Wallace David

8/6/2019 Wallace David

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JAMESCOOKUNIVERSITY

SCHOOLOFENGINEERING

EG4011/2

D e s i g n o f a P o t e n t i a l l y A n t i f o u l i n g

E n g i n e e r i n g S u r f a c e b y M i m i c k i n g

t h e A n t i F o u l i n g F u n c t i o n o f S h e l l

F i s h

DavidWallace

ThesissubmittedtotheSchoolofEngineeringinpartialfulfilmentofthe

requirementsforthedegreeof

BachelorofEngineering(MechanicalEngineering)

November7th2008


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Statement of Access

I,theundersigned,theauthorofthisthesis,understandthatJamesCookUniversity

willmakeitavailableforusewithintheUniversityLibraryand,bymicrofilmorother

means,allowaccesstousersinotherapprovedlibraries. Allusersconsultingwith

thisthesiswillhavetosignthefollowingstatement:

Inconsultingthisthesis, Iagreenottocopyorcloselyparaphrase it in

wholeor inpartwithoutwritten consentof theauthor;and tomake

properpublicwrittenacknowledgementforanyassistance,whichIhave

obtainedfromit.

Beyondthis,Idonotwishtoplaceanyrestrictiononaccesstothisthesis.

5/11/08

DavidWallace Date

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Sources Declaration

Ideclarethatthisthesisismyownworkandhasnotbeensubmittedinanyformfor

another degree or diploma at any university or other institution of tertiary

education. Informationderivedfromthepublishedorunpublishedworkofothers

hasbeenacknowledgedinthetextandalistofreferencesisgiven.

5/11/08

DavidWallace Date

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Abstract

Foulinginfluencesawidevarietyofindustriesandasaresulthasmanyundesirable

physical, ecological and economical effects. Many efforts have been made to

prevent fouling via different defence mechanisms, with the most common being

chemicalbased. Thetoxicantifoulingsystemsthatareusedarehighlynonspecific

andthusoftenaffectspeciesthatarenotthedirecttargetofthechemical. Natural

antifouling deterrents can be broken down into three main groups being the

chemical, mechanical and physical. Previous research has shown that the

morphology of a surface is strongly correlated to the way in which it deters the

settlementoffouling.

Therefore, the aim of this thesis was to determine the surface parameters for

shellfish thatarenaturallyclean in theirenvironment, thenengineerand surface

thathadthesamecharacteristics. Todothisthreespeciesofshellfishwerechosen

for their antifouling properties. The Mytilus galloprovincialis and TellinaplicataspeciesofshellfishhaveahighdegreeoffoulingresistanceandtheAmusiumballotispecieshasalowresistancetofouling. Fromthesethreespecies,several3Dimages

were taken using the Laser Scanning Confocal Microscope to capture the

morphology of the surface. The 3D images were then converted into height

encodedimagessothatanumericalanalysisofthesurfacecouldbeperformed.

From the information that was gathered in the numerical analysis, correlations

weremadebetweentheknownantifoulingcharacteristicsoftheshellfishandthe

parameters that were calculated during the numerical analysis. Surfaces were

generatedonapieceof stainless steel togetgroundingonwhat surface finishes

were achievable with different surface finishing techniques. These generated

surfaceswerethenanalysedinthesamewaythattheshellfishweretodetermine

theparametersofthegeneratedsurfaces. Onceparameterswerecollectedforthe

Optimum shellfish surface and the generated surfaces, they were compared to

determinethesimilarities. Oncethesimilaritiesbetweenthethreesurfaceswere

determined,arevisedsurfacefinishingtechniquewasproposed. Oncethissurface

finishingprocesshasbeen finalisedand thesurface finishhasbeenverifiedasan

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antifoulingsurfacethenitcanbeappliedinmanyapplicationtohelpminimiseand

insomecaseeliminatefoulingaccumulation.


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Acknowledgements

ThankstoZhongxiaoPengforhertirelesseffortinsupportingmethisyear.

ThankstoKevinBlakeandShaneAskewattheAdvancedAnalyticalCentre,JCUfor

theirassistanceincapturingexcellentimagesintheAdvancedAnalyticalCentre.

ThankstoNickPaulforhisassistanceinanalysingthedatacapturedintheAAC.

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TableofContentsAbstract................................................................................................................. ivAcknowledgements............................................................................................... viIntroduction.......................................................................................................... 1Chapter1:LiteratureReview................................................................................. 41.1 FoulinganditsEffects.........................................................................................4

1.1.1. Typesoffouling...........................................................................................4

1.1.2. ApplicationsAffectedByFouling.................................................................6

1.1.3. Methodsusedtocontrolfouling.................................................................7

1.2 HeatExchangers.................................................................................................8

1.2.1. TypesofHeatExchangers............................................................................8

1.2.2. Methodsusedtocombatfoulinginheatexchangers...............................10

1.3 SurfaceTopographyandAntifoulingProperties..............................................12

1.4 Surfacefinishingtechniques.............................................................................18

1.4.1. Electropolishing.........................................................................................18

1.4.2. Sanding......................................................................................................19

1.4.3. SurfaceGrinding........................................................................................19

1.5 SurfaceAnalysismethod..................................................................................20

1.5.1. QualitativeAnalysis...................................................................................20OpticalMicroscope.................................................................................21

ScanningElectronMicroscope................................................................22

1.5.2. QuantitativeAnalysis.................................................................................23

StylusProfiler..........................................................................................23

AtomicForceMicroscopy........................................................................24

LaserScanningConfocalMicroscopy......................................................25

1.6 TestingandEvaluationTechniques..................................................................26

1.7 Summary...........................................................................................................27

Chapter2:Methodology...................................................................................... 282.1 CharacterisationofShellFishSurfaces.............................................................28

2.1.1. Sampleselection........................................................................................28

2.1.2. ImageAcquisition......................................................................................31

2.1.3. ImageProcessingandAnalysis..................................................................33

2.1.4. VerificationoftheMatlabandOptimassoftware....................................35

2.2 Generationofstainlesssteelsurfaceswithantifoulingfunction....................36

2.2.1. Surfacefinishingtechnique.......................................................................37

2.2.2. Stainlesssteelsurfacesvs.shellfishsurfacesusingnumericalparameters

...................................................................................................................38

2.3 Testingandevaluationofsurfacefinishes.......................................................38

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viii

2.3.1. Experimentalapparatus............................................................................39

2.3.2. Testingprocedures....................................................................................40

2.3.3. Performanceevaluation............................................................................40

Chapter3:ResultsandDiscussion....................................................................... 413.1 ImageAcquisitionandprocessing....................................................................41

3.1.1. LCSMandLasersharp2000settings..........................................................42

3.1.2. 3DImageProcessinginMatlab.................................................................42

Tellinaplicata..........................................................................................44

Mytilusgalloprovincialis..........................................................................45

Amusiumballoti......................................................................................47

3.2 ValidationDatafromStylusProfiler.................................................................48

3.3 QuantitativeSurfaceAnalysisResults..............................................................51

3.3.1. TabulatedSurfaceAnalysisResults...........................................................51

3.3.2. GraphicalSurfaceAnalysis.........................................................................54

3.4 StudyofAntifoulingProperties........................................................................58

3.5 SurfaceParametersfromstainlesssteelsurfaces............................................60

Chapter4:ConclusionandFutureWork..............................................................62References..67AppendixA:StylusProfilerCharts69AppendixB:SPSSAnalysisGraphs73


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TableofFiguresFigure1:TubeandShellHeatExchanger.....................................................................9

Figure2:PlateHeatExchanger..................................................................................10

Figure3:FouledShellandTubeheatexchanger.......................................................11

Figure4:Parametersforsurfacecharacterisation....................................................13

Figure 5: Scanning Electron Microscope images of the engineered

microtopographies.....................................................................................................14

Figure6:Electropolishingmethod.............................................................................18

Figure7:Surfacegrindingmachine...........................................................................20

Figure8:OpticalMicroscope.....................................................................................21

Figure9:ScanningElectronMicroscope....................................................................22

Figure10:StylusProfiler............................................................................................23

Figure11:AtomicForceMicroscope.........................................................................24

Figure12:LaserConfocalScanningMicroscope........................................................25

Figure13:AntifoulingtestingapparatusproposedbyZettler(2005).......................27

Figure14:Tellinaplicata(Brownpigment)sample...................................................29

Figure15:Tellinaplicata(Whitepigment)sample....................................................30

Figure16:Mytilusgalloprovincialissample...............................................................30

Figure17:Amusiumballotisample............................................................................30

Figure18:LaserScanningConfocalMicroscopeatJamesCookUniversity..............32

Figure19:ComputercontainingtheLasersharp2000imagecapturingsoftware....33

Figure20:Testingapparatus(Friedrich,2008)..........................................................39

Figure21:(a)MBIand(b)HEIforTellinaplicata.......................................................44

Figure 22: Analysis results from the Tellina plicata sample separated into form,

wavinessandroughnessprofiles...............................................................................44

Figure23:(a)MBIand(b)HEIforMytilusgalloprovincialis......................................45

Figure24:AnalysisresultsfromtheMytilusgalloprovincialissampleseparatedinto

form,wavinessandroughnessprofiles.....................................................................46

Figure25:(a)MBIand(b)HEIforAmusiumballoti...................................................47

Figure26:Analysis results from theAmusiumballoti sample separated into form,

wavinessandroughnessprofiles...............................................................................47

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Figure27:Combinedaveragesofthevalidationdata...............................................50

Figure28:RavaluesforallSubsamples. (321referstosubsample1,ofindividual2

ofspecies3)................................................................................................................55

