Design optimization of fluid machinery: applying computational fluid dynamics and numerical optimization

308 Pages·2019·16.71 MB·English

DesignOptimizationofFluidMachinery

Design Optimization of Fluid Machinery
ApplyingComputationalFluidDynamicsand
NumericalOptimization
Kwang-YongKim
InhaUniversity
Incheon
RepublicofKorea
AbdusSamad
IndianInstituteofTechnologyMadras
Chennai
India
ErnestoBenini
UniversityofPadova
Italy
Thiseditionfirstpublished2019
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LibraryofCongressCataloging-in-PublicationData
Names:Kim,Kwang-Yong,1956-author.
Title:Designoptimizationoffluidmachinery:applyingcomputationalfluid
dynamicsandnumericaloptimization/Kwang-YongKim,Professor,Inha
University,Incheon,AbdusSamad,AssociateProfessor,IndianInstituteof
TechnologyMadras,Chennai,India,ErnestoBenini,Professor,University
ofPadova,Italy.
Description:Hoboken,NJ:Wiley,2019.|Includesbibliographicalreferences
andindex.|
Identifiers:LCCN2018044844(print)|LCCN2018045697(ebook)|ISBN
9781119188322(AdobePDF)|ISBN9781119188308(ePub)|ISBN9781119188292
(hardcover)
Subjects:LCSH:Computationalfluiddynamics.
Classification:LCCTA357.5.D37(ebook)|LCCTA357.5.D37K562019(print)|
DDC620.1/064–dc23
LCrecordavailableathttps://lccn.loc.gov/2018044844
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–Benini

vii
Contents
Preface xiii
1 Introduction 1
1.1 Introduction 1
1.2 FluidMachinery:ClassificationandCharacteristics 2
1.3 AnalysisofFluidMachinery 4
1.4 DesignofFluidMachinery 7
1.4.1 DesignRequirements 7
1.4.2 DeterminationofMeanlineParameters 7
1.4.3 MeanlineAnalysis 8
1.4.4 3DBladeDesign 8
1.4.5 Quasi3DThrough-FlowAnalysis 8
1.4.6 Full3DFlowAnalysis 8
1.4.7 DesignOptimization 8
1.5 DesignOptimizationofTurbomachinery 9
References 10
2 FluidMechanicsandComputationalFluidDynamics 11
2.1 BasicFluidMechanics 11
2.1.1 Introduction 11
2.1.2 ClassificationofFluidFlow 11
2.1.2.1 BasedonViscosity 12
2.1.2.2 BasedonCompressibility 12
2.1.2.3 BasedonFlowSpeed(MachNumber) 12
2.1.2.4 BasedonFlowRegime 13
2.1.2.5 BasedonNumberofPhases 14
2.1.3 One-,Two-,andThree-DimensionalFlows 14
2.1.3.1 One-DimensionalFlow 15
2.1.3.2 Two-andThree-DimensionalFlow 15
2.1.4 ExternalFluidFlow 15
2.1.5 TheBoundaryLayer 15
2.1.5.1 TransitionfromLaminartoTurbulentFlow 16
2.2 ComputationalFluidDynamics(CFD) 16
2.2.1 CFDanditsApplicationinTurbomachinery 17
2.2.1.1 AdvantagesofUsingCFD 18
viii Contents
2.2.1.2 LimitationsofCFDinTurbomachinery 18
2.2.2 BasicStepsInvolvedinCFDAnalysis 19
2.2.2.1 ProblemStatement 19
2.2.2.2 MathematicalModel 19
2.2.3 GoverningEquations 19
2.2.3.1 MassConservation 20
2.2.3.2 MomentumConservation 20
2.2.3.3 EnergyConservation 21
2.2.4 TurbulenceModeling 21
2.2.4.1 WhatisTurbulence? 22
2.2.4.2 NeedforTurbulenceModeling 22
2.2.4.3 Reynolds-AveragedNavier–StokesEquations 22
2.2.4.4 TurbulenceClosureModels 23
2.2.4.5 LargeEddySimulation(LES) 27
2.2.4.6 DirectNumericalSimulation(DNS) 27
2.2.5 BoundaryConditions 27
2.2.5.1 Inlet/OutletBoundaryConditions 28
2.2.5.2 WallBoundaryConditions 28
2.2.5.3 Periodic/CyclicBoundaryConditions 28
2.2.5.4 SymmetryBoundaryConditions 29
2.2.6 MovingReferenceFrame(MRF) 29
2.2.7 VerificationandValidation 30
2.2.8 CommercialCFDSoftware 30
2.2.9 OpenSourceCodes 31
2.2.9.1 OpenFOAM 31
References 32
3 OptimizationMethodology 35
3.1 Introduction 35
3.1.1 EngineeringOptimizationDefinition 36
3.1.2 DesignSpace 36
3.1.3 DesignVariablesandObjectives 37
3.1.4 OptimizationProcedure 40
3.1.5 SearchAlgorithm 40
3.2 Multi-ObjectiveOptimization(MOO) 41
3.2.1 WeightedSumApproach 42
3.2.2 Pareto-OptimalFront 42
3.3 Constrained,Unconstrained,andDiscreteOptimization 43
3.3.1 ConstrainedOptimization 43
3.3.2 UnconstrainedOptimization 44
3.3.3 DiscreteOptimization 44
3.4 SurrogateModeling 44
3.4.1 Overview 44
3.4.2 OptimizationProcedure 44
3.4.3 SurrogateModelingApproach 44
3.4.3.1 ResponseSurfaceApproximation(RSA)Model 45
3.4.3.2 ArtificialNeuralNetwork(ANN)Model 46