Holdings: Optimization and computational fluid dynamics

Optimization and computational fluid dynamics:

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Bibliographic Details
Format:	Book
Language:	English
Published:	Berlin [u.a.] Springer 2008
Subjects:	Computação aplicada Dinâmica dos fluídos Mathematisches Modell Fluid dynamics > Mathematical models Mathematical optimization Numerische Strömungssimulation Technisches System Optimierung
Online Access:	Inhaltsverzeichnis
Physical Description:	XIV, 293 S. Ill., graph. Darst.
ISBN:	9783540721529 9783540721536

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245	1	0	\|a Optimization and computational fluid dynamics \|c Dominique Thévenin ... ed.
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adam_text	DOMINIQUE THEVENIN * GABOR JANIGA EDITORS OPTIMIZATION AND COMPUTATIONAL FLUID DYNAMICS 4Y SPRINGER CONTENTS PART I GENERALITIES AND METHODS 1 INTRODUCTION 3 DOMINIQUE THEVENIN REFERENCES 16 2 A FEW ILLUSTRATIVE EXAMPLES OF CFD-BASED OPTIMIZATION . 17 GABOR JANIGA 2.1 INTRODUCTION 18 2.1.1 PURPOSE 18 2.1.2 HEAT EXCHANGER OPTIMIZATION (CASE A) 19 2.1.3 OPTIMIZATION COUPLED WITH CHEMICAL REACTIONS (CASE B) 21 2.1.4 DETERMINATION OF TURBULENCE MODEL PARAMETERS BASED ON OPTIMIZATION (CASE C) 22 2.2 EVOLUTIONARY ALGORITHMS FOR MULTI-OBJECTIVE OPTIMIZATION 23 2.2.1 MULTI-OBJECTIVE OPTIMIZATION 23 2.2.2 THE CONCEPT OF PARETO DOMINANCE 25 2.2.3 EVOLUTIONARY ALGORITHM FOR MULTI-OBJECTIVE PROBLEMS 26 2.3 THE OPTIMAL POSITION OF THE TUBES IN A HEAT EXCHANGER (CASE A) 28 2.3.1 TUBE BANK HEAT EXCHANGER 28 2.3.2 PROBLEM PARAMETERS. . . 29 2.3.3 OPAL (OPTIMIZATION ALGORITHMS) PACKAGE 29 2.3.4 EVALUATION OF THE OBJECTIVES FOR CASE A 30 2.3.5 PARALLELIZATION /* 33 2.3.6 COMPUTATIONAL RESULTS 34 2.4 MULTI-OBJECTIVE OPTIMIZATION OF A LAMINAR BURNER (CASE B) 38 CONTENTS 2.4.1 GOVERNING EQUATIONS 38 2.4.2 NUMERICAL SOLUTION 40 2.4.3 OPTIMIZATION OF THE LAMINAR BURNER 42 2.5 OPTIMIZATION OF THE STANDARD K-U TURBULENCE MODEL PARAMETERS (CASE C) 46 2.5.1 GOVERNING EQUATIONS 48 2.5.2 NUMERICAL RESULTS 50 2.6 CONCLUSIONS 52 REFERENCES 56 MATHEMATICAL ASPECTS OF CFD-BASED OPTIMIZATION 61 HANS GEORG BOCK AND VOLKER SCHULZ 3.1 INTRODUCTION 62 3.2 SIMULTANEOUS MODEL-BASED