Parametric Modeling and Optimization of Advanced Propellers for Next-Generation Aircraft

128 Pages·2017·7.52 MB·English

Parametric Modeling and
Optimization of Advanced
Propellers for
Next-Generation Aircraft
Ing. Peter Cornelis Klein
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Parametric Modeling and Optimization of
Advanced Propellers for Next-Generation
Aircraft
by
Ing. Peter Cornelis Klein
ToobtainthedegreeofMasterofScience
attheDelftUniversityofTechnology,
tobedefendedpubliclyonThursdayAugust31,2017at2:00PM.
Studentnumber: 4250079
Projectduration: April1,2016–August31,2017
Thesisregistrationnumber: 149#17#MT#FPP
Thesiscommittee: Prof.Dr.-Ing.G.Eitelberg, TUDelft(FPP)
Dr.ir.M.Pini, TUDelft(FPP)
Dr.J.Sodja, TUDelft(AS&CM)
Ir.T.Sinnige, TUDelft(FPP),Dailysupervisor
Ir.S.Vitale, TUDelft(FPP),Dailysupervisor
Anelectronicversionofthisthesisisavailableathttp://repository.tudelft.nl/.

Preface
Inearbypresentthefinalreportofmythesisentitled“ParametricmodelingandOptimizationofAdvanced
PropellersforNext-GenerationAircraft". ThisreportiswritteninthepursuitofthedegreeofMasterofSci-
enceattheDelftUniversityofTechnology,atthefacultyofAerospaceEngineering,atthedepartmentofFlight
Performance&Propulsion.
I’vededicatedthelastyeartoproduceathesisthatIamveryproudof. Itwasahardandstressfulbut
rewardingyearthatmarkstheendofmytimeattheDelftUniversityofTechnology,whichstartedbecause
IfeltIwasn’tchallengedenoughatmypreviouseducation. Well, itissafetosay thatI gotwhatIwished
for,hereatthefacultyofAerospaceEngineering. Ithasbeenfiveintense,challenging,butamazingyears,in
whichIhavehadtheprivilegeofgettingtolearnfrominspiringteachersandotherpeople.
IwouldliketothankfirstTomasandSalvatore,whoguidedmethroughadifficultthesisproject. They
havebeenverypatientwithmeandwerealwayswillingtohelporofferadviseatthetoughmoments.Iwould
liketothanktheremainingmembersofthecommitteewhomadethemselvesavailablesothatIcangraduate.
Andoffcourse,myparents,Evelien,andJelle;youaresimplyamazing.
Ing.PeterCornelisKlein
Delft,August2017
iii

Summary
Astraditionalfossilfuelsbecomescarcerandmoreattentionisgiventoenvironmentalimpactofthecom-
bustionoffossilfuels,fornext-generationaircraft,thefocusofdevelopmentwillmainlybeonreducingfuel
consumption.Openrotorengineshavetheadvantageoverconventionalturbofansthattheyareexpectedto
perform25%to30%betterintermsoffuelconsumption.Thetopicofthisthesisfocusesononeofthecurrent
challengesrelatedtoopenrotorconfigurations;theunwantedunsteadyeffectsimposedontheaerodynamic
characteristics of a propeller, imposed by an upstream pylon. There is a potential for reducing undesired
propeller-pyloninstallationeffectsbytakingtheseeffectsintoaccountinaerodynamicdesignprocessofthe
propeller.Apropellerdesignoptimizationroutineisimplementedthatincludesaparametricmodelingtool,
alow-andhigh-fidelityperformanceanalysismethodandanexistinginstallationeffectsperformancemodel.
