Nafems Benchmark Aerospace

7/25/2019 Nafems Benchmark Aerospace

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Special Edition:Engineering Analysis

& Simulation in the

Aerospace Industry

BENCH

MARKTHE INTERNATIONAL MAGAZINE FOR ENGINEERING DESIGNERS & ANALYSTS FROM NAFEMS

Aerospace issue . . .

COMPOSITES RESEARCH ON THE RISE

COMPOSITE PROCESS SIMULATION

HOW TO GET THE PART DIMENSIONS RIGHT

RESIDUAL STRESS CALCULATION FOLLOWING A REPAIR PROCESS

DYNAMIC SIMULATION OF FLIGHT TEST MANOEUVRES

IMPROVING THE SIMULATION OF BIRD STRIKE ON PLASTIC WINDSHIELDS

HIGH LIFT SYSTEM VIRTUAL TEST

IMPROVING STRUCTURAL MODELLING

ROCKET SCIENCE

FATIGUE IN ALUMINIUM HONEYCOMB-CORE PLATES

COUPLING 1D AND 3D CFD

Special Edition:Engineering Analysis

& Simulation in the

Aerospace Industry


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from your

editorDavid Quinn

[email protected]

@benchtweet

Welcome to this special edition of Benchmark, which has brought

together a series of past articles that are strongly relevant to

simulation in the aerospace industry. Aerospace manufacturers and

suppliers are facing an increasingly challenging and competitivemarketplace. The current industry demands that engineers design

safe and reliable aircraft, meet increasingly stringent fuel-economy

standards, and invent cost-effective approaches to the use of

cutting-edge materials. Utilizing the latest simulation tools with

accuracy and efficiency has never been more critical, as aerospace

engineering continues to move into highly-advanced technological

space.

As part of our annual industry series, we are hosting an aerospace

event which will look specifically at the challenges that the industrycurrently faces, and will also explore how simulation and analysis

can help meet the industrys goals in a cost-effective and efficient

manner. Within this special edition of Benchmark, you will find

articles on many topics related to the aerospace industry, all of

which give a best-in-class perspective on a range of the issues that

are prevalent to all involved.

NAFEMS is the only independent, international association dedicated

to engineering analysis and simulation. Our range of best-practiseguides, benchmarks, how to publications, as well as seminars,

courses, e-learning and conferences, allow us to bring industries

together to share and exchange experience and knowledge in order

to drive the technology forward. Our members come from every

industry around the world, giving a truly global perspective to our

activities and allowing our community to benefit from the wealth of

its own experience. You can find out more about NAFEMS and our

activities, as well as details on our industry and technology specific

events, by visiting nafems.org


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4

CompositesResearch onthe Rise

IntheUS, thereareseveralinitiati veslaunchedrecentlyfromtheDepartment ofEnergy,NASA, andtheWh iteHouse.In theDepartmentof Energy,OakRidge NationalLaboratoryishome totheDepartment ofEnergys(DOE)newCarbonFiber TechnologyFacility(CFTF)a42,000squarefootinnovative technologyfacility.TheCFTF offersahighlyflexible, highlyinstrumented carbonfiberline fordemonstratingadvancedtechnology scalabilityandproducingmarket-developmentvolumes ofprototypicalcarbonfibers.The CFTFservesasa nationaltestbedforgovernmentandcommercial partnerstoscale-upemergingcarbonfiber technology.Amajorgoal ofthecarbonfiberline istobring downthecost ofproducingcarbonf iberandpartof thiseffor t is l ookingatalternativeprecursorsthatcould belessexpensivetoproduce.

Earlyin2015, theWhite HouseandDepartment ofEnergyannouncedtheformation ofanInstitute forAdvancedCompositesManufacturingInnovation (IACMI)ledbytheUniversityofTennesseewith alargeteam ofcompanies,researchinstitutes,universities andU.S.Stategovernments.The focuswillbeon manufacturinginnovationforapplications inthe automotive,wind

energy,andcompressedgas storageindustries.Part ofIACMIwillfocuson virtualsimulation toolsforcompositesandthis effortwillbe ledbyPurdueUniversityandProf.Byron Pipes(seearticleoncdmHUB).

NASAhaslaunchedan AdvancedCompositeResearchPartnershiptoadvance certificationofcompositestructuresforaerospaceapplications. TheteamincludesBellHelicopter,GEAviation ,LockheedMartin, NorthropGrumman,Boeing, andUnitedTechnologies. Certifyingcompositestructuresismuch morecomplexand costlythancertifyingmetallic structuresanda majorgoaloftheeffortis toutilize simulationmethodsto bringdownthecostof certifyingnewmaterials andstructuresmadefromnewcomposite materials.

TheSAEAircraftSeat Committeeisalso developingastandardforcompositeaircraft seatswhichwill addresstheuniqueaspec tsofcompos iteseats . Theworkinprogressstandard(ARP6337)willdefine anddeveloptestparameters,testmethods, measurements,andacceptableperformancecriteriaforcomposite aircraftseatstructures.The rationalebehindthe standardisthe

Inthe70s,80s, andintothe90s, therewasalot ofresearchmoneyspenton compositematerials.Itstartedwithpolymericcompositesbutin the90s,muchof thiswenttometal-matrixandceramic-

matrixcomposites.Muchof thisresearchwasfunded bytheUS, European,andJapanesegovernmentsandwasdirectedtowardsaerospaceapplicationsof composites.Bythe endofthe90s, muchofthe

advancedmaterialsgovernmentresearchfundingwenttowardsnanomaterialswiththeprivate sectortakingonthecompositematerialsresearcheffort. Thisledtothe Boeing787andAirbus A350whichhave

over50%oftheir structuremadefromadvancedcompositematerials. Inthelastfew years,aresurgenceofinterestintraditionalcompositematerialshasled toseveralgovernmentsupportedresearchinitiatives

andconsortiumsinthis area.Muchof thisinterestisin thefieldsofnon-aerospacecompositeswhichdominatedtheresearchfundingin the70s,80s,and90s. Areviewofsomeof thehigherprofileinitiatives

andconsortiumsisoutlinedhere.

"...a resurgence of interest in traditional compositematerials has led to several government supported

research initiatives and consortiums..."

Dr.RobertN. YanceyVP AerospaceandComposites, AltairEngineering 4

Composites

Research

on the Rise

Composite ProcessSimulation Digitally Reinforcing High-RateComposite ManufactureDr.PeterGiddings CEngMIMechEResearchEngineer,ManufacturingProcessSimulation, NationalCompositesCentre UK

MiroslavStojkovic MScCEngMRaesEngineeringCapabilityManager,Design Stressand Simulation,NationalComposites CentreUK

Fibrereinforcedpolymercomposites havebeenamainstayofresearchan ddevelopmentin aerospaceandmotorsportindustries fordecades.Withm ass

reductionandincreased structuralefficiencybecoming akeypriorityin thetransport,renewable energy,marineandconstructionsectors,thecomposites industryfacesnewchallengestomeetth egrowingdemand andcutcomponentcosts.

Developinghighlyrepeatable automatedproductionlinesiscriticalforcomposite manufacturingindustriesto makethetransitionfrom lowvolumebusinessm odelstothehighvolumecost-efficient manufacturingthesen ewmarketsdemands.

TheNationalComposites CentreUK(www.nccuk.com)istheUKhub forcompositesmanufacturing industryandprovidesafocalpoint forresearchanddevelopment intoautomatedcompositeprocessing.The Bristol-basedcentrehousesam ultidisciplinaryteamof over140staffwhoaresuccessfullysupporting industrialpartnersinunderstandingandsolving arangeof issuesfacingcompositemanufacturers.

Aspartof theNCCtechnology development,manufacturingprocesssimulation playsakey roleindevelopinginsightand guidingthe developmentofcompositesmanufacturingprocessesto accelerateinnovationand reducethecostand riskassociatedwithprocessdevelopment.Amongthe wideranging researchintoautomatedmanufacturing, automatedfibre

placement,resininfusion andinduction weldingofthermoplasticsstandout asexampleswherechallengingsimulationshave providedrealbenefittoNCC members.

Automatedfibreplacement (AFP)Automatedfibreplacement (AFP)isused inthemanufactureofhigh-value compositecomponents,whereprecisionand repeatabilityoffibre placementarekeytothe performanceofsafety-criticalcomponents.

Tapesofcomposite material,between6.35mm and25.4mmwide,are compactedontoa toolusingacompliantpolymerrollermou ntedtoa roboticpositioner.MostAFPsystemsalso heatthein comingmaterialvialaser, infra-redlightor XenonFlash-lamp(asystemmanufactured byHeraeusNobleLight anddevelopedincollaboration withtheNCC) toachievetheidealprocessingconditions.

AFPisakeytechnologyattheNCC,w ithl ivedevelopmentprogramsfor thermosetcomposites(suchascarbon/epoxy),dry fibrematerialsaswell asthermoplasticmatrixcomposites alreadyyieldingindustrialbenefits.

Simulatingthe AFPprocesspresentsmany challenges,withlargegradients inbothpressure andthermalfieldsaroundtherapidly movingroller.However,byaddressingspecificmanufacturing issues,theNCCsimulationengineers areprovidingrealben efitsontheshopfloor.

Recently,theNCC hasdevelopedefficient methodsforpredictingthem aximumachievablecourse width(thenumberoftapes depositedina singlepass)andalsohowchangesin appliedheatingpower influencetheas-depositedmaterialstate.