OPTIMIZATION 63 3.2.1 SEQUENTIAL QUADRATIC PROGRAMMING (SQP) 63 3.2.2 MODULAR SQP METHODS 65 3.2.3 MULTIPLE SET-POINT OPTIMIZATION 69 3.2.4 MULTIGRID OPTIMIZATION 70 3.3 UNSTEADY PROBLEMS 72 3.3.1 TIME-DOMAIN DECOMPOSITION BY MULTIPLE SHOOTING 73 3.3.2 PARALLEL MULTIPLE SHOOTING 75 3.3.3 REAL-TIME OPTIMIZATION AND NONLINEAR MODEL PREDICTIVE CONTROL 75 3.3.4 SENSITIVITY DRIVEN MULTIPLE SHOOTING 76 REFERENCES 77 ADJOINT METHODS FOR SHAPE OPTIMIZATION 79 KYRIAKOS C. GIANNAKOGLOU AND DIMITRIOS I. PAPADIMITRIOU 4.1 INTRODUCTION 80 4.2 PRINCIPLES OF THE ADJOINT APPROACH 83 4.2.1 THE DISCRETE ADJOINT APPROACH 83 4.2.2 THE CONTINUOUS ADJOINT APPROACH 84 4.2.3 DIFFERENCES BETWEEN DISCRETE AND CONTINUOUS ADJOINT 85 4.3 INVERSE DESIGN USING THE EULER EQUATIONS 86 4.4 INVERSE DESIGN USING THE NAVIER-STOKES EQUATIONS 90 4.5 VISCOUS LOSSES MINIMIZATION IN INTERNAL FLOWS 91 4.5.1 MINIMIZATION OF TOTAL PRESSURE LOSSES 92 4.5.2 MINIMIZATION OF ENTROPY GENERATION 93 4.6 COMPUTATION OF THE HESSIAN MATRIX 94 4.6.1 DISCRETE DIREOVADJOINT APPROACH FOR THE HESSIAN... 95 4.6.2 CONTINUOUS DIRECT-ADJOINT APPROACH FOR THE HESSIAN (INVERSE DESIGN) 96 4.7 APPLICATIONS 97 CONTENTS IX 4.7.1 GRADIENT AND HESSIAN-BASED INVERSE DESIGN OF A 2D DUCT 97 4.7.2 LOSSES MINIMIZATION OF A 2D COMPRESSOR CASCADE 99 4.8 CONCLUSIONS 104 REFERENCES 106 PART II SPECIFIC APPLICATIONS OF CFD-BASED OPTIMIZATION TO ENGINEERING PROBLEMS 5 EFFICIENT DETERMINISTIC APPROACHES FOR AERODYNAMIC SHAPE OPTIMIZATION ILL NICOLAS R. GAUGER 5.1 INTRODUCTION 112 5.2 PARAMETERIZATION BY DEFORMATION 113 5.2.1 SURFACE DEFORMATION 114 5.2.2 GRID DEFORMATION 115 5.3 SENSITIVITY-BASED AERODYNAMIC SHAPE OPTIMIZATION 117 5.4 SENSITIVITY COMPUTATIONS 119 5.4.1 FINITE DIFFERENCE METHOD 119 5.4.2 CONTINUOUS ADJOINT FORMULATION 120 5.4.3 ALGORITHMIC DIFFERENTIATION (AD) 122 5.5 ADJOINT FLOW SOLVERS 124 5.5.1 CONTINUOUS ADJOINT FLOW SOLVERS 124 5.5.2 DISCRETE ADJOINT FLOW SOLVERS 125 5.6 AUTOMATIC DIFFERENTIATION APPLIED TO AN ENTIRE DESIGN CHAIN 126 5.6.1 TEST CASE DEFINITION 127 5.6.2 FINITE DIFFERENCES 127 5.6.3 AUTOMATIC DIFFERENTIATION 132 5.7 ADJOINT APPROCH FOR AERO-STRUCTURE COUPLING 133 5.7.1 ADJOINT FORMULATION FOR AERO-STRUCTURE COUPLING 133 5.7.2 IMPLEMENTATION 140 5.7.3 VALIDATION AND APPLICATION 141 5.8 ONE-SHOT METHODS J 142 REFERENCES 144 6 NUMERICAL OPTIMIZATION FOR ADVANCED TURBOMACHINERY DESIGN 147 RENE A. VAN DEN BRAEMBUSSCHE 6.1 INTRODUCTION . /. 