Figure29:RavaluesforallIndividuals. (32referstoindividual2ofspecies3).......56

Figure30:RavaluesforallSpecies. (3referstospecies3)......................................57

Figure34:RavaluesforgivenSubSamples..............................................................70

Figure35:RavaluesforgivenIndividuals..................................................................70

Figure36:RavaluesforgivenSpecies.......................................................................71

Figure37:RqvaluesforgivenSubsamples...............................................................72

Figure38:RqvaluesforgivenIndividuals..................................................................72

Figure39:RqvaluesforgivenSpecies.......................................................................73

Figure40:RskvaluesforgivenSubsamples.............................................................74

Figure41:RskvaluesforgivenIndividuals................................................................74

Figure42:RskvaluesforgivenSpecies......................................................................75

Figure43:RkudataforgivenSubsamples................................................................76

Figure44:RkuvaluesforgivenIndividuals................................................................76

Figure45:RkuvaluesforgivenSpecies.....................................................................77

Figure46:FdvaluesforgivenSubsamples...............................................................78

Figure47:FdvaluesforgivenIndividuals..................................................................78

Figure48:FdvaluesforgivenSpecies.......................................................................79

Figure49:StrvaluesforgivenSubsamples..............................................................80

Figure50:StrvaluesforgivenIndividuals.................................................................80

Figure51:StrvaluesforgivenSpecies.......................................................................81

Figure52:WavaluesforgivenSubsamples.............................................................82

Figure53:WavaluesforgivenIndividuals................................................................82

Figure54:WavaluesforgivenSpecies......................................................................83

Figure55:WqvaluesforgivenSubsamples.............................................................84

Figure56:WqvaluesforgivenIndividuals................................................................84

Figure57:WqvaluesforgivenSpecies......................................................................85

Figure58:WskvaluesforgivenSubsamples.............................................................86

Figure59:WskvaluesforgivenIndividuals...............................................................86

Figure60:WskvaluesforgivenSpecies....................................................................87

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Figure61:WkuvaluesforgivenSubsamples...........................................................88

Figure62:WkuvaluesforgivenIndividuals..............................................................88

Figure63:WkuvaluesforgivenSpecies....................................................................89

Figure64:FdvaluesforgivenSubsamples...............................................................90

Figure65:FdvaluesforgivenIndividuals..................................................................90

Figure66:FdvaluesforgivenSpecies.......................................................................91

Figure67:StrvaluesforgivenSubsamples..............................................................92

Figure68:StrvaluesforgivenIndividuals.................................................................92

Figure69:StrvaluesforgivenSpecies.......................................................................93


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TableofTablesTable1:2DSurfaceParameters.................................................................................15

Table2:SurfaceParameters......................................................................................16

Table3:3DSurfaceParameters.................................................................................17

Table4:FinalisedSurfaceParameters.......................................................................35

Table5:ValidationData.............................................................................................49

Table6:Combinedaveragesofthevalidationdata..................................................49

Table7:Raw roughnessprofiledata fromMatlabandOptimas software (1&2

Tellinaplicata,3 Mytilusgalloprovincialis,4 Amusiumballoti).............................52

Table 8: Raw waviness profile data from Matlab and Optimas software (1 & 2

Tellinaplicata,3 Mytilusgalloprovincialis,3 Amusiumballoti).............................53

Table9:AveragedroughnessdatafromTable7.......................................................54

Table10:AveragedwavinessdatafromTable8.......................................................54

Table11:Hypothesisedantifoulingparameters........................................................60

Table12:ComparisonbetweenOptimumshellvaluesandgeneratedstainlesssteel

values.........................................................................................................................61

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INTRODUCTION

Introduction

Foulinginfluencesawidevarietyindustry,frommarinetominingandeventhefood

industry. Fouling can be described as the undesirable build up of material on a

surface and is a side effect of the environment in which the surface is exposed.

Therearemanynegativeeffectsthatfoulingcanhaveonasystemandallofthese

effects can be put into one of the following categories: physical, ecological and

economicalfactors. Heatexchangersarewidelyusedinavarietyofindustriesthat

arehighlysusceptibletofoulinganditcanbeforeseenthatfoulingwouldbeoneof

themostprominentproblems thatwouldcommonlyoccurduring theiruse. The

physical, ecological and economical factors in turn affect the design,

implementationandmaintenanceofasystemwithaheat transfersurface. Inall

cases,thesideeffectsoffoulingbuildupshouldbeminimised ifnoteliminated in

ordertomaximisetheefficiencyofasurface.

Thephysicalpartoftheinefficiencyoffoulingcanbeattributedtothehindranceof

the water flow over a surface, the obstruction of the heat transfer through the

surfaceandthedamagethatthefoulingcausestothesurface. Forexampleinheat

exchangers the hindrance of water flow and the added resistance of the heat

transfersurfacecanbeattributedtothebuildupofbothscaleandbiofilmonthe

pipesandplatesoftheheatexchangeraswellasthepipesthat leadtoandfrom

theunit. Thelossinconductivityminimisestheeffectivenessoftheheatexchanger

and thus, over time the heat exchanger loses its efficiency and needs to be

shutdownandmaintainedinordertoreclaimtheitslosses.

Ecologically theadditionofantifoulants to thewateradds to the toxic chemicals

that are released back into the environment. The antifoulants are not the only

addedpollutantsthatfoulingcauses,duetotheadditionalemissionsofgreenhouse

gassesandthelikeintotheatmospherebecauseofthehigherenergyneedstopush

the water through the system in the case of a heat exchanger. Because of the

physicalinefficiencies inthesystem,thereareseriouseconomicalramificationson

thesystemasthecosttorunandmaintainthesystemrisesandtheprofitdecreases

astheoutputofthesystemdecreases.

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INTRODUCTION

Asaruleofthumb,engineersdesignheattransfersystemssothatthelossesdueto

thefoulinginthepipsandonplatesarebuiltintothedesign. Thismethodisnot

favourable as it results in greater running and building costs. Fabrication costs

increasedueto the largerheatexchangerandassociatedpipingthatneedstobe

accounted for and the running costs are increased through the higher energy

demandforalargerpump.

Asanalternativetothepastapproachofsimplybuildingtheheatexchangeraround

the problem, a more modern approach is to change the surface finish on the

surfacethatispronetofoulinginordertominimiseorideally,eliminatethefouling

completely. Withdifferentsurfacefinishes,therearedifferentpropertiesthatcan

be changed about the surface and thus the susceptibility to fouling. Surface

topography or microtopography describes the various surface parameters that

describe the surface. Previous research has shown that properties of the

topography that are of interest include the roughness, the waviness and the

skewnessoffbothoftheseproperties(Hudleston(2004)).

In recent years, researchers have found that a good source of fouling resistant

surfaces is those seen on shellfish. Some shellfish naturally possess fouling

resistance mechanisms. In addition to the physical antifouling properties,

mechanicalandchemicaldeterrentsexist. Thephysicalpropertiesoftheshellare

ofmostinterestastheotherpropertiesarerelatedtothematerialthattheshellis

madeofand thechemicals thatare secreted todeter fouling. Bymimicking the

physicalpropertiesofashellasurfacecanbecreatedthatwillhopefullypossessthe

sameantifoulingproperties.

Previous methods used to analyse the surfaces and capture surface parameters

used primitive twodimensional techniques, an antifouling surface cannot be

successfullydesignfromtheseresults,astheydonotcaptureenoughdetailabout

the surface. To better capture the definition on the surface, new methods of

capturingsurfacemicrotopographyneeded tobeutilisedand thesewere Atomic

ForceMicroscopy (AFM)and LaserScanningConfocalMicroscopy (LSCM). These

twomethodscananalysethesurfaceinthreedimensionsandthustheparameters

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INTRODUCTION

3

that in the past have only been attainable in the twodimensional for now are

availableinthreedimensions. Theaddeddetailobtainedinthethreedimensional

images allows for better insight into the antifouling nature of some species of

shellfish. By analysing several different shells and their respective antifouling

properties, a data set will be created which describes the necessary surface

parameterstomaximisetheantifoulingfunctionofthesurface.

When the data has been collected from several shells the desired surface

parameterswillbedetermined. Theseparametersincludetheaverageroughness,

root mean square roughness, skewness and kurtosis of the profile, the fractal

dimension of the surfaces and the texture aspect ratio of the roughness and

wavinessprofilesthatareobtainedfromtheshellfishsurface. Thenexttaskwillbe

toreplicatethesurfaceontoastainlesssteelsurface. Themethodforthecreation

of thesurfacewilldependon thesurfaceparametersthatareneeded. Once the

surfacehasbeen created then itwillbe scrutinised in the samewayas the shell

surfaces. Bydoingthisitcanbeconfirmedthatthesurfacesindeedhavethesame

or similar microtopography that will result in the same of similar antifouling

resistance as the shellfish surface. The surface will then be placed in the heat

exchangertestapparatusandtestedagainstothersamplestofindoutthesurface

finishwillbeapplicableinthefield.

Ifthisconceptisprovensuccessful,itwillprovideindustrywithameansofmaking

theirheattransfersystemsmoreefficientwithoutcompromisingtheenvironment.

