ABSTRACT - University of Georgia
Transcript of ABSTRACT - University of Georgia
CHARACTERIZATION AND IMPLEMENTATION OF A
UV/O3 PILOT-SCALE PROTOTYPE FOR DISINFECTING AND RECYCLING
POULTRY CHILLER WASTEWATER
by
SEAN S. IRELAND
(Under the Direction of S. Edward Law)
ABSTRACT
Synergistic bactericidal performance consistently demonstrated by combined ozone and ultraviolet irradiation treatments on poultry chiller water with bench-scale reactors has led to the detailed engineering design and fabrication of a mobile, self-contained, 16 gpm (60 L/min) prototype for testing such technology on a flow-through basis. The individual system components of this advanced oxidation process (AOP) have been integrated by means of a programmable logic controller (PLC) using ladder logic and human-machine interface software. Initial prototype analysis considered solids removal efficiency of a formulated suspension of selected bone meal (ρ = 1.67 g/cm3, median diameter = 57 µm) demonstrating a 57% solids removal efficiency while onsite chiller water (median diameter = 49 µm) had a 29% solids reduction. Microbiological analysis indicates that bactericidal efficacy of the AOP is limited by the presence of such solids. System modifications for extended solids removal are necessary to prepare wastestreams for effective deactivation of suspended pathogens. With such preconditioning, this AOP method could readily be expanded to remediate many other processing wastewaters.
INDEX WORDS: Poultry chiller water, Ozone, UV irradiation, Pilot-scale prototype, PLC,
Ladder logic, Human-machine interface, Solids removal, Advanced oxidation process, Pathogenic microorganisms, Food safety, Water conservation
CHARACTERIZATION AND IMPLEMENTATION OF A
UV/O3 PILOT-SCALE PROTOTYPE FOR DISINFECTING AND RECYCLING
POULTRY CHILLER WASTEWATER
by
SEAN S. IRELAND
B.S.E.H., The University of Georgia, 2001
B.S.B.E., The Univesity of Georgia, 2001
A Thesis Submitted to the Graduate Faculty of The University of Georgia in Partial Fulfillment
of the Requirements for the Degree
MASTER OF SCIENCE
ATHENS, GEORGIA
2004
© 2004
Sean S. Ireland
All Rights Reserved
CHARACTERIZATION AND IMPLEMENTATION OF A
UV/O3 PILOT-SCALE PROTOTYPE FOR DISINFECTING AND RECYCLING
POULTRY CHILLER WASTEWATER
by
SEAN S. IRELAND
Major Professor: S. Edward Law
Committee: Mark A. Harrison Takoi K. Hamrita
Electronic Version Approved: Maureen Grasso Dean of the Graduate School The University of Georgia December 2004
ACKNOWLEDGEMENTS
To my major professor, Dr. S. Edward Law, I am grateful for the many lessons he has
taught me, both engineering and life related; and to Michael Diaz, my predecessor, mentor, and
friend, I will never be able to repay them for the knowledge I have gained while working in the
Applied Electrostatics Laboratory.
To my advisory committee, I thank Drs. Mark A. Harrison and Bruce Upchurch for
always being there when I needed them and lightening the challenges of my problems; for not
only assisting, but explaining matters and encouraging my progress. To Dr. Takoi Hamrita for
her willingness to step in and assist me as a committee member even when near the final stages
of my thesis completion.
I am grateful for those in Dr. Harrison’s Food Science & Technology Laboratory,
particularly Ruth Ann Rose-Morrow, who have generously assisted with procedures and have
repeatedly adjusted their schedule to accommodate the needs of my project.
To our industry supporter, Gold Kist, Inc., for providing overflow chiller water and
power connections during onsite prototype testing. Their contributions and grant funding from
the Georgia Food Processing Advisory Council (FoodPAC) is what made this project possible.
Thanks to all the staff and graduate students in the Biological and Agricultural
Engineering Department, especially Javier Sayago, Geoff Smith, and Fayette Yang, for sanity
and sympathy when times were difficult. Also, to the very many other true friends that have
supported me every step of the way, even when I was unable to be a friend in return. I could not
have come this far with one less.
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Finally, I am grateful for my family which has been so very far away in miles, but close
to me in my heart and thoughts. Communication has sometimes been limited, but they have
always been there for me regardless of the circumstances.
Above all, I am thankful to GOD. It is with HIS patience and love that I have been able to
endure life’s challenges, presenting me with many amazing people and experiences to
accomplish everything associated with this project and all else. Thank you!
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TABLE OF CONTENTS
Page
ACKNOWLEDGEMENTS........................................................................................................... iv
LIST OF TABLES....................................................................................................................... viii
LIST OF FIGURES .........................................................................................................................x
CHAPTER
1. INTRODUCTION ...............................................................................................................1
2. OBJECTIVES ....................................................................................................................3
3. LITERATURE REVIEW......................................................................................................4
3.1 Poultry Water Use and Cost ...............................................................................4
3.2 Chiller Water Characteristics .............................................................................5
3.3 Regulation History .............................................................................................7
3.4 Methods Developed for Water Treatment..........................................................8
3.5 UV/O3 Possibilities and AEL Research ...........................................................11
4. THEORETICAL ANALYSIS ..............................................................................................13
4.1 Factors Affecting Treatment Efficiency...........................................................13
4.2 Direct UV/O3 Reaction.....................................................................................14
4.3 Hypothesis ........................................................................................................16
5. PILOT-SCALE TREATMENT SYSTEM..............................................................................17
5.1 Detailed Flow-Through Process.......................................................................17
5.2 Sensors and Controls Description ....................................................................21
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6. PLC CENTRALIZED SYSTEMS INTEGRATION ................................................................24
6.1 Hardware Communications and Setup .............................................................24
6.2 RSLogix Ladder Logic Programming..............................................................25
6.3 RSView Human-Machine Interface .................................................................30
7. EVALUATION OF SOLIDS REMOVAL ..............................................................................41
7.1 Testing of Formulated Suspension ...................................................................42
7.2 Poultry Chiller Water Treatment ......................................................................48
8. ANALYSIS OF MICROBIOLOGICAL TREATMENTS...........................................................51
8.1 Introduction ......................................................................................................51
8.2 Sampling Procedure .........................................................................................52
8.3 Preliminary Data...............................................................................................54
8.3 Final Results .....................................................................................................57
9. OVERALL CONCLUSIONS...............................................................................................66
REFERENCES ..............................................................................................................................69
APPENDICES
A. OZONE DOSAGE CALCULATIONS ..................................................................................75
B. PLC LADDER DIAGRAM................................................................................................77
C. HMI TAG TABLE ........................................................................................................110
D. TSS TABULAR DATA ..................................................................................................113
E. CHILLER WATER STATISTICAL ANALYSIS ..................................................................115
F. ABBREVIATIONS .........................................................................................................122
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LIST OF TABLES
Page
Table 3.1 Poultry processing production averages and water related expenses .............................5
Table 3.2 Relative power of selected common oxidants. .............................................................10
Table 7.1 Particle options considered and tested for prototype evaluation with formulated
solids suspension..........................................................................................................42
Table 7.2 List of filters, surfactants, and defoamers used for testing adequate suspension
of bone meal particulate without flocculation or filter collection of defoaming
agent.............................................................................................................................45
Table 7.3 Two separate analyses of effective bone meal density for determining the
weighted average used during formulated suspension testing.....................................46
Table 8.1 Latin square experimental design for bactericidal testing of three different levels
of ozone (0, 39, 78 mg/L) and two levels of UV irradiation (on, off) for oxygen-
sparged samples ...........................................................................................................57
Table 8.2 Averaged aerobic plate counts (APC) for all 6 replications of chiller water
treatments showing treatment levels, direct counts, and differences in counts
between inlet vs. reactor and inlet vs. column .............................................................59
Table 8.3 Averaged counts (TC and E. coli) for all 6 replications of chiller water
treatments showing treatment levels, direct counts, and differences in counts
between inlet vs. reactor and inlet vs. column .............................................................61
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Table 8.4 Averaged turbidity (NTU) for all 6 replications of chiller water treatments
showing treatment levels, direct counts, and difference between inlet vs.
reactor and inlet vs. column.........................................................................................63
Table D.1 TSS for formulated suspension testing ......................................................................113
Table D.2 Chiller water TSS evaluation .....................................................................................114
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LIST OF FIGURES
Page
Figure 3.1 Bactericidal effect of three different treatments on Salmonella Typhimurium
inoculated poultry-broiler overflow chiller wastewater as functions of
treatment duration.......................................................................................................12
Figure 4.1 Reaction cycles for photolytic ozonation ....................................................................15
Figure 5.1 Pilot-scale prototype for UV-enhanced wastewater ozonation ...................................17
Figure 5.2 Prototype solids removal processes (a. hydrosieve, b. settling tank,
c. hydrocyclone) .........................................................................................................18
Figure 5.3 Prototype treatment stages following equalized wastewater division by a
1-to-3 manifold (a. venturi ozone injector, b. UV reactor, c. contact columns).........19
Figure 5.4 Transport trailer for mobile, pilot-scale prototype. .....................................................20
Figure 5.5 Figure 5.5 Prototype monitor panel (a. low concentration ozone monitor,
b. rotameters and pressure gauge, c. high concentration ozone monitor,
d. turbidity monitor, e. dissolved ozone monitor, f. ORP meter, g. UV radiometer
and multiplexer, h. ozone generator, i. UV power supplies)......................................22
Figure 6.1 Prototype control panel (a. circuit breaker switches, b. PLC, c. solenoids,
d. motor relay switch, e. uninterruptible power supply) ...........................................25
Figure 6.2 Human-machine interface for control and operation of the ozonation-
irradiation prototype ...................................................................................................31
Figure 6.3 HMI temperature trend display for the flowstream inlet and outlet ............................36
x
Figure 6.4 Pressure PID-processing screen created with RSView software ................................37
Figure 6.5 Datalogging window for various datasets within the HMI program...........................38
Figure 6.6 Display screen for controlling flush cycles during prototype cleaning and
sanitizing.....................................................................................................................39
Figure 7.2 Particle size distribution comparison between averaged poultry chiller
water samples and a combination of Espoma® (sieved) and Tiger Brand®
bone meals in aqueous suspension .............................................................................44
Figure 7.3 Weighted particle size distributions characterizing TSS removal for formulated-
suspension testing of pilot-unit’s solids removal capabilities ....................................47
Figure 7.4 Weighted particle size distributions characterizing TSS removal for chiller
water testing of pilot-unit’s solids removal capabilities.............................................49
Figure 8.1 Collected-sample bags on ice with oxygen feedlines (sparge tubing to the
right of the sample rack).............................................................................................53
Figure 8.2 Log reductions (i.e., outlet concentrations subtracted from post-solids removal
quantities) of wastewater bacteria populations (APC, Total Coliform, and E. coli)
resulting from various treatment levels of O3 and/or UV on-line at poultry-
processing plant (non-sparged samples).....................................................................56
Figure 8.3 Log-based reductions of averaged aerobic plate counts (APC) for indicated
UV/O3 treatments of chiller water as sampled after both the UV reactors and
contact columns (standard deviation bars shown)......................................................60
Figure 8.4 Reductions in turbidity of chiller water resulting from indicated UV/O3
treatments as sampled after the UV reactors and after the contact columns
(standard deviation bars shown).................................................................................64
Figure B.1 PLC flow-through block diagram...............................................................................77
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CHAPTER 1
INTRODUCTION
Consumer demand for a comparatively healthy, low-priced meat product has led to a vast
increase in U.S. annual poultry consumption, doubling over the past ~30 years to a present-day
per capita consumption of more than 71 lbs boneless, trimmed weight per year (USDA, 2004).
Along with this increase, a great deal of attention has been focused on the poultry industry
including demands for higher product quality and safety. However, increasing product standards
has lead to escalating resource consumption. Case in point, Perkins (1999) stated that HACCP-
related (Hazard Analysis Critical Control Point) guidelines have resulted in an additional water
usage between 2 to 5 gallons per bird.
Given an overall average water use of 1.3 MGD per plant (USPEA, 2001), poultry
facilities welcomed a 1987 amendment to the Federal Poultry Products Inspection Act which
allowed regulated recycling of poultry chiller water (USDA, 1995). The relatively lax regulations
of 1987 were significantly strengthened in 1999 and have phased out older diatomaceous earth
filters (USDA, 1999a). Several treatment methods have attempted to achieve these stringent
requirements but most have produced limited results in comparison to effective filtration with
ozone (O3) application, a process applied to many different water reuse systems. Despite its
obvious benefits, the introduction of this autoxidative compound had been limited until full
acceptance by the FDA as a food additive in 2001 (Rice and Graham, 2001).
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While several research papers have demonstrated the effectiveness of ozone to treat
poultry chiller water, work respectively presented and published by Diaz and Law (1997, 2001)
was the first to explore the application of ozone and ultraviolet (UV) irradiation simultaneously,
allowing for the beneficial production of highly reactive free radicals. Using benchtop batch
reactors, they clearly showed that the combined effect of these treatment methods outperforms
the additive effect when used separately. As an example of this data, UV/O3 application to E.
coli inoculated chiller water produced an additional 1.7 Log reduction over the added individual
treatments, confirming a synergistic effect had occurred.
The potential of this combined advanced oxidation process (AOP) spawned the design
and fabrication of a UV/O3, sanitary-grade, pilot-scale prototype for the treatment of onsite food-
processing wastewaters which is capable of a flowrate of 60 L/min (16 gpm) (Law and Diaz,
2001). Entry water initially courses through three individual suspended-solids removal
components (hydrosieve, settling tank, and hydrocyclone) before equally dividing into three
separate treatment channels for the independent application of UV and/or ozone. Each parallel
process line has identical flowrate and pressure to provide direct comparisons between treatment
methods.
This thesis initially evaluates literature related to poultry chiller water and its related
reconditioning methods, further analyzing the factors that affect UV and ozone efficiency.
Thereafter the constructed pilot-scale treatment system is described, and its ability to treat
poultry chiller water is hypothesized. Discussion follows with the primary thesis goal of using
PLC programming to integrate the many process components of the prototype. It proceeds to
analyze its solids removal aspects and treatment capabilities by evaluating statistical results.
Conclusions are then derived about the prototype’s current performance, and recommendations
are made for possible modifications and future plans to treat other processing wastewaters.
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CHAPTER 2
OBJECTIVES
(1) Develop and apply programmable logic controller (PLC) technology to integrate the physical
controls, treatment methods, and monitoring equipment of a UV/O3 pilot-scale prototype into
a collective wastewater treatment system.
(2) Experimentally characterize the operational performance of the suspended-solids removal
components within the system during the treatment of a formulated wastewater supply as
well as processing-plant chiller water.
(3) Determine the engineering efficiency and bactericidal efficacy of the integrated treatment
system across a range of ozone concentrations with and without simultaneous UV irradiation
during the treatment of overflow chiller water onsite at a local poultry-processing plant.
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CHAPTER 3
LITERATURE REVIEW
3.1 Poultry Water Use and Cost
In 2001, the U.S. Poultry and Egg Association (USPEA) conducted a survey of 32
chicken processing plants throughout the United States and determined that, on average, facilities
operate 250 days a year, processing 200,000 birds/day, and consume 1.3 MGD of fresh water
(USPEA, 2001). This production typically results in 5-10 gallons of wastewater per bird, with an
average of approximately 6.7 gallons. Estimates suggest that, given over 8.5 billion chickens
slaughtered in 2001, greater than 50 billion gallons of wastewater, heavily laden with BOD, has
undergone some sort of treatment process.
Clearly, this enormous consumption of water costs the poultry industry a large amount of
money (Table 3.1). With an average fresh-water acquisition expense of $1.77/1000 gallons,
producers are collectively paying $95 million annually (USPEA, 2001). Additionally,
wastewater treatment and discharge cost the industry even more money; the USPEA survey
reports an average $2.81/1000 gallons for wastewater disposal. Assuming that all water entering
the plant requires such a fee, this expense equates to $151 million annually (USPEA, 2001).
Expenses for poultry production related solely to water use each year total $246 million (viz.,
$4.58/1000 gallons) while still excluding energy demands and BOD removal (~20¢/lb) (NCCES,
1999a). Although this corresponds to only about 3¢ cents per bird, clearly the total yearly
expense for national poultry production is quite staggering.
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Table 3.1 Poultry processing production averages and water related expenses (USPEA, 2001).
Cost/1000 gal Plant Daily Averages National Yearly Totals Number of birds processed -- 200,000 8 billion Amount of water consumed -- 1.3 million gal 54 billion gal aWater cost $1.77 $2,300 $95 million Wastewater treatment cost $2.81 $3,650 $151 million Total water expenses $4.58 b $5,950 $246 million a Calculated by assuming an average of 6.7 gallons per bird b This value excludes any extra expenses (e.g., BOD removal, energy demands)
Approximately 10% of this large amount of water is used to lower the temperature of the
birds to <4.4 °C (USPEA, 2001; Sheldon et al., 1989). Once the birds have been defeathered,
eviscerated, and rinsed, they typically travel for 30-40 minutes through large, open tanks filled
with counter-flowing, chilled water. Water is continuously being added and removed from the
vessel, thereby creating a flow-through system where the average plant chills and dispenses
130,000 gallons each day. Not only is a large amount of water consumed during this process, a
significant amount of energy is required to chill the water to near freezing temperatures. Reports
indicate that this costs facilities greater than $1.00/1000 gallons, increasing the total expense
devoted solely to chilling the chicken carcasses to over $181,000 annually for the average
chicken processor (NCCES, 1999b).
3.2 Chiller Water Characteristics
The chilling process is inherently a major concern for the poultry industry. Not only does
the process consume a significant amount of water and energy, it has often been proven to be the
source for microbial cross-contamination. A national survey conducted by the Food Safety and
Inspection Service (FSIS) showed that the number of Salmonella-positive broilers entering the
plant was 3-5% before processing and had increased to 36% after processing (Green, 1987), a
5
fact affirmed by Lillard (1989). Additional research has shown that this problem most frequently
originates from the immersion chiller and occurs with other microorganisms such as
Enterobacteriaceae (Lillard, 1990; Daengprom et al., 1993; Veerkamp, 1990).
Common microbiological characteristics of poultry chiller water are as follow: 3.1-5.9
Log10/mL aerobic plate count, 1.0-3.4 Log10/mL coliform, and 2.0-2.3 Log10/mL Escherichia
coli with some facilities reporting the presence of Salmonella (Blank and Powell, 1995; Tsai et
al., 1986; Diaz et al., 2001; Diaz et al., 2002; Lillard 1989). Further analyses show these
additional parameters: COD 1731-2074 mg/L, total suspended solids 361-486 mg/L, and 41.2-
50.8% light transmission at 500 nm (Diaz et al. 2001, 2002). Additionally, Schade et al. (1990)
determined the proximate analysis of poultry chiller water from one tested facility to contain:
0.35% total solids, 0.19% fat (54% of solids), 0.12% ash (34%), and 0.011% Kjedahl nitrogen
(3%).
In a study by Tsai et al. (1987), several poultry chiller water samples from three different
facilities were determined to have twelve saturated and unsaturated aliphatic aldehydes (listed
from least to greatest quantity): pentanal, decanal, 2,4-nonadienal, trans-2-undecenal, 2,4-
decadienal, heptanal, trans-2-decenal, trans-2-octenal, octanal, trans-2-nonenal, nonanal, and
hexanal, these last two comprising almost 50% of the total amount. The presence of such
compounds is a result of autoxidation of unsaturated fatty acid esters (e.g., oleic, linoleic,
palmitoleic, and linolenic acids) which are commonly found in chicken lipids. The presence of
these aldehydes is important because chicken carcasses are permitted to gain up to 8% body
weight via water uptake in an immersion chiller (USDA, 1973). As a result, product quality
could be affected.
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3.3 Regulation History
Because of the strong concern for cross-contamination, poultry processors have
determined the chilling process to be part of the HACCP program, a contamination prevention
plan which first gained interest in the late 1950’s but became mandated by FSIS in 1996 (USDA,
1999b). This regulated guideline system was designed to reduce chemical, physical, and
microbiological hazards by evaluating overall food processing systems at critical control points
where hazards are likely to occur. As a result of the program, microbial numbers have been
reduced, but water demands have significantly increased (Pierson, 1999).
The European Economic Community (EEC) was so concerned with the microbial
problem posed by chillers that they issued a rule banning water immersion chilling after January
1978 (Veerkamp, 1990). Although the EEC doesn’t enforce the ban due to the introduction of
other regulations, many poultry processors switched their cooling stage to air-chilling and
evaporative air-chilling, despite the fact that water immersion uses less water and energy than
these other chilling methods (Campbell et al., 1983). These same concerns have led the USDA to
require a minimum of 0.5 gallon of water added to the chiller for each bird that passes through
the process (Chang, et al., 1989).
Despite safety concerns related to immersion chillers, the industry has been seeking new
ways to reduce their expenses by recycling chiller water, mainly due to its significant
contribution to expenses incurred and water consumed. As early as the mid-70’s, studies have
been conducted for poultry water reuse using diatomaceous-earth filtration (Lillard, 1978). These
studies set the framework for the first recycling regulations which were established by FSIS in
1987 (Chang, et al., 1989). Such regulations required a microbial removal of 60% as well as a
maintenance of 60% light transmission when compared to entry waters (USDA, 1995).