147 6.2 OPTIMIZATION METHODS ... F 150 6.2.1 SEARCH MECHANISMS 150 6.2.2 OBJECTIVE FUNCTION 156 CONTENTS 6.2.3 PARAMETERIZATION 159 6.3 TWO-LEVEL OPTIMIZATION 160 6.3.1 ARTIFICIAL NEURAL NETWORKS 162 6.3.2 DATABASE 164 6.4 SINGLE POINT OPTIMIZATION OF TURBINE BLADE 166 6.4.1 2D BLADE GEOMETRY DEFINITION 166 6.4.2 PENALTY FOR NON-OPTIMUM MACH NUMBER DISTRIBUTION PMACH 168 6.4.3 DESIGN OF A TRANSONIC TURBINE BLADE 170 6.5 MULTIPOINT OPTIMIZATION OF A LOW SOLIDITY DIFFUSER 172 6.6 MULTIDISCIPLINARY OPTIMIZATION 175 6.6.1 3D GEOMETRY DEFINITION 176 6.6.2 MULTIDISCIPLINARY OBJECTIVE FUNCTION 178 6.6.3 DESIGN CONDITIONS AND RESULTS 180 6.7 CONCLUSIONS 187 REFERENCES 188 CFD-BASED OPTIMIZATION FOR AUTOMOTIVE AERODYNAMICS .. 191 LAURENT DUMAS 7.1 INTRODUCING AUTOMOTIVE AERODYNAMICS 192 7.1.1 A MAJOR CONCERN FOR CAR MANUFACTURERS 192 7.1.2 . EXPERIMENTS ON BLUFF BODIES 192 7.1.3 WAKE FLOW BEHIND A BLUFF BODY 193 7.1.4 DRAG VARIATION WITH THE SLANT ANGLE 194 7.2 THE DRAG REDUCTION PROBLEM 195 7.2.1 DRAG REDUCTION IN THE AUTOMOTIVE INDUSTRY 196 7.2.2 NUMERICAL MODELIZATION 197 7.3 FAST AND GLOBAL OPTIMIZATION METHODS 199 7.3.1 EVOLUTIONARY ALGORITHMS 199 7.3.2 ADAPTIVE HYBRID METHODS (AHM) 201 7.3.3 GENETIC ALGORITHMS WITH APPROXIMATED EVALUATIONS (AGA) 203 7.3.4 VALIDATION ON ANALYTIC TEST FUNCTIONS 205 7.4 CAR DRAG REDUCTION WITH NUMERICAL OPTIMIZATION 207 7.4.1 DESCRIPTION OF THE TEST CASE 207 7.4.2 DETAILS OF THE NUMERICAL SIMULATION 207 7.4.3 NUMERICAL RESULTS 209 7.5 ANOTHER POSSIBLE APPLICATION OF CFD-O: AIRPLANE ENGINES 212 7.5.1 GENERAL DESCRIPTION OF THE OPTIMIZATION CASE 212 7.5.2 DETAILS OF THE COMPUTATION 213 7.5.3 OBTAINED RESULTS/ 213 7.6 CONCLUSION ! 214 REFERENCES 214 CONTENTS XI 8 MULTI-OBJECTIVE OPTIMIZATION FOR PROBLEMS INVOLVING CONVECTIVE HEAT TRANSFER 217 MARCO MANZAN, ENRICO NOBILE, STEFANO PIERI AND FRANCESCO PINTO 8.1 INTRODUCTION -. 