
-------
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APPENDIX C
Raw Data for Instantaneous F/M Controlled Pilot Study
LOCATION: Influent
KEY: v
1. Month
2. Day
3. Time
4. Flow Rate (manual), gpm
5. Flow Rate (continuous), gpm
6. Total Organic Carbon (continuous), mg/1
7. Total Organic Carbon (laboratory), mg/1
8. Chemical Oxygen Demand, mg/1
9. Biochemical Oxygen Demand, mg/1
1,0. Total Phosphorus, mg/1
11. Suspended Solids, mg/1
12. Volatile Suspended Solids
NOTE: A (-1) value designates missing data..
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LOCATION: Effluent
KEY:
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4. Turbidity (continuous)r JTU
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NOTE: A (-1) value designates missing data.
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APPENDIX D
Raw Data for Constant Loading Pilot Study
LOCATION: Influent
KEY:
1. Month
2. Day
3. Time
4. Flow Rate (manual), gpm
5. Flow Rate (continuous), gpm
6. Total Organic Carbon (laboratory), mg/1
7. Total Organic Carbon (laboratory), mg/1
8. Chemical Oxygen Demand, mg/1
9. Biochemical Oxygen Demand, mg/1
10. Total Phosphorus, mg/1
11. Suspended Solids, mg/1
12. Volatile Suspended Solids
NOTE: A (-1) value designates missing data.
124
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129
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LOCATION: Aerator
KEY:
1. Month
2. Day
3. Time
4. Total Flow Rate (continuous) gpm
5. Dissolved Oxygen (continuous), mg/1
6. Dissolved Oxygen (process meter) , xng/1
7. Dissolved Oxygen (bench meter), mg/1
8. Air Flow (continuous), cfm
9. Air Flow (rotameter), cfm
10. Air Pressure, psi
11. Temperature (continuous), C
12. Temperature (manual), °C
13. pH (bench meter)
14. Suspended Solids (continuous), mg/1
15. Suspended Solids (laboratory), mg/1
16. Volatile Suspended Solids (laboratory), mg/1
17. Chemical Oxygen Demand (laboratory), mg/1
NOTE: A (-1) value designates missing data.
130
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LOCATION:
KEY:
1.
2.
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Clarifier
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NOTE: A (-1) value designates missing data.
135
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1830.
1900.
1930.
2000.
2030.
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2130.
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30.
100.
130.
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LOCATION: Recycle Line
KEY:
1. Month
2. Day
3. Time
4. Recycle Flow Rate, gpm
5. Sludge Wasting Rate, gallons/4 hours
6. Suspended Solids (laboratory), mg/1
7. Volatile Suspended Solids, mg/1
8. Chemical Oxygen Demand, mg/1
NOTE: A (-1) value designates missing data.
138
-------
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141
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-1-
JULY
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142
-------
LOCATION: Storage Chamber
KEY:
1. Month '
2. Day
3. Time
4. Dissolved Oxygen (continuous), mg/1
5. Dissolved Oxygen (process meter) , ing/1
6. Dissolved Oxygen (bench meter), mg/1
7. Air Flow (continuous), cfm
8. Air Flow (rotameter), cfm
9. Air Pressure, psi ,
10. Suspended Solids (laboratory), mg/1
11. Volatile Suspended Solids, mg/1
12. Chemical Oxygen Demand, mg/1
NOTE: A (-1) value designates missing data.
143
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148
-------
LOCATION: Effluent
KEY:
1. Month
2. Day
3. Time
4. Turbidity (continuous) , JTU
5. Turbidity (laboratory), JTU
6. TOG (continuous), mg/1
7, TOG (laboratory), mg/1
8. Soluble TOG (laboratory), mg/1
9. COD (laboratory) f mg/1
10. Soluble COD (laboratory), mg/1
11. BOD, mg/1
12. Soluble BOD, mg/1
13. Total Phosphorus, mg/1
14. Suspended Solids (laboratory), mg/1
15. Volatile Suspended Solids (laboratory), mg/1
NOTE: A (-1) value designates missing data.
149
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-600/2-80-131
3. RECIPIENT'S ACCESSION-NO.
4. TITLE AND SUBTITLE
CONTROL STRATEGIES FOR THE ACTIVATED SLUDGE PROCESS
5. REPORT DATE
August 1980 (Issuing Date}__
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO.
Thomas K. Keinath and Bryan S. Cashion
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Environmental Systems Engineering
Clemson University
Clemson, S.C. 29631
10. PROGRAM ELEMENT NO.
1BC611 SOS#2
11. CONTRACT/GRANT NO.
R864357-01-0
12. SPONSORING AGENCY NAME AND ADDRESS
Municipal Environmental Research Laboratory-Cin., OH
Office of Research and Development
U.S. Environmental Protection Agency
Cincinnati. OH 45268
13. TYPE OF REPORT AND PERIOD COVERED
Final Report-3/75-6/77
14. SPONSORING AGENCY CODE
EPA/600/14
15. SUPPLEMENTARY NOTES
Project Officer: Walter W. Schuk (513) 684-2621
16. ABSTRACT '~ ~
The focus of this research centers on strategies to control both mean solids
retention time (MSRT) and food to microorganism ratio (F/M). Two solids inventory
control strategies were examined: (1) control of the recycle flow rate when provision
las been made for a fixed volume storage chamber; and (2) control of the recycle
flow rate when provision has been made for a variable volume storage chamber. Both
strategies were evaluated by simulation using a structured model. The first strategy
was also evaluated through a pilot study conducted at the Blue Plains Pilot Waste
Treatment Facility. The pilot plant investigation was conducted in two phases. The
first was an uncontrolled study to establish base-line conditions. The second phase
was the actual application of the control strategy. Extensive data collection
allowed comparison of the two studies and evaluation of the utility of the control
trategy.
7.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED/TERMS
c. cos AT I Field/Group
Automation
Automatic Control
Instruments
Waste Treatment
Process Control
Activated Sludge
13B
8. DISTRIBUTION STATEMENT
RELEASE TO PUBLIC
19. SECURITY CLASS (ThisReport)"
UNCLASSIFIED
21. NO. OF PAGES
173
20. SECURITY CLASS (Thispage)
UNCLASSIFIED
22. PRICE
EPA Form 2220-1 (9-73)
I63
*U.S. GOVERNMENT PRINTING OFFICE: 1980—657-165/0118
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