6

6Composite Process

Simulation

Digitally

Reinforcing High-Rate Composite

Manufacture11

How To Get the PartDimensions Right inComposites ProcessingGranFernlund1,2,Anoush Poursartip1,2,AbdulArafath 2,CoreyLynam21TheUniversity ofBritish Columbia2ConvergentManufacturingTechnologies

Compositepartswilln othavethe samedimensionsasthetool onwhichthey wereprocessed,becauseofmechanismssuchas tooldimensionalchange

duringheat upandresidual stressbuild-upwithin thepartduringcure/solidification andcool-down.This istrueforallcompositematerialsand processes,andonlythemechanismsdifferslightlybetween differentmaterialsystemsandprocesses.Dimensionalchange becomesaproblemifthe magnitudeofchange isgreaterthan thedimensionaltolerancerequirementsof thepart.

Aerospacestructuretolerancescanbe astightas +/-0.010inchesfromnominal engineeringdimensions,andthiscanbedif ficul ttoachievewithoutagooddimensionalmanagementstrategy.Manycompositefabricatorsarefamiliarwith spring-inorspring-backwhichisthe closingofangles duetostrain anisotropy[Nelson&Cairns].However, dimensionalmanagementisabiggersystemslevelproblemand manyotherparametersalsoaffectfinal curedpartdimensions.Thesystemsparametersthataffectdimensional change,andanyotheroutcome inacomposites process,canbedividedinto threebroadgroups relatedtopart,tooling orprocess[Johnstonetal.].Some ofthemain driversare:

Part:Geometry,Materialbehavior, Lay-up

Tooling:Geometry,Materialbehaviour

Process:Temperature,Pressure,Time,Heattransfer

Anyonewhohasbakedacakeintheirhomekitchenknowsthathowthecaketurnsoutdoesnotonlydependonthedoughbutalsothetypeofpanused, typeofoven,

locationinthe oven,temperatureandtime intheoven,cooldown,and removalfromthepan.Th esameistrueforcompositesprocessingit isasystemsproblemwherethepart, toolingandprocessall interacttodeterminetheoutcome.

PredictingDimensionalChangeIfatool ismachinedto thenominalengin eeringdimensionsofthe compositepart,dimensionalmeasurementsonmultiplepartsmade offthattool willgenerallyshowamean deviationfromnominal andsomevariabilityaroundthe mean.Ifthe totaldeviationfromnominalislessthan thedimensionaltolerances,dimensionalconformanceisachieved andnofu rtheractionisrequired. Ifnot,the part,toolingand/or processhavetobe modifiedtoachieve dimensionalconformance.Thiscanbe acostlyand timeconsumingiterativeprocess,asitis difficulttoanticipate theeffectof systemparameterchangesifthere isnopredictive model.

Itisincreasingly unacceptabletodepend ontrial-and-errortoachieve dimensionalconformance,especiallyoncethetool ismadeand fullscalepartsare produced.Othertypicaloptions areexperience,expertopin ion,tests,orsimulation.Experience andexpertopini onoftenfallshortif thepartand processiscomplexor deviatesfromthepreviousexperience base.Testdataare oftenoflimiteduseas finalcureddimensions dependonpart,toolingandprocess,which makescalingofresults fromsmalltestcouponsto thefull-sizepart andprocessoftenmisleadingandthus risky.Themosteffective option,particularlyforlargeand complexstructures,is

11How To Get the Part

Dimensions Right in

Composites Processing

14

Residual StressCalculation FollowingA Repair ProcessSderlundHarald,Shailesh Chillal,AshaKoshy &SushovanRoychowdhury

GKNAerospace14Residual Stress

Calculation Following

A Repair Process

20

Dynamic Simulation ofFlight Test Manoeuvreson the Diamond D-Jet

Thenumericalsimulation ofthe complexfluid-structureinteractiontakingplacewhen manoeuvringanaircraft remainsachallenge.Arealisticanalysisof theairplanemanoeuvrability ofteninvolvesthepresenceofmoving parts,such asthe deflectionofthe elevators,theailerons,or theelevons.For conventionalComputationalFluidDynamics(CFD)codes,dealingwithsuchmovinggeometr iesisachallengingtask.The followingworkuses asoftwarebased onthelattice-Boltzmannmethod(L BM)to overcometheseissues.

Thisarticle,whichwontheBestPresentedPaperawardatthe2013NAFEMSWorld Congress,presentsa numericalstudyon thedynamicsimulationofflighttestmanoeuvresontheDiamondD-JET,usingtheXFlowvirtualwindtunnel.Thepitchcapturemanoeuvreisfirst simulated,studying thepitch oscillationresponseofthe aircraft.Dutchroll flightmode isthen numericallyreproduced.Finally,theD -JETangleof attackis evaluatedinthepost-stallregimeunder controlledmovementsof theelevator.

20Dynamic Simulation

of Flight Test

Manoeuvres on the

Diamond D-Jet

Parts:MecaplexLtd,Grenchen,SwitzerlandSimulation:AerofemGmbH,Ennetburgen,SwitzerlandProject:UniversityofAppliedSciencesandArtsNorthwesternSwitzerlandFHNW/InstituteofProductandProductionEngineering,Windisch,Switzerland

Improving theSimulation of BirdStrike on PlasticWindshields

29

29Improving the

Simulation of Bird

Strike on Plastic

Windshields

35

High Lift SystemVirtual TestMrJaymeenAm in, DrTobiasUlmer (AirbusOperationsGmbH, Bremen),MrPhilip Neuhaus(FTIEngineering NetworkGmbH,

onbehalf ofAirbus OperationsGmbH,Bremen)

Winner of the NWC13 Best Paper Award for

Greatest Business Impact of Simulation

35High Lift System

Virtual Test

40

Improving StructuralModelling of HighStrain Rate Behaviourof Composite MaterialsUsing High SpeedImagingDuncanA.Crump, JaniceM.Dulieu-Barton,and StephenW.BoydUniversityofSouthampton

Thereis adrivet owardsproducinglightervehicles thatare faster,moremanoeuvrable

andmorefuel efficientto improvethesustainabili tyoftransport systems. Theexcellent

specificstiffness/strengthpropertiesof fibrereinforcedpolymercomposite, e.g.carbon

andglassfibres, makethem anincreasinglyattractive optionforstructures inhigh-end

andmilitary applications.

Thesecomplexmaterialsarebeingusedinapplicationswherethereisarealr iskof

impactorhi ghvelocity loading,whetherthis isbird strikeonpassenger aircraft(Figure

1),slammingloadsonmarinevesselsorexplosionsintheproximityofmilitaryvehicles.

Forefficientstructural designit isvital thataccurateand pertinentmaterial properties

areavailab leforinputintofiniteelement(FE)models.Whilethequasi-staticbehaviour

ofcompositematerialsisgenerallywellunderstood[1],thereisaneedtoforfurther

analysisathighvelocityloading[2,3].

40Improving Structural

Modelling of High

Strain Rate

Behaviour of

Composite MaterialsUsing High Speed

Imaging44

Rocket ScienceAttherecentSiemensNXCAESymposium,held inCharlotte,NC,USA,

benchmarktooksome timeto speaktoNathan ChristensenofATK

LaunchSystemsabout theiranalysis processes,anduse ofsimulation.

NathanjoinedATKasadesignengineer incompositestructures,designingandanalyzingmissilesandrockets.Hespentasignificantportionofhis28-year careerworkingwithPLM/CAD/CAEandcomputationaltoolsfor designandanalysis.Christensenisoneofthet echnicalfoundersofATKsPLMsystem,whichnowmanageshundredsofthousandsofpiecesofproductandengineeringinformationusedat ATKfacilitiesacrosstheUS.Hehas publishednumeroustechnicalarticlesandpapersonrocketmotor designandanalysis,CAEtoolsandcomputationalmethods.Healsoholdsapatentfor hybridpressurevessels.

Christensenwasfirstappointedmanagerofthe CAEgroupin1992,with responsibilitiesforengineeringcomputationaltoolsandmethods.Inhiscurrentpositionas managerofEngineeringToolsandAnalysisgroup,hisresponsibilitiesincludePLM/CAD/CAEtools,trendanalysis,rocketmotorperformancedatabases,analyticalmethodsandsoftwaredevelopment,reliabilityengineeringandhigh-performancecomputing.

BackgroundimagecourtesyofATK LaunchSystems.NathanChristensenphotographedbyBrancoLiu,Siemens

44Rocket Science

47

honeycomb

Fatigue inAluminiumHoneycomb-corePlates

LaurentWahl,Arno Zrbes,StefanMaas andDanile Waldmann,fromthe

UniversityofLuxembourg, investigatethefatigue propertiesofthe honeycombcoreof aluminiumsandwich panels,as usedthroughoutthe aerospaceand

automotiveindustries.

47Fatigue in Aluminium

Honeycomb-core

Plates

54

Coupling 1D and 3D CFD

The Challenges and

Rewards of Co-SimulationVincentSoumoyofEURO/CFDandDavidKelsallofFlowmasterLtd,bothmembers

oftheNAFEMSCFDWorkingGroup,provideanoverviewoftherecentNAFEMSUKseminaroncoupling1Dand3D.

Thebenef itsofcoupl ing1Dand3DCFDcodes havelongsincebeenr0ecognised.

Automotiveandaerospacecompanieshaveused 1Dcodestogainabetter understandingofsystemperformance(suchas fuelssystems),whilst3Dcodes areusedtoanalysedetailedbehavi ourwithinandaroundkey components.Withthatinmind,theNAFEMSCFDWorkingGrouprecentlyarranged aseminaratthe HeritageMotorCentreinGaydon UKtounderstandthebenefitsof suchlinksandassessthecurrentstate oftheart.Approximately40interestedparties

fromacrosstheNAFEMSmembershipattendedto hearanumberofinteresting andthought-provokingpresentationsfromvariousspeakers.