Thelow-fidelityisolatedpropellerperformanceanalysismethodwasusedtoapproximatetheisolated
performanceofapropellerinanoptimizationenvironment. Threeexistingtoolswereinitiallyconsidered:
Xrotor,JavaPropandaschemebyAdkins&Liebeck.Avalidationstudywasperformed,basedonalow-speed
propellerdesign(N250), totheassessaccuracyofeachmethod’sperformancepredictioncapabilities, and
alsotocomparethedifferencesbetweenthedifferentmethodsinordertomakeaselectionforonemethod
tobeusedintheremainderofthisthesis. Itwasshownthatoutofthethreeexistingmethodsconsidered,
Xrotorwasthemostaccurateandthesecondmostreliablemethod.JavaPropwastheleastaccuratemethod
andtheAdkins&Liebeckschemewastheleastreliablemethod.ItwasthereforedecidedtouseXrotorforthe
remainderofthethesis.
Thehigh-fidelityisolatedpropellerperformanceanalysismethodwasusedtoverifytheprecisionofthe
low-fidelityisolatedpropellerperformanceanalysismethodforthebenefitoftheoptimizationroutine. A
CFDanalysismethodwiththeopen-sourcesolverSU2wassetup,includingtheimplementationofamesh
generator. Then,avalidationstudywasperformed,basedonahigh-speedpropellerdesign(APIAN),toas-
sesstheaccuracyoftheCFDanalysismethod. Moreover,themethod’ssensitivitytomeshrefinementwas
studied, inordertotostudythemethod’ssensitivitytomeshrefinement, inordertomakeaselectionfor
onemeshrefinementleveltobeusedintheremainderofthisthesis. Thevalidationofthehigh-fidelityiso-
latedpropellerperformanceanalysismethodshowedthattheimplementedCFDmethodisvalidandableto
predictisolatedpropellerperformancewithacceptableaccuracy. Themostnotabledifferencesincludean
increasingdeviationbetweentheCFDthrustcoefficientresultsandthereferencedatawithincreasingad-
vanceratio. Moreover,thepredictionofthetipvortexintensityinthewakeofthepropellerandtheposition
ofthebladeleadingedgevortexonthebladesuctionsideturnedouttobechallenging.Forthelevelsofmesh
refinementconsideredhere,nosignificantimprovementswereobservedintheCFDresults.Fortheremain-
derofthisthesis,onerefinementlevelwasselectedbasedonthesensitivityresults,correspondingtoagrid
of4.7millioncells.
Thepropellerparametrizationtoolwasusedtoaccuratelyrepresentacomplexpropellergeometrywith
theleastamountofparameters,fortheoptimizationroutine. Somehighlightsofthetoolincludethepos-
sibility to parametrize a spinner and hub geometry, the modeling of blade chord, pitch, sweep, and lean
distributions , as well as methods for defining blade thickness and camber. A verification study was per-
formed in which three different tests were conducted. In the first test, it was demonstrated that, for two
differentpropellers(N250, APIAN)ofdifferentlevelsofcomplexity, itispossibletoaccuratelyrecreatethe
propellergeometrywiththeparametrizationtool.Inthesecondtest,theparametrizedN250propellermodel
wasusedtodemonstratethatforthelow-fidelityisolatedpropellerperformanceanalysismethod,itispos-
sibletoachievealmostidenticalaccuracyaswiththereferenceN250propellermodel. Inthefinaltest,the
parametrizedAPIANpropellermodelwasusedtodemonstratethatforthehigh-fidelityisolatedpropeller
performanceanalysismethod,itispossibletoachievesimilaraccuracyaswiththereferenceAPIANpropeller
model.
Inthesetupofthepropellerbladeoptimizationforminimizedinstallationeffects,anexistinginstalled
propellerperformanceanalysismethodwasimplemented.Fortheobjectivefunction,twospecificunwanted
installation effects are considered: unsteady fluctuations in thrustperformance and worse installed noise
performance.Nonoisepredictionmethodswereincludedintheanalysis,sincetheyarenotwithinthescope
of this thesis. Instead, worse installed noise performance was represented by focusing on the main aero-
dynamicdriversofinstalledpropellernoise. Theseeffectswereformulatedindifferentcandidateobjective
functions,forwhichthesensitivityofeachobjectivefunctionisinvestigated. Furthermore,asecondaryob-
v
jectivefunctionisimplementedbyapplyingamulti-objectiveoptimizationstrategywiththegoalofmaxi-
mizingmeaninstalledefficiencyperformance.Asingleconstraintisimplementedtokeepthemeaninstalled
thrustperformanceconstant.