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Since the idea of chiller water recycling was conceived, significant interest has been
devoted to the use of ozone for such purpose. However, only recently did regulations permit such
use. In 1982, the FDA approved a petition from the International Bottled Water Association
considering ozone to be generally recognized as safe (GRAS), but still prohibited ozone to be
directly applied to all other food products unless an appropriate food additive petition was
approved (Rice and Graham, 2001). In 1997 the FDA non-specifically relaxed the restrictions on
ozone by stating that any organization willing to affirm a “substance” as GRAS when contacting
foods is free to do so, assuming the organization accepts full responsibility for its actions (Rice
and Graham, 2001). Although implementations of such technology had already begun, expansion
was still rather slow until the FDA accepted and published a food additive petition on June 26,
2001 (Rice and Graham, 2001). As a result of process approval by FDA, ozone status now
allows for the direct application of ozone to food products.
However, during the battle for approval of ozone as a food additive, chiller recycling
standards were significantly increased. Currently, the following criteria are required for water
reuse: total plate count <500 CFU/mL, total coliform and fecal coliform absent, turbidity <5
NTU, and >1 ppm free chlorine (USDA, 1999a). This regulatory standard became effective on
January 26, 2000 (McGrane et al., 2001).
3.4 Methods Developed for Water Treatment
There have been several different methods developed for the treatment of poultry chiller
water other than ozone addition. Some attempts have simply added higher concentrations of
chlorine to the chiller water (Waldroup et al., 1992) or trisodium phosphate (Ismail et al., 2001)
while another experiment attempted adding salts in conjunction with electric stimulation (Li et
8
al., 1994). Because many facilities have reported adding chlorine at levels of 20-50 ppm, there
has been strong concern about the formation of trihalomethanes, proven carcinogens (Kim et al.,
1999). Although all of these procedures somewhat reduced microbial loads, they did not address
the concern for water reuse.
Filtration has occasionally been successful for achieving both microbial reduction and
water reuse, it being often combined with mild chlorination (USEPA, 1978; Lillard, 1978;
USEPA, 1983; Chang, et al., 1989; Chang and Sheldon, 1989). However, there are several
problems associated with filtration methods: filters require frequent addition of filter aid, media
must be recharged or discarded on a regular basis, adequate microbial reduction is not always
achieved, and filters can serve as a medium for bacterial growth (Waldroup et al., 1993).
Additionally, filtration rates diminish over time due to solids accumulation.
The USEPA investigated the use of other methods to remove solids from chiller water
(USEPA, 1978) and concluded that neither cyclonic desludgers, vibrating screens, or flotation
cells combined with centrifugal waste concentration effectively achieved solids removal. The
study also investigated the use of ultraviolet radiation in conjunction with diatomaceous-earth
filters, but determined it was not a necessary, cost-effective addition.
None of the afore mentioned filtration and chlorination systems would be adequate for
today’s regulations without significant improvements. In search for a better system, a great deal
of attention has been focused on the use of filtration in conjunction with ozonation. Although
ozone has seen numerous applications over the last century, U.S. research on poultry chiller
water only began in 1985 with work by Sheldon et al. (1985), demonstrating very promising
results. After further research and approval from the USDA, the first ozonation system was
9
implemented in a turkey processing plant in 1991 (Waldroup et al., 1993). Since that time,
several patents have been developed and treatment systems applied.
As compared with chlorine, there are several benefits associated with ozone treatment. It
is well documented that ozone has a 52% greater oxidation potential than chlorine (Table 3.2),
and is considered to be safer for workers and the environment alike. Although ozone has the
potential to create disinfection byproducts, the effect is far less pronounced than when using
chlorine (Schade et al., 1990). The disinfection process of chlorine occurs after the ion diffuses
into the living cell itself, while ozone immediately attacks cell walls and lipids thereby leading to
cell lysis (Waldroup et al., 1993). This results in a more effective deactivation of some pathogens
such as Escherichia coli and Cryptosporidium (EPRI, 1999).
Table 3.2 Relative power of selected common oxidants.
Compound Oxidation potential
(volts)
Relative power
vs. chlorine Fluorine 3.06 2.25 H ydroxyl radical (OH·)a 2.80 2.05
A tomic oxygen (O·)a 2.42 1.78
O zone 2.07 1.52
C hlorine 1.36 1.00
Diatomic oxygen 0.40 0.29 a Reactive species formed when ozone decomposes in water.
Although it has been reported that microbial populations within chiller water slightly
increase as the day progresses, as with any chiller system, studies have shown that populations in
ozonated water and on the carcasses were reduced, thereby extending the product shelflife by as
10
much as two days (Waldroup et al., 1993; Vineet et al., 1995). Additionally, several findings
indicate that ozone does not affect product organoleptic properties (Mulder, 1995).
3.5 UV/O3 Possibilities and AEL Research
In 1995 at the University of Georgia’s Applied Electrostatics Laboratory (AEL), Law
began investigating a unique approach for the treatment of poultry chiller water (Law, 1995) and
in subsequent years more fully developed the process via thesis research by Diaz (Diaz 1996;
Diaz et al., 1997, 2001, 2002). Although this method had only been executed with bench-scale
batch reactors at that time, evidence indicated remediation of chiller waters to be greater than all
other previous treatment systems.
Their research utilized the synergistic effect of combining ozone’s autoxidative potency
with the photoreactive action of ultraviolet irradiation. Each individual destructive component is
a strong reactant by itself, but when the two are combined, the collective reaction can be as much
as 102 to 104 fold greater (Prengle et al., 1975). Results from a study by Diaz and Law (1997)
showed that O3/UV treatment of E. coli in ozone demand-free water produced a 50-fold
additional synergistic reduction when compared to the additive capabilities. Furthering their
research, they conducted tests on unscreened overflow chiller water which produced a >0.8
Log10 increased reduction of APC bacteria (Diaz et al., 2001). Additionally, when treating
Salmonella Typhimurium inoculated wastewater, they detected a >1.1 Log10 increased reduction
(Figure 3.1).
The synergistic effect produced by these agents within an aqueous medium is due to the
production of free radicals. When using UV low-pressure mercury vapor lamps with a peak
irradiance of 253.7 nm, ozone undergoes strong photochemical excitation, leading to the
11
production of oxygen and hydroxyl radicals. Additionally, UV irradiation is able to generate
more free radicals than ozone from neutral and refractory molecules, thus making the over-all
reaction go much faster (Diaz, 1996). The mechanism for these extremely reactive substances,
which are more destructive than either of the products’ precursors, was first determined by
Peyton and Glaze (1988) and is further discussed in Chapter 4.
ParametersUV dosage: 295 mW/LOzone dosage: 5.11 mg/L·min
O2/O3
O2/O3/UV
O2/UV
O2
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
0 1 2 3 4 5 6 7 8
Treatment Time (min)
Log
CFU
/mL
Figure 3.1 Bactericidal effect of three different treatments on Salmonella Typhimurium inoculated poultry-broiler overflow chiller wastewater as functions of treatment duration (Diaz et al., 2001).
The use of UV irradiation alone is effective via the production of irreparable numbers of
thymine dimers within the cellular DNA, ultimately leading to the inability for cells to replicate.
Ozone’s destructive capabilities affect the cell membrane itself, causing cell lysis, but is also
known to destroy dehydrogenating enzyme systems, respiratory systems, sulfhydryl groups,
genetic material, and to alter polypeptide chains (Kim et al., 1999). These two modes of
pathogen destruction are further enhanced by the production of free radicals, which are known to
have much faster reaction rates than ozone but work to kill cells in much the same manner.
12
CHAPTER 4
THEORETICAL ANALYSIS
4.1 Factors Affecting Treatment Efficiency
Of the several factors which affect the energy efficiency and bactericidal efficacy of a
UV/O3 treatment system, foremost is the presence of organic matter known to inhibit ozone and
hydroxyl radicals from reacting with microorganisms (Kim et al., 1999). Additionally, the
physical attachment of microorganisms onto suspended matter may hamper the accessibility
afforded for reactants to kill pathogens (Kim et al., 1999). These particles not only weaken the
effect of the direct reactants, but can also absorb and block UV irradiation before allowing ozone
to be utilized for free radical production. Removing dissolved and suspended organic matter
provides several advantages which minimize ozone requirement, optimize ozone usage, utilize
organic material for rendering, and improve the disinfection capability of chlorine residual
(McGrane et al., 2001).
Other treatment-limiting factors include the concentration of ozone in the gaseous state
and the rate at which it is applied, as well as ozone’s mass transfer capability into water. Typical
ozone mass transfer follows saturation curve response (Denis et al., 1992) and yield a water-
solubility 13-times greater than oxygen (Hill and Rice, 1982). Concentration and rate of ozone
application is limited only by generation-equipment available, typically achieving up to 15 wt%
O3 in oxygen feedgas streams.
13
Physiochemical operating parameters that affect ozone concentration include
temperature, pH, and pressure. A decrease in the temperature of an aqueous medium creates an
exponential increase in ozone’s solubility and hence reactivity (Horvath et al., 1985). For effluent
chiller water temperatures, typically <15°C, ozone solubility will be significantly enhanced over
typical room temperatures. Increased pressure within the treatment system (e.g., 10 psi) will also
enhance ozone solubility due to its direct positive linear relationship (Masschelein, 1982). The
influence of pH however, will not pose a significant alteration in the treatment capabilities.
When using UV/O3 in a water of low pH, reaction times are significantly faster (Peyton et al.,
1982), yet typical chiller water pH does not vary far from 7.0 (Lillard, 1978).
There are also mechanical parameters that can affect ozone’s reactivity with a selected
substrate. If treatment-gas bubble size is rather large, less gaseous surface area inhibits ozone’s
transfer into an aqueous phase, plus the bubbles will rise to the surface of a vessel at a greater
rate (Masschelein, 1982). When wastestream flowrates are high (fast diffusion rates), ozone
concentrations increase (Kuo and Yocum, 1982). Therefore, considering that ozone injection into
the prototype system is accomplished via venturi gas injectors at a high liquid velocity (1.17
m/s), interfacial area and mass transfer will be optimized for thorough mixing to occur.
4.2 Direct UV/O3 Reaction
The general pathway by which ozone photolysis (~254 nm) is achieved in an aqueous
medium can be represented by the following simplified equations (Peyton and Glaze, 1988):
O3 + H2O O2 + H2O2 [1] hv
H2O2 2 OH· [2] hv
H2O2 HO2- + H+ [3]
O3 + HO2- 2 O2 + OH· [4]
14
Here it is seen that photolysis of aqueous ozone yields hydrogen en peroxide (H2O2) which th
igure 4.1) can potentially achieve 102 to
04 fol
works with UV photons and ozone to form hydroxyl radicals (OH·). A major advantage to
photolytic ozonation is that there is more than one pathway for hydroxyl radical generation,
allowing for the reaction system to adjust the mechanistic pathway to suit reaction conditions.
Ultimately, the hydroxyl radical is the principal active species in photolytic ozonation, being
derived from approximately ⅓ of the ozone transferred into the water during steady state
conditions (Peyton and Glaze, 1998; Denis et al., 1992).
The mechanistic pathways of ozone photolysis (F
1 d increases in oxidative capabilities (Prengle et al., 1975). Although case studies by Diaz
et al. (1997, 2001, 2002) have demonstrated a lower potential (i.e., 50-fold), the combined
treatment method is still much stronger than the additive effects of the individual agents. The
direct reactions of molecular ozone and ultraviolet photoexcitation, combined with free radical-
mediated destruction, will provide increased decontamination of poultry chiller waters, given an
adequate removal of organic material.
Figure 4.1 Reaction cycles for photolytic ozonation (Peyton and Glaze, 1988).
15
4.3 Hyp
f a UV/O3 pilot-scale flow-through prototype for the onsite treatment of poultry
othesis
The use o
chiller wastewater will demonstrate that photolytic ozonation’s disinfection capabilities can be
scaled up to greatly enhance the speed and extent to which chiller water may be recycled, as
compared to the additive effect of ultraviolet radiation and ozonation used separately.
16
CHAPTER 5
PILOT-SCALE TREATMENT SYSTEM
5.1 Detailed Flow-Through Process
Due to the impressive results from the earlier AEL work, funding was obtained for the
design and fabrication of a UV/O3, sanitary-grade, pilot-scale prototype for the continuous flow-
through treatment of poultry chiller water (Law and Diaz, 2001). This prototype accommodates a
60 L/min (16 gal/min) wastewater stream, a quantity approximating 10% of the chiller water
discharged from a ⅓-million bird per day poultry-processing plant (Figure 5.1).
Figure 5.1 Pilot-scale prototype for UV-enhanced wastewater ozonation.
17
The prototype is equipped with three suspended-solids removal processes intended to
enhance treatment efficiency (Figure 5.2). Initially the water cascades over a 0.5-mm screen size
hydrosieve and drains by gravity into a settling tank, coursing successively through four parallel
channels for a retention time of 2 minutes before passing into a variable speed centrifugal pump
for pressurized flow throughout the remainder of the system. Water then tangentially enters a
hydrocyclone for the centrifugal removal of micron-sized particles, achieving a 98% mass
removal of all particulates of 74 µm diameter and nearly complete removal of most larger sizes
for mass density in the vicinity of ρ = 2.6 g/cm3. Solids accumulated within the hydrocyclone are
periodically purged for two seconds at 8-min intervals by pneumatic actuation of a ball valve
located at the base of the collection sump.
a. c.
b.
Figure 5.2 Prototype solids removal processes (a. hydrosieve, b. settling tank, c. hydrocyclone).
Water exiting the hydrocyclone then enters a 1-to-3 manifold for equalized division of
treatment water into three parallel channels, allowing for independent application of O3 and/or
UV irradiation (Figure 5.3). Once divided, an ozonated oxygen stream can then be introduced
18
into any selected liquid pathway by an in-line venturi injector being controlled by a manually
adjustable rotameter. A water-cooled ozone generator, capable of producing up to 15 wt% O3
from oxygen feedgas cylinders, supplies the ozone. Immediately following gas injection (~800
ms), the wastewater is retained within a UV reactor for a period of 40 seconds. Here ultraviolet
radiation may be administered at a peak emittance of 254 nm by means of two coaxial, low-
pressure mercury vapor lamps for the production of the highly reactive hydroxyl radical
(nominal lamp surface output is 30 mW/cm2).
b.
Figure 5.3 Prototype treatment stages following equalized wastewater division by a
c. a.
1-to-3 manifold (a. venturi ozone injector, b. UV reactor, c. contact columns).
After specified treatment applications, water from each pathway resides for 8.5 minutes
within its separate contact column to maximize the reaction of remaining ozone with suspended
pathogens. Herein, elevated pressure is maintained at 10 psi by regulation of an air-actuated
throttling valve, located after water reconverges into a 3-to-1 manifold. Treatment effectiveness
is finally evaluated in part by measurements taken with sensing equipment and monitors,
including dissolved ozone, outlet temperature, turbidity, and redox potential. Thereafter water
19
may be passed through a centrifugal degasser for removal of residual ozone and its elimination
by a manganese dioxide ozone-destruct unit before exhausting to the atmosphere. However,
considering ozone is now an accepted food additive (Rice and Graham, 2001), this step is not a
requirement. The treated wastewater stream then leaves the pilot-scale prototype at atmospheric
pressure and is pumped back into the processing plant by means of a submersible pump placed
within a rectangular holding tank beneath the self-contained prototype system.
Figure 5.4 Transport trailer for mobile, pilot-scale prototype.
The overall prototype covers a 145 × 305 cm footprint which stands 173 cm high (4 ft 9
in. × 10 ft × 5 ft 8 in.) and is sized to conveniently fit within a mobile trailer which also houses a
small laboratory space (Figure 5.4). This assembly allows for convenient setup and breakdown at
virtually any onsite location, only requiring inputs of electricity and chiller water for treatment
evaluation.
20
5.2 Sensors and Controls Description
A variety of sensors and controls are incorporated within the pilot-scale prototype for
automation of selected features and overall maintenance of operation performance. Many of the
sensors and controls are associated with individual monitors in addition to signal transfer with
the PLC and have been mounted onto one collective panel for quick reference and control
(Figure 5.5). The processing plant’s wastewater is delivered to the onsite prototype by an exterior
centrifugal pump actuated by a conductivity water-level sensor mounted atop the pilot unit’s
settling tank. This sensor also regulates the position of the pneumatic inlet ball valve, turning on
the transfer pump and opening the inlet valve as water is required. Once inside the unit, inlet
water temperature is detected with a resistive temperature device (RTD#1) mounted within the
sump of the hydrosieve; this temperature can be compared with that from RTD #2 positioned at
the outlet, thereby determining the system total heat input.
After main-pump flow acceleration, the electrically-conductive process water passes
through the applied magnetic field of an electromagnetic flowmeter to produce a voltage signal
that is then converted to the necessary analog signal for PLC feedback control of the main-pump
operation to maintain prescribed liquid flowrate and pressure. Solids-laden water is periodically
removed automatically from the hydrocyclone’s sump by another pneumatically actuated ball
valve. Upon leaving the hydrocyclone the wastewater is split into three channels for O3 and/or
UV application. The ozone generator utilizes frequency-controlled electric discharge to create
ozone in oxygen feedgas and is concentration-regulated using measurements taken from an
ultraviolet-absorption ozone monitor. Each UV reactor has two mounted photodiode sensors, one
manufacturer-provided for simple determination of relative lamp intensity and another installed
21
for directly quantifying radiation intensity. Measurements from each reactor are alternately
collected each minute by means of a multiplexer and stored for later analysis.
g h
a b
c d
e f
i
Figure 5.5 Prototype monitor panel (a. low concentration ozone monitor, b. rotameters and pressure gauge, c. high concentration ozone monitor, d. turbidity monitor, e. dissolved ozone monitor, f. ORP meter, g. UV radiometer and multiplexer, h. ozone generator, i. UV power supplies).
Following treatment applications and contact-column residence, the pressure of the
recombined water is sensed by a piezoresistive transducer providing feedback to control the
throttling valve. Two sidestreams of water, ~1 L/min each, are then used for outgoing detection
of dissolved ozone concentration and turbidity. The first stream passes through a counter-current
packed column which strips ozone from the water, passing this ozone-laden air into another
ozone monitor. The second stream passes through a relatively quiescent horizontal chamber for
nearly 3 minutes for bubble extraction before continuing into a turbidity sensor. This allows
light-refracting bubbles to be removed from the water before a direct-light scatter turbidimeter
22
senses the quantity of particles suspended in the treated water. After RTD#2, a final sensing
element measures the oxidation-reduction potential (ORP) of the outlet water, this being useful
for indirect measurement of the outgoing ozone concentration.
Additionally, one of the most important aspects of the collective system is the strategic
placement of wastewater sampling ports throughout the flow-through process to test
microbiological treatment effectiveness. Locations include: prior to the inlet ball valve, after the
hydrocyclone (for evaluating solids removal), after UV reactors, and after residence contact
columns. Chapter 8 provides further relevant discussion.
23
CHAPTER 6
PLC CENTRALIZED SYSTEMS INTEGRATION
Control and overall monitoring of the prototype operation is conducted within a
centralized human-machine interface (HMI) program that has been created for interaction with
the PLC operating system. Here ladder logic programming has provided an integration of
individual subassemblies to work as a collective network for the overall management of the
comprised components.
6.1 Hardware Communications and Setup
Physical connections between the centralized processing unit and the laptop computer
were made possible through the DH-485 connection on the SLC 5/03 main processor. With the
combination of available hardware, three individual drivers may be used for this interface: a
PCMK card directly installed in the computer along with its associated cable, a PIC converter for
RS-232 connection on the laptop, or an AIC+ for cord extension and data conversion to also link
with the 9-pin com-port on the laptop. The latter of these methods is the primary path used for
maximized response time and reduced communication interruption, although the other two
assemblies provide for adequate available connection backup should the data transfer ever fail.
To link the programming software with the centralized processing unit, the computer
must be configured through the Rockwell program known as RSLinx. This allows for
recognition of assigned com-ports and communication types for association with and between
24
required software. However, within both the ladder program and HMI, such designations must
also be made to recognize the setup of the collective communication process.
6.2 RSLogix Ladder Logic Programming
Sensing equipment and control operations throughout the pilot-scale prototype are
monitored and maintained via a programmable logic controller (PLC) comprised of several
individual processing modules for the reception and delivery of prototype component signals
(Figure 6.1). The framework for this control is made possible by ladder logic programming
created with RSLogix software and is fully listed in Appendix B along with detailed comments
regarding the operation of each rung of information.
a
b
d c
e
Figure 6.1 Prototype control panel (a. circuit breaker switches, b. PLC, c. solenoids, d. motor relay switch, e. uninterruptible power supply).
25
Nearly all communication between the processor and prototype components, other than
simple actuation, is sent by 4-20 mA signals to and from each associated accessory. Rungs
within the ladder logic programming allow this information to be scaled to units of user interest
and include the following instruments: high-concentration ozone monitor (0.00-15.00 wt.%),
electromagnetic flowmeter (0.00-94.64 L/min), pressure transducer (0.0-100.0 psi), low-
concentration ozone monitor (0.000-5.000 ppmv), dissolved ozone monitor (0.000-10.00 mg/L),
turbidity meter (0.000-400.0 NTU), and ORP meter (±1500 mV). Two other forms of data
received by the PLC include ASCII information from the UV radiometer and resistance values
from the platinum element within the RTDs.