DarrenMorrisonstartedthetechnicalpresentationsby sharinganinterestingview onthesubjectfromtheperspective ofalargeaerospacecompany(AIRBUS).Validationisseen asdesperatelyimportant,sothatmuchof theirworkisto provethatany couplingsareproducingrealisticandreasonablyaccuratepredictions. Indesigningfuelsystems, muchof

theanal ys is isdonewith1Dcodesforreasonsofcomputationaleconomybut sometimesthepassagesandfluid interactionsaresocomplexthatonl ya3Dtreatmentisfelt appropriate.Hithertoresultshaveb eenpassedmanuallyfrom1D to3Danalyses.Thereisa desireforsuchcouplingstobeautomaticbutw ithoutcompromisingtheintegrity oftheanalysis.

Representingavendorsperspective,DomonikSholz fromANSYSGermanycalledforparticipatingcodesto developa

54Coupling 1D & 3D CFD

The Challenges and Rewards of

Co-Simulation


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Composites

Research onthe Rise

In the US, there are several initiatives launched recentlyfrom the Department of Energy, NASA, and the WhiteHouse. In the Department of Energy, Oak Ridge NationalLaboratory is home to the Department of Energys (DOE)new Carbon Fiber Technology Facility (CFTF)a 42,000square foot innovative technology facility. The CFTF offersa highly flexible, highly instrumented carbon fiber line fordemonstrating advanced technology scalability andproducing market-development volumes of prototypicalcarbon fibers. The CFTF serves as a national testbed forgovernment and commercial partners to scale-upemerging carbon fiber technology. A major goal of thecarbon fiber line is to bring down the cost of producing

carbon fiber and part of this effort is looking atalternative precursors that could be less expensive toproduce.

Early in 2015, the White House and Department of Energyannounced the formation of an Institute for AdvancedComposites Manufacturing Innovation (IACMI) led by theUniversity of Tennessee with a large team of companies,research institutes, universities and U.S. Stategovernments. The focus will be on manufacturinginnovation for applications in the automotive, wind

energy, and compressed gas storage industries. Part ofIACMI will focus on virtual simulation tools forcomposites and this effort will be led by PurdueUniversity and Prof. Byron Pipes (see article oncdmHUB).

NASA has launched an Advanced Composite ResearchPartnership to advance certification of compositestructures for aerospace applications. The team includesBell Helicopter, GE Aviation, Lockheed Martin, NorthropGrumman, Boeing, and United Technologies. Certifyingcomposite structures is much more complex and costlythan certifying metallic structures and a major goal of

the effort is to utilize simulation methods to bring downthe cost of certifying new materials and structures madefrom new composite materials.

The SAE Aircraft Seat Committee is also developing astandard for composite aircraft seats which will addressthe unique aspects of composite seats. The work inprogress standard (ARP6337) will define and develop testparameters, test methods, measurements, andacceptable performance criteria for composite aircraftseat structures. The rationale behind the standard is the

In the 70s, 80s, and into the 90s, there was a lot of research money spent on composite materials. It

started with polymeric composites but in the 90s, much of this went to metal-matrix and ceramic-matrix composites. Much of this research was funded by the US, European, and Japanese governments

and was directed towards aerospace applications of composites. By the end of the 90s, much of the

advanced materials government research funding went towards nanomaterials with the private sector

taking on the composite materials research effort. This led to the Boeing 787 and Airbus A350 which have

over 50% of their structure made from advanced composite materials. In the last few years, a resurgence

of interest in traditional composite materials has led to several government supported research initiatives

and consortiums in this area. Much of this interest is in the fields of non-aerospace composites which

dominated the research funding in the 70s, 80s, and 90s. A review of some of the higher profile initiatives

and consortiums is outlined here.

"...a resurgence of interest in traditional compositematerials has led to several government supported

research initiatives and consortiums..."

Dr. Robert N. YanceyVP Aerospace and Composites, Altair Engineering


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recent interest in the use of composite structures for 9-gstatic and 16-g dynamic aircraft seat applications.

Historically the design, fabrication, inspection andmaintenance of aircraft seats has centered on the use ofmetallic structures. The use of composites materialsrequires additional guidance and information to maintainthe current level of aircraft seat safety and performance.This effort is tightly coupled with efforts on theCommittee to move to a certification by analysis standardfor aircraft seats.

For Aerospace and Marine applications, the US Office ofNaval Research (ONR) established the CompositesManufacturing Technology Center (CMTC) of Excellenceas one of nine Centers of Excellence supporting NavyManufacturing Technology. The CMTC develops improved

manufacturing processes for composites and advancedmaterials and facilitates technology transfer for theresolution of manufacturing and repair issues identifiedand prioritized by the Navy's Program Executive Offices(PEO's), other Department of Defense (DoD) services andindustry.

"...many companies have

launched significant research

efforts to evaluate increased

use of carbon composites..."

In Europe, there are also several composite initiativesnewly established. In the UK, the National CompositesCentre (NCC) is one of several Catapult Centers focusedon Manufacturing Technologies. The Centre, led by theUniversity of Bristol, includes several companiesincluding Airbus, Rolls Royce, Agusta Westland, GEAviation, GKN, and Cytec. The NCC brings togethercompanies and academics to develop new technologiesfor the design and rapid manufacture of high-quality

composite products. The combination of academic andbusiness strengths will speed progress from laboratoryto design to factory and into products.

In Germany, the Technical University of Munich (TUM)established the Institute for Carbon Composites in 2009.The Institute is sponsored by the SGL Group and iscomposed of an interdisciplinary team that can go fromraw materials through implementation of manufacturingtechnologies to complete composite components. A keyarea of expertise of the Institute is simulation methods

that have been developed to virtually model the completecomposite manufacturing process. TUM has also

partnered with Singapore Polytechnic and ST Kinetics toextend their research and efforts to Southeast Asia.

Recently, MAI Carbon Cluster Management GmbH wasestablished to research methods to dramaticallydecrease the cost of carbon fiber. The $100 millionresearch project is backed by Germanys federalgovernment and more than 70 businesses and researchinstitutes with major involvement from BMW and Audi forautomotive applications. BMW is aggressively lookingbeyond the carbon fiber rich i3 and i8 models to includecarbon fiber in other BMW models.

In Japan, Mitsui & Co. of Tokyo will work with the

Innovative Composite Materials Research andDevelopment Center of the Kanazawa Institute ofTechnology (KIT) on experimental research for newproduction methods for the fabrication of automotiveparts and other industrial products using carbon fibercomposite materials. This center is supported by theJapanese Ministry of Economy as well as the JapaneseAutomotive Industry.

In addition to these federal government initiatives, manycompanies have launched significant research efforts toevaluate increased use of carbon composites and developthe simulation and manufacturing technologies to easethe transition from metals to composites. This includespartnerships between Ford and Dow, BMW and SGL,General Motors and Teijin, Toyota, Toray, and FHI, andothers. These partnerships between carbon fibersuppliers and automotive OEMs benefit both industriesby increasing the applications of carbon fiber and henceincreasing the demand while reducing vehicle weight toreduce the fuel emissions for the automotive industry.Also, BMW and Boeing have partnered to workcollaboratively on design and analysis methods forcomposite structures taking the best of the aerospaceand automotive industries to advance the state of the art.

Overall, it is an exciting time to be involved in the

composites industry. With now a firm footing in thecommercial aviation, sporting goods, and marineindustries and growing applications in the automotive,energy, and building industries, the composites industryis poised to accelerate its growth. A key to this growthwill be modeling and simulation methods for compositesthat are robust, proven, and accessible to the design andanalysis community. NAFEMS will play a critical role inestablishing the modeling methods, practices, andprotocols for composite materials and structures.


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Composite Process

Simulation Digitally Reinforcing High-RateComposite Manufacture

Dr. Peter Giddings CEng MIMechEResearch Engineer, Manufacturing Process Simulation, National Composites Centre UK

Miroslav Stojkovic MSc CEng MRaesEngineering Capability Manager, Design Stress and Simulation, National Composites Centre UK

Fibre reinforced polymer composites have been amainstay of research and development in aerospaceand motorsport industries for decades. With mass

reduction and increased structural efficiency becoming akey priority in the transport, renewable energy, marine andconstruction sectors, the composites industry faces newchallenges to meet the growing demand and cutcomponent costs.

Developing highly repeatable automated production linesis critical for composite manufacturing industries to makethe transition from low volume business models to thehigh volume cost-efficient manufacturing these newmarkets demands.

The National Composites Centre UK (www.nccuk.com) is

the UK hub for composites manufacturing industry andprovides a focal point for research and development intoautomated composite processing. The Bristol-basedcentre houses a multidisciplinary team of over 140 staffwho are successfully supporting industrial partners inunderstanding and solving a range of issues facingcomposite manufacturers.

As part of the NCC technology development,manufacturing process simulation plays a key role indeveloping insight and guiding the development ofcomposites manufacturing processes to accelerateinnovation and reduce the cost and risk associated withprocess development. Among the wide ranging research

into automated manufacturing, automated fibreplacement, resin infusion and induction weldingof thermoplastics stand out as examples wherechallenging simulations have provided realbenefit to NCC members.

Automated fibre placement (AFP)

Automated fibre placement (AFP) is used in themanufacture of high-value composite components,where precision and repeatability of fibre placement arekey to the performance of safety-critical components.

Tapes of composite material, between 6.35mm and25.4mm wide, are compacted onto a tool using acompliant polymer roller mounted to a roboticpositioner. Most AFP systems also heat the incomingmaterial via laser, infra-red light or Xenon Flash-lamp(a system manufactured by Heraeus NobleLight anddeveloped in collaboration with the NCC) to achieve theideal processing conditions.

