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.

iv

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!

v

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

vi

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

vii

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

viii

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

ix

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

xi

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).

1

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.

2

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.

3

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.

4

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.

6

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).

7

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

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ion-

irrad

iatio

n pr

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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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Chang, S.Y., R.T. Toledo and H.S. Lillard. 1989. Clarification and decontamination of poultry

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Diaz, M. E. and S.E. Law. 1997. Ultraviolet photon enhanced ozonation for microbiological

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Kim, J.G., A.E. Yousef and S. Dave. 1999. Application of ozone for enhancing the

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Lillard, H.S. 1990. The impact of commercial processing procedures on the bacterial

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Peyton, G.R. and W. H. Glaze. 1988. Destruction of pollutants in water with ozone in

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Pierson, J. 1999. Reducing HACCP’s Appetite for Water. PoultryTech 11(2):2.

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Prengle, H.W., Jr., C.E. Mauk, R.W. Legan and C.G. Hewes, III. 1975. Ozone/UV process

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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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