218 8.2 LITERATURE REVIEW 219 8.3 PROBLEM STATEMENT 222 8.3.1 GOVERNING EQUATIONS 223 8.3.2 FLUID DYNAMIC BOUNDARY CONDITIONS 224 8.3.3 TEMPERATURE BOUNDARY CONDITIONS 225 8.4 NUMERICAL METHODS 228 8.4.1 FLUID DYNAMIC ITERATIVE SOLUTION 228 8.4.2 THERMAL FIELD ITERATIVE SOLUTION 229 8.5 GEOMETRY PARAMETRIZATION 231 8.5.1 WAVY CHANNELS 231 8.5.2 CC MODULE 234 8.6 OPTIMIZATION METHODS 235 8.6.1 DESIGN OF EXPERIMENT 238 8.7 OPTIMIZATION ALGORITHMS 239 8.7.1 GENETIC ALGORITHM 242 8.7.2 MULTI-OBJECTIVE APPROACHES 243 8.7.3 MULTI-CRITERIA DECISION MAKING (MCDM) 246 8.7.4 OPTIMIZATION PROCESS 247 8.8 RESULTS AND DISCUSSION 249 8.8.1 LINEAR PIECEWISE OPTIMIZATION 249 8.8.2 NURBS OPTIMIZATION 250 8.8.3 LINEAR PIECEWISE VERSUS NURBS 255 8.8.4 THREE-DIMENSIONAL ANALYSIS 256 8.8.5 CC MODULE 258 8.9 CONCLUDING REMARKS 262 REFERENCES 263 9 CFD-BASED OPTIMIZATION FOR A COMPLETE INDUSTRIAL PROCESS: PAPERMAKING 267 JARI HAMALAINEN, TAIJA HAMALAINEN, ELINA MADETOJA AND HENRI RUOTSALAINEN 9.1 INTRODUCTION J. 267 9.2 OPTIMAL SHAPE DESIGN OF THE TAPERED HEADER 269 9.3 OPTIMAL CONTROL OF THE FIBER;ORIENTATION IN THE SLICE CHANNEL 1 272 9.3.1 ON MODELING FIBER ORIENTATION 272 9.3.2 HOCS FIBER - A TROUBLE SHOOTING TOOL 273 9.3.3 DEPTH-AVERAGED NAVIER-STOKES EQUATIONS 274 9.3.4 VALIDATION OF THE DEPTH-AVERAGED NAVIER-STOKES EQUATIONS 276 9.4 MULTI-OBJECTIVE OPTIMIZATION OF PAPERMAKING 278 XII CONTENTS 9.4.1 MULTI-OBJECTIVE OPTIMIZATION 279 9.4.2 MODELING AND OPTIMIZING THE COMPLETE PAPERMAKING PROCESS 281 9.4.3 NUMERICAL EXAMPLES 284 9.5 TOWARDS DECISION SUPPORT SYSTEMS 286 9.6 CONCLUSIONS 287 REFERENCES 288 INDEX 291
adam_txt	DOMINIQUE THEVENIN * GABOR JANIGA EDITORS OPTIMIZATION AND COMPUTATIONAL FLUID DYNAMICS 4Y SPRINGER CONTENTS PART I GENERALITIES AND METHODS 1 INTRODUCTION 3 DOMINIQUE THEVENIN REFERENCES 16 2 A FEW ILLUSTRATIVE EXAMPLES OF CFD-BASED OPTIMIZATION . 17 GABOR JANIGA 2.1 INTRODUCTION 18 2.1.1 PURPOSE 18 2.1.2 HEAT EXCHANGER OPTIMIZATION (CASE A) 19 2.1.3 OPTIMIZATION COUPLED WITH CHEMICAL REACTIONS (CASE B) 21 2.1.4 DETERMINATION OF TURBULENCE MODEL PARAMETERS BASED ON OPTIMIZATION (CASE C) 22 2.2 EVOLUTIONARY ALGORITHMS FOR MULTI-OBJECTIVE OPTIMIZATION 23 2.2.1 MULTI-OBJECTIVE OPTIMIZATION 23 2.2.2 THE CONCEPT OF PARETO DOMINANCE 25 2.2.3 EVOLUTIONARY ALGORITHM FOR MULTI-OBJECTIVE PROBLEMS 26 2.3 THE OPTIMAL POSITION OF THE TUBES IN A HEAT EXCHANGER (CASE A) ' 28 2.3.1 TUBE BANK HEAT EXCHANGER 28 2.3.2 PROBLEM PARAMETERS. . .' 