AFP is a key technology at the NCC, with livedevelopment programs for thermoset composites (suchas carbon/epoxy), dry fibre materials as well asthermoplastic matrix composites already yieldingindustrial benefits.

Simulating the AFP process presents many challenges,with large gradients in both pressure and thermal fieldsaround the rapidly moving roller. However, byaddressing specific manufacturing issues, the NCCsimulation engineers are providing real benefits on theshop floor.

Recently, the NCC has developed efficient methods for

predicting the maximum achievable course width (thenumber of tapes deposited in a single pass)and alsohow changes in applied heating power influence the as-deposited material state.

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The method developed to predict maximum course widthprovides clear programming rules for manufacturingengineers that ensure material will receive sufficientcompaction pressure. This critical information isextracted from local quasi-static finite elementsimulation describing the compaction of a roller onto atool surface at critical locations (simulated boundary ofpositive contact pressure shown as green ellipse in Fig. 2.Built-in modelling options describing materials

behaviour, geometric non-linearity and sliding contactwithin Abaqus Standard (provided by NCC memberDassault Systmes) efficiently capture the complexphysical behaviour. By taking component geometry, fibreorientation and experimentally measured load-deflectionresponse of the roller [1] as inputs, these models returnmaximum course width within around 90 minutes foreach desired fibre orientation and feature on the tool.For a complex component, just 2.5 days of simulationeffort is required to generate design rules to guideprocess specification and ensure good manufacturability.These rules reduce operator uncertainty and variability inprogramming while saving days or weeks of costly on-machine trials.

The prediction of as-deposited material state has begunby tackling AFP manufacturing using thermoplasticcomposites as part of the Core Research Program.

Dr. Peter Giddings, simulation engineer responsible forthat effort explains Our objective was to quantify how wecould manipulate heater power to maximise quality of thedeposited material by predicting material stateparameters like degree of bonding between layers orpercentage of voids.

The underpinning simulation method is an in-house finitedifference code, written in MatLab, that predicts heat

diffusion within the deposited material as the thermaland pressure boundary conditions imposed by the rollermove across a component. To enhance predictions fortemperature and material state distributions, the codeupdates key material properties that influence thermaldiffusion [2,3], for example density, during each solutionincrement.

Today these coupled thermo-chemical simulations arehelping to define process windows for high quality carbonfibre/PEEK composites for aerospace structures. As thecapability is extended to cover the full range of materialsand heat sources used in AFP it will help morecustomers, these simulations can offer guidance oneffective machine settings and usable design rules forAFP manufacturing to help broaden the viability ofautomated fibre placement and minimisecommissioning risk says Dr. Giddings.

Figure 1: The NCC has two Coriolis Composites AFP machines (pictured with GKN composite winglet) and anadditional Accudyne machine with choice of laser, infrared and patented Xenon FlashLamp heat sources.

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Resin flowMany composite components begin as preforms of dry

reinforcing fibres before being impregnated with anuncured liquid resin and heated to cure the resin. Forcomponents requiring excellent surface finish andincreased mechanical performance, that impregnationoccurs in a closed metallic tool in a process called resintransfer moulding (RTM). Prediction of how the resinflows through the preform to fill the mould, whether anyareas will fail to be completely impregnated and theoptimisation of injection location and pressure are allchallenges that the NCC is working toward resolving.Over the past two years NCC core research hasdeveloped effective RTM simulation approaches as Dr.Christian Lira explains: today, if a customer comes to uswith a problem in their infusion, even if it is thick orhighly curved, we can help. Tooling design, where youinject the resin and how you adjust the pressure can allbe included to guide them to a solution.

These successes have been achieved using ESIssoftware PAM-RTM which Dr. Lira says provides a finiteelement solution to Darcys flow equation (flow throughporous media) and allows us to make useful simulationswithin industrial timescales. With infusion, the processhas inherent variability, small but unavoidable changes inmaterial permeability cause big changes in flow rate soany simulation is indicative, not perfectly predictive[4].However, the simulations are still extremely valuable for

comparing the effects of various parameter changes onprocess outcomes.

The understanding of material and process variationbuilt up at the NCC has made it clear that flowsimulations cannot predict the exact dimensions of adefect but do indicate whether defects may occurand their likely locations . Within these limits, Dr.Liras infusion simulations are already guidingengineers through more efficient test plans andhave made simulation-led process design fortraditional RTM a reality at the NCC.

To meet the tight timescales demanded by high volumeautomotive customers and produce cured composite

parts in less than 5 minutes, resin infusion technology ismoving to higher injection pressures and faster curingresins. High pressure RTM (HP-RTM) injects resin into apreform at pressures of up to 140 bar to fill moulds inseconds before the fast curing resin systems begin toharden. The speed and violence of the HP-RTM processmeans that the understanding of infusion simulation,built up in traditional RTM development, is no longerenough to effectively guide manufacture.

The challenges posed require new approaches as Dr. Liradescribes we have to update material permeability andfluid viscosity during the simulations as resin pressuredeforms the fibres and fast reacting resins begin to cure

during injection. Were working with software providers tohelp extend RTM simulation techniques to deal withthese effects, but the effects of small quantities ofpolymeric compounds applied to the dry fibres to holdperforms together, known as binders, is not so simple.The methods for capturing the influence of binders withinHP-RTM are not well understood even within thescientific community and so arriving at a predictive

Figure 2: Simulation of critical features in AFP layup to determine maximum course width showing manufacturingchallenge and an example FE contact patch output with extraction of maximum course width

Figure 3: Prediction of resin infusion througha carbon fibre preform of a vehicle wheel

using ESI's PAM-RTM software


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simulation of HP-RTM requires a longer-termcommitment to develop and refine the simulationcapability. That commitment has already begun as theNCC works with academics, software vendors andmanufacturers around the world to bring insightfulsimulation of HP-RTM towards industrial

implementation.

These efforts are made possible by the installation of aSchuler 36-Kilotonne press in December 2014 at theBristol site to explore the infusion of large compositecomponents via HP-RTM. The unique combination ofopen-access industrial scale equipment together withon-site laboratory mean that the novel simulationsnecessary to support rapid development of HP-RTMprocesses can be grounded in high qualityexperimentation. That industrial scale validation iscritical to understand how machinery and processes willrespond under the extreme conditions that HP-RTMimposes.

Multiphysics simulation of induction weldingTogether with enhanced environmental resistance,recyclability and novel processing routes, one of thebenefits for thermoplastic composites is thatcomponents may be joined structurally by welding twocomponents together. The resulting joints can replacemechanical fasteners to help components retain more ofthe strength of the pristine laminate by eliminatingdrilled holes as well as reducing part count in largecomposite assemblies.

A particular interest at the NCC is induction welding ofcarbon fibre composites. In this emerging compositesprocess, a magnetic field is used to heat the carbonfibres within composite materials through electrical eddycurrents generated by electromagnetic induction withinthe conductive fibres. Through controlled application of

an oscillating magnetic field the heating effect can bemanaged so that the polymer matrix melts in the desiredlocations to permit welding to take place.For simulation engineers at the NCC, capturing theinduction heating effect in layered anisotropic materialshas proven to be a hugely satisfying project. The processsimulation team chose MSC MARC Nonlinear FEAsoftware (supported by MSC Software Ltd, Frimley) tobuild simulations for induction heating of thermoplasticcomposite joints.

The task of improving simulation results to be of use inprocess specification for composite welding requiredcoupling of thermal and electromagnetic models, andcareful specification of material parameters. Theresearch posed challenges to the materials test andtooling manufacture supply chains as well.Materials tests were identified or developed to provideunusual but necessary simulation input data overdescribing properties such as dielectric permeability,among others, for anisotropic composite materials. Oncepreliminary models were validated against literaturedata, more detailed analyses were developed with MARCto design test fixtures and induction coils suitable toexperimentally characterize the induction heatingprocess [5,6].

Figure 4: Europes only open-access 3.4m 2.6m press installed and making parts at the NCC


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The simulation of induction heating is a strong firststep towards developing the predictive tools forinduction welding of composites, and is alreadyhelping tooling suppliers to refine fixture designs thatretain components without impacting the deliveredmagnetic field. The effort expended in building thesecapabilities has allowed the NCC to validate methodsfor predicting heat input within induction heating ofcomposite plates as the centre moves towardssimulation of real industrial welding processes.

ConclusionThe outlook for process simulation in composite

manufacture is incredibly bright. There is vibrantacademic research activity extending our fundamentalunderstanding and coupled with strong growth inindustrial demand for composites. Automationtechnology is becoming established in a broaderrange of industrial applications and simulation toolsfrom ESI, Dassault Systmes, MSC Software andothers offer suitable platforms in which to builduseable and powerful process simulations.

The simulation successes at the NCC are just the tipof the iceberg for composite process simulation; thereare some fascinating challenges and tangiblecommercial opportunities for simulation engineers

within composites. However, real progress is neededin bringing these complex simulations into the supplychain to aid in industrialisation of automatedcomposite manufacture.

The NCC aims to pave the way for the simulationsupply chain to effectively support the compositessector and help demonstrate that the fascinatingmultiphysics problems bring real returns on the shopfloor and also in the finished product.

References[1] Helenon, F. D. H.-J. A. Lukaszewicz, Ivanov,D and Potter,

K. Modelling slit tape deposition during automated fibreplacement. 19th International Conference onComposite Materials (ICCM19), Montreal, Canada, 2013

[2] Cogswell, F. N. Thermoplastic aromatic polymercomposites. 1st Edition, Elsevier Science andTechnology. 1992

[3] Stokes-Griffin, C.M. Compston, P. A combined optical-thermal model for near-infrared laser heating ofthermoplastic composites in an automated fibreplacement process. Composites Part A (In Press) .