With this finish applied to heat transfer surfaces in a plate heat exchanger for

example, the frequency of the cleaning cycle for the heat exchanger can be

lengtheneddramaticallyifnoteliminated. Thesurfacefinishwillhavetheabilityto

complimentortotallyreplacetheantifoulantchemicalscurrentlyused intheheat

transfersystemsandcouldpotentiallyeliminatetheneedtooverdesignthesystem

inthefirstplace. Thissurfacefinishisnotonlyapplicabletoheatexchangersasit

mightwellbeusedinavarietyofindustriesinanassortmentoflocationstocombat

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LITERATUREREVIEW

Chapter 1: Literature Review

Several itemswillbeoutlined inthischapterallofwhichwillgivethebackground

informationrequiredtodevelopanantifoulingsurfacefinish. It isenvisionedthat

thissurface finishcanthenbeappliedtostainlesssteelforuse inheatexchanger

applications to resist the accumulationof fouling. This information isbrokenup

intothefollowingheadings:

foulinganditseffects, heatexchangers, surfacetopographyandantifoulingproperties, surfacefinishingtechniques, surfaceanalysismethods, surfacetestingandevaluation.

The research carried out under the above headings will give background

information to further the advancement of the Designing of a Potentially Anti

foulingEngineeringSurfacebyMimickingtheAntiFoulingFunctionofShellFish.

1.1 Fouling and its Effects

1.1.1. Types of fouling

Foulingonasubmergedsurfacecomesinmanyformsandisprimarilytheresultof

the surface being exposed to unfavourable environmental conditions. In most

cases,foulingisanundesiredbuildupmaterialonasurfacethathinderstheflowof

fluid past the surface as well as decreasing the amount of heat that can pass

throughthesurface. Epstein(1981)classifiedfoulingintofivemainformsthatare

identifiedasbeingaproblemforindustry. Healsodefinedthefivestagesinwhich

theprocessoffoulingprogressed. Hisclassificationsoffoulinganditsmechanisms

wasrevisedagainby Sheikholeslami(2000)andislistedbelow:

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LITERATUREREVIEW

Crystallisation(precipitation):Crystallisationfouling or scaleformation is temperature dependant; a degree ofsupersaturationisalsoneededbeforetheprecipitationwilloccur(Bott1997).

Particulate:Particulatefouling is similar toCrystallisation ina sense that thereneeds tobeasupersaturationof thefluid toallow theformationof theparticles thatwill internattachtothesurface.

Biological:BiologicalfoulingorBiofoulingoccurswhen theorganisms thatarepresent in thefluidadheretotheheattransfersurface. ThisformsaBiofilmthatactsinthesamewaythattheotherformsoffouling.

Corrosion:Thisoccurswhenthebasemetalstartstocorrodeandthisinhibitstheflowandheattransfercharacteristicsof thematerial. As thecorrosion inducesa roughsurface,othermaterialisusuallycaughtupinthisfoulingaswell.

Chemicalreaction:Chemical reaction corrosion is when reactants mix eitherpre or during theflowthrough the heat exchanger and produce the fouling that then adheres to thesurfaceoftheheatexchanger(WatkinsonandWilson1997).There are many independent parameters which affect the type and quantity of

fouling that a surface receives (Malayeri and MllerSteinhagen 2007). Some of

theseparametersaregivenbelow:

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LITERATUREREVIEW

surfacetemperature, bulktemperature, bulkcompositionandchemistry, fluidvelocityandturbulence, physicalpropertiesoftheworkingfluid(viscosity,density), surfacespecifications(material,surfacefinish,roughness), physical properties of the deposit (density, thermal conductivity,

stickability),

solubilityequilibrium,and chemicalkinetics(chemicalreaction).

1.1.2. Applications Affected By Fouling

Foulingaspreviouslydescribed istheundesiredbuildupofmaterialonasurface.

Thisisaworldwideprobleminindustryandimpingesonalmosteverywaterbased

process. Theextentoffoulingin industrywasexplainedbyVladkova(2007)when

shedescribedseveralindustriesthataresusceptibletofoulingincluding:

pulpandpaperManufacturing, foodindustry, biomaterials, membranetechnologies, underwaterconstructions,

theshippingandmarineindustry,

fishfarmsandwellasfishingnets, desalinationplants,and heatexchangers.

Astheworldfacesafreshwatershortage,manycountrieshaveturnedtooperating

desalinationplantstoproducefreshwater. Despitethetechnologicaladvancesthat

have been made with the processes that are carried out in these plants a large

proportionoftheplantsarestillthermallydriven. Thismeansthattheefficiencyof

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LITERATUREREVIEW

theseplantsdiminishesataremarkableratewiththeformingoffoulingontheheat

transfer surfaces. It is commonpractice toavoid fouling ratherby implementing

strategies rather than facing theproblem witha solution. Operating the system

belowtheoptimumtemperaturetominimisetheeffectsofsupersaturationofthe

salt water, building the heat exchanger bigger than it needs to be in order to

compensateforthefoulingeffectordosingthesystemwithexcessiveamountsof

antifoulantareall strategies thatareemployed tocombat fouling indesalination

plants. Alloftheseareregardedasnotbestpracticeandasaresultcomeunder

heavy scrutiny from environmental agencies due to their high operational and

ecologicalcost(MalayeriandMllerSteinhagen2007).

Thedairyindustryisalsohighlysusceptibletofoulinginplateheatexchangersused

topasteuriseandsterilisemilksincethe1930s. Theplateheatexchangersneedto

be cleaned a minimum of once per day to remove the layer of biofilm that

accumulatesonthesurfaceoftheplates. Thisisamajorproblem,asthecleaning

ofthisequipmentrequiresthattheprocessbeshutdowntemporarilysothatthe

bio filmcanbecleanedaway. Asa result, therearemajorcosts involved fornot

onlythematerialsandlabourtocleantheequipmentbutalsothemassivecostof

theequipmentdowntimeandaneffluentproblembroughtonbythe intermittent

cleaning. The fouling on the plates in this case caused by heatsensitive whey

proteinsandtheheat inducedprecipitationofcalciumphosphatesaltsoutof the

milk(VisserandJeurnink1997).

1.1.3. Methods used to control fouling

Manydifferentstrategiesareusedtocombatfoulinginindustry. Oneofthemost

predominant methods for controlling fouling in industry applications are

technologies such as toxic antifouling coatings and the addition of antifouling

chemicals. These methods are easily implemented and are the conventional

methodsofcombatingfouling. Thesemethodsandsimilarareheavilyscrutinisedas

they pose significant environmental hazards if the process is not monitored

properly. Itiscommonpracticetoavoidfoulingratherbyimplementingstrategies

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LITERATUREREVIEW

rather than facing the problem with a solution (Malayeri and MllerSteinhagen

2007).

Theuseoftoxicantifoulantsonshiphullshasbeenahistoricmethodofcontrolling

fouling but biocides such as lead, arsenic, mercury and their organic derivatives

have been banned due to the environmental risks that they posed to the

surroundingmarinelife(Chambers,Stokesetal.2006). TributyltinorTBTisoneof

thetoxicantifoulantsusedtobothdeterandkillanymarineorganismswhichare

exposedtoit;theuseofwhichhasbeenbannedduetoenvironmentaldamagethat

it causes. The use of organotins was eventually banned due to severe shellfish

deformitiesandthebioaccumulationoftininsomeducks,sealsandfish(Chambers,

Stokesetal.2006). Thereareantifoulingcoatings thatdonotuseheavymetals;

these are called foul releasing coatings and simply do not allow the fouling to

adheretothecoatedsurface(MllerSteinhagen2000).

1.2 Heat Exchangers

1.2.1. Types of Heat Exchangers

Aheatexchanger isadevicebuilt forefficientheat transfer fromonemedium to

another. They are widely used in space heating, refrigeration, air conditioning,

power plants, chemical plants, petrochemical plants, petroleum refineries, and

natural gas processing. There are numerous types of heat exchangers used in

industrytoday. ThetwomaintypesofHeatExchangersarethePlatetype(Visser

and Jeurnink1997;MalayeriandMllerSteinhagen2007)andtheTubeandShell

type. ThesearenotexclusivelytheonlytypesofHeatExchangersusedasthereare

multipleapplicationsandthesetwotypescouldnotpossiblebeversatileenoughto

coveralltypes. TheTubeandShelltypeHeatExchangerpresentedinFigure1has

manydifferentconfigurationsrangingfromsinglepasstomultiplepassdepending

ontheapplications. ForthepurposeoftheprojectthistypeofHeatExchangerwill

not be considered, as the process of conceiving a method of applying a surface

finishtotheinsideofapipewouldbeverylengthy.

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LITERATUREREVIEW

The Plate Heat Exchanger on the other hand is the perfect candidate for the

applicationofasurfacefinishonthesurfaceoftheplates. AspresentedinFigure2

thePlateHeatExchanger ismadeupof severalplates that separate theprocess

fluidonthehotsideandthecoolingfluidonthecoldside. Thenumberofplates

used in the Plate Heat Exchanger is entirely dependent on the outcome that is

desired. Agreaternumberofplateswill increasethesurfaceareaandthusthere

willbeagreaterheattransferacrossthesurface(Zettler,Weietal.2005).Withan

increase in thenumberofplates to increase theheat transfer, therewillalsobe

moresurfaceareaavailabletobefouled.

PlateHeatExchangersareusedwhere they canbe as theyareeasy tomaintain

have an excellent heat transfer capability and by nature are compact (Shah,

Subbaraoetal.1988). Primarilystainlesssteelisusedinsideheatexchangersasit

hasahighresistancetocorrosionandgoodthermalconductivity. Heatexchangers

haveawidevarietyofofapplicationsinindustry.Somereleventindustriesinclude

wineandbrewing,dairy,chemicalprocessing,refrigeration,powergrenerationand

thewastewater industry. Inalloftheseapplicatoins it is importantthattheheat

transfer through the surface is maximised while the flow over the surface

experiecestheleastamountofresistance.

Figure1:TubeandShellHeatExchanger.

