A combined approach to optimize by simulation the aerodynamic function of the fan system used for engine cooling in automotive application
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A combined approach to optimize by simulation the aerodynamic function of the fan system used for engine cooling in automotive application

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A combined approach to optimize by simulation the aerodynamic function of the fan system used for engine cooling in automotive application A combined approach to optimize by simulation the aerodynamic function of the fan system used for engine cooling in automotive application Presentation Transcript

  • A combined approach to optimize by simulation theaerodynamic function of the fan system used for enginecooling in automotive application(6th European Altair Technology Conference)(6th European Altair Technology Conference)Presented by Dr. Macoumba N’Diaye(Manuel Henner, Elias Tannoury, Zebin Zhang, Bruno Demory)
  • OutlineIntroduction / ContextFan optimization through parameterizationHigh Power ComputingRemote simulation on external clusterNumerical DOE for cooling system2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 2Numerical DOE for cooling systemURANS and LES for acoustic purposesInnovative solutionConclusions
  • Introduction / Context
  • VALEO ENGINE COOLING:Automotive supplier for cooling module– Fan Systems– Heat exchangers– Front-end moduleSystems integrator in charge of developmentIndustrial PartnershipsAutomotive Engine Cooling Module2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 4FLUOREM master reseller for Cradle Europe:Parameterized CFD Software provider─ Sensitivity studies─ OptimizationEuropean master reseller for CRADLE solutionsR&D center: partner of major European researchprograms in Automotive and Aerospace
  • Highly demanding thermal specifications forcooling module:Several types of heat exchangers (radiator, condenser,Charged Air Cooler, Oil cooler, exhaust gas recirculationfor NOx reduction)Compact system integrated in the underhood betweenthe engine and the front face (air entrance, grill,bumper, logo).Fan systems’ specifications are evolving2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 5Axial positionPressureHeat exchangersFan systemEngine positionAir entrancesQv (m3/h)Fan systems’ specifications are evolvingconstantly:Strong agility needed to fulfill a wide range ofspecifications (from 100 to 1200 Watts)The willing to have best efficiencies lead toconduct optimization process for every projectTough specifications through multi-objectives andmulti-physics requirements (aerodynamics,aeroacoustics)
  • Fan optimization through parameterization
  • Parameterized geometryParameterized CAD models :designers have now the opportunity to build parametric models, allowing them to varygeometry easilyUntil recently and despite the efforts of editors to interface CAD and simulation,changes were based on the designers intuition, that checks a posteriori the validity ofthe concept by a simulation or a test.Aerodynamic profile for a fan blade2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 7Parameterization for the stagger angle (left) and the camber (right)
  • Towards improved methodologies for optimizationMethods to support the design process for fan systemsKnow-how, standard, procedure, lesson-learned cards are among themeans to help the designer in his choicesSkilled and experimented engineers are needed when the parametersare numerous and have coupled influences on the aerodynamics.Experimental designs of experiment (DOE) are sometimes available ifthe investment in time and resources could be made. In this case, one2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 8the investment in time and resources could be made. In this case, onecould start considering optimization process.How can this matter of fact be improved?Instantaneous assessment of the aerodynamic performance of the fanafter a geometric modification would be the ideal case.A second step would be to propose the optimized fan regarding to thetargeted operating pointIs it a Utopia?
  • Parameterized simulationsParametric simulation for 2D profilesOne single simulation to provide a result and its derivativesDatabases are build from the reconstructed solutions: any set of parameters isassociated to a solutionReference simulation « Derived » simulation2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 9Optimization process for the aerodynamic propertiesthe optimal solution is in the database and corresponds to at least one set ofvalues of the parametersA search for an optimum is done by querying the database by a more or lesssophisticated method (Monte Carlo or genetic algorithm), which remains fast (no re-calculation).
  • Sensitivity analysis for the parametersPareto Front can be obtained from the database (all entities that are optimum forgiven criteria)Coupled effects of parameters are highlighted by cross-derivative effect compared tosingle parameters3 profiles selected according to conditions at various blade span positions (bottom,mid and top)2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 10Improvement of the solution BottomMid spanTop
  • Design optimization for 3D cases3D fan blade optimizationOptimum profiles are re-used to build a blade by stacking profiles from bottom to topThe blade is further optimized by searching for best solutions for stagger angles andstackingStackingStagger angles(bottom and top)Comparison of optimum solutions(choice is an engineering decision)2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 11Stacking
  • Final accurate performance predictionFan performances predictionsComputational effort limited for lastchecking on selected geometriesEquivalent solutions between k-Epsilon and k-omega turbulencemodel for our casesRequire of fine mesh (4,8 ME) or agood zonal refinement (240 kE)Mesh independence study-10001002003004005000 1000 2000 3000 4000 5000Pressurerise(Pa)ExperimentCoarse 40kEMedium 120 kEAdaptatif 120 kEAdaptatif 240 kE2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 12good zonal refinement (240 kE) -100Flow rate (m3/h)Effect of turbulence model-10001002003004005000 500 1000 1500 2000 2500 3000 3500 4000 4500Flow rate (m3/h)Pressurerise(Pa)Experimentk-eps 4,8MEk-ome 4,8MEZonal automated mesh refinement