Data from the radiometer is sent to the PLC via RS-232 serial communication and is
translated into floating point numeric values by several lines of programming code for string
selectivity and mathematical operations. This allows for simplified numeric display within the
human-machine interface (HMI) program for illustrating UV lamp intensity trends and also
minimizes efforts needed for data transfer and interpretation during later analysis. The
radiometer alternates between each sensor according to an added combination of bit values
within the ladder programming, selecting the appropriate multiplexer channel on demand.
Readings are constantly scaled within the radiometer for its respective sensor calibration factor,
yet only one value is collected by the PLC each minute to allow for necessary settling before
ASCII data transfer.
Operations involving routine actuation include the control of hydrocyclone purge timing,
discussed earlier, as well as the delivery of process water to the pilot-unit. Due to the high
sensitivity of the water level sensor, the relay switch repeatedly opens the hard-wired inlet ball
valve in short bursts when only mild water undulations occur within the settling tank, a near
26
constant scenario induced by entry water. To remove this undesirable effect from the control of
the transfer pump, a delay was encoded within the programming so that the level sensor must be
at its current state for one full second before engaging or disengaging the supplied power, thus
eliminating rapid power cycling that can damage the pump over time.
The most challenging attributes of the ladder program are the PID loops (proportional-
integral-derivative) used to maintain desired entry values for the process flowrate, ozone delivery
concentration, and contact column pressure. Such programming utilizes an extensive series of
embedded algorithms and entered parameter values for computing the necessary signal output
intensity of the process variable (e.g., throttling valve) while constantly receiving feedback from
the control variable (e.g., pressure transducer) and adjusting accordingly. The primary user-
determined constants that are necessary for proper algorithm computation include gain, integral,
derivative, and loop update with each of these parameters interacting with one another, often
varying the response from all factors when a single value is altered. The complicated process of
tuning a PID loop can be assisted with additional expensive software, but is often conducted by
trial and error with general process understanding, particularly when only a select few are to be
tuned.
The tuning process requires the observation of the control variable signal, process
variable response, and desired component setpoint for proper adjustment of necessary parameters
to achieve the desired response from the feedback loop. This is most conveniently achieved by
visual observation of real-time graphic display laid out within an HMI program. Typical
response for a set of PID constants may be ideal for maintenance at steady-state but not for
process fluctuation adjustment, lagging in response time or reaction intensity (i.e., over-damped),
while other situations produce intense responses that do not allow for setpoint settling (i.e.,
27
under-damped). Extensive literature can be found on the topic of PID tuning but ultimately each
loop is specific to the selected operation, requiring ingenuity and creativity on the part of the
programmer.
The first PID loop encountered along the flow process receives an input signal from the
electromagnetic flowmeter for control of the main pump drive. Placement of the “magmeter”
was chosen to minimize the distance between the process variable and control variable for
enhanced feedback response while still maintaining adequate pipe length for reduced turbulence
through the magnetic field. Allowing for a close proximity between the output sensor and
operating receiver is essential to maximize the control of any PID subassembly.
Induction of the O3/O2 flowrate is manually adjusted by needle-valve rotameters,
however ozone concentration is dependent upon control of the ozone generator via feedback
provided by the high-concentration ozone monitor. Although these two devices are closely
situated, necessary purge time within the monitor is a limiting factor for immediacy of returned
values. Nonetheless, PID programming still allows for control of the delivered ozone
concentration with proper entered parameters.
The piezoresistive pressure transducer, mounted immediately downstream of the contact
columns, provides the necessary feedback for position control of the pneumatic throttling valve,
releasing and applying compressed air as needed to maintain the user-entered pressure setpoint.
The sensor in this case has an overwhelming response sensitivity that requires time averaging to
remove the large erroneous amplitude obtained from typical signal reception. Programming
collects and adds together the sensor reading every 50 ms for 10 counts before providing a half-
second average for processing within the PID loop and presentation of more meaningful data.
28
After the completion of each water treatment test, additional rungs added to the end of the
ladder program can be initiated for automated assistance of the cleaning and sanitizing
procedure. While the overall process and programming is somewhat complex, several sets of
rungs repeat their operation to simplify and condense the procedure as much as possible.
Collectively, the series allows for rinsing the prototype with full-flow of fresh water through the
drain of each sequential component of the system before an overall final rinse and eventual
closed loop circulation of selected chlorinated detergent or acid sanitizer.
Once the flush procedure is initiated, the pump drive is latched into manual operation to
escape automatic processing from the PID loop and further steps are suspended while waiting for
the inlet solenoid to close, indicating that the settling tank, previously rinsed and vacuumed
clean, is now full of water. The initial stages cause the sequencing of a 20-second flush period
with the pump drive at maximum output followed by a 70-second drain time while the pump
remains idle. This is repeated four times through the automatically opened hydrocyclone ball
valve and waits for the user to engage the next stage. The hydrocyclone’s pneumatic valve then
closes and the UV reactors and contact columns follow the same series of steps, but with manual
closure of drain valves before each successive stage is activated. At this point the program enters
a new set of commands that energize the main pump at 100% output for 45 seconds, afterward
pausing to check the water level of the settling tank. If the water is of adequate depth, the pump
re-engages, repeating this process ten times to completely fill the prototype with water. The next
activated stage provides the same operation for a final rinse. Finally, after the outlet is manually
placed in the closed loop position, the next stage will circulate the water with added cleaning or
sanitizing agent for a length of 45 minutes.
29
Programming also allows for the entire flush procedure to pause at any given moment,
forcing the pump to stop while allowing the process to remain in the same stage and also retain
the number of completed cycles within the given step. This action causes all flushing and
draining timers to be reset yet holds the accumulated time for the closed loop stage. The
characteristics of the pause button are embedded throughout the ladder program and are detailed
to this extent to ensure that each set of components is thoroughly flushed clean, requiring each
stage to pass through a minimum number of cycles before continuing the overall process. Of
course, provisions have also been made to abort the entire flush procedure as well, resetting all
timers, counters, bits, and pump controls.
The last few rungs of the ladder program conduct no demanding operations, but instead
are solely for the purpose of animated figures within the HMI program. These indicate when
each stage of the flush procedure is complete and allow for 4-second cycling of various images
for aesthetic operations.
6.3 RSView Human-Machine Interface
Ladder logic programming provides a skeletal structure for the overall processing
network, but the HMI created within RSView 32 is what enables the user to readily adjust the
system, quickly view all data in one concentrated location, achieve data acquisition, and display
real-time data trends. The completion of this software precludes the user ever having to re-
explore the lengthy, complex series of the if-then-else statements within the ladder program
focusing solely on the illustrated display screens of the HMI (Figure 6.2).
30
Figu
re 6
.2 H
uman
-mac
hine
inte
rfac
e fo
r con
trol a
nd o
pera
tion
of th
e oz
onat
ion-
irrad
iatio
n pr
otot
ype.
31
6.3.1 Tag Database
While the ladder program is constantly reiterating all values and bits within their assigned
data files, the HMI program only uses specified addresses selected by the user for data collection
and internal processing within the laptop computer. Any of the processed data within the PLC
that is required for HMI operation must be assigned a tag name and data type for the address of
interest, along with other associated, ancillary parameters (i.e., minimum and maximum values,
labels, possible scaling, units, and a description). Each tag is held within a collective database
(Appendix C) and can be linked to various processes within the program such as actuation, value
observation/alteration, PID parameter adjustment, and animation, ultimately monitoring and
controlling the entire prototype system.
Digital tags have two possible states, true or false, while most tags are analog and can
have a range of values between specified limits. The other possible form of data is in string
format to permit the transfer of alpha-numeric characters as a set series. All varieties of data are
incorporated into the graphic display of the HMI, but only some are viewed in their direct
numeric form, while others may indicate appearance, position, activity, or initiate a response.
6.3.2 Graphics Display and Animation
The primary viewing screen (Figure 6.2) illustrates the wastewater flow-through process
of the prototype across the upper portion of the graphic with the monitor panel in the lower left
portion and the most essential data and operations presented in the remaining lower right. Each
pixel and simulated font was created using the graphic editor provided, often accomplished while
magnified at the maximum viewing capacity before presentation as seen by the user. This
provides an extraordinarily realistic image of the prototype closely scaled to the real-life
components.
32
Most values of interest, such as various sensor readings and entry values, are displayed
on the primary screen to collectively analyze the prototype in one concentrated location. Where
possible, actual monitor readings are re-displayed on their respective graphic representation (i.e.,
ozone monitors, turbidity meter, and ORP sensor) and sensor readings have been distributed
across the flow-through diagram as well (flowrate, pressure, plus remaining time before the
hydrocyclone purge).
Several animated features have also been added to the display to indicate various
situations of the process for both aesthetic reasons and to serve as necessary illustrations of a
given process. When the inlet valve is open, the inlet arrow will change to a light blue color with
moving particles and will also highlight the indicators labeled ‘Solenoid #1’ and ‘Level Meter’ on
the graphic control panel. If programming and hard-wired communication between the level
sensor and the PLC fail, the solenoid light will remain off when the settling tank water level
drops. After the level sensor detects low water for the ladder-programmed delay of one second,
the hydrosieve will display falling water and may indicate that the ‘Transfer Pump’ is on,
depending on the state of the automation buttons. Normally the transfer pump automatically
operates according to the level sensor, however when the AUTO/MANUAL button is latched, the
pump can be manually controlled with the ON/OFF button.
The hydrocyclone sump displays the seconds of time remaining before the hydrocyclone
purges. This number is shown as black when the ‘Cycle Initiation’ button is ON, and red when the
button is OFF, alerting the user whether the hydrocyclone is set to purge. When the valve opens,
the number disappears and water is shown to pour from the base of the sump for the allotted
2-second duration. This operation may also be accomplished when the ‘Latch Open’ button is
33
depressed, although as a safety feature established in the ladder program, this action is only
possible while the ‘Cycle Initiation’ is engaged.
The flow-through diagram also rotates the needle position of the inline pressure gauges
that are mounted both before and after the UV reactors. Although these gauges do not send
sensory information to the PLC, the second set of gauges have been linked to the pressure
transducer to illustrate the approximate pressure prior to the contact columns. Also, given that
the pressure prior to the venturi injectors is proportional to the pressure following the UV
reactors, a roughly approximated factor of 4 is applied to the transducer average to position these
gauges as well. Despite this imprecise representation, standard operating conditions (i.e., 10.0 psi
inside the contact columns) show these gauges display a fairly correct representation of the
observed 40 psi gauge position.
For user visualization, indicating lights have been placed directly beside UV sensor
readings to illustrate the position of the UV multiplexer channel at any given time. Before the
light changes to the following channel, the data is collected and displayed as a floating-point
value in µW/cm2, shifting between each sensor every minute. The latch button located directly
beside these values allows for manual operation of the multiplexer such that the ON position
automatically changes between channels, while the OFF position permits the user to manually
rotate a dial on the multiplexer to select the sensor of choice, although preventing interruption of
data collection.
Also animated on the flow-through diagram is the blue outlet arrow. When the averaged
pressure transducer reading is above 2 psi, its appearance is much like that of the inlet arrow, but
is otherwise seen as a constant brown. This display requires water to have reached the pressure
34
transducer, located near the end of the process line, for significant period before treated water is
shown to be flowing through the prototype outlet.
6.3.3 Data Trends
All of the relevant analog data displayed on the main user interface is collected and
stored within RSView for the duration of the operated project and is presented within created
graphic illustrations. By simply moving the mouse pointer across the screen, highlighted boxes
will appear around various process components, monitors, and panel labels that separately link to
related pop-up windows, accessible by clicking the left mouse button. Several sets of boxes will
open the same graph. For example, the high concentration ozone monitor, panel label, and each
of the three venturi injectors will all open the same window for display of the ozone
concentration coming from the ozone generator.
Figure 6.3 illustrates, for example, the temperature-trend display; all other trend windows
have the same features. Once the prescribed window is opened, data will begin to scroll across
the screen, although the presentation can be altered in several ways. The time scale of the x-axis
can be adjusted to read any period of collected data by scrolling forward or backward through
time and quickly reset to actively processed values, as indicated by the available buttons. The
time range can also be redefined by moving the slider bar along its track or by entering specific
values other than the standard 300-second allotment. The y-axis has similar features that also
provide a varied span and scale within the range of the tag limits.
35
Figure 6.3 HMI temperature trend display for the flowstream inlet and outlet.
6.3.4 System Integration and PID Control
Three buttons located on the lower left of the graphic control panel (PUMP, PRESSURE, and
OZONE) have been used for tuning the process control PID loops and can monitor their response
to setpoint alteration and system fluctuations. The pressure display (Figure 6.4) covers a fixed
60-second period for comparison between the user-selected setpoint, pressure transducer,
averaged pressure, and mA signal for the throttling valve position. Trendlines are scaled across
the full height of the y-axis, but displayed values are associated with the selected tag from the
associated legend, having minimum and maximum limits set within the graph programming.
Of user interest is the ability to enter setpoint values within the pop-up windows or on the
software control panel, both of which display the process variable in close proximity, however,
enhanced control for each of the feedback loops is available within the detailed display. Here the
control variable can also be operated in manual mode by adjusting the control output to the
36
desired percent level. This step is often necessary to override automated systems and eliminates
any variation in the output signal to the controlled device.
Figure 6.4 Pressure PID-processing screen created with RSView software.
6.3.5 Data Acquisition
All of the tags assigned to the RSView program are available for data logging and
storage, but to eliminate such a cumbersome amount of unnecessary data, categories of the most
important data were arranged into three reduced models entitled basics, actions, and PID loops.
Each of these categories can be controlled individually or as a collective group located within the
data log display window (Figure 6.5), opened by clicking the DATA LOG button on the main
screen. The basic data model is set to log each minute and consists of tags for all of the prototype
monitors and sensors. Action data is only logged every 15 minutes or when the state of the
assigned tags, like the hydrocyclone purge valve and PID setpoints, change their value. Finally,
PID loop parameters are solely recorded when a particular value changes.
37
Operations for management of these models is arranged in four columns of buttons and is
the same for each one, the final column facilitating simultaneous action of all three models. The
first two rows of buttons allow for the model(s) to begin or end logging data. In the event that
data transfer is interrupted and must be stored into the assigned ODBC backup files, the
following two buttons allow for the pathway to switch back and re-merge the secondary file to
the original destination. Finally, the last row of buttons enables the user to take a “snapshot” of
the model’s tags at any desired moment. There is also a box available for string input that is
exceptionally useful for recording time-marked comments about the prototype process during
treatment tests.
Figure 6.5 Datalogging window for various datasets within the HMI program.
During primary data logging, all of the recorded data are sent to respectively grouped
model tables for tags, floating numeric values, and string information, all located within a
designated MSAccess project. These lengthy tables can then be rearranged and assimilated by
conducting coded queries for selection of a desired time frame and specified tags. Rearranged
data is transferred to MSExcel for ease of data manipulation and computation prior to statistical
analysis.
38
6.3.6 Flush Cycle
Operation of the cleaning and sanitizing procedure is controlled within the flush cycle
panel (Figure 6.6) and has been significantly discussed in Chapter 5. The user interface has been
automated as much as possible and has been simplified to only five operation buttons. After the
hydrosieve and settling tank have been emptied and manually cleaned, the flushing process is
engaged by depressing the START FLUSH button and sequentially progresses to each following
stage by clicking the NEXT STAGE button. Each time a stage is completed, the indicator light will
flash and an audible alarm on the laptop will sound to alert the user of the flush status, both can
be disabled by clicking OK. The number of flush cycles within each stage that have been fully
completed is presented in the upper right portion of the window, displaying an integer up to 4 for
the first three stages and up to 10 for ‘System Filling’ and ‘Final Rinse’. During the ‘Closed Loop’
portion of the process a timer will count away the remaining time in seconds before the 45-
minute duration is completed.
Figure 6.6 Display screen for controlling flush cycles during
prototype cleaning and sanitizing.
To provide a visual aid of how the program is progressing, indicator lights are not only
set up to illustrate the given stage, but also show the prototype status within each cycle and
39
throughout the process for determining whether the settling tank is filling (‘Inlet Open’), the
pump is operating (‘Flushing’), or the system is ‘Draining’. The entire process can be paused at
any time or completely aborted, and, to advance to any desired stage, repeated activation NEXT
STAGE button is all that is required.
40
CHAPTER 7
EVALUATION OF SOLIDS REMOVAL
Effective treatment of process waters is highly dependent upon the removal of suspended
solids to maximize UV transmittance and minimize the presence of oxidative-compound
scavengers. To evaluate the performance of the three solids removal components of the
prototype, a controlled test with simulated chiller water was developed by suspending carefully
selected particles in water and passing the suspension through the system, collecting samples
before and after the hydrosieve, settling tank, and hydrocyclone. A similar test was also
conducted onsite with poultry chiller water, all samples being analyzed for particle size
distribution and total suspended solids (TSS) removal.
7.1 Testing of Formulated Suspension
Before analyzing the performance of the prototype on actual poultry chiller water, a
controlled formulated particle suspension was created from carefully selected particles and was
used for initial prototype evaluation for TSS removal. This allowed replicable test waters to be
passed through the solids removal components to yield consistently reproduced data for
comparison with future onsite test waters.
7.1.1 Particle Selection
Three characteristics were considered for formulation of the modeled test waters:
inability to dissolve in water, a challenging low mass density, and similar particle size
41
distribution to that of poultry chiller water. Initially a list of insoluble options was derived for
comparison with other selection criteria (Table 7.1). Most densities were typically greater than
2-3 times that of water, while those that provided a possible challenge for particle removal, such
as polymer microspheres, were excessively expensive. Ceramic beads also looked promising, but
their extremely low wettability caused them to float when placed in water.
Table 7.1 Particle options considered and tested for prototype evaluation with formulated solids suspension.
Tested Materials Density (g/cm3)
Limestone Powder 2.7 Blasting Impact Beads 2.6
Sand 2.6 Glass Beads 2.5
Human Bonea 2.35 Bone Meal (surfactant)b 2.02
Diatomaceous Earth 2.0 Bone Meal (warm water)c 1.67 Polymethylmethacrylate 1.19
Polystyrene Microspheres 1.06 Ceramic Beads 1.05 Glass Spheres 0.34 Blood Meal --
Ceiling Texture -- a Not a tested material, for reference only. b Displacement tested with a solution of DI water, 0.1% Trtiton-X-100
surfactant, and 0.2% Helena Silicone “Foam Buster”. c Displacement tested with warm water and agitation (52°C, 180 rpm).
The other criterion used to select test materials was particle size distribution similarity to
poultry chiller water whereby particulate waters were analyzed with a Malvern Mastersizer, an
instrument based upon the Mie theory for laser-light scattering. From known properties of the
tested particles (i.e., refractive index, density, and absorption), numerous photodiodes register a
light-scatter “fingerprint” from the aqueous suspension and translate this to a particle size
42
distribution. Initially, materials were properly mixed by gentle tumbling for dry samples or a
magnetic stirrer for chiller water. These were then directly added to a small volume sample
dispersion unit in amounts able to achieve adequate light obscuration while being suspended by
an axial impeller, rotation dependent upon particle density. For materials with a low wettability,
Triton-X-100 surfactant was used in conjunction with a defoaming agent to ensure adequate
particle dispersion.
Duplicate samples were collected from the chiller-water overflow outlet and analyzed for
three different times on three separate days before averaging the data together for a base
comparison with the list of particle options. Nearly all materials previously listed were tested, but
as found with particle density, most were either too large or too small by comparison with the
bimodal distribution of poultry chiller water. However, Tiger Brand® bone meal fit the smaller
range very well and could be combined with sieved portions of another brand, Espoma®, to fit
the curve quite well (Figure 7.2).
Given the relatively low wettability of bone meal, the true density was not useful for
experimental testing because of a reduction in the effective particle density when suspended in
water. As a result, the densities of all sieved samples were individually determined by
displacement of water in volumetric flasks. However, a surfactant had to be added to suspend the
bone meal and fully wet the surface area of each particle. From the collection of data, a weighted
effective density for the mixture of bone meal was determined to be 2.02 g/cm3, providing a
significant challenge to the solids removal components of the prototype.
43
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
0.01 0.1 1 10 100 1000
Particle Size (µm)
Perc
ent V
olum
e
Initial Chiller Average
Tiger & Espoma Bone Meal
VOLUME BASIS0-106 µm, 45%175-220 µm, 4%
300-425 µm, 13%Tiger, 38%
MASS BASIS0-106 µm, 38.2%175-220 µm, 3.8%
300-425 µm, 12.4%Tiger, 45.6%
® ®
Figure 7.2 Particle size distribution comparison between averaged poultry chiller water samples and added distributions of Espoma® (sieved) and Tiger Brand® bone meals in aqueous suspension.
7.1.2 Make-Up Suspension
To supply an adequate volume of formulated suspension water to the prototype, an 800-
gallon woodpulp macerator was used as the mixing vessel and slurry holding tank. However,
agitation of bone meal with wetting surfactant in the reactor caused foaming and flocculation of
testing material. To reduce undesirable foaming, various combinations of vendor-recommended
low-foaming surfactants and defoaming agents were used, yet this produced another unforeseen
difficulty.
