stevens institute of technology systems engineering research center … · 2016-10-30 · 1 stevens...
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StevensInstituteofTechnology&
SystemsEngineeringResearchCenter(SERC)SystemsEngineeringTransformationthrough
ModelCentricEngineeringPresentedBy:
Dr.MarkR.BlackburnWithContributingResearchers(RT-48,118,141,157):
Dr.MaryBoneDr.GaryWitus
Dr.RobertCloutierProf.Eirik Hole
GeorgetownUniversity(RT-168)GeorgiaTechUniversity(RT-170)
StevensInstituteofTechnology(RT-157,168,170)UniversityofMaryland(RT-170)
UniversityofSouthernCalifornia(RT-168)
MarkR.Blackburn, Ph.D. 2
Outline
• Problem,ObjectivesandTerminology(PhaseI)
• BottomLine(UpFront)
• Currentresearchthrusts
• PerspectivesnewRT-157/RT-170(PhaseII)
• Status
• ConclusionsandImpacts
• Backup:pastRT-48/118/141(PhaseI)
• Acknowledgments
• AcronymsandImagecredits
Certain commercial software products are identified in this material. These products were used only for demonstration purposes. This use does not imply approval or endorsement by Stevens, SERC, or NAVAIR, nor does it imply these products are necessarily the best available for the purpose. Other product names, company names, images, or names of platforms referenced herein may be trademarks or registered trademarks of their respective companies, and they are used for identification purposes only.
MarkR.Blackburn, Ph.D. 3
FeasibilityStudyObjectives
Problemstatement(PhaseI):
Ittakestoolongtobringlarge-scaleairvehiclesystemsfromconcepttooperation
Primaryquestion:Is it Technically Feasible to have a Radical Transformationthrough Model Based Systems Engineering (MBSE) and achievea 25 percent reduction in the time to develop large-scale airvehicle system (using computer/digital models)?
Corollary:How do we know that models/simulations used to assessPerformance have the needed Integrity to ensure predictionsare accurate (i.e., that we can trust the models)?
MarkR.Blackburn, Ph.D. 4
Sponsor’sVisionatKickoffMeeting:Cross-Domain,Multi-Physics,ModelsIntegration
Continuousrefinementofmodelsthroughcross-domain&multidisciplinaryanalysissupportingvirtualV&VfromCONOPStomanufacturing
IntegratedEnvironmenttoProduceDigitalSystemModel:SingleSourceofTechnicalTruth
MarkR.Blackburn, Ph.D. 5
• Over30organizationaldiscussions“mostholisticapproach…”:―Model-BasedEngineering(MBE),IntegratedModel-CentricEngineering,InteractiveModel-CentricSystemsEngineering(IMCSE),Model-DrivenDevelopment,Model-DrivenEngineering(MDE),andevenModel-BasedEnterprise,whichbringsinmorefocusonmanufacturability
―DigitalThreadenvisionsframeworksthatmergesphysics-basedmodelsgeneratedby(cross)disciplineengineersduringdetaileddesignprocesswithMBSE’sconceptualandtop-levelarchitecturalmodels,resultinginasingleauthoritativerepresentationofthesystem[West,Pyster,INCOSE2015]
•MCE characterizesthegoalofintegratingdifferentmodeltypeswithsimulations,surrogates,systemsandcomponentsatdifferentlevelsofabstractionandfidelityacrossdisciplinethroughoutthelifecyclewithmanufacturabilityconstraints
• WecouldhaveusedthewordsDigitalEngineering,whichwedo
ModelBasedSystemEngineering(MBSE)versusModel-CentricEngineering(MCE)
MarkR.Blackburn, Ph.D. 6
ConceptualReferenceModel:IntegratedEnvironmentforIterativeTradespaceAnalysisofProblemandDesignSpace
Multidiscipline Design,Analysis andOptimization(MDAO)
SingleSourceofTechnicalTruth:ToolAgnostic,SemanticallyPreciseCrossDomainIntegration&InteroperabilityenabledbyHPC
Performance Integrity
SecurePlugin
Cost&Schedule
Systems,Surrogates&Platforms
DocGen
Appropriate Views for Stakeholders
Knowledge …
ContinuousWorkflow
Orchestration
ComputerAugmentation
&Training
PLM