29 2.3.3 OPAL (OPTIMIZATION ALGORITHMS) PACKAGE 29 2.3.4 EVALUATION OF THE OBJECTIVES FOR CASE A 30 2.3.5 PARALLELIZATION /* 33 2.3.6 COMPUTATIONAL RESULTS 34 2.4 MULTI-OBJECTIVE OPTIMIZATION OF A LAMINAR BURNER (CASE B) 38 CONTENTS 2.4.1 GOVERNING EQUATIONS 38 2.4.2 NUMERICAL SOLUTION 40 2.4.3 OPTIMIZATION OF THE LAMINAR BURNER 42 2.5 OPTIMIZATION OF THE STANDARD K-U TURBULENCE MODEL PARAMETERS (CASE C) 46 2.5.1 GOVERNING EQUATIONS 48 2.5.2 NUMERICAL RESULTS 50 2.6 CONCLUSIONS 52 REFERENCES 56 MATHEMATICAL ASPECTS OF CFD-BASED OPTIMIZATION 61 HANS GEORG BOCK AND VOLKER SCHULZ 3.1 INTRODUCTION 62 3.2 SIMULTANEOUS MODEL-BASED OPTIMIZATION 63 3.2.1 SEQUENTIAL QUADRATIC PROGRAMMING (SQP) 63 3.2.2 MODULAR SQP METHODS 65 3.2.3 MULTIPLE SET-POINT OPTIMIZATION 69 3.2.4 MULTIGRID OPTIMIZATION 70 3.3 UNSTEADY PROBLEMS 72 3.3.1 TIME-DOMAIN DECOMPOSITION BY MULTIPLE SHOOTING 73 3.3.2 PARALLEL MULTIPLE SHOOTING 75 3.3.3 REAL-TIME OPTIMIZATION AND NONLINEAR MODEL PREDICTIVE CONTROL 75 3.3.4 SENSITIVITY DRIVEN MULTIPLE SHOOTING 76 REFERENCES 77 ADJOINT METHODS FOR SHAPE OPTIMIZATION 79 KYRIAKOS C. GIANNAKOGLOU AND DIMITRIOS I. PAPADIMITRIOU 4.1 INTRODUCTION 80 4.2 PRINCIPLES OF THE ADJOINT APPROACH 83 4.2.1 THE DISCRETE ADJOINT APPROACH 83 4.2.2 THE CONTINUOUS ADJOINT APPROACH 84 4.2.3 DIFFERENCES BETWEEN DISCRETE AND CONTINUOUS ADJOINT 85 4.3 INVERSE DESIGN USING THE'EULER EQUATIONS 86 4.4 INVERSE DESIGN USING THE NAVIER-STOKES EQUATIONS 90 4.5 VISCOUS LOSSES MINIMIZATION IN INTERNAL FLOWS 91 4.5.1 MINIMIZATION OF TOTAL PRESSURE LOSSES 92 4.5.2 MINIMIZATION OF ENTROPY GENERATION 93 4.6 COMPUTATION OF THE HESSIAN MATRIX 94 4.6.1 DISCRETE DIREOVADJOINT APPROACH FOR THE HESSIAN. 95 4.6.2 CONTINUOUS DIRECT-ADJOINT APPROACH FOR THE HESSIAN (INVERSE DESIGN) 96 4.7 APPLICATIONS 97 CONTENTS IX 4.7.1 GRADIENT AND HESSIAN-BASED INVERSE DESIGN OF A 2D DUCT 97 4.7.2 LOSSES MINIMIZATION OF A 2D COMPRESSOR CASCADE 99 4.8 CONCLUSIONS 104 REFERENCES 106 PART II SPECIFIC APPLICATIONS OF CFD-BASED OPTIMIZATION TO ENGINEERING PROBLEMS 5 EFFICIENT DETERMINISTIC APPROACHES FOR AERODYNAMIC SHAPE OPTIMIZATION ILL NICOLAS R. GAUGER 5.1 INTRODUCTION 112 5.2 PARAMETERIZATION