Defoamers left a significant residue on glass fiber filters during TSS testing. To eliminate
this problem, several other readily available and distributor-suggested filters were evaluated to
allow the defoaming agents to pass through the collection surface (Table 7.2). Tests in the
44
laboratory determined that polycarbonate nuclepore filters were ideal for this consideration, not
collecting the selected Ecco Defoamer NSD or the Triton-X-100. However, persistent particulate
flocculation led to another method for bone meal suspension, i.e., hot water (130°F, 54°C).
Table 7.2 List of filters, surfactants, and defoamers used for testing adequate suspension of bone meal particulate without flocculation or filter collection of defoaming agent.
At higher temperatures water can readily penetrate the pores of the bone while still
inhibiting flocculation; however, this alters the effective density of the test material. Therefore
densities were reevaluated by modeling conditions within the macerator using volumetric flasks
for heated water displacement in an agitated temperature-controlled water bath shaker (180 rpm,
52°C) for a 30 minute duration. Results from this analysis produced a weighted bone meal
average of 1.67 g/cm3, significantly less than the density determined using a solution of
surfactant and defoamer (Table 7.3).
Another possible alteration to bone meal suspended in heated water is the rate of
absorption and how it affects particle size distribution. Experimental results showed that bone
meal will imbibe water after an extended duration (~1½ days), expanding particles and
increasing density. However, samples from prototype testing were analyzed promptly after
SurfactantsFisher Scientific Triton-X-100
Triton Nonionic Low Foam DF-12 Dow Tergitol Min-Foam 1X
Filters1.2 µm Whatman GF/C Binder-Free Glass Fiber
1.0 µm Whatman Nuclepore Polycarbonate 0.45 µm Gellman Sciences Hydrophilic Mixed Cellulose Esters
0.45 µm Whatman Nylon Polycarbonate
DefoamersHelena Silicone “Foam Buster”
Eastern Color & Chem. Co. Ecco Defoamer NSD Defoamer.com TD 1545 “Bulldog”
0.45 µm Whatman Cellulose Nitrate
45
collection (< 3 hours) to minimize this effect as proven by repeated investigation of size
alteration over time. Also, solubility was not of concern. Although bone meal is comprised of 30-
35% collagen and can be denatured into gelatin at boiling temperatures, it was not significantly
affected at test temperatures. The remaining 65-70% is comprised of hydroxyapatite and is
essentially insoluble.
Table 7.3 Two separate analyses of effective bone meal density for determining the weighted verage used during formulated suspension testing. a
Sieved Size Percent Mass Effective Density (g/cm3) Range (µm) Required in Solutiona in Hot Waterb
0-106 38.2 1.67 1.79 106-150 1.73 1.84 150-175 1.78 1.91 175-220 3.8 1.85 1.97 220-300 1.90 2.01 300-425 12.4 1.87 2.01 Tiger® 45.6 2.36 1.45
Weighted Average 2.02 1.67 a Displacement tested with a solution of DI water, 0.1% Trtiton-X-100 surfactant, and 0.2% Helena Silicone “Foam Buster”. b Displacement tested with warm DI water and agitation (52°C, 180 rpm).
7.1.3 Prototype Testing Process and Performance
The woodpulp macerator was filled with ~500 gallons of 54°C water and agitated with its
axially-positioned impeller (180 rpm) and recirculating pump (80 gpm). The selected amounts of
bone meal were slowly added to the water and fed to the prototype’s transfer pump from a 1 in.
diameter port located on a 90° elbow of the recirculating line. After enough time had passed for
the suspension to fully fill and course through the three solids removal components at 60 L/min
(15.9 gpm), samples were simultaneously collected before and after each unit at elapsed times of
10, 15, 20, and 25 minutes. This test was conducted on three separate occasions, with one set of
46
1-L bottles used for TSS testing and another set for particle size analysis, all sample bottles
undergoing three randomized testing replications.
Bone meal concentrations were expected to yield TSS values of ~500 mg/L, however,
analysis showed an actual average of 397 mg/L at the prototype’s inlet. This is likely attributable
to poor solids suspension, having larger particles remain within the macerator, and is evidenced
by fewer of these solids present during particle size analysis, explaining an inexact match to
modeled chiller water. Regardless, overall comparison of the prototype performance is still quite
valid and has been illustrated by assimilating each component’s TSS data and weighted particle
size distributions into one graphical representation (Figure 7.3).
Figure 7.3 Weighted particle size distributions characterizing TSS removal for
formulated-suspension testing of pilot-unit’s solids removal capabilities.
47
Because initial bone meal tests revealed that a density variation exists across the size
distribution, a graphic representation of the true solids removal processes cannot be directly
derived, although, given similar particle densities, the weighted average has produced an
excellent simulation. Considering this, an exact recreation of the graph would likely reveal a shift
towards smaller particles for the latter two solids removal components, understood by Stokes’
law of particle settling in the presence of given forces.
Overall, a total of nearly 60% of the particulate mass was removed from the formulated
suspension, with successive stages of treatment removing 10% post-hydrosieve, 40% post-
settling tank, and 57% post-hydrocyclone. Effective removal of larger particle sizes by the
hydrosieve was evident, while the dominant removal of bone meal occurred during the two-
minute retention time of the settling tank. Thereafter, an additional 17% reduction was attributed
to the centrifugal force of the hydrocyclone.
7.2 Poultry Chiller Water Treatment
After the skid-mounted pilot-unit was carefully installed into the transport trailer and
transferred to a local poultry-processing plant, initial onsite tests focused upon solids removal
efficiency as well as bactericidal efficacy.
7.2.1 Sampling Procedure
Startup of the prototype typically began at 7:00am and achieved steady-state operation
within 30 minutes. Thereafter samples were collected at approximately 9:00am and 11:00am to
allow for a minimum steady-state operation of 1-1½ hours and were not collected during
hydrocyclone purge time or while inlet flowstream was intermittent (i.e., ball valve open and
transfer pump engaged). This eliminated concerns associated with pump acceleration when the
48
ball valve was automatically opened as well as sample variation attributed to idle waters.
Furthermore, samples were collected between times for removal of hydrosieve solids
accumulation, accomplished with a wet-dry vacuum every 15 minutes.
7.2.2 Results and Discussion
As was the case with bone meal testing, all chiller water samples were analyzed for TSS
and particle size distribution for efficiency evaluation of solids removal processes. Results from
these onsite tests (Figure 7.4) clearly show less effective TSS reduction (29% total) in
comparison with the lab-based bone-meal results. This is likely attributable to lower particle
mass densities of the on-line wastewaters at the poultry plant.
Figure 7.4 Weighted particle size distributions characterizing TSS removal for
chiller water testing of pilot-unit’s solids removal capabilities.
49
Over eight individual days of testing and multiple replications, measured inlet TSS
concentrations ranged from 367-891 mg/L and were then reduced by the successive removal
stages to a final concentration ranging from 276-547 mg/L. The only effective onsite solids
removal was by the hydrosieve, physically removing all particles greater than the 500 µm screen
size, plus many smaller particles as well. This added removal likely results from the
accumulation of solids that adhered to other waste collecting on the surface of the sieve over
time, which also reduced the effective width of bar screen spacing and is evidenced by greater
percent solids removal at later collected samples. Additionally, the overall shift toward smaller
particle sizes exiting the hydrosieve can be attributed to the shearing of particles from water-fall
within the hydrosieve itself.
After the physical removal of particles by the hydrosieve, TSS values were not
significantly altered within the settling tank. However, it is worth noting that there was a build-
up of foam (a useful renderable product) throughout the coursing channels. Had these floatable
solids been removed, further reduction in TSS would have been likely, thus preventing such
build-up from re-entraining itself into the flow pathway and into the centrifugal pump.
Water then passed through the hydrocyclone, purged every 8 minutes, without
significantly reducing TSS any further. Nonetheless, the size distribution of the exiting water
shifted toward smaller particle sizes because of process energy inputs, a result of pump
mechanics and hydrocyclone centrifugal forces. Although this final stage did not appreciably
remove any additional particles from poultry chiller water, had solids such as sand and soil
(density ~2.6 g/cm3) been entrained in the wastestream as typical for produce wash-water, these
particles would have been effectively removed. This can be confirmed by manufacturer’s
specifications stating a 98% mass removal of all particulates of 74 µm diameter and nearly
complete removal of most larger sizes having this greater mass density.
50
CHAPTER 8
ANALYSIS OF MICROBIOLOGICAL TREATMENT S
A primary objective of this thesis was to determine the ability of the collective prototype
system to remediate poultry chiller water using UV irradiation and/or ozonation. This was
accomplished by analyzing water samples collected throughout the prototype process line for
levels of microbiological plate counts and turbidity at prescribed levels of the selected
treatments.
8.1 Introduction
After the prototype’s flowstream has passed through the three solids-removal stages, the
process water is equally divided into three independent channels for separate application of
specific treatments on identical wastewater, thereby allowing for the addition of any
concentration of ozone in conjunction with, or without, UV irradiation. To alter the mass of
ozone injected by each venturi, the ozone generator was set to produce a selected concentration
while needle-valved rotameters were adjusted for the desired volumetric flowrate. In order to
ensure an unchanged wastewater flowrate through each of the three channels when the ozonated
oxygen gas was not being applied, a 3-way valve mounted on each venturi was positioned to
passively draw in ~3.2 L/min of filtered ambient air, determined to have insignificant
bacterial loads.
51
Immediately following ozone or air induction (~800 ms), the wastewater enters the UV
reactors where wiper bars were manually operated every 15 minutes to reduce fowling of the
quartz tubes surrounding the low pressure mercury vapor lamps. Following a 40-second
residence, wastewater subsequently resides within contact columns for approximately 8.5 min at
10 psi to allow ozone to further react with entrained microorganisms before each channel
converges and exits the prototype. To determine the bactericidal efficacy of the various treatment
combinations, water samples were collected after the UV reactors and the contact columns, then
compared with samples of entry waters collected post-solids removal.
8.2 Sampling Procedure
Before collecting test samples, each sampling port was initially purged with a high
velocity stream of treated water to shear away any particles along the sidewalls (~300 mL) then
wiped with bactericidal ethanol for sanitization. Thereafter ports were allowed to dry, ~15
minutes, and a 50-100 mL microbiological sample was collected following an additional low-
velocity purge of ~50 mL. Each sample was collected in a sterilized Whirl-Pak® bag containing
10 mg of sodium thiosulfate to arrest the action that any residual chlorine may have on bacteria
populations. Depending on the desired evaluation, some bags were promptly sparged with
oxygen (0.2 L/min, >8 min) in order to displace any unreacted ozone; this permitted a time
evaluation of how the ozone affected the bacteria populations before and after the contact
columns’ 8-min residence time (Figure 8.1). Non-sparged samples showed the bactericidal effect
upon water that would normally re-enter the processing plant. All samples were placed on ice
and taken to the University’s Department of Food Science and Technology for microbiological
analysis of aerobic plate count (APC), total coliform (TC), and E. coli using 3M PetrifilmTM.
52
Figure 8.1 Collected-sample bags on ice with oxygen feedlines (sparge
tubing to the right of the sample rack).
For turbidity analysis, an inline forward-light-scatter turbidimeter preceded by a
quiescent bubble removal chamber was used to analyze a 1 L/min sidestream of converged outlet
waters. Additionally, a Hach benchtop turbidimeter was used to measure NTUs with 90° light-
scattering inspection of cuvette samples that were collected promptly after bagging
microbiological samples. To remove entrained bubbles from the water, all cuvettes were placed
into a vacuum chamber at -22 in. Hg within 3 minutes after collection and were analyzed after a
30-minute duration. This was necessary to arrest the action of any remaining ozone and eliminate
light-refracting bubbles. Afterward, a significant amount of remaining solids had been forced to
the surface of the water and the cuvette had to be shaken for attempted flocculent re-entrainment,
then set idle for ~5 min. Each sample was then gently and repeatedly inverted prior to
measurement of turbidity.
53
8.3 Preliminary Data
Several treatment tests were initially conducted with the prototype to adjust for initial
unforeseen challenges. Data collected from these experiments was primarily used to evaluate
bactericidal effects associated with non-sparged samples and is understood to be comparable to
water that would normally be recycled to the processing plant.
8.3.1 Evaluation Considerations and Precautionary Measures
Due to the inherent differences of a flow-through process vis-a-vis the bench-top batch
reactors used in earlier studies, sampled waters at the multiple collection points throughout the
prototype are not directly comparable yet are still valid measurements after multiple replications
have been conducted (i.e., water collected at a later stage of treatment is not entirely identical to
a sample collected at the inlet, thereby producing greater treatment response variability).
Additionally, sample inconsistency can be attributed to the presence of solids remaining in the
onsite wastestream (71% still present). Such solids accumulated within the headspaces of the UV
reactors and the contact columns forming a layer of foam which tended to re-entrain into the
collected sample as the ports were opened, inadvertently increasing microbiological populations
(Diaz et al., 2001). Care was taken to minimize this problem by only partially opening sample
valves during the sampling process. Also reactor and column construction was altered to
internally elevate the outlet of each vessel, reducing both the amount of foam accretion and
possible resuspension.
An evaluation of the variability of the wastewater bacterial loads throughout a given day
was compared to the corresponding quantities measured over different days. This investigation
determined that inlet APC had a limited variability over a 4-hour period (standard deviation σ =
0.3 Log) when compared with 5 days of testing over a 1-month period (σ = 0.9 Log). Thus, any
54
treatment combinations tested over a given day would likely have greater similarity than if tested
between days.
8.3.2 Initial Results
Inlet concentrations of APC, total coliform, and E. coli were initially measured over 11
separate days during a four-month period, averaging 4.6±0.6 Log10 CFU/mL, 2.4±0.5 Log10
CFU/mL, and 1.7±0.6 Log10 CFU/mL, respectively (count ± standard deviation). The effect of
the prototype’s solids removal processes on these counts was not significant and counts
effectively remained unchanged before entering ozonation and/or UV irradiation treatment for
collected samples evaluated without oxygen sparging. For comparison of the bactericidal
efficacy of the various wastewater treatments, mean values of replicated Log-reductions (outlet
concentrations subtracted from corresponding post-solids removal quantities) measured from a
select number of tests are illustrated in Figure 8.2. It is important to note that no individual value
in this data set has been separately compiled from more than two days of testing, although
between 2-9 sample replications were collected for each day.
To optimally evaluate treatment differences, the bactericidal effects should be observed
when nearly all microorganisms have been killed, thereby producing larger comparable values
while still remaining within a detectable range. This is the case for Figure 8.2 and is the
reasoning why different ozone concentrations are displayed. Regardless of the bacterial
evaluation, O3/UV treatments are consistently more effective than ozone alone, this being
especially clear when comparing APC values at the 87 mg/L ozone concentration. For this
condition, the individual effects of UV and O3 added together equal that of the combined O3/UV
treatment (4.4 Log10 CFU/mL reduction, or >99.99%). For the cases of total coliform and E. coli,
55
Figure 8.2 indicates that a 36 mg/L ozonation provided Log reductions equal to those achieved
by UV irradiation, namely 1.3 Log10 CFU/mL and 1.5 Log10 CFU/mL, respectively (both >90%).
O3/UV4.4
O3
3.0
UVonly
1.4O3/UV
1.4 O3
1.3UVonly
1.3
O3/UV1.9
O3
1.5UVonly
1.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
Trea
tmen
t Effe
ctiv
enes
s (L
og10
CFU
/mL
Red
uctio
ns)
APC, 87 mg/L TC, 36 mg/L E. coli, 36 mg/L
Plating Method, Ozone Concentration (mg/L)
O /UV
O
UV
E. coli , 36 mg/LTC, 36 mg/LAPC, 87 mg/L
O3/UV
O3
UV only
Figure 8.2 Log reductions (i.e., outlet concentrations subtracted from post-solids removal
quantities) of wastewater bacteria populations (APC, Total Coliform, and E. coli) resulting from various treatment levels of O3 and/or UV on-line at poultry-processing plant (non-sparged samples).
Despite the presence of solids remaining in treated waters, both O3 and O3/UV
applications killed all detectable E. coli and total coliform at ozone concentrations as low as 20
mg/L (1.1 Log10 CFU/mL reduction, >90%) while higher ozone inputs (>36 mg/L) with UV
repeatedly reduced their numbers to undetectably low values for all inlet concentrations (up to
2.5 Log10 TC CFU/mL and 2.4 Log10 E. coli CFU/mL). Perhaps most impressive is the
bactericidal response of APC during O3/UV treatment, consistently producing greater reductions
than O3 treatment alone, for all comparable ozone concentration levels. Additionally, this
56
combination was able to reduce APC counts by >97% when only 11 mg/L of ozone was applied
in the presence of UV irradiation.
8.4 Final Results
After determining the most responsive levels of bactericidal efficacy from ozone
application from sparged-sample analysis, an experimental design was established to evaluate six
different treatment combinations, three levels of ozone concentration (0, 39, and 78 mg/L) in
conjunction with two levels of UV irradiation (on and off).
8.4.1 Experimental Design
Consideration for experimental design selection came from preliminary studies
demonstrating that inlet bacteria concentrations varied across time of day more so than between
days. Additionally, a concern existed over possible differences between treatment channels. To
concomitantly block these effects, a Latin square experimental design was selected. The overall
test procedure required randomly ordering the six treatments within a given day and then
repeating for six individual tests so that every treatment was applied once for each possible time
and channel combination (Table 8.1).
Table 8.1 Latin square experimental design for bactericidal testing of three different levels of ozone (0, 39, 78 mg/L) and two levels of UV irradiation (on, off) for oxygen-sparged samples.
Block1 \ Block2 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 9am, Channel1 39, off 39, on 0, on 0, off 78, off 78, on 9am, Channel 2 0, on 39, off 0, off 78, on 39, on 78, off 9am, Channel 3 78, off 78, on 39, on 39, off 0, off 0, on 11am, Channel 1 0, off 0, on 78, on 78, off 39, off 39, on 11am, Channel 2 78, on 0, off 78, off 39, on 0, on 39, off 11am, Channel 3 39, on 78, off 39, off 0, on 78, on 0, off
57
The Latin square experimental design allowed for comparisons of each treatment
combination after UV reactors and after contact columns for Log-based reductions of CFU/mL
and was statistically evaluated with SAS software. Within this program, several contrast tests
were used to analyze the significance of treatment factors in addition to the levels of each
treatment. This evaluation was conducted for APC and turbidity test results only, realizing that
TC and E. coli populations were often reduced to statistically invalid amounts for many of the
treatments.
8.4.2 Microbiological Evaluation
Average inlet microbiological concentrations over the six tested days for APC, TC, and
E. coli were 4.3±0.3 Log CFU/mL, 2.1±0.4 Log CFU/mL, and 1.7±0.4 Log CFU/mL,
respectively (Table 8.2). The effect of the three solids removal stages on these counts was
expectedly not significant, yet samples from both the inlet and post-solids removal locations
were affected by the collection time (P≤0.05) and not the testing day. This is contrary to
preliminary data that was evaluated for five individual days of testing over 4-hour periods (9am,
11am, 1pm) and was a partial basis for the selected experimental design. However, data analysis
was conducted for Log-based reductions of microbiological counts rather than direct
concentrations and was proven to have no effect on the outcome of treatment comparisons.
After solids removal, the three independent process channels tested each level of
treatment and results were evaluated with the Latin square experimental design. Here it was
shown that among the blocked effects, neither time nor day affected the treatment responses
measured from the UV reactors or the contact columns. However, selected process channels had
a very significant and unexpected effect on microbiological samples collected after the contact
columns (P≤0.0001), although not after the UV reactors. This is likely attributable to the
orientation of post-column sampling ports and a slightly unlevel 3-to-1 converging manifold.
58
Because of gas and foam collection in the headspace of prototype vessels, the three treatment
channels are not entirely filled with process water. This allows for the horizontally positioned
radial sampling ports of the coplanar exit tubes to readily re-entrain floating solids, compounded
by a variation between each port due to a minor slant in the 3-to-1 manifold. Indeed, the
difference between the two outside post-column samples was greater than that between the
center channel versus outer channels, leading to a linear change across the three channels.
Table 8.2 Averaged aerobic plate counts (APC) for all 6 replications of chiller water treatments showing treatment levels, direct counts, and differences in counts between inlet vs. reactor and nlet vs. column. i
APC POPULATIONS
Direct Counts (Log10 CFU/mL)a Inlet Difference aO3(mg/L) UV
Inlet Solidsb Reactorb Columnb Reactorb Columnb
0 off 4.2 ± 0.3 4.3 ± 0.5 4.1 ± 0.3 3.8 ± 0.5 0.1 ± 0.3 0.5 ± 0.5 0 on 4.3 ± 0.3 4.3 ± 0.4 3.9 ± 0.8 3.8 ± 0.7 0.4 ± 0.9 0.6 ± 0.6 39 off 4.3 ± 0.3 4.3 ± 0.4 3.8 ± 0.5 3.6 ± 0.7 0.4 ± 0.6 0.6 ± 0.9 39 on 4.2 ± 0.3 4.3 ± 0.4 3.8 ± 0.7 3.3 ± 0.8 0.5 ± 0.5 0.9 ± 0.8 78 off 4.3 ± 0.4 4.2 ± 0.3 3.2 ± 0.9 3.2 ± 0.9 1.1 ± 0.8 1.1 ± 0.8 78 on 4.2 ± 0.3 4.2 ± 0.4 3.1 ± 0.9 3.4 ± 1.7 1.0 ± 0.9 0.8 ± 1.8
a Direct counts and differences are followed by ± standard deviation. b Sample collection sites follow the listed prototype component.