(http://content.answers.com/main/content/wp/en commons/c/cd/Straight

tube_heat_exchanger_1pass.PNG)

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LITERATUREREVIEW

Figure

2:

PlateHeatExchanger.

(http://www.separationequipment.com/images/alfa laval_plate_heat_exchanger.gif)

1.2.2. Methods used to combat fouling in heat exchangers

HeatExchangersarehighlysusceptibletofoulinginmanycombinationsofitsform.

Duetothemanyapplicationsofthispieceofequipmentisusedinthereisabroad

rangeoffoulingthattheycanbeexposedto. Thecoldsideaswellasthehotsideof

theheattransfersurfacecanbeaffectedbyfouling. AspresentedinFigure3heat

exchangerscanbecomeextremelycongestedovertimeasthefoulingincreasesand

theopeningslowlyrestrictstheflowofthewater.

Thetriedandtestedsolutiontotheproblemoffoulinginheatexchangersistoover

designthesystemandbuild intothedesigntheaccumulationofabiofilmornon

organic fouling. This is an inefficient and costly procedure for designing heat

transfer system. The cost for the construction and installation of a bigger heat

exchangerwillnodoubtbegreaterforabiggersystem. Notonlywillthecostofthe

construction rise but the cost of all the associated machines and running will

increase,asthesystemhastoallowforthebiggerheatexchanger.

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Figure3:FouledShellandTubeheatexchanger.

(http://en.wikipedia.org/wiki/Fouling)

Anothermethodusedtodeterfoulingontheheattransfersurfaceistheplacement

ofcorrugations intheheattransfersurface inaherringbonedesign. Theseplates

are called chevron plates and they increase the turbulence in the plate heat

exchanger,whichhelpstopreventfoulingsettlingontheheattransfersurfaces.

There isanabundanceofresearchdone intotheareaoffoulingandthemethods

usedtocombat itsmany forms. Inrecentyears,the focushasturnedaway from

the toxic coatingsandadditives thatareapplied topreventor kill fouling that is

prevalent inmanywaterbased environments. The newmethod that is used to

combatfouling iscalledsurfaceengineering. Surfaceengineering involvesaltering

thechemicalcompositionandmorphology,surfacetopographyandroughness,the

hydrophilic/hydrophobicbalanceandthesurfaceenergyandpolarityofthesurface

togiveitthebestantifoulingparameters(Vladkova2007).

Byoutliningthecurrentmethodsusedtopreventoratmostminimisetheeffectsof

fouling, it can be seen that there is a need to enhance our knowledge about

methodsthatarebothenvironmentallyfriendlyandeconomicallyefficient. Surface

engineering has the potential satisfy both of these requirements with more

research.

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1.3 Surface Topography and Antifouling Properties

As mentioned above surface engineering aims to alter the chemical composition

and/or morphology, surface topography and roughness, the hydrophilic/

hydrophobicbalanceand thesurfaceenergyandpolarityof thesurface tobetter

resist fouling. Although there are many different properties that can be altered

surfacetopography istheonlypropertythatwillbediscussed inthispaperasthe

other properties relate to the material and the chemical composition of the

material, which cannot be changed in this case. Hudleston (2004) showed the

settling of fouling organisms on a surface is strongly affected by its surface

microtopography.

Biofoulingrapidlycoversthesurfaceofmanysubmergeditemsthatareplacedina

marine environment. The surfaces of many shell fish however, seem to remain

relatively unfouled when exposed to the same conditions. It is from this

observationthatthestudyofthetopographicalormicrotopographicalfeaturesof

thesecreatureshasbecomeasignificantresearchtopic.

The study of many surfaces have already been conducted with Bers (2006)

conductinganantisettlingstudyontwodifferentspeciestheMytilusedulis (bluemussel)andPernaperna(brownmussel). Thesewerecomparedwithadesignatedrough surface and a designated smooth surface that were a lot rougher and

smoother respectively. Thenaturalmussel shellsonnearlyalloccasions repelled

more fouling than both the rough, which always suffered the most fouling, and

smoothsurfaces.

Scardino (2003) reported on the antifouling properties of the MytilusgalloprovincialisandthePinctadaimbricata. ThestudyshowsthatthemeanheightoftheMytilusgalloprovincialis(1238.1 m),issignificantlylowerwhencomparedtothatofthePinctadaimbricata(1.870.07 m). Themicrotopographicsurfaceofthe Mytilus galloprovincialis proved to be more resistant to fouling while thePinctada imbricata surface suffered more fouling but still less than 15% of thesurfacewerefouledafterafourteenweekexposureperiod.

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Scardino (2004)also tested the foulingdeterrenceof theMytilusgalloprovincialisandtheAmusiumballotiaswellashighresolutionmouldsofeachoftheshellandagain smooth and rough comparison moulds. This test resulted in theMytilusgalloprovincialis shell and mould having significantly less fouling than the othermoulds. The major effects were in the test surfaces with and without

microtopography. Be it the structured microtopography of the Mytilusgalloprovincialisanditsmouldorinthecaseoftherandomsandedmouldtheyallexhibited less foulingcoverwithinasixweekperiod. Aftersixweeks,the fouling

deterrentsurfaceeffectsofthemouldsdiminishedandthesurfacesbegantofoul.

Scardino (2003)were the first to systematically study the surfaceof the shellfish

andcomprehensively reporton thenumericalparametersof the surface. In the

past,many researchershaveonlyquantified theparameter ina twodimensional

senseandhaveattributedalmostalloftheanti foulingpropertiesofasurface to

thesurfaceroughness. Thismeansthattheyhavenottakenintoconsiderationany

of theotherparameters that the shellmaypossess. Scardino (2003) studied the

surfaces in three dimensions as opposed to two dimensions in the past to

quantitativelyanalysenotonlytheroughnessofthesurfacebutthetextureaswell.

Thistextureisbrokendownintothefollowingparameters:Averageroughness(Ra),

Averagewaviness(Wa),Skewnessofthesurfaceroughnessprofile(Rsk),Skewness

of the surface waviness profile (Wsk), Texture aspect ratio (Str), and Fractal

dimension(D).

Figure4:Parametersforsurfacecharacterisation.

(http://www.asp.org/database/images/mtsp/Sect2214.GIF)

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Hudleston (2004) analysed 31 species of shell fish using the parameters stated

above. Threedimensional images of the shell fish surfaces were taken and the

roughness, waviness and form surface profiles were generated for each of the

imagesusing aprogram developed byPeng (1998). By using the 31 specimens,

Hudlestonwasabletocompileacomprehensivedatabaseofshellfishspeciesand

theirrespectivemicrotopography. Thismicrotopographydatabasealongwiththe

visual inspection of the shellfish in their natural habitat allowed for the fouling

abilityofeachoftheshellstobematchedwiththetopographicalparametersofthe

particular specimen. InTables1,2 and3 areallof the surfaceparameters that

Huddleston initiallyused todescribe the shellfish surfaces. Acorrelationanalysis

wasusedtominimisethenumberofparametersthatwereusedandthisallowed

thecomputationaltimetobeminimised.

IncontrastthenaturallyoccurringsurfacetopographiesSchumacher(2007)studied

theeffectofthefeaturesize,geometryandroughnessonthesettlementoffouling

ontoa surface. They tested thedesignspresented inFigure5aswellas control

smoothcastofthesamematerial. Theresults fromthisexperimentshowedthat

thedesigninboxAwasthebestfollowedbyB,C,Dandthenthesmoothsample.

Figure5:ScanningElectronMicroscopeimagesoftheengineeredmicrotopographies.

(Schumacher,Carmanetal.2007)

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Table1:2DSurfaceParameters(Huddleston2004)Parameter Name Definition Equation

Ra

Average

roughness

The arithmetic mean of the departure

of the surface profile from the meanline.

over 2 20 consecutive samplinglengths, where L is the number ofsampling points and z is theresidual surface

Rq

Root mean

squareroughness

The root mean square of Ra.

Rz

10 point height The average height between the fivehighest peaks and the five lowestvalleys within the sampling length, this

parameter is also known as the 10pointheight parameter. where Ypi represents the highest

peaks and Yvi represents thelowest valleys

Rp

Depth ofsurface

The maximum height of the surfaceprofile above the mean line within thesampling length.

Rt

Peak to valleyheight

The maximum peak to valley height ofthe surface profile in the samplinglength.

Rv

Maximumprofile depth

The maximum depth of the profilebelow the mean line within thesampling length.

Rti

Maximumpeak to valleyheight

The maximum peak to valley of theprofile in one sampling.

Rtm

Mean depth ofroughness

The mean of all the Rti values recordedfor the assessment length.

Rpm

Mean depth ofsurface

The mean value for Rp recorded foreach assessment length.

Rsk

Skewness The symmetry of the amplitudedistribution curve about the mean line.