Rich Modeling Interfaces “Web” Interface integrated
with Rich Visualizations
“Illities”
MarkR.Blackburn, Ph.D. 7
ScopeofDataCollectionforTask1TracedtoEvidence(notexhaustive)
Discussion(Topics(not(exhaustive) N
ASA
/JPL
A B C Alta
ir
GE
Sand
ia
DARP
A5M
ETA5(V
B)
DARP
A5M
ETA5(B
AE)
Mod
el5Cen
ter
Autom
otive
CREA
TE
Performance
Integrity
Affordability
Risk
Metho
dology
Single5Sou
rce5of5Tech5Truth
Prioritization5&
Tradeo
ff5Analysis
Concep
t5Engineering
Architecture5&
Design5Analysis
Design5&5Test
Reuse5&5Synthesis
Active5System
Characterizatio
n
Hum
anMSystem
Integration
Modeling5CONOPS x x x x x x xModeling5Patterns x x x x x x x x xMultiMPhysics5Modeling5and5Simulation x x x x x x x x x x x x x x xMultiMDiscpline/Domain5Analysis5and5Optimization x x x x x x x x x x x x x x x x x x xMissionMtoMSystemMlevel5Simulation5Integration x x x x x x x x x x xAffordability5Analysis x x x x x x x x x xQuantification5of5Margins x x x x x x x x x x xRequirement5Generation5(from5Models) x x x x x x x xTool5agnostic5digital5representation x x x x x x x x x x xModel5measures5(thru5formal5checks) x x x x x x x x x xModeling5and5Sim5for5Manufacturability x x x x x x x x x x x x x xProcess5Automation5(workflows) x x x x x x xIterative/Agile5use5of5MCE x x x x x x xHigh5Performance5Computing x x x x x x x x x x x x x x xPlatformMbased5and5Surrogates x x x x x x x x3D5Environments5and5Visualization x x x x x x x x x x x x x x x xImmersive5Environments x x x x x xDomainMspecific5modeling5languages5 x x x x x x x x x x x x x x x xSetMbased5design5 x x x x x x x x xModel5validation/qualification/trust x x x x x x x xModeling5Environment5and5Infrastructure x x x x x x x x x x x x x x x x x x x x x x x x
Instances5where5discussed5(not5exhaustive) From5Kickoff5BriefingCharacteristics
MarkR.Blackburn, Ph.D. 8
SETransformationPhaseII(Q42015)“DoingEverythingwithModels– 25%ReductioninCycle-time”
2) Model Integrity1) Model Cross-Domain Integration
3) Modeling Methodology Implementation at NAVAIR 4) SE Transformation Roadmap
Targeted discussions with Government, Industry & Academia on developing and operating in modeling framework enabling cross-domain model integration& Single Source of TechnicalTruth (SSTT) methodology
Define Methodologies for Model Integrity and Uncertainty Quantification:• Provide trust in model-based predictions, with
Quantification of Margins & Uncertainties• Framework for integrating risk and understanding
uncertainty in the data
Develop a roadmap to rollout capabilities addressing all five perspectives in parallel:1. Technologies and infrastructure for SSTT2. Methodologies and processes3. People, competencies
and SSTT interfaces4. Operational & contractual
paradigms for transformedinteractions with industry
5. Governance
MarkR.Blackburn, Ph.D. 9
BottomLine• Organizations(withafewexceptions)wereunwillingtosharequantitativedata
• QualitativedataintheaggregatesuggeststhatMCEtechnologiesandmethodsareadvancingandadoptionisaccelerating
NAVAIRExecutiveLeadershipResponse:
• NAVAIRmustmovequicklytokeeppacewithotherorganizationsthathaveadoptedMCE
• NAVAIRmusttransforminordertoperformeffectiveoversightofprimesthatareusingmodernmodelingmethodsforsystemdevelopment
March2016:ChangeofCommandhasAcceleratedtheSystemsEngineeringTransformationandBroadenedtheScope
MarkR.Blackburn, Ph.D. 10
Model-CentricEngineeringCanEnableNewTypesofCoordination
• Ina“DigitalEngineering”environment,governmentandindustryneedtoworkinadifferentway
MarkR.Blackburn, Ph.D. 11
FrameworkforNewOperationalParadigmBetweenGovernmentandIndustry
MarkR.Blackburn, Ph.D. 12
RT-157 Perspectives
MarkR.Blackburn, Ph.D. 13