[4] Arbter, R. Experimental determination of thepermeability of textiles: A benchmark exercise.Composites: Part A 42: 1157-68, (2011)

[5] Moser, L. Experimental Analysis and Modelling ofSusceptorless Induction Welding of High PerformanceThermoplastic Polymer Composites, PhD Thesis,Institut fur Verbundwerkstoffe (2012 )

[6] Rudolf, R. Mitschang, P. & Neitzel, M. Induction heatingof continuous carbon-fibre-reinforced thermoplastics,Composites: Part A 31: 1191-1202 (2000)

About the NCC: www.nccuk.com

The NCC is a 25m investment supportedby: the Department for Business, Innovationand Skills (12m); the South West RDA(Regional Development Agency) (4m); and9m from the European RegionalDevelopment Fund (ERDF). It is owned andhosted by the University of Bristol. TheGovernment announced a further 28m inthe 2012 Autumn Statement for theexpansion of the NCC. The NCC is a partnerof the High Value Manufacturing Catapult.

Figure 5: Induction welding simulation of lap shear test specimen conductedat the NCC showing specimen dimensions and resulting heated area


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How To Get the Part

Dimensions Right inComposites ProcessingGran Fernlund1,2, Anoush Poursartip1,2, Abdul Arafath2, Corey Lynam21The University of British Columbia2Convergent Manufacturing Technologies

Composite parts will not have the same dimensionsas the tool on which they were processed, becauseof mechanisms such as tool dimensional change

during heat up and residual stress build-up within thepart during cure/solidification and cool-down. This is truefor all composite materials and processes, and only themechanisms differ slightly between different materialsystems and processes. Dimensional change becomes aproblem if the magnitude of change is greater than thedimensional tolerance requirements of the part.

Aerospace structure tolerances can be as tight as +/-0.010 inches from nominal engineering dimensions, andthis can be difficult to achieve without a gooddimensional management strategy. Many compositefabricators are familiar with spring-in or spring-backwhich is the closing of angles due to strain anisotropy[Nelson & Cairns]. However, dimensional management isa bigger systems level problem and many otherparameters also affect final cured part dimensions. Thesystems parameters that affect dimensional change, andany other outcome in a composites process, can be

divided into three broad groups related to part, tooling orprocess [Johnston et al.]. Some of the main drivers are:

Part: Geometry, Material behavior, Lay-up

Tooling: Geometry, Material behaviour

Process: Temperature, Pressure, Time, Heat transfer

Anyone who has baked a cake in their home kitchenknows that how the cake turns out does not only dependon the dough but also the type of pan used, type of oven,

location in the oven, temperature and time in the oven,cool down, and removal from the pan. The same is truefor composites processing it is a systems problemwhere the part, tooling and process all interact todetermine the outcome.

Predicting Dimensional ChangeIf a tool is machined to the nominal engineering

dimensions of the composite part, dimensionalmeasurements on multiple parts made off that tool willgenerally show a mean deviation from nominal and somevariability around the mean. If the total deviation fromnominal is less than the dimensional tolerances,dimensional conformance is achieved and no furtheraction is required. If not, the part, tooling and/or processhave to be modified to achieve dimensional conformance.This can be a costly and time consuming iterativeprocess, as it is difficult to anticipate the effect of systemparameter changes if there is no predictive model.

It is increasingly unacceptable to depend on trial-and-error to achieve dimensional conformance, especially

once the tool is made and full scale parts are produced.Other typical options are experience, expert opinion,tests, or simulation. Experience and expert opinion oftenfall short if the part and process is complex or deviatesfrom the previous experience base. Test data are often oflimited use as final cured dimensions depend on part,tooling and process, which make scaling of results fromsmall test coupons to the full-size part and process oftenmisleading and thus risky. The most effective option,particularly for large and complex structures, is


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simulation where a physics-based model is generated.This model links system parameters such as part, toolingand process to the relevant process outcomes in thisinstance dimensional change.

Physics-Based Process Models

To accurately predict dimensional change, a physics-based process model must include a high fidelitydescription of the part, including geometry, lay-up and adetailed description of the curing material behavior asthe composite material properties evolve during thecure/consolidation cycle. Also needed is a gooddescription of the tooling, which includes geometry andthermo-physical material properties. Finally, the modelneeds to capture the process: temperature and pressureapplication over time, and heat transfer to the part andtool [Fernlund et al.]. This type of multi-physics processmodel is internally fairly complex but nowadays can berelatively easy to set up and run if the right solutionpackage is selected. Without suggesting that this is anexhaustive list, and looking beyond general capabilitiesavailable in general purpose codes with user definedcapabilities, there is some embedded capability withinMSC.Marc and ANSYS, as well varying levels of morefocused capability within ESI PAM-DISTORTION, LUSASHPM, and Convergents RAVEN and COMPRO.

In terms of modelling details, the first step is to solve thethermochemical problem: this consists of a transient

thermal analysis of the part on the tool with typicallyconvective heat transfer boundary conditions; a criticalfeature is to have an accurate representation of the heatgeneration due to the cure reaction of the matrix in thecomposite part, as well as property evolution as afunction of both temperature and degree of cure. Moresophisticated analyses may include a flow and

compaction modelling stage, but the next necessary stepis to model the development of residual stress due to thecumulative mismatch in free strains throughout the partand tool, where the part is viscoelastic in nature; notethat prior to gelation (the beginnings of a 3-D network inthe polymer matrix allowing for residual stress todevelop) the matrix has no memory and no ability todevelop residual stress. As the matrix vitrifies, itbecomes increasingly able to develop residual stress, andthus the effects of cure shrinkage towards the end of theprocessing cycle and thermal cool-down effects becomecritical. The constitutive representation of the material,the complexity of the solution, the ability to characterizeand calibrate the model, and the efficiency of the solution

become key issues in getting meaningful answers. Thecurrent state of the art is that it is possible to accuratelyand efficiently solve for a wide range of importantindustrial processes, and improvements in capability areaccelerating as demand grows rapidly.

Figure 1A shows an example of a finite element model ofa part on a tool subject to a cure cycle that was quicklydeveloped from existing CAD information using DassaultSystemes CATIA and ABAQUS design and simulation

Figure 1. A) Finite element mesh of part and tool; B) Calculated temperature profile during heat-up and cure;C) Calculated dimensional change.


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software together with Convergents COMPRO processsimulation software. Figure 1B shows the predictedtemperature gradient during heat-up and Figure 1C, thecalculated dimensional change.

Managing Dimensional Change

Once a process model is created for the part, tool andprocess of interest, it can be used both for predicting theexpected mean dimensional change as shown in Figure1C but also to identify the systems parameters that drivevariability in the process. The most effective way toaddress the mean dimensional change of the part isoften by geometric compensation of the tool surface as itcan be done without changing laminate or processparameters. Using the COMPRO CATIA ABAQUSsolution set, geometric compensation of the tool can bedone automatically by transferring the calculateddimensional change back to the CATIA designenvironment and morphing the tool surface so thatdimensional conformance is achieved. Altering the lay-upsequence and/or modifying the cure cycle are alternativeoptions that can be developed and evaluated in the samesimulation environment.

Once the system parameters have been adjusted to give amean dimensional outcome that matches the nominalengineering dimensions, the model can be used toidentify and set bounds on the allowed variability ofsystems parameters such that the dimensional variabilityof the part is within dimensional tolerances.

ClosingThe composites process simulation technology andmethodology presented here is currently increasingly androutinely used by the large aerospace OEMs. It is clear wehave reached the tipping point of convergence withpowerful and effective process simulation tools andcheap and fast computational power. Increasingly,

composites processing should no longer be treated as anart and should leave the domain of empiricism.Processing can be approached with the same analyticalmindset and design and simulation tool sets as any otheraspect of engineering. This is critical for us to succeed indesigning and building large complex compositestructures that can compete with metal structures. Theera of simulation supported, knowledge-basedcomposites manufacturing is here, and there is noturning back if we want to remain competitive.

References

Nelson, R. H., & Cairns, D. S. (1989). Prediction of dimensional changes incomposite laminates during cure. Tomorrow's Materials: Today., 34, 2397-2410.

Johnston, A., Vaziri, R., & Poursartip, A. (2001). A plane strain model forprocess-induced deformation of laminated composite structures. Journalof composite materials, 35(16), 1435-1469.

Fernlund, G., Floyd, A., Shewfelt, M., & Hudek, M. (2007, September).Process analysis and tool compensation for a complex composite panel.In Proceedings of the 22nd American society for composites technicalconference (ASC), Seattle, Washington, USA.


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Residual Stress

Calculation FollowingA Repair ProcessSderlund Harald, Shailesh Chillal,Asha Koshy & Sushovan Roychowdhury

GKN Aerospace


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Influence of Residual Stresson The Life of a Bolted

Flange Subjected to Repair

from a Manufacturing Defect


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Aero engine structural components such ascasings are usually made as cast or fabricatedpieces and welded together before the finalassembly. Deviations during the machiningoperations or mishandling during its

manufacturing stages could cause damage to thestructure resulting in permanent deformations such asbends or dents. Such deviations on any part, in an

aerospace industry caused during the manufacturingprocess, are commonly termed as Non-conformances(NC).

Due to cost implications, considerable effort is spent torepair such deviations, instead of completely rejecting thepart. However to accept the part, it is quintessential toanalyze and understand the impact of the repair processon the components structural integrity both in terms ofstrength and life requirement fulfillments. A carefullydesigned simulation process can quantify this impactmore accurately. An understanding of how the repairprocess is carried out is essential to estimate thedeformation and residual stresses that could arise due to

the repair.