Rku

Kurtosis The measure of shape (sharpness) of

the amplitude distribution curve

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Table2:SurfaceParameters(Huddleston2004)

Parameter Name Definition Equation

q

Root mean

square ofprofile height

The root mean square of the

profile height over theassessment length

where y is the differential of theprofile y

q

Root mean

square ofspatialwavelength

The root mean square of the

spatial wavelength content of thesurface

Ar

Roughness

width

The roughness width within one

sampling length

where n is the number of sampleswithin one sampling length

AR

Mean

roughnessstep

The mean of Arover the entire

assessment length

where n is the number of sampleswithin entire assessment length

Aw

Waviness

width

The waviness width within the

sample length

Aw

Averagewaviness step

The average waviness widthwithin the assessment length

where n is the number of sampleswithin entire assessment length

R3z

Average

roughnessdepth

The mean separation of the third

highest peak and third lowestvalley in each of five consecutivesampling lengths

W

Wavinessheight

Separation of the highest peakand lowest valley waviness overthe sampling length

a

Average

wavelength

The average wavelength within

the assessment length

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Table3:3DSurfaceParameters(Huddleston2004)

Parameter Name Definition Equation

Sq

Root mean square

deviation

The values of the surface

departure within thesampling area

Sz

Ten point height

of the surface

The average height

between the five highestpeaks and the fivelowest valleys within thesampling area

where pi and vi are the five highestpeaks and the five lowest valleys

respectively

Ssk

Skewness ofsurfacetopographydistribution

The measure of theasymmetry of surfacedeviations about the

mean plane

where p() is the probability densityfunction of the residual surface (x,y)

Sku

Kurtosis oftopography heightdistribution

The measure of thepeakiness or sharpnessof the surface heightdistribution

There issignificantcontradiction inthe literatureas towhattheeffectof surface

roughnesshasontheantifoulingpropertiesofagivensurface. Examplesofthese

contradictions can be found throughout the literature. For example, Richards

(Richards 1996) documented that there is no correlation between the material

roughnessand theamountofcelladhesion toasurface. WhilstGjaltema (1997)

reportedthatincreasedsurfaceroughnesspromotedahigherbiofilmaccumulation.

AfterresearchingthistopicKerr(2003)statedthattheconfusionthatispresentin

theliteraturecouldbeattributedtothelackofcontrol ofthemanyvariablesthat

affecttheexperiments inthisfield. Withnumerousexperimentsbeingconducted

inthisarea,thereisaneedformoredetailaboutthesurfaceroughnessvaluesthat

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havebeenused. Instinctivelyasmothersurfacefinishpossessesbetterantifouling

propertieswhencomparedtoaroughsurface.

1.4 Surface finishing techniques

Inordertotestthedifferenttypesofsurfaces,amethodofapplyingthefinishesto

thestainlesssteelneedstobeconceived. Afterresearchingalternativemethodsfor

creatingthedesiredmicrotopographyonasurfacethefollowingprocesswereseen

tohavepotential.

1.4.1. Electropolishing

Electropolishingisanelectrochemicalprocessbywhichsurfacematerialisremoved

byelectrolysis. Sometimesreferredtoas"reverseplating",electropolishingactually

removes surfacematerial,beginningwith the highpointswithin themicroscopic

surfacetexture. Thecathodeofthesystemwillbemadetomirrorthefeaturesof

theworkpieceandtheanodeistheworkpieceitself. Theelectricalchargethatis

thenappliedacrosstheelectrolytecausesthehighspotsontheworkpiecetobe

dissolvedatagreater rate than thatof the lower spots thushavinga smoothing

affect on the surface. After the electropolishing treatment, the workpiece is

passed through a series of steps to neutralize, rinse, clean and dry the surfaces

(Electropolishing2008).

Figure6:Electropolishing method.(http://www.harrisonep.com/services/electropolishing/default.html#bennefits )

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1.4.2. Sanding

Medilanski (2002)useddifferent 3different gradesof sandpaper (P80,P500and

P100), diamond polishing paste and an electropolishing process to produce 5

different samples of roughness. The stainless steel samples were first

electropolishedtogivethemallauniformsurface. Theywerethenscratchedusing

the different grades of sandpaper giving them the following roughness

characteristics: P80(0.89m),P500(0.25m),P1000(0.16 m),diamondpolishing

(0.05 m) and electropolishing (0.03 m). The samples were then exposed to

foulingandtheresultsweretaken. Thisexperimentshowedthattherewasnotably

lessfoulingonthesurfacewitharoughnessof0.16 m,whichwascreatedbythe

P1000gritsandpaper.

1.4.3. Surface Grinding

Surfacegrinderscanbeusedeithertoprovideaprecisionsizeortoapplyaspecific

surface finish. Typically, a surface grinder, depending on the condition of the

machineandtheoperator,canapplyaprecisionfinishof0.002mm(+/ 0.0001").

A surface grinding machine consists of a table that moves both left to right and

fronttobackacrossundertherotatinggrindingdisc. Thefeedthatmovesthetable

inthehorizontalplanecanbedrivebyeitherhydraulicorelectricmotorsorhand

driven. The grinding wheel rotates in the spindle head and depending on the

machine can the height can be adjusted by any of the methods previously

described. Ifthemachine issetupwithhydraulicorelectricmotorstomovethe

tableandthegrindingheadthenthere isachancethat itwillbesemiautomated

andwillrequireminimalhandsononcetheprocesshasstarted.

Aswithanygrindingoperation, the typeof thewheel that isusedwilldetermine

the finish that is applied to the surface. The addition of coolant to the system

allowsforafinerfinishanditremovesthemetaldust(metalandgrindingparticles)

thatisproduced. Dependingontheworkpiecematerial,theworkisgenerallyheld

bytheuseofamagneticchuck. Thismaybeeitheranelectromagneticchuckora

manuallyoperated;bothtypesareshown inthefirst image(Degarmo,Blacketal.

2003).

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Figure7:Surfacegrindingmachine.

(http://en.wikipedia.org/wiki/Surface_grinder)

1.5 Surface Analysis method

The analysis of a surface can bebroken down into twomain sections being the

qualitativeandquantitative. Thequalitativeanalysismethodscanonlygivepicture

ofthesurfacewithnonumericaldata. Thequantitativeanalysisontheotherhand

results in thecollectionofnumericaldata thatcanbeanalysed togivenumerical

parameters.

1.5.1. Qualitative Analysis

This describes the analysis of a surface using visual inspectionmethods. Some

methods of qualitative analysis are optical microscopy and scanning electron

microscopyandtheseareoutlinedbelow.

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OpticalMicroscope

Opticalmicroscope likeoperateasshown inFigure8andbymovingtheobjective

lenstheimagebecomesfocused. Opticalmicroscopes,throughtheiruseofvisible

wavelengthsof light,arethesimplestandhencemostwidelyusedtypeofbiology

and geology. Optical microscopes use refractive lenses, typically of glass and

occasionallyofplastic,tofocuslightintotheeyeoranotherlightdetector. Typical

magnificationofa lightmicroscope isupto1500xwithatheoreticalresolutionof

around0.2 mor200 m. Opticalmicroscopesareeasytooperateandhaveno

complexpartsbutthereisacostandthatisthelowresolutionandthefactthatthe

surfacecanonlybemeasuredintwodimensions. Thiswillnotprovideuswiththe

necessary information toparameterise the surfaceof the shellfish. Thismethod

howevercanprovideuswithamethodofanalysing the surfaceonce ithasbeen

fouled.

Figure8:OpticalMicroscope.

(PengandTomovich2008)

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ScanningElectronMicroscope

ElectronMicroscopesweredevelopeddue tothe limitationsof lightmicroscopes.

In the early 1930's the theoretical limithadbeen reached, this required 10,000x

plusmagnification,whichwasjustnotpossibleusingalightmicroscope.

The first Scanning Electron Microscope (SEM) debuted in 1942 with the first

commercial instruments available in 1965. Its late developmentwasdue to the

electronics involved in "scanning" thebeamofelectronsacross the sample. The

SEMworksbyfiringelectronsataspeciallypreparedsurfaceandthenanalysingthe

electronsandxraysthatarereflectedfromthesurface. Thegeneralsetupofthe

SEMcanbeseeninFigure9. Thesurfaceofthesamplethatistobescannedneeds

tobereflectiveasisusuallyputthroughaprocesscalledgoldsputteringtogivethe

surfaceareflectivenature. Becauseofthissurfacepreparation,thisprocessisvery

expensive. SEMcangiveveryhighresolutiontwodimensionalimages. However,a

standardSEMcannotgiveanyheightinformation.

Figure9:ScanningElectronMicroscope.

(http://www.steve.gb.com/images/science/scanning_electron_microscope.png)

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1.5.2. Quantitative Analysis

Asthere isaneedtodeterminethenumericalparametersofasurface,there isa

needtoanalysethedepthofthesurfaceortheprofileintheZdirection. Fromthe

methodsthatcouldbeusedthreeofthemorepracticalmethodshavebeenchosen

andaresurfacemeasurementbyStylusProfiler,AtomicForceMicroscopyandLaser

ScanningConfocalMicroscopy. Thesemethodswillbeoutlinedbelow.

StylusProfiler

The stylusprofilerhasavery simpledesignandworksby letting the stylusmove

overthesurface. ThestylusisthenconnectedtoarodthatisinsideaLinerVariable

Differential Transformer (LVDT). When the stylusmoves up and down over the

surfacetherodmovesinsidetheLVDTandthiscausesasignaltobegeneratedthat

canthenbecapturedandanalysedtogivethesurfaceprofileofthesample. The

StylusProfilermeasures the twodimensionalamplitudevariations froma chosen

datumpoint. Thismethodcanbeusedtocalculatevariousroughnessterms. The

StylusProfilerislimitedtomeasuringlargetwodimensionalsurfacesasthereisno

waytostitchtogethertheslicesoftheprofilesthatarecreatedbyonepass. This

intrusivemethodcandamagethesurfaceofthesampleifitisnotdoneproperly.

Figure10:StylusProfiler.