TracingtheCampaignandMissionAnalysistoSystemCapabilitiesofEvolvingPlatforms
MarkR.Blackburn, Ph.D. 14
DynamicCONOPSIntegratedwithMissionSimulationstoBetterUnderstandNeededSystemCapabilities
Simulated-basedStudyViewsMethod
StructuresandFormalizestheJCIDS*Conceptsprior
toDoDAFModeling
*Joint Capabilities Integration and Development System (JCIDS)
MarkR.Blackburn, Ph.D. 15
MultidisciplinaryDesign,AnalysisandOptimizationSupportsTradespaceAnalysisAcrossDisciplines
VehicleDesign
Geometry&Packaging Airframe&
EngineAero
Sensors
Propulsion
Structures
“illites”
Comm./Radar
Store/Payloads
DetailedDesignfromAssociatedDisciplinesandCompetencies
MDAOImplementsWorkflowwithSolverstoEvaluate
TradesSystematicallyDrivenbyDesignofExperiment
MarkR.Blackburn, Ph.D. 16
NeedtoBetterIntegrateMultipleLevelsofSystemModelswithDiscipline-SpecificDesigns
VehicleDesign
Geometry&Packaging Airframe&
EngineAero
Sensors
Propulsion
Structures
“illites”
Comm./Radar
Store/Payloads
Architectural,SystemandComponentModels
DefinetheCross-DomainIntegrationandBringinDetailedBehaviors
Iterative Process
MarkR.Blackburn, Ph.D. 17
Re-defineRequiredEngineeringDataandAssociatedContractLanguage
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Domains Associated with Competencies
Syst
em L
evel
s
CD
RL
Dat
a “B
ough
t” Hi
stor
ical
lyNear Term Transformation
Focus on Value and Risk-Driven “Digital CDRLs”That Relate to Key Cross-Domain System
MarkR.Blackburn, Ph.D. 18
StructureofSETRChecklistQuestions
MarkR.Blackburn, Ph.D. 19
MethodologiesareCriticalBecauseCommercialToolsareMethodAgnostic
Reference Technology Platform (RTP)
Program RTP Instance Program RTP Instance Program RTP Instance
Cross-domainmethodologies ensuretoolusageproducescompleteandconsistentinformationcompliantwithontologiesofSSTT
DigitalSystemModel:SingleSourceofTechnicalTruth(SSTT)
MarkR.Blackburn, Ph.D. 20
OrganizationsareModelingandSimulatingManufacturingBeforeTooling
• Set-baseddelaysdesignselectionandincreasinglyfactorsinmanufacturability
MarkR.Blackburn, Ph.D. 21
SETransformation“Role-out”Strategy
Capability Development
SE Transformation Research (SERC + SET Team)
Capability Development
SET Framework Operations & Maintenance (SEDIC/4.1)
Research State-of-the=art
Research Literature
Pilot 1 – MQ-25A (SERC + SET Team + SEDIC)
Pilot 2 – TBD
Pilot 3 – TBD
Research Collaboration
Release Release Release
Lessons Learned
Lessons Learned
Lessons Learned
Enterprise Deployment
Dev
elop
men
t A
pplic
atio
n &
Dep
loym
ent
• Model Integration • Model Integrity • Implementation Methods • Roadmap
SET Framework • Modeling Environment • System Model • Standard Language • Modeling Analysis
Cap. Dev.
Capability Development
SERC Research
Res
earc
h
MarkR.Blackburn, Ph.D. 22
StatusAgainstFrameworkResearch(1/3)–ContractingthroughDigitalEngineering
• DevelopingsurrogateUAVtodemonstratehowmodelsrepresentrequirementatlogicalandfunctionallevels―ConceptcanbepartofaSOWandRFPfornewcontractualvehiclebasedonDigitalEngineeringforcompetitivedownselect(NDIAinvolvedinthiseffort)
―IllustratelinksfromsystemmodelstoMDAOandothertypesofmodels―Modelssupportvalidationofrequirementsandprovidesameansforverificationplanningandbasisofestimatefortesting
―ExamplesalreadypresentedatworkingsessionsandincludedinRT-157InterimTechnicalReport
• Developingmodelsofmethodsandprocessestoillustratelinkagebetweenmission,system,referenceandMDAO,etc.models
• Planistodevelop“surrogate”UAVmodelasameansforillustratingwhatneedstobemodeledbeyondDoDAF focusedonnet-readyviews
MarkR.Blackburn, Ph.D. 23
StatusAgainstFrameworkResearch(2/3)–MDAOExampleRelevanttoUAV