Samples collected from the outlet of the contact columns could have also been affected
by alterations that were made to internally elevate vessel outlets. Slight differences between
vessel headspace would have created different amounts of foam buildup and consistently led to
dissimilarity between process channels. However, if this were an affect, it would have likely
been detected at post-UV reactor ports as well, leading back to the concern for port and piping
orientation. To further support this conjecture, the tubes leaving the UV reactors turns vertically
before sample collection, thus eliminating port-orientation concerns along with related channel
differences.
59
Due to the inherent growth response of microorganism reproduction during plating and
the associated techniques, a difference between plated samples is to be expected (e.g., APC inlet
and post-solids samples σ = 0.4 Log, ranging from 0.3 to 0.5 Log). However, this variation was
sharply increased after applied treatment stages, likely due to solids re-entrainment from foam
accumulation in the prototype’s headspaces (e.g., APC post-reactor and post-column σ = 0.8
Log, ranging from 0.3 to 1.7 Log). Given this extensive variation, preliminary studies laboriously
sought to determine optimum ozone test concentrations which would produce the largest
comparable Log-reduction values while still remaining within a statistically valid range (i.e., 25-
250 CFU/plate, APC). Despite the expended effort, the greatest average bactericidal reduction
observed for the combined treatments was 1.1 ± 0.8 Log APC (Figure 8.3).
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0, off 0, on 39, off 39, on 78, off 78, on
Combined Treatment Levels (O3 mg/L, UV)
Post-Reactor
Post-Column
Trea
tmen
t Effe
ctiv
enes
s (A
PC L
og10
CFU
/mL
Red
uctio
n)
Figure 8.3 Log-based reductions of averaged aerobic plate counts (APC) for indicated UV/O3
treatments of chiller water as sampled after both the UV reactors and contact columns (standard deviation bars shown).
60
The extensive variation between the days’ test results for sparged samples precludes
conclusions regarding differences in treatment levels and, again, is directly attributed to the
presence of microorganism-laden foam being drawn into sampling ports. Interestingly, standard
deviation values for each averaged APC increase with increasing gas injection. However, a
statistical evaluation of this trend cannot be tested due to a lack of replications and does not
appear to occur for other bacteria analyses, i.e., TC and E. coli (Table 8.3).
Table 8.3 Averaged counts (TC and E. coli) for all 6 replications of chiller water treatments showing treatment levels, direct counts, and differences in counts between inlet vs. reactor and inlet vs. column. TC POPULATIONS
Direct Counts (Log10 CFU/mL)a Inlet Difference O3(mg/L) UV
Inlet Solidsb Reactorb Columnb Reactorb Columnb
0 off 2.2 ± 0.5 2.1 ± 0.3 2.1 ± 0.3 2.0 ± 0.3 -0.1 ± 0.3 0.0 ± 0.3 0 on 2.1 ± 0.4 2.1 ± 0.4 2.2 ± 0.4 1.5 ± 0.3 -0.1 ± 0.6 0.6 ± 0.5 39 off 2.1 ± 0.5 2.0 ± 0.4 2.0 ± 0.4 1.5 ± 0.4c 0.1 ± 0.5 0.6 ± 0.5c
39 on 2.2 ± 0.5 2.1 ± 0.3 2.0 ± 0.8 1.5 ± 0.6 0.1 ± 0.8 0.6 ± 0.6 78 off 2.0 ± 0.4 1.9 ± 0.4 0.5 ± 0.6c 0.9 ± 0.5c 1.4 ± 0.7c 1.0 ± 0.7c
78 on 2.0 ± 0.3 2.0 ± 0.3 0.7 ± 0.6c 0.5 ± 0.6c 1.3 ± 0.6c 1.5 ± 0.7c
E. coli POPULATIONS
Direct Counts (Log10 CFU/mL)a Inlet Difference O3(mg/L) UV
Inlet Solidsb Reactorb Columnb Reactorb Columnb
0 off 1.7 ± 0.4 1.5 ± 0.3 1.4 ± 0.2 c 1.5 ± 0.4 0.1 ± 0.3 c 0.0 ± 0.2 0 on 1.8 ± 0.5 1.7 ± 0.4 0.9 ± 0.8c 0.7 ± 0.4c 0.8 ± 0.6c 1.0 ± 0.2c
39 off 1.6 ± 0.4 1.6 ± 0.5 0.4 ± 0.4c 0.3 ± 0.3c 1.1 ± 0.3c 1.3 ± 0.3c
39 on 1.7 ± 0.4 1.5 ± 0.3 0.6 ± 1.0c 0.4 ± 0.9c 0.9 ± 1.0c 1.2 ± 0.8c
78 off 1.6 ± 0.4 1.5 ± 0.5 0.0 ± 0.0d 0.0 ± 0.0d 1.5 ± 0.5e 1.5 ± 0.5e
78 on 1.6 ± 0.2 1.6 ± 0.3 0.0 ± 0.0d 0.0 ± 0.0d 1.6 ± 0.2e 1.6 ± 0.2e
a Direct counts and differences are followed by ± standard deviation. b Sample collection sites follow the listed prototype component. c Blue numbers are "estimated" counts (i.e., est. should be written after each value). d Red values are 'less than' the presented value (i.e., < 1 CFU/mL for direct counts). e Differences should read ‘greater than’ the presented values.
61
Contact columns were included in the prototype’s design to facilitate complete reaction
of injected ozone with suspended microorganisms. The benefit of free radicals, particularly OH·,
produced from ozone in the presence of UV irradiation, is that the reaction is nearly
instantaneous, theoretically eliminating the need for a significant residence time. However, there
was no significant difference detected between the bactericidal performance of UV reactors
versus contact columns. This was unexpected given proven reaction rates, but is explainable due
to small response detection and inadvertently collecting foam. Indeed, when each treatment
combination is individually compared through contrasts or use of Tukey’s studentized range test
(P=0.05), there is no significant difference between any of the treatments for samples collected
post-reactors or post-columns. The only confirmed treatment benefit was that the highest level of
ozone (78 mg/L) had a greater bactericidal effect than when no ozone was injected (P≤0.05); UV
application having no determined response in the presence or absence of ozone.
Although results from total coliform and E. coli enumerations may not be statistically
compared within each plate count, it should be noted that they both follow a similar trend to that
of APC. Interestingly, ozone consistently provided greater E. coli reductions than APC or TC,
although this might be attributed to low plate counts being incomparable. It should also be stated
that both reductions appear to have a greater response to the higher concentration level of ozone.
Regardless of the presence or absence of UV, high levels of ozone effectively killed all
reproducing E. coli.
8.4.3 Turbidity Evaluation
An important consideration when evaluating turbidity levels (Table 8.4 and Figure 8.4),
is that when sample cuvettes were placed under vacuum for the removal of light-refracting
bubbles and to arrest the action of ozone, a dissolved air flotation (DAF) effect occurred.
62
Consequently, evacuating bubbles conveyed solids to the surface of the sample where they
formed a thin layer of foam. Although attempts were made to re-suspend these solids, they had
already formed larger agglomerated particles. While taking this into consideration, the turbidity
data was still statistically analyzed.
Table 8.4 Averaged turbidity (NTU) for all 6 replications of chiller water treatments showing reatment levels, direct counts, and difference between inlet vs. reactor and inlet vs. column. t
Turbidity (NTU)a Inlet DifferenceaO3
(mg/L) UV Inlet Solids Reactor Column Reactor Column
0 off 189 ± 17 193 ± 14 146 ± 16 147 ± 12 43 ± 10 42 ± 13 0 on 189 ± 16 190 ± 12 141 ± 16 147 ± 15 47 ± 8 42 ± 14 39 off 192 ± 16 191 ± 11 127 ± 8 136 ± 8 65 ± 13 55 ± 13 39 on 193 ± 21 194 ± 15 127 ± 14 137 ± 12 66 ± 10 55 ± 8 78 off 183 ± 9 189 ± 12 128 ± 17 154 ± 40 55 ± 10 29 ± 30 78 on 190 ± 17 191 ± 12 126 ± 5 154 ± 21 64 ± 10 36 ± 11
a Turbidity readings are followed by ± standard deviation.
Initially, a statistical test was conducted to determine if a correlation existed between the
microbiological and turbidity datasets. Among the comparisons, the bacteria levels at the inlet
and column were not correlated to their respective turbidity samples, but post-solids removal
(P≤0.05) and UV reactors (P≤0.10) did have an association. However, APC reductions at the
reactors and columns were not related to turbidity differences. Furthermore, treatments affected
the turbidity after the UV reactors (P≤0.01), but evidently not after the contact columns.
Although there was no significant difference between the inlet and post-solids removal
turbidity, the blocked levels of day and time produced an effect on post-solids, but not on inlet
water. As for treatment stage reductions, day (P≤0.01) and treatment (P≤0.01) both affected the
UV reactor outcome, but no effects were determined for contact columns. However, there was a
significant difference between reactors and columns (P≤0.01), actually increasing turbidity after
63
the contact columns and providing more evidence that foam collection from column headspace
was re-entering collected water samples.
-10
0
10
20
30
40
50
60
70
80
90
0, off 0, on 39, off 39, on 78, off 78, on
Combined Treatment Levels (O3 mg/L, UV)
Effe
ctiv
e Tu
rbid
ity R
educ
tion
(NTU
)
Post-Reactor
Post-Column
Figure 8.4 Reductions in turbidity of chiller water resulting from indicated UV/O3 treatments as
sampled after the UV reactors and after the contact columns (standard deviation bars shown).
Individual treatment contrast tests for post-UV reactor turbidity reduction corroborate
tests for treatment level effects as well as Tukey’s test. That is, the presence of UV did not
present an effect but that both levels of ozone individually altered the response (P≤0.01), though
there was no difference between the low and high levels. A test to determine if simultaneous
application of UV and O3 provided a synergistic reduction of turbidity as measured post-reactor
showed the additive effects to be greater than those when simultaneously combined, true for both
ozone treatments (P≤0.05). Surprisingly, the first day of sample analysis varied from all other
64
days (P≤0.05), but remaining comparisons showed no significant difference while time nor
selected channel produced an effect.
Comparisons between each treatment effect from column samples revealed no significant
differences, regardless of the testing method, other than a contrast between low and high levels
of ozone (P≤0.05) with day, time, and channel selection not having an effect on the turbidity-
reduction outcome.
8.4.3 Microbiological and Turbidity-Related Conclusions
Standard deviations for treatment evaluation of microbiological data were particularly
high in comparison to the low levels of reduction response, revealing only that the higher tested
level of ozone affected chiller water bacteria counts following the prototype’s UV reactors.
Evaluation of turbidity results prove that testing methods invite error into the results due to solids
flocculation during bubble extraction. The strongest conclusion from all sets of data is that the
removal of solids from the wastewater stream is mandatory for effective treatment with UV
and/or ozone.
65
CHAPTER 9
OVERALL CONCLUSIONS
Integration of process-hardware and instrumentation subassemblies into an overall
operational UV/O3 water-treatment system was fully achieved with PLC programming and
related software. The established HMI minimizes the level of user interaction with the pilot-unit
prototype by automating many of the physical controls, treatment methods, and monitoring
equipment. Additionally, cleaning and sanitizing procedures were incorporated into the
programming to provide uniform self-regulating processes, thus allowing concurrent
management of other operator demands (e.g., manual-demanded cleaning and data processing).
The solids removal evaluation of the prototype revealed that the hydrosieve was effective
at removing particles larger than the installed 0.5-mm screen-size. Additional removal
capabilities were achieved as treatment time increased and chiller water solids accumulated,
essentially reducing screen spacing. Particles with higher densities (ρ = 1.67 g/cm3) were
removed by the settling tank and hydrocyclone during formulated-suspension testing with bone
meal (total mass removal = 57%), but were both appreciably challenged by the solids present in
actual poultry chiller water achieving no significant reduction. These final two solids-removal
stages prior to UV and/or O3 treatment applications are significantly more effective at removing
particulates with a higher density.
Initial tests of chiller-water treatments showed promising results for samples collected
without oxygen sparging. The bactericidal response suggested that combined levels of ozone and
66
UV were more effective than either of the individual treatments, but the small number of
replications limits any strong conclusions and, without sample sparging, contact column
effectiveness could not be evaluated. Prompted by these results, further efforts were exhausted to
find ozone treatment levels that would maximize the microbiological response and test the effect
of the pressurized column residence time by arresting the action of ozone with oxygen sparging.
Despite maximized responses, comparably low inlet microorganism concentrations and
large response variability led to limited confirmed data regarding treatment level effectiveness.
The only positive statement is that high levels of ozone (78 mg/L) affected APCs (P<0.05) for
samples collected after the UV reactors. The strongest conclusion from the statistical analysis of
this test series is that a difference exists between the divided parallel channels, possibly
attributable to sample port orientation enabling the re-entrainment of bacteria-laden foam during
sample collection. To correct this in future tests, sampling port position should be altered and
headspace should be further reduced by vessel outlet adjustment.
Decidedly, improved solids removal must be applied to overflow poultry chiller water for
effective treatment evaluation of ozone and/or UV with the pilot-scale prototype. The presence
of suspended and dissolved solids inhibit the known bactericidal properties of treatment methods
and accumulate as foam in idle headspace of the prototype. Excessive solids in the process water
block of UV irradiation and thus reduce direct bactericidal benefits as well as the production of
the highly bactericidal reactive free radicals. The effectiveness of both UV and ozone are
critically dependent upon removing suspended-solids oxidation scavengers.
Benefits provided by reduced treatment costs for poultry chiller water reuse are clear,
providing economic gain for processing plants and added environmental advantages while still
improving consumer safety by reducing carcass bacterial loads. However, given the challenges
67
faced by persistent suspended solids in chiller water, other treatable poultry process
wastestreams are currently being explored for future testing of the bactericidal performance of
UV-enhanced ozonation with the pilot-scale prototype. Some of the possibilities for re-
evaluation of the system include pre-treated chiller water at another test site or another process
line containing less solids (e.g., inside/outside bird washer).
Early laboratory results by Diaz and Law (1997) with benchtop batch reactor treatments
of poultry chiller water conclusively demonstrated a synergistic bactericidal effect for UV/O3
combinations. However, results from this thesis research demonstrated that the current status of
the engineered pilot-scale prototype have not been able to duplicate this effect on a flow-through
basis due to limited solids removal from the wastestream. Given the strong support from initial
lab-scale data and the excellent functionality of the prototype system, expectations are still quite
promising to eventually prove that a bactericidal synergy exists between UV irradiation and
ozone in waters with low levels of oxidation scavengers. Confirmation on large scale studies will
allow this technology to be transferred to many different applications such as other food
processing facilities, municipal wastewater, and industrial operations.
68
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74
APPENDIX A
OZONE DOSAGE CALCULATIONS
Flowing treatment water was supplied with a venturi-injected ozone concentration (wt.%)
in pressurized oxygen carrier feedgas and was accomplished with instrumentation and
programming described in Chapters 5 and 6. To readily interpret dosage levels for each process
channel, gaseous percent weight was converted to ozone mass concentration per liquid volume
(i.e., mg/L). Part of this conversion requires controlled feedgas flowrates to be adjusted for
rotameter-measured standard air flow (i.e., QS). The following conversion equations are used to
relate general concentration of gases in terms of known wt% to mg/L:
L
GS
P
QQDD
ρ⋅⋅=
100 (A.1)
with 23 /0
10 1
OOGcfcfGS SGP
PPQSGPQQ ⋅+
⋅=⋅⋅= (A.2)
and gmg
TRPMW
TRnPm
Vm TOOTG
G
GG 1
100023 / ⋅⋅
⋅=
⋅⋅⋅
==ρ (A.3)
with ⎥⎦
⎤⎢⎣
⎡⋅⎟⎠⎞
⎜⎝⎛ −+⎥⎦
⎤⎢⎣⎡ ⋅=
2323 1001
100/ OP
OP
OO MWD
MWD
MW (A.4)
where D = dose rate of ozone (mg/L) DP = dose rate of ozone (wt.%) QS = standard feedgas flow rate (SLPM) ρG = density of feedgas (mg/L) QL = liquid flowrate in each channel (L/min) QG = feedgas flow rate as observed on flowmeter (L/min) Pcf = pressure correction factor (unitless) SGcf = specific gravity correction factor (unitless)
75
Po = standard atmospheric pressure, 101.325 kPa P1 = pressure in flowmeter (kPa) SGO3/O2 = specific gravity of feedgas flowing through flowmeter with respect to air mG = mass of feedgas (g) VG = feedgas volume (L) PT = feedgas absolute pressure in flowmeter, i.e. 10 PPPT += n = moles of feedgas (mol) R = universal gas constant, 8.3145 kPa⋅L/mol⋅K T = temperature, 298 K MWO3/O2 = molecular weight of delivered gas mixture (g/mol) MWO3= molecular weight of ozone, 48 g/mol MWO2= molecular weight of oxygen, 32 g/mol.
The specific gravity used for O3/O2 flow through the rotameter is calculated as follows:
AIR
OOOO MW
MWSG 23
23
// = (A.5)
where MWAIR = molecular weight of air, 28.8 g/mol.
Table A.1 Ozone dosage example calculations (wt.% to mg/L).
DP MWO3/O2 P1 QG QS ρG QIa QL D
wt.% O3/O2 (g/mol) (lb/in2) (kPa) (L/min) (SLPM) (mg/L) (L/min) (L/min) (mg/L) 8.08 33.29 12.7 87.6 3.0 3.810 2538 60.04 20.01 39.04 8.08 33.29 12.7 87.6 6.0 7.619 2538 60.04 20.01 78.07
10.29 33.65 12.7 87.6 3.0 3.790 2565 59.98 19.99 50.03 10.29 33.65 12.7 87.6 6.0 7.579 2565 59.98 19.99 100.06
a QI = prototype inlet flowrate (L/min)
76
APPENDIX B
PLC LADDER DIAGRAM
Figure B.1 PLC flow-through block diagram.
77
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
CONFIGUREThis rung configures the input modules.
0000S:1/15
First PassCOP
Copy FileSource #B11:0Dest #O:8.0Length 12
COP#PRESSURE_CONFIG
COPCopy FileSource #B12:0Dest #O:9.0Length 12
COP#HC_O3_CONFIG
78
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
HIGH CONCENTRATION OZONE MONITOR READINGThese two rungs ensure the analog input value to be scaled remains within the limits of 4000 to 20000. This is necessary to prevent "out ofrange" conversion errors in both the SCP and PID instructions.
0001LES
Less Than (A<B)Source A I:9.0 4000<Source B 4000 4000<
LESHC_O3_DATA
MOVMoveSource 4000 4000<Dest I:9.0 4000<
MOVHC_O3_DATA
0002GRT
Greater Than (A>B)Source A I:9.0 4000<Source B 20000 20000<
GRTHC_O3_DATA
MOVMoveSource 20000 20000<Dest I:9.0 4000<
MOVHC_O3_DATA
This rung will scale the HC OZONE MONITOR reading from 0.00 to 15.00 % wt.
0003SCP
Scale w/ParametersInput I:9.0 4000<Input Min. 4000 4000<Input Max. 20000 20000<Scaled Min. 0 0<Scaled Max. 1500 1500<Output N7:7 0<
SCPHC_OZONE_READING
79
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
OZONE GENERATOR CONTROLThese two rungs ensure the input value (SETPOINT) in % wt (e.g., 5.00 % wt = 500) to be scaled remains within the limits of 0 to 1500. Thisis necessary to prevent "out of range" conversion errors in the PID instructions. Scaling from 5.00 to 500 is done within RSView.
0004LES
Less Than (A<B)Source A N7:12 734<Source B 0 0<
LESO3_SETPOINT
MOVMoveSource 0 0<Dest N7:12 734<
MOVO3_SETPOINT
0005GRT
Greater Than (A>B)Source A N7:12 734<Source B 1500 1500<
GRTO3_SETPOINT
MOVMoveSource 1500 1500<Dest N7:12 734<
MOVO3_SETPOINT
This rung will copy the input value (SETPOINT) from the integer Data File into the SETPOINT destination of the PID instruction.
0006COP
Copy FileSource #N7:12Dest #N14:2Length 1
COP#O3_SETPOINT_PID
The source to be scaled is the HC READING and its destination is the PROCESS VARIABLE (PV) of the PID instruction. These values arecalculated knowing that the input is 0.00 to 15.00 % wt., while the scaled range (PV) is 0 to 16383.
0007SCP
Scale w/ParametersInput N7:7 0<Input Min. 0 0<Input Max. 1500 1500<Scaled Min. 0 0<Scaled Max. 16383 16383<Output N14:28 0<
SCPOZONE_PV
0008PID
PIDControl Block N14:0Process Variable N14:28Control Variable N14:29Control Block Length 23
Setup Screen
PIDO3_GENERATOR_PID
80
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
When the OZONE_PID is in manual mode, this rung receives a 0-100% reading from RSView and sends it to the Control Output for the PIDas well as scale the value for direct input to the Control Variable (the ozone generator). This allows for a percent power output to be sent to thegenerator manually, bypassing the PID. Both of these operations are necessary because RSLogix does not allow for a value (0-100) to be sentto the Control Output alone (word 16).