(PengandTomovich2008)

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AtomicForceMicroscopy

Atomic Force Microscope (AFM) works by scanning a fine tip made of either a

ceramic or semiconductor material over a surface much the same way as a

phonographneedlescansarecord. Thetipislocatedattheendofacantileverthat

is fixedat theotherend. As the tipmovesover the surface it is repelledbyor

attractedtothesurfaceandthiscausesthecantileverbeamtodeflect. Ontop,the

cantileverbeamthereisareflectiveplateonwhichlaserisdirected. Asthebeam

deflects,themagnitudeofthedeflectioniscapturedbythelaserthatreflectsatan

obliqueangleofftheendofthecantileverontoaphotosensitivecollectiondevice.

ThisprocessisshowninFigure11. Aplotofthelaserdeviationversustipposition

onthesamplesurfaceprovidesathreedimensionalmapofthehillsandvalleysof

the surface fromwhich the surface topographyparameters canbe extrapolated.

AFMhas theability toproduce ahighresolution threedimensional image in the

rangeofapproximately0.1nm. TheAFMalsodoesnotrequirethesurfaceofthe

sample tobe reflectiveand thus there isnoneed for a surface treatment tobe

appliedpriortoscanningusinganAFM. However,duetothesmallscanningregion

thattheAFMhasitcanbedifficulttolocatetheregionsofinterestonthesurfaceof

thesample.

Figure11:AtomicForceMicroscope.

(http://upload.wikimedia.org/wikipedia/commons/1/1a/Atomic_force_microscope_block_diagram.

png)

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LaserScanningConfocalMicroscopy

TheLaserScanningConfocalMicroscopeoperates inmuchthesamewaythatthe

conventionalmicroscopeworkswitha fewchanges (Huddleston2004). Itcanbe

seeninFigure12thatinsteadofnaturallighttheLSCMusedalaserandinsteadof

having a wide field of view the LSCM focuses on a single point. The three

dimensional imagethat theLSCMproduces isbuiltupofseveraltwodimensional

imageswithout overlap. From this stack of images, it is possibly to extract the

surfacetopographyparameters. TheLSCMrequirescarefuloperation,toproduce

clearandmeaningful imagemany factorsneedattention. Forexampleonce the

stack of images are collected from the LSCM they are put into a program that

encodesthemwithagreyscalerangingfromzerototwohundredandfiftyfive. A

pureblackpixelisrepresentedbyzeroandapurewhitepixelisrepresentedbytwo

hundredandfiftyfive. Towardsthetwoextremitiesofthescaleinformationabout

thetopographyofthesurfacecanbelostifthetwoextremesarenotbalanced. A

height encoded image canbe likened to a contourmapand from thismap the

topographicalparameterscanbedetermined(Hudleston2004).

Figure12:LaserConfocalScanningMicroscope.

(http://www.unimainz.de/FB/Chemie/AKJanshoff/Illustrationen/scheme_confocal_microscopy.jpg)

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ThereareseveralbenefitsthatLSCMhasovertheothertypesof imagecapturing

devices. TheLSCMcanprovideadetailedsurfacecharacterisationwithouttheneed

forasurfacepreparationas inthecaseofSEM. TheLSCMprocesscanbecarried

outinnormalatmosphericconditionswhereasSEMrequiresahighvacuum. LSCM

isanondestructivemethodthatallowsthesurfacetobeanalysedrepeatedlyand

canproducetheseimagesinamuchshorterperiodthentheothermethods. LSCM

isexcellentforgeneratingimageswithlargeverticalresolutionwhereasAFMonly

hasa vertical resolution in theorderof four mwhichminimises thenumberof

surfacestheAFMcanbeusedon.

1.6 Testing and Evaluation Techniques

Inordertoconfirmordenytheantifoulingpropertiesofasurface itfirstneedsto

betestedandevaluatedtodeterminewhetherthesurfacefinish isapplicable ina

practicalsolution.

Scardino(2004)testedtheantifoulingpropertiesaseashellbysimplysubmersingit

intoacreekwith samplesofothershells; inparticularshells thatwereknown to

have excellent anti fouling properties and those which have poor antifouling

properties. Again,acomparisoncouldthenbemadeaboutthedifferentshellsand

thedifferentfoulingpropertiesofeachshell.

Kukulka (2007) tested the different types of plates that had different surface

finishesonthembyplacingthemall inatankandthepassing lakewaterthrough

thetank. Thelakewaterwasonlyusedonceandwasnotrecirculatedsothatthe

supplyoflakewaterwouldkeepthefoulingparticlescomingatarelativelyconstant

rate. Medilanski(2002)testedtheadhesionoffoulingontostainlesssteelplatesby

placingthemintovialsofafluidandthenintroducingthefoulingmediumtothevial

andtestingtheamountoffoulingthatattachestothesurfaces.

Zettler(2005)usedaheatexchangerthatwassetupusingatwofluidmethodthat

runsahotsideandacoldside. Thefoulingisdesignedtoformonthehotsideof

this systemand the cold side is there tokeep theheatexchangerat thedesired

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operating temperature. The Apparatus proposed by Zettler (2005) can be seen

belowinFigure13.

Figure13:AntifoulingtestingapparatusproposedbyZettler(2005).

1.7 Summary

Asheatexchangersarewidelyused in industry,there isaneedforthemtobeas

economicallyandphysicallyefficientaswellasenvironmentallyfriendlyaspossible.

Thishasbroughtontheneedtodevelopanontoxicfoulingmechanismforusein

heatexchangersandhasledtoresearchintothephysicalmechanismsthatshellfish

possess. Inamarineenvironment,therearemanydifferenttypesoffoulingandas

aresult,severalspeciesofshellfishhavedevelopeddefencemechanismsthatcan

reduce or eliminate fouling. These defence mechanisms come in the forms of

mechanical,physicalandchemicalandtheshellfishusesoneoracombinationof

thesetominimisethefouling(Wahl1989). Itisanticipatedthatthesurfaceofthe

shellfish,whichhas themostefficientantifouling function,canbemimickedand

then applied to surfaces tominimise or totally prevent the formation of fouling

material.

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Chapter 2: Methodology

Theobjectiveofthisprojectwastodeterminethepropertiesofasurfacefinishthat

can be applied to a surface so that it has excellent antifouling characteristics by

mimickingthesurfacefinishofashellfish. Inordertoachievethisoutcomethere

areseveralstepsthatweretaken. Thefirstofthesestepswasthecharacterisation

of the shellfish surfaces,whichwasessential indetermining theparameters that

affectantifouling. Oncetheappropriateantifoulingparameterswerefound,itwas

thennecessarytouseasurface finishingtechniquetoapplya finishtoastainless

steel surface so that it may possess the same antifouling properties. Once the

stainlesssteelsurfacewasprepared itwasthencomparedtothatoftheshellfish

surfacetodeterminethelikenessofthetwosurfaces.

2.1 Characterisation of Shell Fish Surfaces

Inamarineenvironment there ismassive foulingpressureapplied toanysurface

that issubmerged. Ithasbeenrecognisedthattherearespeciesofshellfish that

havetheabilitytorepulsethisfoulingpressureandthushaverelativelyclean,foul

freesurfaces. Itisforthisreasonthatthesurfacesofshellfisharethefocusofthis

research and further more recently the use of three dimensional imaging

techniques has improved the understanding of what the important surface

parametersoftheshellfishsurfaceissignificant.

2.1.1. Sample selection

Thechoiceof the right shellfish isan integralpartof this research. If thewrong

shellfishwerechosen,allofthefindingsobtainedfromthestudywouldbeinvalid.

Itisforthisreasonthatthreedifferentshellfishwerechosenforthesamples. From

eachofthespeciestherearebethreedifferentindividualsandfromeachofthese

twosubsamplescanbetakenatrandomlocationstogetanaverageofthesurface

parameters.

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Thethreedifferentshellfishwerechosenbecauseoftheirnaturalantifoulingnature

in amarine environment (Huddleston 2004). The shellswere chosen based on

previousstudies,whichoutlinedparticularspecies fortheirantifoulingproperties.

The three species taken into consideration were the Amusium Balloti, Mytilusgalloprovincialisand Tellinaplicata. TheAmusiumballoti shell surfacepossessesvery little antifouling potential in its natural environment; this shell will be an

excellentexample thatcanbeused to compare it to theotherantifouling shells.

MytilusgalloprovincialisandTellinaplicataspeciesareknowntohaveahighfoulingresistanceintheirnaturalenvironment(ScardinoanddeNys2004). Bychoosinga

rangeofshellfishspeciesthatcoverstheentirespectrumoffoulingresistance,the

parametersthatmaximiseitcanbedetermined. Thefinalspeciesthatwerechosen

forthisanalysisareshownbelow inFigures14,15,16and17. TheTellinaplicataspeciesofshellcameintwodifferentpigmentssothisspecieswasfurthersplitinto

pigmentsasanotherparameterthatcanbeanalysed.

Figure14:Tellinaplicata(Brownpigment)sample.

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Figure15:Tellinaplicata(Whitepigment)sample.

Figure16:Mytilusgalloprovincialis sample.

Figure17:Amusiumballotisample.

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2.1.2. Image Acquisition

The BIORAD Laser Scanning Radiance 2000 laser scanning confocal microscope

(LSCM)wasused to capture the imagesof the shellfish surfaces. In conjunction

withtheLSCM,Lasersharp2000softwarewasused forall imageacquisitions. As

mentionedpreviouslyinsection2.1.1thereweretworandomsamplestakenfrom

eachof thethreeshells foreachspecies. From theseLSCM, theLasersharp2000

softwareoutputsaseriesoftwodimensionalimages,whichwerethesavedinaTIF

format. The imageswerecreatedbysetting twopoints in thezdirection for the

LSCM to scan between. To aid in the setting of these two points the SETCOL

function on the Lasersharp software was used. The lowest point is gained by

focusingtheLSCMonthelowestpossiblefeatureonthesurface;usingtheSETCOL

function,thismeantthatthescreenwaspredominantlygreenwithonlyafewblack

pixels. ThentheLSCMwasfocusedonthehighestpossiblefeatureonthesurface

using the same SETCOL function as before so that the screen in predominantly

greenwithonlyafewblackpixels. Bysettingthehighestandlowestpointsinthe

Lasersharp2000softwarethistellsLSCMthelimitsofitsmotioninthezdirection.

