多学科优化专题研讨会解决方案

DrivingProductDrivingProductInnovationwithCAE:Stateofthekg/s，所需功率为542Wkg/s，所需功率为542W 3|Copyright2014-RedCedarTechnology:AllRightsAxialFanDucthasfixeddiameterof59Fanhubshapeandinnerradiusfixedat19kg/s，所需功率为542W叶片数量,转动速度 4kg/s，所需功率为542W叶片数量,转动速度 4|Copyright2014-RedCedarTechnology:AllRightsParametric3DSection Section SectionDesignSectionSectionSection4―Rotation500―350010―10―10―2.5―152.5―17.52.5―17.50.0―0.0―0.0―-0.5―+0.5-0.5―+0.5-0.5―+0.5Verticalkg/s，所需功率为542W叶片数量,转动速度kg/s，所需功率为542W叶片数量,转动速度 5|Copyright2014-RedCedarTechnology:AllRightsMeshMeshPolyhedralmeshwithbody-fittedprismaticMeshBaselinedesigncontains690,000SimulationSteadyMulti-ReferenceFrameSolverGridTurbulenceRealizableκ−εkg/s，所需功率为542Wkg/s，所需功率为542W叶片数量,转动速度 6|Copyright2014-RedCedarTechnology:AllRightsPowerProcess MassFlowRatekg/s，所需功率为kg/s，所需功率为542W叶片数量,转动速度 7|Copyright2014-RedCedarTechnology:AllRights10coresper8Usescost-effectivetokenkg/s，所需功率为542W叶片数量,kg/s，所需功率为542W叶片数量,转动速度HEEDS分析结果 8|Copyright2014-RedCedarTechnology:AllRightsPowerBaselinem=2.5kg/sp=542WOptimizedm=2.6kg/sp=242Wrriorftrnt叶片数量,转动速度 9|Copyright2014-RedCedarTechnology:AllRights工业风机优化设工业风机优化设挑战2.5kg/s，所需功率为542叶片数量,转动速度Optimate+分析结果 10|Copyright2014-RedCedarTechnology:AllRightsSensitivity&RobustnessHEEDSHEEDS•••目标驱动的优化分Paretofront全自动化的寻优分••复杂过程自动优化分•更广泛意义上多学科CAE问题自动优化分OptimateandOptimateandOptimate&•••••••STAR-PTCCreoCATIAV53D-Optimate/Optimate+分析流Optimate/Optimate+分析流DesignSweep,Optimization,Robustness,BoundaryDesignparameters,geometrypartsReports,plots,scenesMinimum,ColumnsfromcsvfileInbatchInHEEDSAprimaryAprimaryfunction(F)tobeminimized(orLimittherangeofLimittherangeofacceptableConstrainthedesignFeasibleOptimalConstraintInfeasibleFeasibleNeighborhoodofLocalMinGlobalFeasibleNeighborhoodofLocalMinGlobalLocalAdesignx*isalocalminimumofFifisafeasibleandF(x*)<F(x)foranyxinafeasibleneighborhoodofGlobal•Adesignx*isaglobalminimumofFifx*isafeasibledesignandF(x*)<F(x)forallfeasibledesignsx需要变更的量(输入DenotedasDefinethespanof需要变更的量(输入DenotedasDefinethespanofthedesignspacetoN=R=N=R=N=R=N=R=N=R=N=R=N=R=N=R=N=R=MassflowrateStatictemperatureStaticpressureTotaltemperatureTotalpressureMachnumberFlowangles(modifies‘wind’CS)MassfractionsWallroughnessThermalscalars优化设计中的几何几何变更的手段–优化设计中的几何几何变更的手段–Method3:(CAD(w/optionalCAD优化设计中的几何几何变更的手段优化设计中的几何几何变更的手段Method2STAR-CCM+中的3D-CAD参数化建模(woptionalCAD优化设计中的几何几何变更的手段–––优化设计中的几何几何变更的手段–––Method#2STAR-CCM+中的3D-CAD参数化建模(woptionalCAD•••••••••2(Goal=1Maximumallowable(Goal=Easyto0MaximumallowableNormalizedaveragebestStandarddeviationofbest2(Goal=1Maximumallowable(Goal=Easyto0MaximumallowableNormalizedaveragebestStandarddeviationofbest推荐的Evaluation次最少评估次数NotlessthanNumber推荐的Evaluation次最少评估次数NotlessthanNumberofDesignNumberof1-51-DesignofDesignofExperimentsLatinHypercube2LevelFull3LevelFullOptimization优化分𝑳𝑾𝒊Optimization优化分𝑳𝑾𝒊∙𝑺𝒊∙−ParetoParetoOptimumTrade-什么是帕累托优化Pareto什么是帕累托优化ParetorupperlefttlNewoptimizationquestion:FordragxwhatisthePaoptimizationysatisfythisconditionreferredtoasthenon-dominated如何进行帕累托优化分析ParetoOptimate+(archivesize如何进行帕累托优化分析ParetoOptimate+(archivesizeOptimatenowcompletesazeainIwantonmyParetoCycleCycleCycleRankRankRankParetofront–curvedefiningoptimumtrade-offrelationshipNon-dominated-nodesignthatisbetterinbothobjectivesexists生命科学油气生命科学油气能源娱乐设备电子响后视镜位置:响后视镜位置:(5),左右变化对20个后视镜位置进行设计扫描 CustomerSuccess:AerodynamicShapeMorphingImprovehatchbackperformance&fuelMinimizeaerodynamicdrag(forMaximizedownforceCustomerSuccess:AerodynamicShapeMorphingImprovehatchbackperformance&fuelMinimizeaerodynamicdrag(forMaximizedownforce(forroadMinimizeaerodynamicpitch(forBy7morphingcontrolpointschangingfrontandrearbumpers;rearwindow;spoiler;curvatureofwindshield,sidedoors,andfloor;andforehead8%reductioninaerodynamicdragBettertractionandstabilityMuchfasterturnIMundSurfaceTime Multi-objective •射流速度底部射流角度射流宽度Jetson••射流速度底部射流角度射流宽度Jetson•••8Velocity•–••–•–••–Optimate分析结果••旋流最小的最佳设 •••QuadraticsumisminimizedforallOutlet TIVELowerUpper•••QuadraticsumisminimizedforallOutlet TIVELowerUpperRotation-Translation--35.000-35.00085.00083.190Translation--4.000-4.0008.000-0.804FloorFloor••–Optimate+分析结果•–––评估120设计方案135hourson128•injection–设计变量喷嘴位