0009N14:0/1
O3_GENERATOR_PIDCOP
Copy FileSource #N7:21Dest #N14:16Length 1
COP#OZONE_CV_MANUAL_IN
SCPScale w/ParametersInput N7:21 0<Input Min. 0 0<Input Max. 100 100<Scaled Min. 0 0<Scaled Max. 16383 16383<Output N14:29 0<
SCPOZONE_CV
The PID CONTROL VARIABLE is the input for the scale instruction. The PID instruction guarantees that the CV remains within the range 0to 16383. This value is to be scaled to the range of 6242 to 31208, which represents the numeric range that is needed to produce 4 to 20 mAanalog output signal.
0010B3/10 SCP
Scale w/ParametersInput N14:29 0<Input Min. 0 0<Input Max. 16383 16383<Scaled Min. 6242 6242<Scaled Max. 31208 31208<Output O:7.0 6242<
SCPO3_GENERATOR
This rung immediately updates the analog OUTPUT used for the PIDs CONTROL VARIABLE
0011IOM
Immediate Output w/MaskSlot O:7.0Mask 0FFFFhLength 1
IOMO3_GENERATOR
81
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
ELECTROMAGNETIC FLOWMETER READINGThese two rungs ensure the analog input value to be scaled remains within the limits of 4000 to 20000.
0012LES
Less Than (A<B)Source A I:9.7 4000<Source B 4000 4000<
LESFLOWMETER_DATA
MOVMoveSource 4000 4000<Dest I:9.7 4000<
MOVFLOWMETER_DATA
0013GRT
Greater Than (A>B)Source A I:9.7 4000<Source B 20000 20000<
GRTFLOWMETER_DATA
MOVMoveSource 20000 20000<Dest I:9.7 4000<
MOVFLOWMETER_DATA
This rung will scale the electromagnetic flowmeter reading from 0 to 9464 (i.e. 0.0 to 94.64 L/min). This conversion is restricted while thepump is adjusting (5 sec) from hydrocyclone purges (2 sec). While not converting, the last pump reading is sent to N7:2 as shown in rungs21-23.
0014LEQ
Less Than or Eql (A<=B)Source A C5:1.ACC 0<Source B 0 0<
LEQCYLCON_DELAY_COUNTER.ACC
SCPScale w/ParametersInput I:9.7 4000<Input Min. 4000 4000<Input Max. 20000 20000<Scaled Min. 0 0<Scaled Max. 9464 9464<Output N7:2 0<
SCPFLOWMETER_READING
82
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
PUMP DRIVE CONTROLThese two rungs ensure the input value (SETPOINT) in L/min (e.g. 60.0 L/min) to be scaled remains within the limits of 0 to 94.64 L/min (i.e.25 GPM). This is necessary to prevent "out of range" conversion errors in the PID instructions.
0015LES
Less Than (A<B)Source A N7:11 0<Source B 0 0<
LESPUMP_SETPOINT
MOVMoveSource 0 0<Dest N7:11 0<
MOVPUMP_SETPOINT
0016GRT
Greater Than (A>B)Source A N7:11 0<Source B 9464 9464<
GRTPUMP_SETPOINT
MOVMoveSource 9464 9464<Dest N7:11 0<
MOVPUMP_SETPOINT
This rung will copy the input value (SETPOINT) from the integer Data File into the SETPOINT destination of the PID instruction.
0017COP
Copy FileSource #N7:11Dest #N13:2Length 1
COP#PUMP_SETPOINT_PID
The source to be scaled is the FLOWMETER READING and its destination is the PROCESS VARIABLE (PV) of the PID instruction. Thesevalues are calculated knowing that the input is 0 to 94.64 L/min (i.e. 0 to 25 GPM), while the scaled range (PV) is 0 to 16383.
0018SCP
Scale w/ParametersInput N7:2 0<Input Min. 0 0<Input Max. 9464 9464<Scaled Min. 0 0<Scaled Max. 16383 16383<Output N13:28 0<
SCPPUMP_PV
The next three rungs force the PUMP_DRIVE_PID process variable (i.e. the flowmeter reading) to be equal to the lastFLOWMETER_READING during the time that the purge valve is open (2.00 seconds) and for a 3.00 second period immediately after thevalve closes. This is done to reduce any overwhelming response that the PUMP_DRIVE_PID may produce after the opening of thehydrocyclone purge valve.
0019T4:1/DN
PURGE_ON_DELAY/DNB3/4
PURGE_CYCLE_START
B3/5RSVIEW_PURGE_BUTTON
CU
DN
CTUCount UpCounter C5:1Preset 1<Accum 0<
CTUCYLCON_DELAY_COUNTER
83
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
0020GEQ
Grtr Than or Eql (A>=B)Source A C5:1.ACC 0<Source B 1 1<
GEQCYLCON_DELAY_COUNTER.ACC
COPCopy FileSource #N7:2Dest #N7:2Length 1
COP#FLOWMETER_READING
EN
DN
TONTimer On DelayTimer T4:3Time Base 0.01Preset 500<Accum 0<
TONPUMP_ADJUST_TIME
0021T4:3/DN
PUMP_ADJUST_TIME/DN
REST4:3
PUMP_ADJUST_TIME
RESC5:1
CYLCON_DELAY_COUNTER
0022PID
PIDControl Block N13:0Process Variable N13:28Control Variable N13:29Control Block Length 23
Setup Screen
PIDPUMP_DRIVE_PID
When the PUMP_PID is in manual mode, this rung receives a 0-100% reading from RSView and sends it to the Control Output for the PID aswell as scale the value for direct input to the Control Variable (the pump). This allows for a percent power output to be sent to the pumpmanually, bypassing the PID. Both of these operations are necessary because RSLogix does not allow for a value (0-100) to be sent to theControl Output alone (word 16).
0023N13:0/1
PUMP_DRIVE_PIDCOP
Copy FileSource #N7:20Dest #N13:16Length 1
COP#PUMP_CV_MANUAL_IN
SCPScale w/ParametersInput #N7:20 0<Input Min. 0 0<Input Max. 100 100<Scaled Min. 0 0<Scaled Max. 16383 16383<Output N13:29 0<
SCPPUMP_CV
84
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
The PID CONTROL VARIABLE is the input for the scale instruction. The PID instruction guarantees that the CV remains within the range 0to 16383. This value is to be scaled to the range of 6242 to 31208, which represents the numeric range that is needed to produce 4 to 20 mAanalog output signal.
0024B3/10 SCP
Scale w/ParametersInput N13:29 0<Input Min. 0 0<Input Max. 16383 16383<Scaled Min. 6242 6242<Scaled Max. 31208 31208<Output O:7.1 6242<
SCPPUMP_DRIVE_CONTROL
This rung immediately updates the analog OUTPUT used for the PIDs CONTROL VARIABLE.
0025IOM
Immediate Output w/MaskSlot O:7.1Mask 0FFFFhLength 1
IOMPUMP_DRIVE_CONTROL
85
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
PRESSURE TRANSDUCER READINGThese two rungs ensure the analog input value to be scaled remains within the limits of 4000 to 20000.
0026LES
Less Than (A<B)Source A I:8.0 4023<Source B 4000 4000<
LESPRESSURE_DATA
MOVMoveSource 4000 4000<Dest I:8.0 4023<
MOVPRESSURE_DATA
0027GRT
Greater Than (A>B)Source A I:8.0 4023<Source B 20000 20000<
GRTPRESSURE_DATA
MOVMoveSource 20000 20000<Dest I:8.0 4023<
MOVPRESSURE_DATA
This rung will scale pressure reading from 0.0 to 100.0 PSI.
0028SCP
Scale w/ParametersInput I:8.0 4023<Input Min. 4000 4000<Input Max. 20000 20000<Scaled Min. 0 0<Scaled Max. 1000 1000<Output N7:1 2<
SCPPRESSURE_READING
86
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
PRESSURE TRANSDUCER AVERAGE READINGTo reduce erratic fluctuations in the pressure reading, these next three rungs are used to take an average every half second. The first runginitiates a 50 millisecond timer (longest scan time is 20 ms, average 12 ms).
0029 EN
DN
TONTimer On DelayTimer T4:7Time Base 0.01Preset 5<Accum 4<
TONPRESSURE_TIME_SPACE
Each time the timer is 'done', the current PRESSURE_READING is added to the previous value and stored as PRESSURE_ADDITIVE. Thisis completed 10 times.
0030T4:7/DN
PRESSURE_TIME_SPACE/DNADD
AddSource A N7:1 2<Source B N7:23 2<Dest N7:23 2<
ADDPRESSURE_ADDITIVE
CU
DN
CTUCount UpCounter C5:2Preset 10<Accum 0<
CTUPRESS_UV_DENOMINATOR
After 10 pressure readings have been added together, the average of these values is sent to PRESSURE_AVERAGE, whilePRESSURE_ADDITIVE starts back at zero.
0031C5:2/DN
PRESS_UV_DENOMINATOR/DNDIV
DivideSource A N7:23 2<Source B 10 10<Dest N7:24 1<
DIVPRESSURE_AVERAGE
COPCopy FileSource #N7:15Dest #N7:23Length 1
COP#PRESSURE_ADDITIVE
Every time the duration of the PRESSURE_TIME_SPACE timer is 'done', it will be reset by the following rung.
0032GEQ
Grtr Than or Eql (A>=B)Source A T4:7.ACC 4<Source B 5 5<
GEQPRESSURE_TIME_SPACE.ACC
REST4:7
PRESSURE_TIME_SPACE
87
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
When the counter shows that all pressure points have been collected (i.e. 10), the counter is reset by the following rung.
0033EQU
EqualSource A C5:2.ACC 0<Source B 10 10<
EQUPRESS_UV_DENOMINATOR.ACC
RESC5:2
PRESS_UV_DENOMINATOR
88
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
THROTTLING VALVE CONTROLThese two rungs ensure the input value (SETPOINT) in PSI (e.g., 200 = 20.0 PSI) to be scaled remains within the limits of 0 to 100). This isnecessary to prevent "out of range" conversion errors in the PID instructions.
0034LES
Less Than (A<B)Source A N7:13 100<Source B 0 0<
LESTHROTTLE_SETPOINT
MOVMoveSource 0 0<Dest N7:13 100<
MOVTHROTTLE_SETPOINT
0035GRT
Greater Than (A>B)Source A N7:13 100<Source B 150 150<
GRTTHROTTLE_SETPOINT
MOVMoveSource 150 150<Dest N7:13 100<
MOVTHROTTLE_SETPOINT
This rung will copy the input value (SETPOINT) from the integer Data File into the SETPOINT destination of the PID instruction.
0036COP
Copy FileSource #N7:13Dest #N15:2Length 1
COP#PRESSURE_SETPOIN_PID
The source to be scaled is the PRESSURE_AVERAGE and its destination is the PROCESS VARIABLE (PV) of the PID instruction. Thesevalues are calculated knowing that the input is 0 to 100%, while the scaled range (PV) is 0 to 16383.
0037SCP
Scale w/ParametersInput N7:24 1<Input Min. 0 0<Input Max. 1000 1000<Scaled Min. 0 0<Scaled Max. 16383 16383<Output N15:28 16<
SCPVALVE_PV
0038PID
PIDControl Block N15:0Process Variable N15:28Control Variable N15:29Control Block Length 23
Setup Screen
PIDTHROTTLE_VALVE_PID
89
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
When the THROTTLE_VALVE_PID is in manual mode, this rung receives a 0-100% reading from RSView and sends it to the Control Outputfor the PID as well as scale the value for direct input to the Control Variable (the throttling valve). This allows for a percent power output to besent to the throttling valve manually, bypassing the PID. Both of these operations are necessary because RSLogix does not allow for a value(0-100) to be sent to the Control Output alone (word 16).
0039N15:0/1
THROTTLE_VALVE_PIDCOP
Copy FileSource #N7:22Dest #N15:16Length 1
COP#THROTTLE_CV_MANUL_IN
SCPScale w/ParametersInput #N7:22 0<Input Min. 0 0<Input Max. 100 100<Scaled Min. 0 0<Scaled Max. 16383 16383<Output N15:29 0<
SCPVALVE_CV
The PID CONTROL VARIABLE is the input for the scale instruction. The PID instruction guarantees that the CV remains within the range 0to 16383. This value is to be scaled to the range of 6242 to 31208, which represents the numeric range that is needed to produce 4 to 20 mAanalog output signal to the throttling valve.
0040B3/10 SCP
Scale w/ParametersInput N15:29 0<Input Min. 0 0<Input Max. 16383 16383<Scaled Min. 6242 6242<Scaled Max. 31208 31208<Output O:7.2 6242<
SCPTHROTTLING_VALVE
This rung immediately updates the analog OUTPUT used for the PIDs CONTROL VARIABLE
0041IOM
Immediate Output w/MaskSlot O:7.2Mask 0FFFFhLength 1
IOMTHROTTLING_VALVE
90
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
UV RADIOMETER OPERATINGThis rung will terminate UV readings, reset channels & timer, and clear ASCII buffers.
0042B3/0
UV_OPERATION
RESC5:0
UV_CHANNEL
REST4:0
UV_CHANNEL_TIMER
ACLAscii Clear BuffersChannel 0Receive Buffer NoTransmit Buffer Yes
ACL
This rung willl initiate the timer needed to allow the UV sensor reading to stabilize prior to taking a reading and switching channels (60 sec).
0043B3/0
UV_OPERATION
EN
DN
TONTimer On DelayTimer T4:0Time Base 0.01Preset 6000<Accum 493<
TONUV_CHANNEL_TIMER
This rung controls channel numbers starting with #1 and changes them after the timer is done.
0044B3/0
UV_OPERATIONT4:0/DN
UV_CHANNEL_TIMER/DN
EQUEqualSource A C5:0.ACC 3<Source B 0 0<
EQUUV_CHANNEL.ACC
CU
DN
CTUCount UpCounter C5:0Preset 4<Accum 3<
CTUUV_CHANNEL
This rung allows the TTL module to specify the correct channel on the UV multiplexer.
0045GEQ
Grtr Than or Eql (A>=B)Source A C5:0.ACC 3<Source B 1 1<
GEQUV_CHANNEL.ACC
NEQNot EqualSource A C5:0.ACC 3<Source B 2 2<
NEQUV_CHANNEL.ACC
O:4.0/0
1746-OG16
UV_CHANNEL_1
LESLess Than (A<B)Source A C5:0.ACC 3<Source B 3 3<
LESUV_CHANNEL.ACC
O:4.0/1
1746-OG16
UV_CHANNEL_2
O:4.0/2
1746-OG16
UV_CHANNEL_4
O:4.0/3
1746-OG16
UV_CHANNEL_8
91
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
As soon as the timer begins, this rung clears the ASCII channel so that the radiometer does not send a string.
0046LIM
Limit TestLow Lim 1 1<Test T4:0.ACC 493<High Lim 30 30<
LIMUV_CHANNEL_TIMER.ACC
EN
DN
ER
AHLAscii Handshake LinesChannel 0AND Mask 0002hOR Mask 0000hControl R6:0Channel Status 0010h Error 00h
AHLUV_HANDSHAKE_OFF
After a specified amount of time needed for the radiometer reading to stabilize (~ 5 s), this rung will then signal the radiometer to beginsending the ASCII characters and store them in the ASCII buffer.
0047LIM
Limit TestLow Lim 5970 5970<Test T4:0.ACC 493<High Lim 6000 6000<
LIMUV_CHANNEL_TIMER.ACC
EN
DN
ER
AHLAscii Handshake LinesChannel 0AND Mask 0000hOR Mask 0002hControl R6:1Channel Status 0012h Error 00h
AHLUV_HANDSHAKE_ON
This rung will read ASCII characters in the buffer for the UV reading and store them in a string elsewhere.
0048R6:1/EN
UV_HANDSHAKE_ON/EN
OSRB3/1
UV_READING_OSR
EN
DN
ER
ARLASCII Read LineChannel 0Dest ST9:0Control R6:2String Length 14<Characters Read 0 Error 00h
ARLUV_READING
This rung eliminates extraneous characters from stored UV reading (based on its length) and stores the actual reading elsewhere.
0049R6:2/EN
UV_READING/EN
OSRB3/2
UV_EXTRACT_OSRSUB
SubtractSource A ST9:0.LEN 7<Source B 1 1<Dest N7:0 7<
SUBUV_STRING_LENGTH
AEXString ExtractSource ST9:0Index 1Number N7:0Dest ST9:0
AEXUV_READING_STRING
COPCopy FileSource #ST9:0Dest #ST9:[C5:0.ACC]Length 1
COP#ST9:[UV_CHANNEL.ACC]
92
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
This rung clears the buffer prior to making the next reading.
0050GEQ
Grtr Than or Eql (A>=B)Source A T4:0.ACC 493<Source B 60 60<
GEQUV_CHANNEL_TIMER.ACC
OSRB3/3
UV_CLEAR_BUFFERS_OSRACL
Ascii Clear BuffersChannel 0Receive Buffer NoTransmit Buffer Yes
ACL
This rung resets the counter (used to specify channel #) to begin looping with the lower channel.
0051C5:0/DN
UV_CHANNEL/DN
RESC5:0
UV_CHANNEL
This rung resets the timer used for the UV radiometer control.
0052T4:0/DN
UV_CHANNEL_TIMER/DN
REST4:0
UV_CHANNEL_TIMER
93
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
RADIOMETER ASCII INTO FLOATING VALUEThis rung transforms the first numeric digit from the ASCII string value into an integer. (Keep in mind that the radiometer string characterslook like +1.234e-5 or +1.23e-4)
0053ACI
String to IntegerSource ST9:0Dest N7:16 0<
ACIUV_READING_STRING
This rung extracts the decimal digits from the ASCII string and sends them to another string location (this set of characters may include threedigits or two digits followed by an "e". this exponent symbol is removed in the next rung by converting the string into an integer).
0054AEX
String ExtractSource ST9:0Index 4Number 3Dest ST9:4
AEXUV_READING_STRING
This rung transforms the decimal digits from string data to an integer, dropping the 'e' if one existed.
0055ACI
String to IntegerSource ST9:4Dest N7:17 4<
ACIUV_DECIMAL_DIGITS_ST
This rung transforms the decimal digits (if 3) from integer form into an actual floating point decimal value.
0056GRT
Greater Than (A>B)Source A N7:17 4<Source B 99 99<
GRTUV_DECIMAL_DIGITS
DIVDivideSource A N7:17 4<Source B 1000.0 1000.0<Dest F8:3 0.04<
DIVUV_DECIMAL_DIGITS_FL
This rung transforms the decimal digits (if 2) from integer form into an actual floating point decimal value.
0057LES
Less Than (A<B)Source A N7:17 4<Source B 100 100<
LESUV_DECIMAL_DIGITS
DIVDivideSource A N7:17 4<Source B 100.0 100.0<Dest F8:3 0.04<
DIVUV_DECIMAL_DIGITS_FL
This rung adds together the integer part of the value with the decimal fraction to yield the actual UV value, but without the exponent (extractedin the next few rungs).
0058ADD
AddSource A N7:16 0<Source B F8:3 0.04<Dest F8:4 0.04<
ADDUV_FLOATING_VALUE
94
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
This rung extracts the ASCII string exponent value when 8 characters (the minimum) are received.
0059EQU
EqualSource A ST9:0.LEN 7<Source B 8 8<
EQUUV_READING_STRING.LEN
AEXString ExtractSource ST9:0Index 7Number 2Dest ST9:5
AEXUV_READING_STRING
This rung extracts the ASCII string exponent value when 9 characters (the maximum) are received.
0060EQU
EqualSource A ST9:0.LEN 7<Source B 9 9<
EQUUV_READING_STRING.LEN
AEXString ExtractSource ST9:0Index 8Number 2Dest ST9:5
AEXUV_READING_STRING
This rung transforms the string exponent into an integer (e.g. -4).
0061ACI
String to IntegerSource ST9:5Dest N7:18 -6<
ACIUV_EXPONENT_ST
This rung transforms the integer exponent into an actual decimal value (e.g. from -4 into 0.0001).
0062XPY
X To Power of YSource A 10.0 10.0<Source B N7:18 -6<Dest F8:5 1E-006<
XPYUV_EXP_FACTOR_FL
This rung multiplies the floating value with the exponent value to produce the actual numeric UV floating value.
0063MUL
MultiplySource A F8:4 0.04<Source B F8:5 1E-006<Dest F8:6 4.000001E-008<
MULUV_ACTUAL_READING_FL
Here the counter value used to determine the UV channel from before is added to the value 6, allowing the number to be used as an address forstoring the value into a floating file destination (follow into the next rung).
0064ADD
AddSource A C5:0.ACC 3<Source B 6 6<Dest N7:19 9<
ADDUV_FL_VALUE_DEST
95
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
This rung sends the actual floating point reading to the proper uv sensor destination.
0065GRT
Greater Than (A>B)Source A N7:19 9<Source B 6 6<
GRTUV_FL_VALUE_DEST
LESLess Than (A<B)Source A N7:19 9<Source B 10 10<
LESUV_FL_VALUE_DEST
COPCopy FileSource #F8:6Dest #F8:[N7:19]Length 1
COP#F8:[UV_FL_VALUE_DEST]
96
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
RTD OPERATINGThe following rung configures the RTD module to read temperatures within 1/10 F.