Theresultsofthepropellerbladeoptimizationforminimizedinstallationeffectsincludeastudyofpoten-
tialcandidateobjectivefunctions,astudyoftheinfluenceofdifferentoperatingpointsontheoptimization
routineandadetailedinvestigationoftheperformanceofthreedifferentoptimumsolutionsselectedfrom
thefirsttwo. Inthemulti-candidateobjectiveoptimizationstudy,itwasdiscoveredthatatahighpropeller
thrustsetting,thepotentialgaininmeaninstalledefficiencyislimitedtoabout10%.Thedifferentcandidate
objectivefunctionshavedifferentdesigntrends,meaningthatifoneoptimizesforone,theotherinstallation
effectsbecomeworse. Thecandidateobjectivefunctionrelatedtoinstallednoiseperformancewasusedfor
theremainderofthisthesis. Inthemulti-operatingpointoptimizationstudy,twooptimizationswereper-
formedatdifferentpropellerthrustsettings(intermediate andlow). Inthedetailed investigationinto the
performanceofthreedifferentoptimumsolutions,selectedfromthepreviousstudies,itwasdiscoveredthat
theoptimumsolutionsforhighthrustsettingandlowthrustsettinghaveconvergedtomoreorlessthesame
solution,whichmeansthattheoverallperformanceisalsoverysimilar.Theoptimumsolutionatintermedi-
atethrustsettingperformedsignificantlybetterthroughouttheentireoperatingrange,comparedtotheother
two.Thissolutionwasthereforepresentedastheultimateoptimumsolutionfortheobjectiveofminimizing
installationeffects.
Themaindesignchangesinthefinaloptimumpropellerdesign,comparedtothebaselinepropellerde-
signwereanincreaseinchordinthebladehubregionandanincreasedpitchdistributiongradientanda
higheradvanceratio. Forahighthrustsetting,thefinaloptimumsolutionwasa30%installednoisemetric
improvementoverthebaselinepropellerdesign. Atthesamethrustsetting,antheinstalledpropellereffi-
ciencyimprovedby8%,theunsteadyfluctuationsininstalledthrustperformancewerereducedby20%and
theunsteadyfluctuationsininstalledtorqueperformancewerereducedby26%.Foralowthrustsetting,the
finaloptimumsolutionwasa25%installednoisemetricimprovementoverthebaselinepropellerdesign.At
thesamethrustsetting,therewasnosignificantimprovementininstalledpropellerefficiency,theunsteady
fluctuationsininstalledthrustperformancewerereducedby29%andtheunsteadyfluctuationsininstalled
torqueperformancewerereducedby36%.
Itisconcludedthattheoriginalhypothesisofthisthesis,whichwasthatthereisapotentialforreducing
unwantedpropeller-pyloninstallationeffects,bytakingtheseeffectsintoaccountduringtheaerodynamic
designprocessofthepropeller,isconfirmed.considerableimprovementsweremade,comparedtotherefer-
encepropeller.Itisrecommendedthatforfuturework,additionalimprovementscanbemadeonthecurrent
setup. Thisincludesextendingthefunctionalityofthelow-fidelityisolatedpropellerperformanceanalysis
methodtotakesweepandleaneffectsintoaccount,additionalscrutineeringofthedifferencesfoundinthe
CFDanalysismethodvalidationstudy,andahigh-fidelityverificationstudyusingCFDofthefinalbladede-
signresultingfromtheoptimizationforminimizedinstallationeffects.