A Case Study The problemThis paper features a case study on residual stresscomputation and its impact on life evaluation of an aeroengine casing flange subjected to repair after themanufacturing process. The approach is based on FEanalysis using ANSYS as software to simulate the repairprocess in order to determine the residual stresses in thestructure after the repair.

An incident during handling of the component caused atool to impact the flange, causing bending of certain

parts of the flange as shown in Figure 1. The flange isassembled with the adjacent components through boltedjoints. The bending of the flange needs to be straightened

out following standard repair process for properassembly with the adjacent structure and also to preventleakage during operation. The repair is carried out byheating the component locally and cooling it down toroom temperature before assembly. The process ofstraightening during repair induces plastic deformationand residual stresses on the flange. The challenge lies insimulating these processes in a manner that allows arealistic computation of the induced stresses. Theresidual stresses induced after repair is then combinedwith other operational loads to compute the life of the

component.

FE Modeling ApproachThe typical FE model considered in the analysis is shownin Figure 2. The model includes part of two flanges, bolts

and nuts all modeled using 3D solid elements(SOLID186) in ANSYS. Standard frictional contact is usedat the interfaces of bolt-to-flange, flange-to-flange andnut-to-flange regions. Bolt preload is simulated throughpretension elements. Regions around the bolt holes and

the flange fillets are considered the most critical lifelimiting locations in this assembly. This assembly modelis used to simulate both the repair process and the flightmission. By doing so, it is easier to superpose theaddition of residual stresses to the stresses generatedfrom operational loads for life computation at each node.

Simulation of RepairThe FE model shown in Figure 2 corresponds to the finaldesign configuration. In order to simulate the repairprocess, the affected flange has to be first deformed tothe NC configuration. This is achieved first by separatingout the flange component from the assembly by

numerically reducing the stiffness of the adjacentcomponents. The stiffness of components other than theaffected flange is made near zero using ANSYS EKILLcommand. This helps in maintaining the element andnode numbering sequence in the model same throughoutthe analysis and enables superposition of stresses atlater stages.

The overall process to numerically compute the residualstress involves six major steps as shown schematically inFigure 3. The steps 1 and 2 are carried out to obtain theNC configuration before the repair process and steps 3through 6 simulate the repair process. During these sixsteps, only the affected flange is

considered from the whole assembly.Nonlinear material model usingkinematic hardening (option KINH inANSYS) is used during all the steps.This accounts for material behaviorunder the reversed loads. Geometricnonlinearity is included in the

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The challenge lies in simulating these

processes in a manner that allows a realisticcomputation of the induced stresses

Figure 1: Bent Flange configuration


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analysis by using the large deformation option. Thedifferent processes involved in each steps are brieflydescribed next.

In Step 1, the critical NC region is identified on the flange.This is a loading condition where the nodal forces areapplied in the identified NC region and the analysis iscarried out to initiate flange deformation. The

deformation of the actual bent hardware is measured anda scale factor based on the displaced configuration isused as a basis for initial load application in Step 1.

Step 2 is an unloading part, wherein the applied forcesfrom Step 1 are removed. The deformed configuration atthe end of Step 2 should represent the NC configurationboth in shape and magnitude of deformation. Since allthe analyses are non-linear in nature, Steps 1 and 2requires an iterative process to set the magnitude ofinitial force field, in order to match the flange bending atthe end of second step with that of the actual hardware.At the end of second step, the deformation at all the

nodes of the flange surfaces are measured and

stored in an array. Figure 4 showsthe match

between theanalysis andmeasured datafrom actualhardware.

Once the NC configuration is achieved in Step 2, theanalysis is continued in Step 3 by locally subjecting thecomponent to an elevated temperature. This is becausesuch repair processes are normally associated with localheating.

In Step 4, the repair process is initiated by applying ascaled value of unit force to the NC region of the flange.

The force scaling is done using the flange deformationpattern obtained at Step 2. The stored flange nodaldeformation is used to scale this unit force and the forceis applied in the opposite direction to simulate the repairprocess.In Step 5 the external force is removed. Note that in steps3-5, the component is exposed to local heating.

In Step 6 the flange is brought to room temperature. Thedeformations obtained from Step 6 are compared withthe actual repaired hardware to fine tune the scalingfactor to be used in Step 4. Here again an iterativeprocess is used to get an appropriate scale factor in Step4 that would result in a fairly good match of the surface

profile at the end of Step 6 with that of the repairedflange. Figure 5 compares the final flange surface profileobtained from simulation with that of the actual hardwareafter the repair process.

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Figure 2: Bolted Joint Assembly

Figure 3: Schematic representation of the FE simulation of repair process


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Simulation of ResultsAt the end of Step 6, the stresses resulting in the flangeconfiguration is considered to be the residual stressgenerated due to the repair process. It is observed thatthe residual stress is not uniform in the flange afterrepairing the flange nonconformance. In the conventionalprocess used in the current industry, a uniform orconstant residual stress is added all across thecomponent for life computation. This value is normally

obtained from past residual stress measurement data orby experience. From the present analysis it was observedthat the flange regions are subjected to varying residualstress as shown in Figure 6. The normalized stressdistribution for one of the critical mission loads is shownin Figure 7.

A sensitivity study was further performed to evaluate thevariation in residual stress with final surface profile

achieved. It was found to be less sensitive in variation offinal surface profile. A variation of 2 mm in the finalsurface profile resulted in stress varying up to 2.5%.Additionally a variation of residual stress up to 30% hadvery little impact on LCF life as shown in Figure 8.

In order to compute life, a linear superposition of residualstress from repair simulation over the elastic stressesobtained from mission loads is considered. The linear

superposition is valid only when the residual stresses arebelow yield with very little or no plastic strain. Thesestresses should also be much less compared withmission stresses. The six component stresses fromrepair simulation were added to those from each loadcase of the elastic mission stresses. The life is computedusing the neuber corrected stresses for the completemission loads.

Figure 4: Flange deformation comparison between actual hardware and simulation

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Figure 5: Flange surface profile comparison between actual hardware and simulation

A sensitivity study was performed toevaluate the variation in residual stress


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ConclusionsFigure 9 shows the variation of life at bolt hole and flange fillet

using the conventional approach and the current approach. Thecurrent approach is a more realistic way to compute the residualstresses as compared to using a constant stress value. Using aconstant value across all the region could result in over or underestimating the residual stresses and hence impacting thecomputed life numbers.

Based on the observations of the current study, it is recommendedto perform FE simulation of repair process to compute thedistributed residual stress more accurately and use it forestimation of component fatigue life. This would make the NCevaluation process more robust and helps in making a realistic

justification on whether the part can be accepted or rejected afterrepair.

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Figure 6: Residual stress distribution on the flange after the repair simulation (section view)

Figure 7: Flange stresses from the most critical mission load (section view)

Figure 8: Variation of residual stress and LCF lifeComputation of Life

Figure 9: LCF life comparison using conventional &current approach

an FE simulation of the repairprocess is recommended tocompute the distributed residualstress more accurately


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Dynamic Simulation of

Flight Test Manoeuvreson the Diamond D-Jet

The numerical simulation of the complex fluid-structure interactiontaking place when manoeuvring an aircraft remains a challenge. A

realistic analysis of the airplane manoeuvrability often involves thepresence of moving parts, such as the deflection of the elevators,the ailerons, or the elevons. For conventional Computational FluidDynamics (CFD) codes, dealing with such moving geometries is achallenging task. The following work uses a software based on thelattice-Boltzmann method (LBM) to overcome these issues.

This article, which won the Best Presented Paper award at the2013 NAFEMS World Congress, presents a numerical study on thedynamic simulation of flight test manoeuvres on the Diamond D-JET, using the XFlow virtual wind tunnel. The pitch capture

manoeuvre is first simulated, studying the pitch oscillation responseof the aircraft. Dutch roll flight mode is then numericallyreproduced. Finally, the D-JET angle of attack is evaluated in thepost-stall regime under controlled movements of the elevator.


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Luc Van Bavel (Diamond Aircraft Industries, Canada);David M. Holman, Ruddy Brionnaud,Mari a Garci a-Camprubi (Next Limit Technologies, Spain)


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In literature, some CFD works on flight simulationconsist of generating a tabular database of fundamentalaerodynamic parameters, which are later used either tocalculate static and dynamic stability derivatives, or aslookup tables by Six-Degree-of-Freedom simulations(e.g. Ghoreyshi et al. 2010, Lemon, K.A., 2011). Theapplication of this classical two-step approach is limitedsince the aerodynamic forces and moments of an aircraft

with high angle of attack and large amplitudemanoeuvres, responding to sudden changes of the flow,depend on the time history of the motion. For instance,this approach fails particularly when post-stall motionsor propeller slipstreams are considered.

More comprehensive CFD works on the simulation ofdynamic manoeuvres consider the flow equations ondynamic meshes, e.g. Farhat et al. 2001. For conventionalCFD codes, i.e. Eulerian approach, the handling ofdynamic meshes requires a time-consuming remeshingprocess at each time step that often leads to numericalerrors and convergence issues; thus being a challengeeven for simplified geometries (e.g. Shishkin & Wagner,

2010; Johnson, 2006).

A relatively new method which has been investigated thelast decades seems to offer new capabilities to overcomethese limitations: the lattice Boltzmann method (LBM).The LBM is a mesoscopic particle-based approach toCFD and circumvents those moving-mesh issues, whileits refinement algorithms allow the spatial discretizationto be dynamically adjusted during the simulation,according to the wake structure.The CFD software XFlow has been employed for thisstudy, since it is based on the LBM and allows movinggeometries. The ability of XFlow to conduct rigid bodysimulations concurrently with CFD analysis includingfully turbulent airflow cases has been investigated aspart of the ongoing research and development studies forthe design of future aircraft at Diamond AircraftIndustries.