• DevelopedMDAOworkflowforexampleofKPP(range)usingUAVWeight,Aero,Propulsion,Performance,whichlinksbacktosystemmodeltoillustratemethod:― Definingsequenceofworkflows(scenarios)― Identifyingasetofinputsandoutputs (parameters)― DefineaDesignofExperiments(DoE)anduseanalysessuchassensitivityanalysisand
visualizationstounderstandthekeyparametertoscope― UseOptimizationusingsolverswithkeyparametersanddefinedifferent(keyobjectivefunctions
– onoutputs) todeterminesetofsolutions(resultsoftenprovidedasatableofpossiblesolutions)
― Usevisualizationstounderstandrelationshipsofdifferentsolutions
― Conceptapplicableatmission,systemandsubsystems
MarkR.Blackburn, Ph.D. 24
StatusAgainstFrameworkResearch(3/3)–ModelIntegrity
• Steven’sPhDcandidateCol.TimothyWest(advisorMarkBlackburn)runswindtunnelsatArnoldEngineeringDevelopmentComplex
• ResearchinvolvesaproposedmethodologytouseSandiaNationalLaboratory(SNL)DAKOTAToolkit withDoDComputationalResearchandEngineeringAcquisitionToolsandEnvironments(CREATE)AirVehicle(AV) familyofcomputationaltools(e.g.,CFD,FEA),inordertodevelopanoptimizedwindtunnelcampaignfortwodifferentaerodynamicshapestoassesstheprocess
MarkR.Blackburn, Ph.D. 25
ConclusionsandImpacts• NAVAIRisevolvingaframeworkforanewcollaborativeoperationalparadigmwithindustry―Conductingmeetingswithindustryto“validate”conceptandsolicitrecommendationsforimprovementandevolution
• Programs―NAVAIReffortstargetedtorealprograms―Newcontractingmodel/approachneeded―Newcriteriaforassessing“maturity”vice“milestones”
• Policy– canthecurrentpolicystillwork?
• Collaboration:newSERCresearchwithUSArmyARDECtargetingtheirneedsforMCEincollaborationwithNAVAIR
• GovernmentandIndustryForumonMCE
• DigitalEngineeringStrategyInitiative(coordinatedthroughDASD)
• AirspaceIndustryAssociation:CONOPSforIndustry/GovernmentCollaborativeFramework
• NDIAWorkingGroup–UsingDigitalEngineeringforCompetitiveDownSelect
MarkR.Blackburn, Ph.D. 26
BackupRT-48/118/141 Perspectives
MarkR.Blackburn, Ph.D. 27
FourTaskstoAssessTechnicalFeasibilityof“DoingEverythingwithModels”(EverythingDigital)
2) Develop Common Lexicon for Model Levels, Types, Uses, and Representations
1) Global scan and classification of holistic state-of-the-art MBSE
3) Model the Vision of Everything Done with Models and Relate to “As Is” process
4) Fully integrate model-driven Risk Management and Decision Making
• Use discussion framework to survey government, industry and academia
• Quantify, link and trace realized modeling capabilities to Vision (task 3)
Campaign
Mission
Engagement
Engineering
Model Types
Structure/Interfaces
Behavior (functions)
Concurrency
Resources/Environment
Address two classes of risk:• Airworthiness and
Safety• Program Execution
MarkR.Blackburn, Ph.D. 28
Task1:Industry,GovernmentandAcademiaVisitsandDiscussions
•Wehadopen-endeddiscussionsTellusaboutthemostadvancedandholisticapproachtomodel-centricengineeringyouuseorseenused
•Didnotsingleoutspecificcompanies
• Spectrumofinformationwasverybroad
•Therereallyisnogoodwaytomakeacomparison
•Wehaveareportthatsummarizestheaggregateofwhatweheard
MarkR.Blackburn, Ph.D. 29
RT-48/118/141Summary
• Over30discussionsand21onsitewithIndustry,GovernmentandAcademia,withfollow-ups– oursummaryisnotexhaustive
• Developedcommonlexiconofover700termsformodellevels,types,uses,andrepresentations,withmanycontributors
• Modelsarebecomingmoredynamicandintegratedacrossdomains,asopposedtostaticandisolated,enabledbyHPC,semanticprecision,andvisualanalytics
• Severalstrategieshavebeendevelopedandappliedforquantificationofmodelconfidence,enabledbyHPC
• AnswertoSponsor:ItistechnicallyfeasibletoradicallytransformsystemsengineeringatNAVAIRthroughMCSE;however,theevidencedoesnotshowconclusivelythatitwillproducea25%reductioninacquisitioncycletime.