0066S:1/15
First PassCOP
Copy FileSource #B10:0Dest #O:5.0Length 4
COP#RTD_1_CONFIGURATION
The following run converts the temperature reading in deg. F to deg.C within 1/10 C. Note: C = (F-32)/1.8
0067SCP
Scale w/ParametersInput I:5.0 792<Input Min. 320 320<Input Max. 1040 1040<Scaled Min. 0 0<Scaled Max. 400 400<Output N7:4 262<
SCPRTD_1_DEG_C
SCPScale w/ParametersInput I:5.1 794<Input Min. 320 320<Input Max. 1040 1040<Scaled Min. 0 0<Scaled Max. 400 400<Output N7:5 263<
SCPRTD_2_DEG_C
97
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
LOW CONCENTRATION OZONE MONITOR READINGThese two rungs ensure the analog input value to be scaled remains within the limits of 4000 to 20000. This is necessary to prevent "out ofrange" conversion errors in both the SCP and PID instructions.
0068LES
Less Than (A<B)Source A I:9.1 4007<Source B 4000 4000<
LESLC_O3_DATA
MOVMoveSource 4000 4000<Dest I:9.1 4007<
MOVLC_O3_DATA
0069GRT
Greater Than (A>B)Source A I:9.1 4007<Source B 20000 20000<
GRTLC_O3_DATA
MOVMoveSource 20000 20000<Dest I:9.1 4007<
MOVLC_O3_DATA
This rung will scale the LC MONITOR reading from 0.000 to 5.000 PPMV.
0070SCP
Scale w/ParametersInput I:9.1 4007<Input Min. 4000 4000<Input Max. 20000 20000<Scaled Min. 0 0<Scaled Max. 5000 5000<Output N7:6 1<
SCPLC_OZONE_READING
98
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
DISSOLVED OZONE MONITOR READINGThese two rungs ensure the analog input value to be scaled remains within the limits of 4000 to 20000. This is necessary to prevent "out ofrange" conversion errors in both the SCP and PID instructions.
0071LES
Less Than (A<B)Source A I:9.2 4009<Source B 4000 4000<
LESDISSOLVED_O3_DATA
MOVMoveSource 4000 4000<Dest I:9.2 4009<
MOVDISSOLVED_O3_DATA
0072GRT
Greater Than (A>B)Source A I:9.2 4009<Source B 20000 20000<
GRTDISSOLVED_O3_DATA
MOVMoveSource 20000 20000<Dest I:9.2 4009<
MOVDISSOLVED_O3_DATA
This rung will scale the DISSOLVED OZONE MONITOR reading from 0.00 to 10.000 mg/L.
0073SCP
Scale w/ParametersInput I:9.2 4009<Input Min. 4000 4000<Input Max. 20000 20000<Scaled Min. 0 0<Scaled Max. 10000 10000<Output N7:8 6<
SCPDISSOLVED_OZONE_READ
99
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
TURBIDITY METER READINGThese two rungs ensure the analog input value to be scaled remains within the limits of 4000 to 20000. This is necessary to prevent "out ofrange" conversion errors in both the SCP and PID instructions.
0074LES
Less Than (A<B)Source A I:9.4 4712<Source B 4000 4000<
LESTURBIDITY_1_DATA
MOVMoveSource 4000 4000<Dest I:9.4 4712<
MOVTURBIDITY_1_DATA
0075GRT
Greater Than (A>B)Source A I:9.4 4712<Source B 20000 20000<
GRTTURBIDITY_1_DATA
MOVMoveSource 20000 20000<Dest I:9.4 4712<
MOVTURBIDITY_1_DATA
This rung will scale the TURBIDITY METER READING to the range of 0.0 to 400.0 NTU.
0076SCP
Scale w/ParametersInput I:9.4 4712<Input Min. 4000.0 4000.0<Input Max. 20000.0 20000.0<Scaled Min. 0.0 0.0<Scaled Max. 4000.0 4000.0<Output N7:9 178<
SCPTURBIDITY_READING
100
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
ORP METER READINGThese two rungs ensure the analog input value to be scaled remains within the limits of 4000 to 20000. This is necessary to prevent "out ofrange" conversion errors in both the SCP and PID instructions.
0077LES
Less Than (A<B)Source A I:9.3 17254<Source B 4000 4000<
LESORP_DATA
MOVMoveSource 4000 4000<Dest I:9.3 17254<
MOVORP_DATA
0078GRT
Greater Than (A>B)Source A I:9.3 17254<Source B 20000 20000<
GRTORP_DATA
MOVMoveSource 20000 20000<Dest I:9.3 17254<
MOVORP_DATA
This rung will scale the ORP reading from -1500 to 1500 mV.
0079SCP
Scale w/ParametersInput I:9.3 17254<Input Min. 4000.0 4000.0<Input Max. 20000.0 20000.0<Scaled Min. -1500.0 -1500.0<Scaled Max. 1500.0 1500.0<Output N7:10 986<
SCPORP_METER_READING
101
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
TRANSFER PUMP CONTROLIf the Auto/Manual bit is false (i.e. in Auto mode), then Ball Valve #1 determines if the Transfer Pump is on or not. If the bit is true (i.e. inManual mode), then a toggle button in RSView will control the Transfer Pump. To minimize initial rapid on/off of the pump, the solenoid mustbe actuated for 1.0 second to activate the transfer pump, but this will not effect the frequency of the ball valve opening due to its control by theexternal level meter relay.
0080B3/7
TRANS_PUMP_AUTO_MANI:1.0/1
1746-IO8
SOLENOID_1_POWER
EN
DN
TONTimer On DelayTimer T4:5Time Base 0.01Preset 100<Accum 0<
TONDAMPEN_ON
0081T4:5/DN
DAMPEN_ON/DN
B3/7TRANS_PUMP_AUTO_MAN
B3/8TRANS_PUMP_ON_OFF
LO:1.0/2
1746-IO8
TRANSFER_PUMP
Similar to the above two rungs, the following rungs are set to require the solenoid to be closed for 1.0 second in order to unlatch (i.e. turn off)the transfer pump. These rungs inhibit the pump from rapidly turning on and off repeatedly.
0082B3/7
TRANS_PUMP_AUTO_MANI:1.0/1
1746-IO8
SOLENOID_1_POWER
EN
DN
TONTimer On DelayTimer T4:6Time Base 0.01Preset 100<Accum 100<
TONDAMPEN_OFF
0083T4:6/DN
DAMPEN_OFF/DN
B3/7TRANS_PUMP_AUTO_MAN
B3/8TRANS_PUMP_ON_OFF
UO:1.0/2
1746-IO8
TRANSFER_PUMP
102
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
HYDROCYCLONE PURGE VALVE CONTROLOnce the system is turned on and the bit is activated, a 10 minute timer starts. This timer precludes the initiation of the hydrocyclone purgingcycle.
0084 EN
DN
TONTimer On DelayTimer T4:4Time Base 1.0Preset 600<Accum 244<
TONSTARTUP_DELAY
After the initial START_UP_DELAY is completed, an 8 minute timer begins (minus actual purge time, 2.00 sec). This is the duration of timebetween purging, entitled PURGE_ON_DELAY.
0085T4:4/DN
STARTUP_DELAY/DN
EN
DN
TONTimer On DelayTimer T4:1Time Base 1.0Preset 478<Accum 0<
TONPURGE_ON_DELAY
Once the PURGE_ON_DELAY is completed and the PURGE_CYCLE_START is depressed in RSView, SOLENOID_2 actuates (i.e. thehydrocyclone purge valve opens). SOLENOID_2 can also be opened "manually" by depressing a momentary button on RSView while thePURGE_CYCLE_START is engaged. Additionally, SOLENOID_2 is opened when in the hydrocyclone stage of the flush process.
0086T4:1/DN
PURGE_ON_DELAY/DNB3/4
PURGE_CYCLE_START
B3/5RSVIEW_PURGE_BUTTON
B3/4PURGE_CYCLE_START
B3/13STARTED_FLUSH
EQUEqualSource A C5:4.ACC 0<Source B 0 0<
EQUFLUSH_STAGE.ACC
O:1.0/0
1746-IO8
SOLENOID_2
This rung controls the duration of the time for the purge valve to be opened. After 478 seconds pass, the hydrocyclone purge valve opens for2.00 seconds.
0087T4:1/DN
PURGE_ON_DELAY/DN
EN
DN
TONTimer On DelayTimer T4:2Time Base 0.01Preset 200<Accum 0<
TONPURGE_DURATION
Once the 478 second delay is complete and the 2.00 second purge duration is complete, both timers are reset, thereby closing the purge valveand reinstating the 8 minute purge cycle.
0088T4:2/DN
PURGE_DURATION/DN
REST4:1
PURGE_ON_DELAY
REST4:2
PURGE_DURATION
103
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
CLEANING/SANITATION OPERATIONOnce a momentary button is depressed in RSView, the flush process is latched and the pump drive PID is forced into manual mode, thusallowing to write percent output to the pump control. (NOTE: several following rungs have a condition for the action of the pause button. thisallows for each rung to hold at its current state, but the rung interuption will reset any timer. see also rung #0101.)
0089B3/11
START_FLUSHB3/16
PAUSE_BUTTON
LB3/13
STARTED_FLUSH
LN13:0/1
PUMP_DRIVE_PID
RESC5:4
FLUSH_STAGE
After the flush process has started and is latched, the program waits for the inlet valve to close (i.e. the settling tank is full), before initiating thestaged flushing process.
0090B3/13
STARTED_FLUSHI:1.0/1
1746-IO8
SOLENOID_1_POWERB3/16
PAUSE_BUTTON
LB3/12
FLUSHING
If the flushing cycle is enganged, the flush stage is less than three (i.e. hydrocyclone, reactors, or columns), four or less flushing cycles havepassed, and the draining period is not done, then the pump is ramped to 100% power and a 20 second timer is initiated. This allows for 20seconds of flushing.
0091B3/12
FLUSHINGLES
Less Than (A<B)Source A C5:4.ACC 0<Source B 3 3<
LESFLUSH_STAGE.ACC
LESLess Than (A<B)Source A C5:3.ACC 0<Source B 4 4<
LESCYCLE_NUMBER.ACC
B3/16PAUSE_BUTTON
MOVMoveSource 100 100<Dest #N7:20 0<
MOV#PUMP_CONTROL_OUTPUT
EN
DN
TONTimer On DelayTimer T4:9Time Base 1.0Preset 20<Accum 0<
TONFLUSH_TIME
104
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
After the 20 second flush period is done, the rung overwrites the pump control output to be 0% and drain time is initiated for 40 seconds.
0092T4:9/DN
FLUSH_TIME/DNMOV
MoveSource 0 0<Dest #N7:20 0<
MOV#PUMP_CONTROL_OUTPUT
EN
DN
TONTimer On DelayTimer T4:10Time Base 1.0Preset 70<Accum 0<
TONDRAIN_TIME
If draining is complete and the inlet valve is closed (i.e. the settling tank is full), then one flush cycle has been completed, adding to thecounter, and the drain and flush timers are reset for the next cycle, unless four cycles have been completed.
0093T4:10/DN
DRAIN_TIME/DNI:1.0/1
1746-IO8
SOLENOID_1_POWER
CU
DN
CTUCount UpCounter C5:3Preset 4<Accum 0<
CTUCYCLE_NUMBER
REST4:9
FLUSH_TIME
REST4:10
DRAIN_TIME
Once four flush cycles have been completed, the series stops due to cycle number equal to 4, showing the status of the flush progress inRSView and allowing the user to close appropriate drain valves before clicking the "next stage" button. This allows for the flush series toreinitiate and a counter records the stage number.
0094B3/14
NEXT_STAGE_BUTTONB3/16
PAUSE_BUTTON
RESC5:3
CYCLE_NUMBER
CU
DN
CTUCount UpCounter C5:4Preset 8<Accum 0<
CTUFLUSH_STAGE
105
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
After stages for flushing the hydrocyclone, reactors, and columns have been completed (i.e. while in system filling and the counter reads 3) and10 filling cycles have not yet been completed, the initial flushing cycle is unlatched and the pump is again brought to 100% power with a 45sec timer being initiated. If the filling cycle is completed and the stage counter reads 4 (i.e. during final rinse), then this series repeats itself onemore time to allow for the columns to flush and the user to bleed air from the columns as well.
0095EQU
EqualSource A C5:4.ACC 0<Source B 3 3<
EQUFLUSH_STAGE.ACC
EQUEqualSource A C5:4.ACC 0<Source B 4 4<
EQUFLUSH_STAGE.ACC
LESLess Than (A<B)Source A C5:5.ACC 0<Source B 10 10<
LESFILL_AND_RINSE.ACC
B3/16PAUSE_BUTTON
UB3/13
STARTED_FLUSH
MOVMoveSource 100 100<Dest #N7:20 0<
MOV#PUMP_CONTROL_OUTPUT
EN
DN
TONTimer On DelayTimer T4:11Time Base 1.0Preset 45<Accum 0<
TONFINAL_FILL_FLUSH
After the previous timer is completed and the inlet is open (i.e. settling tank not full) then the pump power is reduced to 0% to allow for filling.This will also occur once the 10 fill cycles are completed.
0096T4:11/DN
FINAL_FILL_FLUSH/DNI:1.0/1
1746-IO8
SOLENOID_1_POWER
GEQGrtr Than or Eql (A>=B)Source A C5:5.ACC 0<Source B 10 10<
GEQFILL_AND_RINSE.ACC
MOVMoveSource 0 0<Dest #N7:20 0<
MOV#PUMP_CONTROL_OUTPUT
106
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
If the 60 second timer is done and the inlet valve is closed (i.e. the settling tank is full) then the final fill and flush stage continues. This allowsfor the pump to always operate with high output and to periodically check the height of the settling tank, preventing the pump from runningdry. Also, each time this rung becomes true, the counter is increased until reaching 10, enough cycles to fill the columns and adequately finishflushing the prototype.
0097T4:11/DN
FINAL_FILL_FLUSH/DNI:1.0/1
1746-IO8
SOLENOID_1_POWER
REST4:11
FINAL_FILL_FLUSH
CU
DN
CTUCount UpCounter C5:5Preset 10<Accum 0<
CTUFILL_AND_RINSE
Whenever the "next stage" button in RSView is depressed, the fill and rinse counter is reset, essentially allowing transition from system fill, tofinal rinse, to closed loop. The other occurences when the next stage button resets the counter are irrelevant.
0098B3/14
NEXT_STAGE_BUTTONB3/16
PAUSE_BUTTON
RESC5:5
FILL_AND_RINSE
After the final rinse is complete and the "next stage" button is depressed, increasing the counter value to 5, the pump is again engaged to 100%power for the period of 45 minutes. Here the 3-way outlet valve should have been placed in the loop position and cleaner or sanitizer may beadded.
0099EQU
EqualSource A C5:4.ACC 0<Source B 5 5<
EQUFLUSH_STAGE.ACC
B3/16PAUSE_BUTTON
MOVMoveSource 100 100<Dest #N7:20 0<
MOV#PUMP_CONTROL_OUTPUT
EN
DN
RTORetentive Timer OnTimer T4:12Time Base 1.0Preset 2700<Accum 0<
RTOCLOSED_LOOP_DURATION
Once the closed loop stage is completed, the pump is forced to 0%.
0100T4:12/DN
CLOSED_LOOP_DURATION/DN
GEQGrtr Than or Eql (A>=B)Source A C5:4.ACC 0<Source B 6 6<
GEQFLUSH_STAGE.ACC
MOVMoveSource 0 0<Dest N7:20 0<
MOVPUMP_CONTROL_OUTPUT
After the closed loop stage is completed and the next stage button is depressed in RSView, the loop timer is reset.
0101T4:12/DN
CLOSED_LOOP_DURATION/DNB3/14
NEXT_STAGE_BUTTON
REST4:12
CLOSED_LOOP_DURATION
The 'pause button' in RSView will reset all timers, but hold all counters in their current state so that once the latch button is released, the flushprocess will begin again where it left off.
0102B3/16
PAUSE_BUTTONMOV
MoveSource 0 0<Dest N7:20 0<
MOVPUMP_CONTROL_OUTPUT
107
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
If the counter is equal to 6 (not shown in ladder logic), an indicator within RSView shows the flush process is completed. Thereafter, when the"next stage" button is again activated (i.e. stage counter equals 7), or the abort button is depressed within RSView, all parameters within theflush process are reset.
0103GEQ
Grtr Than or Eql (A>=B)Source A C5:4.ACC 0<Source B 7 7<
GEQFLUSH_STAGE.ACC
B3/15ABORT__RESET
UB3/13
STARTED_FLUSH
UB3/12
FLUSHING
MOVMoveSource 0 0<Dest N7:20 0<
MOVPUMP_CONTROL_OUTPUT
REST4:9
FLUSH_TIME
REST4:10
DRAIN_TIME
RESC5:3
CYCLE_NUMBER
RESC5:4
FLUSH_STAGE
REST4:11
FINAL_FILL_FLUSH
RESC5:5
FILL_AND_RINSE
REST4:12
CLOSED_LOOP_DURATION
108
O3_UV_PROTOTYPE24
LAD 2 - --- Total Rungs in File = 108
RSVIEW ANIMATIONThe following conditions simply code for when each stage of the flush procedure has completed, setting the bit to true. This hereby actuates anindicator light in RSView and alerts the user with an 'alarm bell'.
0104LES
Less Than (A<B)Source A C5:4.ACC 0<Source B 3 3<
LESFLUSH_STAGE.ACC
EQUEqualSource A C5:3.ACC 0<Source B 4 4<
EQUCYCLE_NUMBER.ACC
GRTGreater Than (A>B)Source A C5:4.ACC 0<Source B 2 2<
GRTFLUSH_STAGE.ACC
LESLess Than (A<B)Source A C5:4.ACC 0<Source B 5 5<
LESFLUSH_STAGE.ACC
EQUEqualSource A C5:5.ACC 0<Source B 10 10<
EQUFILL_AND_RINSE.ACC
EQUEqualSource A C5:4.ACC 0<Source B 5 5<
EQUFLUSH_STAGE.ACC
EQUEqualSource A T4:12.ACC 0<Source B 2700 2700<
EQUCLOSED_LOOP_DURATION.ACC
B3/18
STAGEDONE
This rung simply counts 4 seconds repeatedly. The time is used in RSView to animate various graphics (purely asthetics).
0105 EN
DN
TONTimer On DelayTimer T4:8Time Base 1.0Preset 4<Accum 0<
TONANIMATE_TIMER
This rung resets the animation timer to allow for constant repition of the count from 0 to 3.