The Diamond D-JET, shown in Figure 1, is a five-seatsingle engine jet currently undergoing flight testing inCanada. Its cruise speed is 315 knots (580 km/hr) and itis powered by the Williams FJ33-4A-19 turbofan engine. Asophisticated data acquisition system records hundredsof air data and systems parameters at high frequency. Inaddition to flight testing, the D-JET has also undergone

wind tunnel testing at the University of WashingtonAeronautical Laboratory (UWAL) in the US and at theLarge Amplitude Multi-Purpose (LAMP) wind tunnel inGermany.

Numerical ApproachIn the literature there are several particle-based

numerical approaches to solve the computational fluiddynamics. They can be classified in three maincategories: algorithms modelling the behaviour of thefluid at microscopic scale (e.g. Direct SimulationMontecarlo); algorithms which solve the equations at amacroscopic level, such as Smoothed ParticleHydrodynamics (SPH) or Vortex Particle Method (VPM);and finally, methods based on a mesoscopic framework,such as the Lattice Gas Automata (LGA) and LatticeBoltzmann Method (LBM).

The algorithms that work at molecular level have alimited application, and they are used mainly intheoretical analysis. The methods that solve macroscopic

continuum equations are employed most frequently, butthey also present several problems. SPH-like schemesare computationally expensive and in their lesssophisticated implementations show lack of consistencyand have problems imposing accurate boundaryconditions. VPM schemes have also a high computationalcost and besides, they require additional solvers (e.g.schemes based on boundary element method) to solvethe pressure field, since they only model the rotationalpart of the flow.

Finally, LGA (Hardy et al. 1973) and LBM schemes havebeen intensively studied in the last years being theiraffinity to the computational calculation their mainadvantage. Their main disadvantage is the complexity toanalyse theoretically the emergent behaviour of thesystem from the laws imposed at mesoscopic scale.

Lattice Boltzmann methodWhile the LGA schemes use Boolean logic to representthe occupation stage, the LBM method makes use ofstatistical distribution functions fi with real variables,preserving by construction the conservation of mass andlinear momentum.

Figure 1: Diamond D-JET


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The Boltzmann transport equation is defined as follows:

(4)

where fi is the particle distribution function in thedirection i, ei the corresponding discrete velocity and ithe collision operator.

The stream-and-collide scheme of the LBM can beinterpreted as a discrete approximation of thecontinuous Boltzmann equation. The streaming orpropagation step models the advection of the particledistribution functions along discrete directions, whilemost of the physical phenomena are modelled by thecollision operator which also has a strong impact on thenumerical stability of the scheme.

Two common formulation of collision operator exist: thesingle-relaxation time (SRT) and the multiple-relaxationtime (MRT). The single-relaxation time approach, .e.g.the Bhatnagar-Gross-Krook (BGK) approximation (Qianet al. 1992), is commonly used because of its simplicity.Some of the SRT limitations are addressed withmultiple-relaxation-time (MRT) collision operatorswhere the collision process is carried out in momentspace instead of the usual velocity space

(8)

where the collision matrix S ij is diagonal, meqi is theequilibrium value of the moment mi and Mij is thetransformation matrix (Shan & Chen, 2007; d'Humie res,2002).

The collision operator in XFlow is based on a multiple-relaxation time scheme. However, as opposed to

standard MRT, the scattering operator is implemented incentral moment space. The relaxation process isperformed in a moving reference frame by shifting thediscrete particle velocities with the local macroscopicvelocity, naturally improving the Galilean invariance andthe numerical stability for a given velocity set (Premnath

& Banerjee, 2011).

Raw moments can be defined as

(9)

and the central moments as

By means of the Chapman-Enskog expansion theresulting scheme can be shown to reproduce thehydrodynamic regime for low Mach numbers (Ran & Xu,2008; Qian et al. 1992; Higuera & Jime nez, 1989).

Turbulence ModellingThe approach used for turbulence modelling is the LargeEddy Simulation (LES). This scheme introduces anadditional viscosity, called turbulent eddy viscosity t, inorder to model the sub-grid turbulence. The LESscheme used is the Wall-Adapting Local Eddy viscositymodel, which provides a consistent local eddy-viscosity

and near wall behaviour (Ducros et al. 1998).

A generalized law of the wall that takes into account forthe effect of adverse and favorable pressure gradients isused to model the boundary layer (Shih et al. 1999). Theinterpolating functions f1 and f2 given by Shih et al. aredepicted in Figure 2.

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The algorithms that work at molecular level have alimited application, and they are used mainly intheoretical analysis.

(10)

Figure 2: Unified Laws of the Wall


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Treatment of Moving GeometriesThe treatment of moving boundary conditions isstraightforward and similar to the handling offixed boundaries. In basic LBM implementationsthe wall boundary conditions for straightboundaries are typically implemented following asimple bounce-back rule for the no-slip boundarycondition and a bounce-forward rule for the free-

slip. In XFlow the statistical distribution functionsfi coming from the boundaries are reconstructedtaking into account the wall distance, the velocityand the surface properties. The set of statisticaldistribution functions to be reconstructed isrecomputed each time-step based on the updatedposition of the moving boundaries. A referencedistance to the wall, velocity, surface orientationand curvatures are taken into account in order tosolve the wall boundary condition.

Simulations SetupThe simulation of tests points by XFlow has beenconducted in the virtual wind tunnel featured bythe software, designed for external aerodynamicssimulations. The size of the wind tunnel is set to40x30x20 m and periodic boundary conditions areapplied at the top and bottom boundaries, as wellas at the lateral boundaries.

The required inputs to run the simulation are:

D-JET model geometry (actual loft) withflow through inlet

D-JET mass, centre of gravity and fullinertia tensor at the test point time

Test point airspeed, air density,temperature and dynamic viscosity

Flight controls deflections correspondingto the test point, slightly reduced by afactor determined from static wind tunneldata validation where applicable.

The model is placed at the initial angular positionscorresponding to the test point being evaluated,and its behaviour set to rigid body dynamics withthe relevant Degrees Of Freedom (DOF). Once thesimulation starts, no further input from flight testdata is used by XFlow. The average setup time for

these simulations in XFlow is approximately 15min.

The rigid body dynamics simulation settings wereusually as follow: 0.5m resolved scale, 0.125mwake resolution and 0.0625m target resolvedscale.

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Dutch roll frequency and damping must meet

specific requirements for acceptable flighthandling characteristics.

Figure 3: Pitch Capture Simulation

Figure 4: Dutch roll simulation

Flight Test ManoeuvresThis section presents the XFlow numerical results for the Diamond D-JET performing three types of flight test manoeuvres, namely: (i) pitchcapture; (ii) Dutch roll; and (iii) stall. The performance of the CFD toolis evaluated by comparing its results with flight test data for thecorresponding manoeuvres. Additionally, the ability of XFlow tosimulate other kind of manoeuvres is illustrated with the D-JETspinning.

Pitch CaptureThis maneuver involves flight at a predetermined speed in trimmedconditions, aggressively pitching up five degrees for one or two secondswithout re- trimming, then return to the trimmed condition with flight


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controls fixed. The pitch oscillation frequency anddamping are resulting parameters used to qualify flighthandling qualities.Pitch capture is simulated with one degree of freedom inpitch, starting at the flight test out of trim pitch angle at0.7 seconds. The elevator deflection is fixed to thetrimmed condition as in flight test.

Figure 3 shows the pitch evolution of the D-JET for the

given test conditions, where XFlow results arerepresented in orange and flight test data in black. As itis shown in the figure, numerical results yield a similarpitch response curve, although at higher frequency andlower damping than the experimental one.

Dutch RollDutch roll is initiated in level flight with a rudder input toexcite the Dutch roll motion, after which the flightcontrols are held fixed. The resulting yaw causes theaircraft to roll due to the dihedral effect, and subsequentoscillations in roll and pitch are analysed for frequencyand damping. As with pitch capture, Dutch roll frequency

and damping must meet specific requirements foracceptable flight handling characteristics.

Dutch roll is simulated by XFlow with three degrees offreedom: pitch, roll, and yaw. The elevator is set fortrimmed conditions at 100 KIAS and 20500 ft. Thesimulation starts when the rudder is centred (7.6seconds).

Figure 4 shows both the experimental and numericalresults of this test. The agreement between simulationand flight test data is good, with a Dutch roll frequencyonly 9% above flight test. Damping is a match for thefirst oscillations. Similar results are obtained at higher

speeds (up to 200 KIAS) with a slightly higheroverestimate of the frequency, but still within 15%.Simulations at coarser resolution have shown lowerdamping. In this simulation, the resolution of XFlowwould need to be increased to improve the dampingmatch with flight test data for oscillations below 2degrees.

Spiral stability causes the bank angle to slowly divergeduring the Dutch Roll manoeuvre. To facilitatecomparison of the curves, this long period parameterhas been removed from flight test and XFlow bankangles shown in Figure 4.

This 13 seconds simulation was computed in 32 hourson a Dell Precision 7400 with dual quad-core E5440 Xeonprocessors.

The Dutch roll manoeuvre is illustrated in Figure 5,where the position of the D-JET is captured in threedifferent moments of the test. The images highlight theroll motion of the aircraft.

StallThe test point simulated here involves stall and post-

stall behaviour at angle of attack approaching 30degrees. When the angle of attack goes beyond 25degrees, the pilot pushes the nose down as thisrepresents a flight test limit. The aircraft is in a cleanconfiguration (flaps and gear are retracted).