MarkR.Blackburn, Ph.D. 30
Acknowledgment
• WewishtoacknowledgethegreatsupportoftheNAVAIRsponsorsandstakeholders,includingstakeholdersfromotherindustrypartnersthathavebeenveryhelpfulandopenaboutthechallengesandopportunitiesofthispromisingapproachtotransformsystemsengineering.
• WewanttospecificallythankDaveCohenwhoestablishedthevisionforthisproject,andourNAVAIRteam,JaimeGuerrero,GaryStrauss,BrandiGertsner,DavidMeiser andRonCarlson,whohasworkedcloselyonaweeklybasisinhelpingtocollaborativelyresearchthiseffort.WethankHowardOwensandDennisReedwhohavejoinedusinsomeoftheorganizationalvisits.WealsothankLarrySmith,Ernest(Turk)Tavares,Eric(Tre´)Johnsen,whoworkedPhaseI&IIwithus,buthavelefttheproject.
• Wehavehadover40discussionswithorganizationsfromIndustry,Government,andAcademia,andwewanttothankallofthosestakeholders(over200people),includingsomefromindustrythatwillremainanonymousinrecognitionofourneedtocomplywithproprietaryandconfidentialityagreementsassociatedwithTask1.
MarkR.Blackburn, Ph.D. 31
ThankYou
• Formoreinformationcontact:―MarkR.Blackburn,Ph.D.―[email protected]―StevensInstituteofTechnology
MarkR.Blackburn, Ph.D. 32
CDD CapabilityDescriptionDocumentCONOPS ConceptofOperationsCDR CriticalDesignReviewCDRL ContractDataRequirements ListCFD Computational FluidDynamicsDARPA DefenseAdvancedResearchProject
AgencyDASD DeputyAssistantSecretaryofDefenseDoD DepartmentofDefenseDoE DesignofExperimentsFEA FiniteElementAnalysisHPC HighPerformanceComputingIMCE IntegratedModel-Centric EngineeringIMCSE InteractiveModel-centricSystems
EngineeringIoT InternetofThingsJCIDS JointCapabilities Integrationand
DevelopmentSystemKPP KeyPerformanceParameterMBSE Model-based SystemEngineeringMBE Model-Based EngineeringMCE Model-Centric Engineering
MCSE Model-Centric SystemEngineeringMDAO Multidisciplinary DesignAnalysis and
OptimizationMDE Model-Driven EngineeringNAVAIR NavalAirSystemsCommandOV OperationalViewP&FQ PerformanceandFlightQualityPDR PreliminaryDesignReviewPLM ProductLifecycleManagementRT ResearchTaskSLOC SoftwareLinesOfCodeSE Systems EngineeringSET Systems EngineeringTransformationSERC SystemEngineeringResearchCenterSETR Systems EngineeringTechnicalReviewSFR SystemFunctional ReviewSRR SystemRequirements ReviewSoS SystemofSystemsSOW StatementofWorkSSTT SingleSourceofTechnicalTruthSV SystemViewUAV UnmannedAirVehicleV&V VerificationandValidation
Acronyms
MarkR.Blackburn, Ph.D. 33
ImageCredits• Certaincommercialproducts, equipment, instruments, orothercontentidentified inthisdocument doesnot
imply recommendationorendorsement bytheauthors,SERC,orNAVAIR,nordoes itimplythattheproductsidentified arenecessarily thebestavailableforthepurpose.
• Imagecredits/sourcesSlide#4:m.plm.automation.siemens.com,mosimtec.com, www.defenseindustrydaily.com, www.darkgovernment.comSlide#6:www.defenseindustrydaily.com, www.darkgovernment.com,NAVAIRSlide#10:http://www.eonreality.com/hardware/Slide#13:www.defenseindustrydaily.com, www.darkgovernment.com, NAVAIRSlide#11:www.fightercontrol.co.uk, en.wikipedia.org,en.wikipedia.orgSlide#14:Imagecredit:AGI,NAVAIRStudyViewsSlide#15:Imagecredit:AGI,Phoenix IntegrationSlide#16:mosimtec.comSlide#19:CRitical SYSTem EngineeringAcceLeration, Interoperability Specification (IOS)– V1D601.021,ARTEMIS-2012-1-332830, 2014.Slide#20:Slide#18:m.plm.automation.siemens.com,mosimtec.com, www.defenseindustrydaily.com, www.darkgovernment.comSlide#24:ArnoldEngineering DevelopmentComplex