0106T4:8/DN
ANIMATE_TIMER/DN
REST4:8
ANIMATE_TIMER
0107 END
109
APPENDIX C
HMI TAG TABLE
Tag Name and Description Type Min Max Scale Units Address
Animation_Timer Analog 0 100 1 sec T4:8:ACC 4-second repeating timer to allow for animation controls Comments String -- After typing comment, press 'enter' to log to '2StringTable' Dissolved_O3_Monitor Analog 0 10 0.001 mg/L N7:8 Effluent dissolved ozone concentration Flowmeter Analog 0 94.64 0.01 L/min N7:2 System flowrate Flush_Abort_Reset Digital B3:0/15 Momentary, allows for resetting the flush procedure Flush_Cycle Analog 0 4 1 -- C5:3.ACC Indicates which of 4 flush cycles in progress Flush_Drain Analog 0 100 1 sec T4:10.ACC Duration of drain time during flush procedure Flush_Fill_Cycle Analog 0 100 1 -- C5:5.ACC Which of 10 cycles in progress, system fill and final flush Flush_Flushing Analog 0 100 1 sec T4:9.ACC Duration of flush time during flush procedure Flush_Latched Digital B3:0/12 Bit for activation of flush process Flush_Loop_Time Analog 0 2700 1 sec T4:12.ACC Time remaining for final closed loop duration Flush_Next_Stage Digital B3:0/14 Increases counter in RSLogix, progress to next stage Flush_Pause Digital B3:1/0 Halts the flush procedure until latch button released Flush_Stage Analog 0 100 1 -- C5:4.ACC The flush procedure stage indicated by RSLogix counter Flush_Stage_Done Digital B3:1/2 Allows for alarm and indicator light to appear Flush_Start Digital B3:0/11 Bit for activation of flush process Flush_Started Digital B3:0/13 Bit to display indicator light for flush in progress HC_Ozone_Monitor Analog 0 15 0.01 % wt N7:7 Ozone generator setpoint Hydrocyclone_Cycle_Initiation Digital B3:0/4 Initiates the 8 minute cycle for purging the hydrocyclone Hydrocyclone_Manual_Momentary Digital B3:0/5 Manual purge for the hydrocyclone purge valve
110
Tag Name and Description Type Min Max Scale Units Address
Hydrocyclone_Opens Digital 0:1.0/0 Indicates hydrocyclone purges Hydrocyclone_Time_Until_Purge Analog 0 478 1 sec T4:1.ACC Time before the next hydrocyclone purge Inlet_Valve Digital I:1.0/1 Indicates position of inlet valve, 0 closed, 1 open LC_Ozone_Monitor Analog 0 5 0.001 ppmv N7:6 Low concentration ozone reading Level_Meter Digital I:1.0/0 Indicates water level in settling tank, 0 high, 1 low ORP_Meter Analog -1500 1500 1 mV N7:10 Effluent ORP Ozone_Auto_Manual Digital N14:0/1 1 indicates PID loop initiated Ozone_Control_Output Analog 0 100 1 % N7:21 The percent power output to the ozone generator Ozone_Gain_Kc Analog 0 3276.7 0.1 -- N14:3 Ozone generator PID gain value Ozone_Generator_Setpoint Analog 0 15 0.01 % wt N7:12 Ozone generator setpoint Ozone_Loop_Update Analog 0 10 0.01 sec N14:13 Ozone generator PID loop update value Ozone_mA_Input Analog 4 20 0.0006409 mA O:7.0 Current level sent to ozone generator Ozone_Output_Read Analog 0 100 1 % N14:16 The percent power that the ozone generator uses Ozone_Rate_Td Analog 0 327.67 0.01 min N14:5 Ozone generator PID rate value Ozone_Reset_Ti Analog 0 3276.7 0.1 min/r N14:4 Ozone generator PID reset value Pressure_Auto_Manual Digital N15:0/1 1 indicates PID loop initiated Pressure_Average Analog 0 100 0.1 psi N7:24 Contact column pressure averaged every 1/2 second Pressure_Control_Output Analog 0 100 1 % N7:22 The percent output to the throttling valve Pressure_Gain_Kc Analog 0 3276.7 0.1 -- N15:3 Pressure PID gain value Pressure_Loop_Update Analog 0 10 0.01 sec N15:13 Pressure PID loop update value Pressure_mA_Input Analog 4 20 0.0006409 mA O:7.2 Current level sent to the throttling valve Pressure_Output_Read Analog 0 100 1 % N15:16 The percent level that the throttling valve uses Pressure_Rate_Td Analog 0 327.67 0.01 min N15:5 Pressure PID rate value Pressure_Reset_Ti Analog 0 3276.7 0.1 min/r N15:4 Pressure PID reset value Pressure_Setpoint Analog 0 15 0.1 psi N7:13 Pressure setpoint Pressure_Transducer Analog 0 100 0.1 psi N7:1 Contact column pressure, immediate response
111
Tag Name and Description Type Min Max Scale Units Address
Pump_Auto_Manual Digital N13:0/1 1 indicates PID loop initiated Pump_Control_Output Analog 0 100 1 % N7:20 The percent output to the main pump Pump_Gain_Kc Analog 0 3276.7 0.1 -- N13:3 Pump PID gain value Pump_Loop_Update Analog 0 100 0.01 sec N13:13 Pump PID loop update value Pump_mA_Input Analog 4 20 0.0006409 mA O:7.1 Current level sent to the main pump Pump_Rate_Td Analog 0 327.67 0.01 min N13:5 Pump PID rate value Pump_Reset_Ti Analog 0 3276.7 0.1 min/r N13:4 Pump PID reset value Pump_Setpoint Analog 0 94.64 0.01 L/min N7:11 System flowrate 'setpoint' RTD_1_ Analog 0 40 0.1 F N7:4 Influent temperature RTD_2 Analog 0 40 0.1 F N7:5 Effluent temperature Transfer_Pump Digital O:1.0/2 Initiates power to transfer pump through relay switch Transfer_Pump_Auto_Manual Digital B3:0/7 Latch to transfer to manual transfer pump operation Transfer_Pump_On_Off Digital B3:0/8 Will turn on/off the transfer pump when in manual mode Turbidity Analog 0 400 0.1 NTU N7:9 Effluent turbidity UV1_Numeric Analog 0 10 1000000 mW/cm2 F8:8 Floating value of UV1 string data UV2_Numeric Analog 0 10 1000000 mW/cm2 F8:9 Floating value of UV2 string data UV3_Numeric Analog 0 10 1000000 mW/cm2 F8:7 Floating value of UV3 string data UV_Radiometer_Operation Digital B3:0/0 Commands UV Multiplexer to initiate or terminate reading UV_Sensor_1 String ST9:2 UV Sensor 1 reading UV_Sensor_2 String ST9:3 UV Sensor 2 reading UV_Sensor_3 String ST9:1 UV Sensor 3 reading UV_Sensor_Current Analog 0 4 1 -- C5:0.ACC Which UV Sensor is being analyzed by the multiplexer
112
APPENDIX D
TSS TABULAR DATA
Table D.1 TSS for Formulated Suspension Tests
Inlet Water
Time (min) TestA TestB TestC Average StDev10 383.0 403.8 450.0 412.3 34.315 334.8 429.8 437.7 400.8 57.220 405.2 418.8 401.7 408.6 9.125 381.2 351.0 368.8 367.0 15.2
Average 376.0 400.9 414.5 397.2 34.9
Post-Hydrosieve
Time (min) TestA TestB TestC Average StDev10 377.0 280.5 351.3 336.3 50.015 389.0 354.2 406.8 383.3 26.820 335.0 394.3 343.8 357.7 32.025 361.5 338.2 340.0 346.6 13.0
Average 365.6 341.8 360.5 356.0 33.7
Post-Settling Tank
Time (min) TestA TestB TestC Average StDev10 244.7 243.7 245.3 244.6 0.815 261.5 246.7 234.3 247.5 13.620 223.2 247.0 202.8 224.3 22.125 240.5 237.7 244.3 240.8 3.3
Average 242.5 243.8 231.7 239.3 14.6
Post-Hydrocyclone
Time (min) TestA TestB TestC Average StDev10 178.5 162.7 174.5 171.9 8.215 163.3 169.5 164.5 165.8 3.320 177.3 179.0 168.3 174.9 5.725 178.8 175.8 174.0 176.2 2.4
Average 174.5 171.8 170.3 172.2 6.2
TSS SummaryAVG STDEV % Remaining397.2 19.5 100.0356.0 12.5 89.6239.3 6.6 60.3172.2 2.1 43.4
Concentration (mg/L)
Concentration (mg/L)
Concentration (mg/L)
Concentration (mg/L)
Post-Hydrocyclone
Inlet WaterPost-Hydrosieve
Post-Settling Tank
113
Table D.2 Chiller Water TSS Evaluation Inlet Water
Time\Date A, 8-5 B, 8-23 C, 8-26 D, 9-1 E, 9-7 F, 9-27 G, 9-29 H, 10-1 Average StDev9am 493 664 386 891 695 570 643 643 623 14911am 411 681 367 723 593 599 639 764 597 141
Average 452 673 377 807 644 585 641 704 610 141
Post-Hydrosieve
Time\Date A, 8-5 B, 8-23 C, 8-26 D, 9-1 E, 9-7 F, 9-27 G, 9-29 H, 10-1 Average StDev9am 361 542 309 527 548 443 429 512 459 8911am 284 473 289 488 404 443 441 481 413 82
Average 323 508 299 508 476 443 435 497 436 86
Post-Settling Tank
Time\Date A, 8-5 B, 8-23 C, 8-26 D, 9-1 E, 9-7 F, 9-27 G, 9-29 H, 10-1 Average StDev9am 390 531 290 545 508 450 490 479 460 8411am 339 497 279 448 385 412 445 472 410 73
Average 365 514 285 497 447 431 468 476 435 80
Post-Hydrocyclone
Time\Date A, 8-5 B, 8-23 C, 8-26 D, 9-1 E, 9-7 F, 9-27 G, 9-29 H, 10-1 Average StDev9am 394 505 283 547 501 437 483 470 453 8311am 333 495 276 442 395 436 422 469 409 72
Average 364 500 280 495 448 437 453 470 431 78
TSS Summary
AVG STDEV %Remain. AVG STDEV %Remain. AVG STDEV %Remain.623 149 100 597 141 100 610 141 100459 89 74 413 82 69 436 86 71460 84 74 410 73 69 435 80 71453 83 73 409 72 68 431 78 71
11am Overall
Concentration (mg/L)
Concentration (mg/L)
Concentration (mg/L)
Concentration (mg/L)
Post-HydrosievePost-Settling TankPost-Hydrocuclone
9am
Inlet Water
114
APPENDIX E
CHILLER WATER STATISTICAL ANALYSIS
E.1 APC Evaluation
1. Parameters that correlate with treatments (tt) from reactor (y1) and column (y2) a. tt and y1 p = .0129 * b. tt and y2 p = .2861 c. channel and y2 p < .0001 ** d. no other initial correlations
2. Does time or day effect (inlet) a. day p = .2421 b. time p = .0178 *
3. Does time or day effect (solids) a. day p = .2808 b. time p = .0179 *
4. Difference between (inlet) and (solids) a. i_and_s p = .8835
5. Difference between (inlet) and (solids), 9am only a. i_and_s p = .6843
6. Difference between (inlet) and (solids), 11am only a. i_and_s p = .2188
7. Factors effecting reactor treatment (y1) a. day p = .4981 b. time p = .8245 c. channel p = .4364 d. tt p = .2586
8. Factors effecting column treatment (y2) a. day p = .1322 b. time p = .5787 c. channel p < .0001 ** d. tt p = .5738
9. Difference between reactor (y1) and column (y2) a. ry_and_cy p = .3051
10. Contrast differences between treatments for reactor (y1) a. 1 vs 2 p = .7723 b. 1 vs 3 p = .5816 c. 1 vs 4 p = .5280 d. 1 vs 5 p = .0940
115
e. 1 vs 6 p = .0687 f. 2 vs 3 p = .7923 g. 2 vs 4 p = .7307 h. 2 vs 5 p = .1581 i. 2 vs 6 p = .1141 j. 3 vs 4 p = .9353 k. 3 vs 5 p = .2441 l. 3 vs 6 p = .1755 m. 4 vs 5 p = .2767 n. 4 vs 6 p = .1991 o. 5 vs 6 p = .7779
11. Contrast difference between treatment levels (y1) a. uv vs no-uv p = .7048 b. o3 vs no-o3 p = .0888 c. low-o3 vs no-o3 p = .5277 d. high-o3 vs no-o3 p = .0261 * e. low-o3 vs high-o3 p = .0889 f. o3 linear response p = .0261 * g. low-o3+uv vs low-o3/uv p = .8059 h. high-o3+uv vs high-3/uv p = .2860
12. Contrast between (days) for (y1) a. 1 vs 2 p = .1937 b. 1 vs 3 p = .8725 c. 1 vs 4 p = .2519 d. 1 vs 5 p = .9797 e. 1 vs 6 p = .7150 f. 2 vs 3 p = .1721 g. 2 vs 4 p = .8702 h. 2 vs 5 p = .2020 i. 2 vs 6 p = .3410 j. 3 vs 4 p = .2213 k. 3 vs 5 p = .8538 l. 3 vs 6 p = .6171 m. 4 vs 5 p = .2620 n. 4 vs 6 p = .4273 o. 5 vs 6 p = .7340
13. Contrast between (time) for (y1) a. 9am vs 11am p = .8810
14. Contrast between (channel) for (y1) a. 1 vs 2 p = .4647 b. 1 vs 3 p = .6391 c. 2 vs 3 p = .2218 d. 1 vs 2&3 p = .8814 e. 2 vs 1&3 p = .2609 f. 3 vs 1&2 p = .3289
15. Adjustment for multiple comparisons of (y1) effect by (tt)
116
a. All 95% confidence limits for difference between means includes zero 16. Waller-Duncan K-ratio t-Test for (tt) effect on (y1)
a. No significant difference between means at 5% 17. Tukey’s Studentized Range, HSD, Test for (tt) effect on (y1)
a. No significant difference between means at 5% 18. Contrast differences between treatments for reactor (y2)
a. 1 vs 2 p = .9638 b. 1 vs 3 p = .7283 c. 1 vs 4 p = .2825 d. 1 vs 5 p = .1903 e. 1 vs 6 p = .3122 f. 2 vs 3 p = .6947 g. 2 vs 4 p = .2636 h. 2 vs 5 p = .1764 i. 2 vs 6 p = .2932 j. 3 vs 4 p = .4604 k. 3 vs 5 p = .3272 l. 3 vs 6 p = .4866 m. 4 vs 5 p = .8035 n. 4 vs 6 p = .9946 o. 5 vs 6 p = .8212
19. Contrast difference between treatment levels (y2) a. uv vs no-uv p = .7972 b. o3 vs no-o3 p = .1213 c. low-o3 vs no-o3 p = .3007 d. high-o3 vs no-o3 p = .1022 e. low-o3 vs high-o3 p = .4979 f. o3 linear response p = .1022 g. low-o3+uv vs low-o3/uv p = .2850 h. high-o3+uv vs high-3/uv p = .6353
20. Contrast between (days) for (y2) a. 1 vs 2 p = .8867 b. 1 vs 3 p = .4516 c. 1 vs 4 p = .5517 d. 1 vs 5 p = .4531 e. 1 vs 6 p = .0413 * f. 2 vs 3 p = .3777 g. 2 vs 4 p = .6496 h. 2 vs 5 p = .3740 i. 2 vs 6 p = .0307 * j. 3 vs 4 p = .1981 k. 3 vs 5 p = .9573 l. 3 vs 6 p = .2184 m. 4 vs 5 p = .1861 n. 4 vs 6 p = .0115 * o. 5 vs 6 p = .1708
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21. Contrast between (time) for (y2) a. 9am vs 11am p = .5063
22. Contrast between (channel) for (y2) a. 1 vs 2 p = .0007 ** b. 1 vs 3 p < .0001 ** c. 2 vs 3 p = .2650 d. 1 vs 2&3 p < .0001 ** e. 2 vs 1&3 p = .0963 f. 3 vs 1&2 p = .0015 **
23. Adjustment for multiple comparisons of (y2) effect by (tt) a. All 95% confidence limits for difference between means includes zero
24. Waller-Duncan K-ratio t-Test for (tt) effect on (y2) a. No significant difference between means at 5%
25. Tukey’s Studentized Range, HSD, Test for (tt) effect on (y2) a. No significant difference between means at 5%
E.2 Turbidity Evaluation
1. Correlation between (inlet) and (solids) with (Tinlet) and (Tsolids) a. inlet and Tinlet p = .5900 b. solids and Tsolids p = .0448 * c. Tsolids and Tinlet p < .0001 **
2. Correlation between (reactor) and (column) with (Treactor) and (Tcolumn) a. reactor and Treactor p = .0631 b. column and Tcolumn p = .5083 c. Treactor and Tcolumn p = .0912
3. Correlation between reactor (y1 and Ty1) and column (y2 and Ty2) a. no initial correlations
4. Parameters that correlate with treatments (tt) from reactor (Ty1) and column (Ty2) a. tt and Ty1 p = .0004 ** b. tt and Ty2 p = .3737 c. channel and Ty2 p = .4944 d. no other initial correlations
5. Does time or day effect (Tinlet) a. day p = .1058 b. time p = .2560
6. Does time or day effect (Tsolids) a. day p = .0110 * b. time p = .0252 *
7. Difference between (Tinlet) and (Tsolids) a. T_i_and_s p = .5735
8. Difference between (Tinlet) and (Tsolids), 9am only a. T_i_and_s p = .6690
9. Difference between (Tinlet) and (Tsolids), 11am only a. i_and_s p = .5644
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10. Factors effecting reactor treatment (Ty1) a. day p = .0057 ** b. time p = .2456 c. channel p = .8258 d. tt p = .0002 **
11. Factors effecting column treatment (Ty2) a. day p = .6001 b. time p = .9937 c. channel p = .6325 d. tt p = .3621
12. Difference between reactor (Ty1) and column (Ty2) a. Try_and_cy p = .0008 **
13. Contrast differences between treatments for reactor (Ty1) a. 1 vs 2 p = .7304 b. 1 vs 3 p = .0044 * c. 1 vs 4 p = .0002 ** d. 1 vs 5 p = .0065 ** e. 1 vs 6 p = .0005 ** f. 2 vs 3 p = .0080 ** g. 2 vs 4 p = .0011 ** h. 2 vs 5 p = .0164 * i. 2 vs 6 p = .0023 ** j. 3 vs 4 p = .5417 k. 3 vs 5 p = .6262 l. 3 vs 6 p = .5936 m. 4 vs 5 p = .2266 n. 4 vs 6 p = .9767 o. 5 vs 6 p = .2757
14. Contrast difference between treatment levels (Ty1) a. uv vs no-uv p = .2292 b. o3 vs no-o3 p < .0001 ** c. low-o3 vs no-o3 p < .0001 ** d. high-o3 vs no-o3 p = .0002 ** e. low-o3 vs high-o3 p = .7028 f. o3 linear response p = .0002 ** g. low-o3+uv vs low-o3/uv p = .0191 * h. high-o3+uv vs high-3/uv p = .0153 *
15. Contrast between (days) for (Ty1) a. 1 vs 2 p = .0004 ** b. 1 vs 3 p = .0079 ** c. 1 vs 4 p = .0028 ** d. 1 vs 5 p = .0148 * e. 1 vs 6 p = .0073 ** f. 2 vs 3 p = .2038 g. 2 vs 4 p = .2637 h. 2 vs 5 p = .0453 *
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i. 2 vs 6 p = .1014 j. 3 vs 4 p = .7786 k. 3 vs 5 p = .4707 l. 3 vs 6 p = .7682 m. 4 vs 5 p = .2860 n. 4 vs 6 p = .5367 o. 5 vs 6 p = .6422
16. Contrast between (time) for (Ty1) a. 9am vs 11am p = .2644
17. Contrast between (channel) for (Ty1) a. 1 vs 2 p = .7947 b. 1 vs 3 p = .7245 c. 2 vs 3 p = .5429 d. 1 vs 2&3 p = .9637 e. 2 vs 1&3 p = .6213 f. 3 vs 1&2 p = .5737
18. Adjustment for multiple comparisons of (Ty1) effect by (tt) a. Some difference do exist at 95% confidence limit (i.e., not include zero)
19. Waller-Duncan K-ratio t-Test for (tt) effect on (Ty1) a. tt 1 and 2 are not different b. tt 3, 4, 5, and 6 are not different
20. Tukey’s Studentized Range, HSD, Test for (tt) effect on (Ty1) a. tt 1 and 2 are not different b. tt 2, 3, 4, 5, and 6 are not different
21. Contrast differences between treatments for reactor (Ty2) a. 1 vs 2 p = .9466 b. 1 vs 3 p = .3021 c. 1 vs 4 p = .3148 d. 1 vs 5 p = .5174 e. 1 vs 6 p = .4907 f. 2 vs 3 p = .3482 g. 2 vs 4 p = .3861 h. 2 vs 5 p = .4900 i. 2 vs 6 p = .4889 j. 3 vs 4 p = .9158 k. 3 vs 5 p = .1138 l. 3 vs 6 p = .1232 m. 4 vs 5 p = .1245 n. 4 vs 6 p = .1144 o. 5 vs 6 p = .9715
22. Contrast difference between treatment levels (Ty2) a. uv vs no-uv p = .9649 b. o3 vs no-o3 p = .8313 c. low-o3 vs no-o3 p = .1771 d. high-o3 vs no-o3 p = .3330 e. low-o3 vs high-o3 p = .0311 *
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f. o3 linear response p = .3330 g. low-o3+uv vs low-o3/uv p = .6534 h. high-o3+uv vs high-3/uv p = .6778
23. Contrast between (days) for (Ty2) a. 1 vs 2 p = .6740 b. 1 vs 3 p = .5936 c. 1 vs 4 p = .8198 d. 1 vs 5 p = .9727 e. 1 vs 6 p = .3565 f. 2 vs 3 p = .8428 g. 2 vs 4 p = .3904 h. 2 vs 5 p = .5442 i. 2 vs 6 p = .4958 j. 3 vs 4 p = .3220 k. 3 vs 5 p = .4483 l. 3 vs 6 p = .6614 m. 4 vs 5 p = .7957 n. 4 vs 6 p = .1337 o. 5 vs 6 p = .2065
24. Contrast between (time) for (Ty2) a. 9am vs 11am p = .9460
25. Contrast between (channel) for (Ty2) a. 1 vs 2 p = .3810 b. 1 vs 3 p = .6297 c. 2 vs 3 p = .6776 d. 1 vs 2&3 p = .4381 e. 2 vs 1&3 p = .4505 f. 3 vs 1&2 p = .9618
26. Adjustment for multiple comparisons of (Ty2) effect by (tt) a. All 95% confidence limits for difference between means includes zero
27. Waller-Duncan K-ratio t-Test for (tt) effect on (Ty2) a. No significant difference between means at 5%
28. Tukey’s Studentized Range, HSD, Test for (tt) effect on (Ty2) a. No significant difference between means at 5%
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APPENDIX F
ABBREVIATIONS
AIC+ Advanced Interface Converter AMI American Meat Institute APC aerobic plate count ASCII American standard code for information interchange BOD biochemical oxygen demand COD chemical oxygen demand DAF dissolved air floatation EEC European Economic Community FoodPAC Food Processing and Advisory Committee FSIS Food Safety and Inspection Service gpm gallons per minute GRAS generally recognized as safe HACCP Hazard Analysis Critical Control Point HMI human-machine interface hv photon energy λ wavelength (nm) MGD million gallons per day NCCES North Carolina Cooperative Extension Service NTU nephelometric turbidity units ODBC open database connectivity ORP oxidation-reduction potential P probability value (%) PID proportional-integral derivative PLC programmable logic controller psi pounds per square inch (lbs/in2) rpm revolutions per minute RS Rockwell software RTD resistive temperature device ρ density, mass per volume σ standard deviation σ average standard deviation TC total coliform TSS Total suspended solids USDA United States Department of Agriculture USEPA United States Environmental Protection Agency USPEA United States Poultry & Egg Association UV Ultraviolet irradiation
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