vi
Contents
Preface iii
Summary v
Nomenclature ix
1 Introduction 1
1.1 Background. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Researchaimandobjectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Thesisoutline. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 Low-fidelitypropellerperformanceanalysismethod 5
2.1 Overviewofexistingtools. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1.1 Xrotor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1.2 JavaProp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1.3 Adkins&Liebeckscheme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.2 Validationstudy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2.1 Referencecase. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2.2 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3 Low-fidelityperformanceanalysismethodselection . . . . . . . . . . . . . . . . . . . . . . . 11
3 High-fidelitypropellerperformanceanalysismethod 15
3.1 SetupofCFDanalysismethod . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.1.1 Meshgenerator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.1.2 Solversetup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.2 ValidationofCFDmethod . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.2.1 Meshsensitivitystudysetup. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.2.2 MeshSensitivitystudyresults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.2.3 Discussionofresults. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4 Parametrizationtool 31
4.1 Toolstructure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
4.1.1 Preliminarydesignmethod . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.1.2 Bladeparametrization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
4.1.3 Spinnerparametrization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
4.2 Parametrizationtoolverification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
4.2.1 Low-fidelityanalysisverification. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
4.2.2 High-fidelityanalysisverification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.2.3 Discussionofverificationresults. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
5 Propellerbladeoptimizationforminimizedinstallationeffects-Setup 55
5.1 Installedperformancemodel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.1.1 Pylonwakemodel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.1.2 Modelinginstalledeffects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
5.1.3 Exampleofinstallationeffects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5.2 Definitionofoptimizationproblem. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
5.2.1 Referencebaselinecase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
5.2.2 Formaldefinitionofoptimizationproblem . . . . . . . . . . . . . . . . . . . . . . . . 61
5.2.3 Optimizationalgorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
6 Propellerbladeoptimizationforminimizedinstallationeffects-Results 71
6.1 AccuracyofLow-andhigh-fidelityanalysismethod . . . . . . . . . . . . . . . . . . . . . . . 71
6.2 Multi-candidateobjectiveoptimizationstudy . . . . . . . . . . . . . . . . . . . . . . . . . . 72
6.2.1 Minimizinginstalledthrustperformance . . . . . . . . . . . . . . . . . . . . . . . . . 73
6.2.2 Minimizingindividualaerodynamicbladenoisedrivers. . . . . . . . . . . . . . . . . . 75
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6.2.3 Minimizingcombinedaerodynamicbladenoisedrivers. . . . . . . . . . . . . . . . . . 78
6.2.4 Selectionoffinalobjectivefunction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
6.3 Differentoperatingpointoptimizationstudy. . . . . . . . . . . . . . . . . . . . . . . . . . . 83
6.3.1 Optimizationatintermediatethrustsetting:1.40 . . . . . . . . . . . . . . . . . . . . . 83
6.3.2 Optimizationatlowthrustsetting:1.75 . . . . . . . . . . . . . . . . . . . . . . . . . . 84
6.3.3 Selectionofoptimumdesigns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
6.4 Detailedperformanceofselectedoptimumdesigns . . . . . . . . . . . . . . . . . . . . . . . 86
6.4.1 Overviewofoptimumdesigns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
6.4.2 Optimumdesignsinoff-designconditions. . . . . . . . . . . . . . . . . . . . . . . . . 88
6.4.3 Selectionoffinaloptimumdesign . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
7 Conclusions&Recommendations 93
7.1 Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
7.2 Recommendationsforfuturework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
Bibliography 97
A CFDvalidationresults 99
A.1 Overallperformancerelatedresults. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
A.2 Bladepressuredistributionrelatedresults . . . . . . . . . . . . . . . . . . . . . . . . . . . .101
A.3 Wakeflowfieldrelatedresults. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .105
B ParametrizationtoolCFDverificationresults 109
B.1 Bladepressuredistributionresults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .109
B.2 Spinnerpressuredistributionresults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .110
B.3 Wakevelocityresults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .111
C Additionaldifferentoperatingconditionoptimizationresults 113
C.0.1 Initialoperatingpointatadvanceratioequalto1.40. . . . . . . . . . . . . . . . . . . .113
C.0.2 Initialoperatingpointatadvanceratioequalto1.75. . . . . . . . . . . . . . . . . . . .115
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