This simulation focuses on the evolution of the angle ofattack in the post-stall regime, and the effectiveness ofthe elevator in bringing the nose of the aircraft down.Elevator deflection and airspeed are simulation inputs,the values of which are shown in Figure 6. The Angle ofAttack (AOA) is the simulation output and it is shown inFigure 7.

From Figure 7 it can be stated that XFlow reasonablypredicts the elevator effectiveness while the aircraft isfully stalled, though it underestimates the maximumangle of attack by 4 degrees. The simulation may beimproved when feedback controls will be included inXFlow, and allow the elevator to be scheduled tomaintain altitude up to the stall. This way, the Z axis canbe added as an additional degree of freedom foradditional realism.

Figures 8 and 9 show some images of the numericalstall test. The one shown in Figure 9 corresponds to themoment at which the D-JET reaches the maximumangle of attack; it can be observed how the horizontal

tail is fully submerged in the turbulent wing wake.

SpinFlight test data for the spin test of the D-JET is notavailable. Nonetheless, spin simulations have beenconducted with D-Six, a Bihrle Applied Research 6- DOFsimulation software. The D-Six simulation uses dynamicstability data obtained on a D-JET model at the BihrleLarge-Amplitude-Multi-Purpose Wind Tunnel.

When setting up XFlow with mass properties and pro-spin flight controls deflections identical to the D-Sixsimulation, it was found that XFlow reached the samestabilized angle of attack of 47 degrees but the

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Figure 3: Pitch Capture Simulation


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Figure 6: Stall Simulation Inputs: Elevator Deflection and Airspeed

Figure 7: Stall Simulation Output: Angle Of Attack

Figure 8: Stall Manoeuvre


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yaw rate was nearly twice as high. In order toinvestigate this discrepancy, dynamic derivatives weresubsequently determined by XFlow by measuring forcesand moments during pitch and yaw sweeps. Acomparison of several dynamic stability derivatives isshown below:

Wind Tunnel XFlow

Cmq Pitch damping -30.4 -30.9

Cnr Yaw damping -0.271 -0.212

Clr Roll due to yaw rate 0.153 0.145

Cyr Side force due to yaw rate 1.42 1.00

Yaw damping calculated by XFlow is 22% lower thandetermined by wind tunnel. Additionally, XFlowoverestimates rudder control power by one third instatic conditions at the coarse resolution settings usedin this simulation. Higher computing power not

available for this study may improve the levelcorrelation between XFlow and D-Six.

ConclusionsThe lattice Boltzmann method offers the potential ofevaluating the flight handling characteristics of anyaircraft configuration at the conceptual design stage,and can complement wind tunnel data with dynamicstability data including power or propeller slipstreameffects.

Indeed, a total of four flight manoeuvre simulationshave been conducted with the LBM-based softwareXFlow on the Diamond D-JET developed by DiamondAircraft Industries in Canada: the pitch capture, theDutch roll, the stall and spin simulation. Except for spinrate, overall accuracy is showing good potential: thepitch capture has the correct frequency but too highamplitude, the Dutch roll had a perfect match on initialamplitudes but shorter frequency, and the stall showssimilar patterns to experiment but with loweramplitudes in the aircraft incidence angledemonstrating elevator control effectiveness.

Further validation studies will determine its domain of

validity and possibly allow applications beyond aircraftdesign. For example, XFlow may eventually beconsidered as a flight test risk mitigation tool bysimulating a range of flight test manoeuvres such asdeep stall and spins prior to actual testing.

Figure 9: Stall Manoeuvre At Maximum Angle of Attack

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The lattice Boltzmann method offers thepotential of evaluating the flight handlingcharacteristics of any aircraft configurationat the conceptual design stage


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Figure 10: Tunnel Model (Top) - Spin Simulation on XFlow (Bottom)

REFERENCES

Chen, H., Chen, S., & Matthaeus, W., 1992, Recovery of theNavier-Stokes equations using a lattice-gas Boltzmannmethod, Physical Review A, vol. 45, pp. 5339.

Ducros, F., Nicoud, F., & Poinsot, T., 1998, Wall-adaptinglocal eddy-viscosity models for simulations in complexgeometries, Proceedings of 6th ICFD Conference on

Numerical Methods for Fluid Dynamics, pp. 293-299.Farhat, C., Pierson, K. & Degand, C., 2001, MultidisciplinarySimulation of the Maneuvering of an Aircraft. Engineeringwith Computers 17: 16-27.

Ghoreyshi, M., Vallespin, D., Da Ronch, A.,Badcockx, K. J.,Vos, J. & Hitze, S., 2010, Simulation of Aircraft ManoeuvresBased on Computational Fluid Dynamics. AmericanInstitute of Aeronautics and Astronautics.

Hardy, J., Pomeau, Y., & de Pazzis, O., 1973, Time evolutionof a twodimensional model system. I. Invariant states andtime correlation functions. J. Math. Phys., 14(12):1746-1759.

Higuera, F.J., & Jimenez, J., 1989, Boltzmann approach tolattice gas simulations, Europhysics Letters, vol. 9, pp. 663-668.

Holman, D.M., Brionnaud, R.M., Marti nez, F.J., & Mier-

Torrecilla, M., 2012,Advanced Aerodynamic Analysis of the NASA High-Lift TrapWing with a Moving Flap Configuration. 30th AIAA AppliedAerodynamics Conference, New Orleans, Louisiana, 25 - 28June.

d'Humie res, D., 2002, Multiple-relaxation-time latticeBoltzmann models in three dimensions, PhilosophicalTransactions of the Royal Society of London. Series A:Mathematical, Physical and Engineering Sciences, Vol. 360,No. 1792, 2002, pp. 437-451.

Johnson, A.A., 2006, Dynamic-mesh CFD and its applicationto flapping-wing micro-air vehicles, 25th Army ScienceConference, Orlando.

Lemon, K.A., 2011, Application of a six degrees of freedomadaptive controller to a general aviation aircraft. MScThesis, Wichita State University.

Premnath, K., & Banerjee, S., 2011, On the Three-Dimensional Central Moment Lattice Boltzmann Method,Journal of Statistical Physics, 2011, pp. 1- 48.

Qian, Y.H., DHumie res, D., & Lallemand, P., 1992, LatticeBGK models for Navier-Stokes equation. EPL (EurophysicsLetters), 17:479.

Ran, Z., & Xu, Y., 2008, Entropy and weak solutions in thethermal model for the compressible Euler equations,axXiv:0810.3477.

Shan, X., & Chen, H., 2007, A general multiple-relaxation-time Boltzmann models in three dimensions, InternationalJournal of Modern Physics C, Vol. 18, No. 4, 2007, pp. 635-643.

Shih, T., Povinelli, L., Liu, N., Potapczuk, M., & Lumley,1999, J., A generalized wall function, NASA Technical

Report.Shishkin, A. & Wagner, C., 2010, Numerical modeling offlow dynamics induced by fruit flies during free-flight, VEuropean Conference on Computational Fluid Dynamics,ECCOMAS CFD 2010, Lisbon (Portugal), 14- 17 June.

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Parts: Mecaplex Ltd, Grenchen, SwitzerlandSimulation: Aerofem GmbH, Ennetbu rgen, SwitzerlandProject: University of Applied Sciences and Arts Northwestern Switzerland FHNW / Instituteof Product and Production Engineering, Windisch, Switzerland

Improving the

Simulation of BirdStrike on PlasticWindshields

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Important issuesFinite element programs, such as LS Dyna which wasused in this project, offer a wide range of materialmodels, from simple linear elastic to complexnonlinear with damage models and so on. But theanswer to the important question, which one is bestsuited to the task at hand, needs to be found by theusers themselves. To find a suitable model, knowledgeabout the material and understanding its loadingconditions are necessary in order to know thecapabilities that need to be included in the materialmodel.

The first task therefore was to give some thought to theloading of the parts and the consequences of this, inorder to ensure a reliable FEM simulation.

For example these are:

High impact velocites lead to high strain rates in theplastic materials used. Their behaviour is stronglystrain rate dependent, meaning their stiffnessbehaviour at high rates of deformation differs fromones measured at low rates.

The impact leads to a bending deformation of thewindshield, resulting in tensile and compressivestresses. The materials behave differently in eachmode, not only regarding the stiffening but also thefailure behaviour.

As aircraft fly in a wide variety of weatherconditions, materials need to work from low to hightemperatures. Plastics properties also change withaltering temperatures.

There are many more considerations like this. To beginwith, we concentrated on analysing the strain rate andload condition dependency of the most commonly usedmaterials and on how to represent thesecharacteristics correctly in FEM simulations of thebirdstrike.

Material model calibration: An exampleAs already mentioned, layers of glassy polymers can becombined using an interlayer material, which can forexample be a thermoplastic polyurethane (TPU). Thesethin films of thermoplastic elastomers show a highlynonlinear elastic behaviour, completed by strain ratedependency and being nonsymmetric regarding tensionand compression loads.

To find a suitable modelling method, we first conducteda thorough study of the literature to get a betterimpression of the necessary behaviours in FEsimulation of these materials. While it would also befeasible to model such interlayers by using specialcontacts (*Tiebreak in LS DYNA) or cohesiveelements, we chose to use continuum elements for the

interlayer. Only with the complex material modelsavailable there was it possible to include all relevantmaterial behaviours. Two candidates were chosen asmaterial model:

*Mat_ Plasticity_Compression _Tension (Mat_124),an elasto plastic material model offering thepossibility to define different base curves and strainrate dependencies for tension/compression.Through a Maxwell type viscoelasticity includedwith a Prony Series also the elastic part can beinfluenced. One drawback is that only base curvesof true stress versus plastic st

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