  • Adaptative mesh for flow feature extractionTip clearance recirculationTip clearance creates a recirculation between the lower side and the upper side of thebladeThis recirculation creates a swirl in the wakeSuch a phenomenon is difficult to predict and visualize, since it is convected in theflow and location is variableAdaptive mesh is able to densify mesh on such local phenomena2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 13
  • Adaptative mesh for flow feature extraction2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 14
  • High Power Computing
  • Remote access to computer centersContribution to an experimental project supportedby a national research fund (Expamtion)Experiments conducted on the new platform CLOVISbased at URCA / Reims2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 16Access by a web interfaceCFD simulations performed on CLOVIS with 256 parallellicenses of SC-TetraExperimentation of methodologies based on high powercomputing
  • Simulation managementSubmission portal, licenses and queue managementSimulations submitted with an intuitive web interfaceData transfers (upload and download) operated by the systemLicenses and queue management supported by the remote clusterUsage of the computing power2013 European Altair Technology ConferenceApril 22nd-24th – Turin, Italy25/04/2013 I 17Usage of the computing powerDay to day simulations for engineersNumerical DOE with a high number ofsimulations for cooling module (severalhundred in a limited timeframe)Unsteady simulations for acousticpurposes with LES models
  • Numerical DOE for cooling module2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 18
  • Cooling module simulations on CLOVISFanRadiatorAir entranceBackplateBumper2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 19First Numerical Design Of Experiment :Fan behavior in actual tiny environmentData extraction for aerothermal studiesand aeroacoustic predictionsMeta-model building with neural network
  • Distribution of Flow RateDistribution of Distance_RAD0204060801001200 10 20 30 40 50 60Number of RunDistance_RADextremesNOLH and factorial samplingNOLHMethodology :Simulations conducted on CLOVIS (remotecluster) with 256 processors~ 15 millions of elements by simulationAutomated pre-processing for fastsubmission of the jobsAutomated post-processing of variousquantities2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 20Distribution of Flow Rate500150025003500450055000 10 20 30 40 50 60Number of RunFlowRateextremesParameter distribution(11 parameters in this case)quantities
  • Metamodel for global performancesMetamodel based on neural network2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 21Modify values of input parameters to compute new output values .Input Parameters Values Minimum Maximum Output Parameters ValuesAeroResistanceFactor 1 0,5 3,7 Y1_Dp(Pa) 322,14Calage1 68 60 76 Y2_T(Nm) 1,79Calage5 74 66 82 Y3_Eff_analytique(%) 15,85%DistanceBackplate 1000 110 1000DistanceRAD 30 10 106Hmax1 0,08 0,04 0,12Hmax5 0,05 0,01 0,09Lcorde1 65 30 78Lcorde5 75 51 99MassFlow 1500 1000 5000Sweep 100 68 132Neural network predictionP1P2P3P4P5P6P7P8P9P10P11
  • Extension of the method to a sophisticated modelProvide tool for pre-competition ofconcept:Find the best architecture for a coolingmodule and the best fan designTake into account roughly effects of airentrance and underhood blockageAssess the performances of variousconfigurations2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 22Response surface for 22 parameters :Neural network for global performances:Pressure rise, fan torque, efficiency.Split the surface of the radiator in 10*10 sub-surfaces and build a response surface for airvelocity on each of them.Excel sheet with 22 parameters, 3 outputs forglobal performances, 100 outputs for airvelocityLink with Kuli for thermal effect assessment
  • Unsteady simulations for acoustics2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 23
  • Fan trailing-edge noise (self noise)Trailing-edge noise is a major source of noise generated bylow speed fansTrailing-edge noise, caused by the scattering of boundary-layer vortical disturbances into acoustic waves, occurs atthe trailing edge of a lift-generating deviceAmiet’s model for broadband noisez)x,x,x(x 321====rturbulence characteristics to know :The input data are the aerodynamic wall pressurespectrum, the convection velocity and the2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 24xyz)y,x(S ====0U2021022203,,,)(2),( ′Φ=SxkUxLSxkdSxckxScyppppωωωπω lrspectrum, the convection velocity and thetransverse correlation scale associated with theincident turbulence (can be extracted frommeasurements).The integral of radiation can be analytically deducedfrom unsteady aerodynamic theories.Wall pressure spectrum at a point near the trailing edge
  • Large Eddy Simulation on the “Control Diffusion” (CD) profileApplication to an aerodynamic profile2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 25Large Eddy Simulation on the “Control Diffusion” (CD) profileValeo test case for simulation validationLarge amount of data (experimental and numerical) for pressure distribution, boundarylayers separation, velocities in the wake, etc…tiphub34215tiphub34215CFD post-processingBoundary layer data extracted to feed the source modelBlade span decomposed in strips and airfoil Amiet’s theory appliedto each stripWake properties furthermore extracted for Sear’s model (statornoise)Full 3D LES for a blade (on-going PhD thesis)
  • LES on a 2D extruded profile2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 26
  • 2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 27
  • 2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 28
  • Numerical approach for new concept designBenefits of mastering the simulation process:SC tetra simulations for performance predictionEasy and fast comparisons between variousconfigurationsPost-processing and flow analysis to guideevolution and trigger new ideasOn-going further developments with Fluorem’sparameterized tools2013 European Altair Technology ConferenceApril 22nd-24th – Turin, ItalyI 29parameterized toolsExperiment and validations still required for alimited number of selected solutions
  • SC/TetraApplication Fields2013 European Altair Technology ConferenceApril 22nd-24th – Turin, Italy- Robust auto-mesh generator enablescapturing complex geometry- Best-in-class memory saving andcomputation speedApplication Fields- Automotive- Aerospace- Energy- Mechanical and Heavy Manufacturing- Chemical ReactionFeatures- Overset mesh- Arbitrary Lagrangian-Eulerian (ALE)- Dynamical motion of element- Heat radiation / Solar radiation- Fan model- Diffusion / Chemical reaction, Combustion- Multiphase flow / Free surface flowhjjhjhjh