This gives the differing z level twodimensional images that range from deepest

troughtothehighestridge.

TheLSCMisaverycomplexpieceofmachineryandhasseveralsettingsthatcanbe

varied inordertoobtainthebestquality image. Hudleston (2004)describedtwo

main functions thatwere important forqualitycontrol. Firstly, thequalityof the

imagecanbeadjusted through thehardware settingsand then these settingcan

thenbefurtherdefinedthroughtheLasersharpsoftware. Theotherfunctionthat

canbeadjustedisthereflectivityofthesample. Tominimisethecomplexityofthe

setupoftheLSCMandtheLasersharpsoftwarenotallofthepossiblefunctionsof

theLSCMwereused.

Todeterminethebestpossiblemagnificationdifferentlenseswereusedtoexamine

thesurface. Itwasdecidedthatthesurfacepropertiesthatwerestudiedwouldbe

ona mscale,andtocapturethesefeaturesa100x lenswouldbeneeded. Once

theappropriate lenswas selected then theonlyothervariable thatwas changed

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wastheintensityofthelaser. Thiswasadjustedsothattherewasnosaturationin

the image. Tobestadjustthe laser intensitytheSETCOLtoolwasusedagainand

this allowed a colour representation on the screenwhere greenwas defined as

partsoftheimageoutoffocus,thegreyscalefilledtheareasthatwereinfocusand

red defined areas thatwere saturatedwith light (white). The aim of the laser

intensityadjustmentswere tomake sure that therewas little tonoareason the

imagethatweresaturated(red).

Figure18:LaserScanningConfocalMicroscopeatJamesCookUniversity.

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Figure19:ComputercontainingtheLasersharp2000imagecapturingsoftware.

2.1.3. Image Processing and Analysis

OncetheimageswerecollectedfromtheLSCMitthenneededtobeconvertedinto

imagesthatwillallowthedeterminationofthesurfaceparameters. TheLasersharp

2000softwareoutputsanumberofTIF imagesthataredescribedasan imageof

step in the zdirection. Allof the images thatareobtained from the LSCMwere

convertedintoheightencodedimages(HEI)andmaximumbrightnessimages(MBI)

foruseinthespeciallydesignedMatlabprogramdevelopedbyPeng(2004).

TheMBI iscomprisedofpointsofmaximumbrightness foreachpixel location for

each individual image in the stack of twodimensional images resulting in a

reflectance image of the sample surface (Hudleston 2004). The MBI was then

illustratedusingagreyscalethatseparateseachlayeranddenotesaspecificshade

ofgreytoit. Thescalegoesfromzerototwohundredandfiftyfivewherezeroisa

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pureblackpixelandtwohundredandfiftyfiveisapurewhitepixel. Towardsthe

extremesofthesescoloursinformationmaybelostasthecolourssaturates.

AHEIcanbethoughtofasacontourmaptoacomputerasitcanreadtheheightof

each pixel in relation to all of the others. It is from the HEI that the important

surfaceparametersaredetermined.

Aswellas theMBIandHEI, theMatlab softwarealsooutputsotherusefuldata.

Two other outputs of the Matlab software are the roughness and waviness HEI

images. These images are used in a data analysis program called Optimas to

determinethefractaldimensionandtextureaspectratioofboththeroughnessand

wavinessprofiles. TheMatlabcodealsooutputsaWorddocumentthathastheRa,

Rq, skewness and kurtosis measurements of the surface. These measurements

along with those of the Optimas software are used to determine the numerical

parametersofanantifoulingsurface.

Many numerical parameters have been used in the past to describe the

microtopographyofasurface. Hudlestons(2004)researchwentthroughallofthe

surfaceparameterspresentedinTable1,Table2andTable3. Acorrelationanalysis

wasconductedontheseparameterstodeterminewhichoftheseweresimilarand

whichweredifferent. Thepointofthisissothatunnecessaryparameterswerenot

usedtodescribethesurface. Anexcessiveamountofunnecessaryparameterswill

addasignificantamountoftimetotheanalysisphaseoftheprojectandsomeof

the parameters will be obsolete. It is because of this that the large group of

parameters was reduced significantly to only a group of seven. The seven

parameters thatwere chosen todescribe the surfacesof the samplesare shown

belowinTable4. Theseparameterswerethenusedinthisstudy.

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Table4:FinalisedSurfaceParameters

Parameter Definition

AverageRoughness

(Ra)

AverageRoughnessisthearithmeticmeanoftheabsolute

valuesofthesurfacedeparturesfromthemeanplane.

RootMeanSquare

Roughness(Rq)

RootMeanSquareRoughnessisthesquarerootofthe

arithmeticmeansquaredoftheabsolutevaluesofthe

surfacedeparturesfromthemeanplane.

AverageWaviness

(Wa)

AverageWavinessisthearithmeticmeanoftherepeating

irregularitieswithspacinggreaterthanthatofthe

roughness.

Skewnessofthe

roughnessprofile(Rsk)

wavinessprofile(Wsk)

Skewnessisthemeasureoftheamountofmaterialabove

andbelowthemeanline.

Textureaspectratio

(Str)

TheTextureaspectratiodefinestheAnisotropyor

Isotropyofthesurface.

Fractaldimension(D) FractalDimensionmeasuresthecomplexityoftheshape.

OncetheLSCMimageswereproducedandtheparametersofeachofthesurfaces

werecalculated,acorrelationanalysiswasundertakentodeterminewhichofthe

parameter/scouldbeassociatedwiththeantifoulingnatureoftheshellfish. With

the rangeofshells,ahypothesiscanbemadeasto thechange in theantifouling

characteristicsof the surface resulting froman increasingordecreasingdifferent

thevaluesoftheparameters. AsHudlestonsparameterswereusedagain inthis

study,theresultsfromthisstudywerethencomparedtotheresultsthatHudleston

(2004)obtainedforconfirmation.

2.1.4. Verification of the Matlab and Optimas software

It is important in all experiments that the results that are obtained using one

methodcanbe replicatedusingadifferentmethod toensure that themethod is

accurate. Toensure that thedatacollected in thiscase isaccurateamethod for

dataverificationisneeded. ToverifythedatainthiscaseaStylusProfileristobe

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usedand thiswillprovideadirectRameasurementof the surface. It isvirtually

impossibletousethispieceofequipmentonalloftheshellstoobtainroughness

measurementfornumerousreasons. Thesurfaceofashellisnotflatandinsome

cases, the roughness profile that is trying to be measured is applied to a wavy

surface. ThiswouldmeanthattheStyluswouldhavetotraveldowntroughsand/or

over ridges to take a measurement. This would no doubt interfere with the

measurementoftheroughnessofthesurface.

Toremedythisproblemapieceofsheetstainlesssteelofdimensions100x75mm

wasusedwithdifferentsurfacefinishesoneachsidetodothistest. Ononesideof

the sheet the surface was be buffed using a cloth buffing wheel and buffing

compound before being further polished by hand using a piece of cloth and a

polishing agent. The other side of the sheet was rubbed on a piece of 150grit

sandpaperinacircularpatternuntilthesurfacehasauniformtexture.

Thesameprocesswasusedtocapturethesurfacesofthestainlesssteelsheetas

those used to capture the surface of the shells. Three random positions were

chosen from each side of the sheet to obtain an average later on. The Stylus

profiler was then used on four random points on the surface to determine the

roughness. Once the data from the two tests is compiled then the Matlab and

Optimascodecanbeconfirmedaccurateornot.

2.2 Generation of stainless steel surfaces with anti-fouling

function

Thefocusofthisprojectistoengineerasurfacefinishthatcanbeusedinindustry

tohelpmitigateifnoteliminatebiofouling. Stainlesssteelisusedalmostexclusively

inindustryinareasassociatedwithhightemperaturesandcorrosivefluids. Itisfor

this reason that this project focuses on applying an antifouling surface finish to

stainless steel surfaceswherepossible tohelp reduce theeffect that fouling can

haveonasystem. Onesuchsystemthatcanbeheavilyinfluencedbyfoulingisheat

exchangersandtheirassociatedplumbing. Byproducingasurfacefinishthatcanbe

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appliedtotheplatesinaplateheatexchangerforexample,itcanbeforeseenthat

savingsonrunningandmaintenancewillnodoubtfollow. Astherearenumerous

waysinwhichthesurfaceparameterscanbeapplieditisimportanttonotethatthe

facilitiesatJamesCookUniversity(JCU)didnotpermitthis.

2.2.1. Surface finishing technique

Several surface finishes can be applied to the surface of the stainless steel, but

thereareonlyalimitednumberofmachinesinJCUworkshop. Theeasiestwayto

getavarietyofsurfacefinishesistoapplythesurfacewithdifferentgradesofwet

anddrysandpaper. Idealisticallythespecimenswouldhaveallbeelectropolished

initiallytogiveallofthetestspecimensauniformsurfacefinishtostartwith. The

method that is finally used to apply the surface finish to the stainless steel was

dependentontheparametersthataredefinedafterthefirstpartoftheanalysisof

thesurfacewascompleted. Medilanski(2002)usedthismethodofsandingtoapply

surfacefinishestothestainlesssteelsamplesthatwereused.

Surface grinding was another method that could have been used to apply the

surface finish to the samples. The samples would have been passed under the

surface grinder and a linear pattern will be left on the surface that will

hypotheticallyreplicatethesurfacefinishoftheshellfishspecieswiththegreatest

antifoulingproperties. Severalsamplescouldbecreatedwith thesurfacegrinder

byvaryingthenumberoftimesthewheelispassedoverthesamepointaswellas

thepressurethatisappliedtothesurfaceofthesampleandthedifferentgradesof

wheelthatareused. Inbothcases,thestainlesssteelwouldhavetobeleftinopen

airforaperiodtoallowtheoxidelayeronthestainlesssteeltoregenerate.

Byhavingmorethanonepreparationmethod,awidevarietyofsurfacescouldbe

formedand tested togive thebest chanceofcreatinga surfacewith thecorrect

parameters.

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2.2.2. Stainless steel surfaces vs. shell fish surfaces using

numerical parameters

Afterthegeneratedsurfaceswereleftforawhiletoreaccumulatetheoxidelayer

onthem,thetestpieceswereplacedundertheLSCMforanalysis. Inthesameway,

that the surface of the shellfish were analysed the surface of the stainless steel

samplewerescannedinthreerandomlocationsacrossitssurface. Theresultsfrom

these scans were scrutinised using the same methods as the shellfish surfaces.

After the resultsof the shellfishand the stainless steel samplesare compared, it

wasdeterminedoftheappliedsurfacefinishwouldbethesameorsimilartothatof

theshellfish.

Iftheproducedsurfacesdonotmatchupwiththeparametersthatareneededthen

a second iterationof samplewillbemade. The surface finish thatgave thebest

outcomefromthefirstsetofstainlesssteelsampleswasdecided. Thisdecisionwas

madeusing theparametersand the likenessof thestainlesssteelsamplesurface

andthatoftheshellfishsurface. Themethodthatwasusedtocreatetheclosest

matchtotheshellsurfacewasthenmodifiedsothatthenextiterationofsamples

wasaclosermatchtothatofthesurfaceoftheshellfish.

In thecasewhere there isnosimilaritybetween thesurface finishapplied to the

stainless steel samples and the shell fish sample then the method used in the

generationofthesurfacesneedstobefurtherresearched.

2.3 Testing and evaluation of surface finishes

Itisimportantthatthesurfacesthataregeneratedbetestedsothatthevalidityof

the project can be confirmed. Many proposed methods are used to put the

required surfaces under significant fouling pressure on the test samples. The

methodsareoutlinedinthebelowsectionsandarejustifiedaccordingly.

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40

2.3.2. Testing procedures

Thetestingoftheantifoulingsurfacewasconductedusingtheapparatusthatwas

builtbyPeterFriedrich. Theplatewasmountedintheheatexchangerandthenthe

systemwillrunforapproximately72hourstoallowsufficienttimeforthefoulingto

accumulateonthesurface.

Thesurfaceparametersthathavebeentakenfromthesurfaceoftheshellfishare

primarilyknownfortheiroutstandingantibiofoulingabilities. Theperformanceof

theshellfishsurfaceinaparticulatefoulingcaseisnotknownandtheresultstaken

during this experiment will help to determine whether the shellfish surface

parameterscanbeappliedtomorethanoneapplicationoffouling. Thesetestswill

be conducted in collaboration with the builder of the testing apparatus Peter

Friedrichinordertooptimisethetestingapparatusforthebestoutcome.

2.3.3. Performance evaluation

Toevaluate theperformanceof the surface thereare severalmethods thatwere

used. Whilethetestingapparatusisbeingused,thefluidthatisbeingrunthrough

thehotsideofthemachinewaskeptataconstanttemperature. Thefluidinboth

sidesoftheapparatuswaspumpedataconstantflowrateandthustheheatthatis

lostacrosstheheattransfershouldgointoequilibriumafteraperiodifthereisno

formationoffouling.

The rateatwhich fouling is accumulatingon the surfacewasdeterminedby the

placementoftwothermocouplesinthetestapparatus. Onethermocouplewillbe

used tomeasure the temperatureof thehot fluidand theother tomeasure the

temperatureofthefluidonthecoldsideoftheexchanger. Asthefoulingincreases

ontheheattransfersurfacethethermalresistanceoftheplatewillalso increase.

This differential in temperature was plotted using a computer attached to the

apparatus todetermineatwhat rate fouling isaccumulatingon thesurface. The

heat transfer surface was also inspected at the end of the testing period to

determinehowmuchfoulinghasaccumulatedonthesurface. Thefoulingcoverage

wasanalysedforbothofthedifferenttypesoffoulingtodeterminewhichsurfaces

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RESULTSANDDISCUSSION

Chapter 3: Results and Discussion

Theoverallobjectiveof thisanalysiswas todetermine if there isa single surface

parameteroracomplexcombinationofsurfaceparametersthatcandescribethe

surfacemorphologyofanantifouling surface. Threedifferent speciesof shellfish

have been analysed to create a database of information that can be used to

determine thenumericalparameters foranantifouling surfacemorphology. The

threespeciesofshellthatwerechosenforthisanalysiswerepickedfortheirfouling

resistance in their natural environment. Of the three species, selected Tellinaplicata and Mytilus galloprovincialis are known to have a high level of foulingresistance in their natural environment where as the

Amusium

balloti species is

knowntohavealowfoulingresistance.

Thedata foreachofthesurfaceswasacquiredusingaLCSM. Thedata fromthe

LCSM was then analysed using Matlab and Optimas software and from this, the

numericalparametersaregiven. Oncetheparametersforeachofthesurfacesare

known, a correlation analysis was done to determine the combination of

parametersthatcanbeusedtoforanantifoulingsurfacemorphology.

Themanysectionsthatarereportedinthissectionareasfollows. Thefirstbeing

the data that was retrieved from the shellfish samples using the Matlab and

Optimassoftware. Thesecondwasthevalidationdatathatwasobtainedusingthe

stylus profiler and the third was the data collected from the stainless steel

specimen. Thevalidationdatawas important inthisanalysisasthedatathatwas

collectedusingtheLCSMandthesoftwarepackagesneededtobevalidatedagainst

the physical data of the stylus profiler. The stainless steel samples were also

analysed to determine if they in fact had similar morphology as that of the

antifoulingshellfish.

3.1 Image Acquisition and processing

To determine the antifouling properties of the surfaces, computerised image

capturingandanalysis softwarewasused. Todo this the imageswere captured

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using the Laser Scanning Confocal Microscope along with the Lasersharp 2000

imagingsoftwareaccordingtotheprocessoutlinedabove.

3.1.1. LCSM and Lasersharp 2000 settings

Inorder to captureaccurate imagesusing theLCSM therewere severalvariables

thatcouldbechanged. Belowarealistofvariablesthatwereusedtosetupforthe

images that were taken in this analysis, as well as the reasoning and any

repercussionsofthatchange.

Optical Lens A 100x lens was used for the Tellinaplicata and Mytilusgalloprovincialisspecieswhilea50x lenswasusedfortheAmusiumballotispeciesasaclearimagecouldnotbecapturedwiththe100xlens. The100x

lensresultsina122.88 msquareimageandthe50xlensresultsina256.78

msquareimageatazoom=1.

Laser Intensity This was adjusted for all images, as some surfacesweremorereflectivethanotherswereandthusrequiredthelaserintensitytobe

lowered. ThiswasalladjustedusingtheSETCOLfunctionintheLasersharp

2000software.

ImageSizeA512x512imagingareawaschosenforalloftheimagesasitgivesanimagewithalotofdetailwithoutusingexcessivememory.

StepSizeA0.05 mstepsizewasusedfortheTellinaplicataandMytilusgalloprovincialis species while a 0.2 step size was used for theAmusiumballoti as the shell had excessive curvature and a 0.05m resulted in animagethatwouldhavemorethan225images,whichisnotachievablewith

thishardware.

ScanningSpeedForallofthe imagesthescanningspeedwassetto166loopsper second (lps)as thisgaveahighresolution image. The scanning

speed was raised to 500 lps during the setup period to make the setup

processquicker.

3.1.2. 3D Image Processing in Matlab

TheimagescapturedabovewerethenfurtherprocessedusingMatlabsoftwareto

construct3DimagesthatcouldbeanalysedusingtheOptimasSoftware. Boththe

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Tellinaplicata

(a) (b)

Figure21:(a)MBIand(b)HEIforTellinaplicata.

Figure22:AnalysisresultsfromtheTellinaplicatasampleseparatedintoform,wavinessand

roughnessprofiles.

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Figure21showstheMBIandHEIfortheTellinaplicataSpeciesofshellfish. TheMBIistheimagethatisconstructedbyMatlabtoshowwhatthesurfacewouldlooklike.

It isscaledsothatthedarkestpartsofthe imagedenotethedeepestholeswhile

the lightestpartsof the imagedenote the ridgesof the surface. TheHEI isa2

dimensionalprojectionof thedepthof thebrightestpixelswithinavolumealong

oneof the threemajoraxes. MatlabandOptimasuse theHEI todetermine the

numericalparametersofthesurface.

Figure22 isaMatlaboutputand shows that the surfaceof theTellinaplicata isrelativelysmooth. Theformprofileshowstwothings,onebeingthatthesectionof

shellthatwasscannedhasminimalcurveand theotherbeingthat thesectionof

theshellthatwasscannedisnotparalleltothelens. Asaresult,arelativelysmooth

surfacetooka longtimetoscanasthemicroscopeneededtotakemanyslicesto

captureallofthesurfa

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