BY DEFORMATION 113 5.2.1 SURFACE DEFORMATION 114 5.2.2 GRID DEFORMATION 115 5.3 SENSITIVITY-BASED AERODYNAMIC SHAPE OPTIMIZATION 117 5.4 SENSITIVITY COMPUTATIONS 119 5.4.1 FINITE DIFFERENCE METHOD 119 5.4.2 CONTINUOUS ADJOINT FORMULATION 120 5.4.3 ALGORITHMIC DIFFERENTIATION (AD) 122 5.5 ADJOINT FLOW SOLVERS 124 5.5.1 CONTINUOUS ADJOINT FLOW SOLVERS 124 5.5.2 DISCRETE ADJOINT FLOW SOLVERS 125 5.6 AUTOMATIC DIFFERENTIATION APPLIED TO AN ENTIRE DESIGN CHAIN 126 5.6.1 TEST CASE DEFINITION 127 5.6.2 FINITE DIFFERENCES 127 5.6.3 AUTOMATIC DIFFERENTIATION 132 5.7 ADJOINT APPROCH FOR AERO-STRUCTURE COUPLING 133 5.7.1 ADJOINT FORMULATION FOR AERO-STRUCTURE COUPLING 133 5.7.2 IMPLEMENTATION 140 5.7.3 VALIDATION AND APPLICATION 141 5.8 ONE-SHOT METHODS J 142 REFERENCES 144 6 NUMERICAL OPTIMIZATION FOR ADVANCED TURBOMACHINERY DESIGN 147 RENE A. VAN DEN BRAEMBUSSCHE 6.1 INTRODUCTION . /. 147 6.2 OPTIMIZATION METHODS . F 150 6.2.1 SEARCH MECHANISMS 150 6.2.2 OBJECTIVE FUNCTION 156 CONTENTS 6.2.3 PARAMETERIZATION 159 6.3 TWO-LEVEL OPTIMIZATION 160 6.3.1 ARTIFICIAL NEURAL NETWORKS 162 6.3.2 DATABASE 164 6.4 SINGLE POINT OPTIMIZATION OF TURBINE BLADE 166 6.4.1 2D BLADE GEOMETRY DEFINITION 166 6.4.2 PENALTY FOR NON-OPTIMUM MACH NUMBER DISTRIBUTION PMACH 168 6.4.3 DESIGN OF A TRANSONIC TURBINE BLADE 170 6.5 MULTIPOINT OPTIMIZATION OF A LOW SOLIDITY DIFFUSER 172 6.6 MULTIDISCIPLINARY OPTIMIZATION 175 6.6.1 3D GEOMETRY DEFINITION 176 6.6.2 MULTIDISCIPLINARY OBJECTIVE FUNCTION 178 6.6.3 DESIGN CONDITIONS AND RESULTS 180 6.7 CONCLUSIONS 187 REFERENCES 188 CFD-BASED OPTIMIZATION FOR AUTOMOTIVE AERODYNAMICS . 191 LAURENT DUMAS 7.1 INTRODUCING AUTOMOTIVE AERODYNAMICS 192 7.1.1 A MAJOR CONCERN FOR CAR MANUFACTURERS 192 7.1.2 . EXPERIMENTS ON BLUFF BODIES 192 7.1.3 WAKE FLOW BEHIND A BLUFF BODY 193 7.1.4 DRAG VARIATION WITH THE SLANT ANGLE 194 7.2 THE DRAG REDUCTION PROBLEM 195 7.2.1 DRAG REDUCTION IN THE AUTOMOTIVE INDUSTRY 196 7.2.2 NUMERICAL MODELIZATION 197 7.3 FAST AND GLOBAL OPTIMIZATION METHODS 199 7.3.1 EVOLUTIONARY ALGORITHMS 199 7.3.2 ADAPTIVE HYBRID METHODS (AHM) 201 7.3.3 GENETIC ALGORITHMS WITH APPROXIMATED EVALUATIONS (AGA) 203 7.3.4 VALIDATION ON ANALYTIC TEST FUNCTIONS 205 7.4 CAR DRAG REDUCTION WITH NUMERICAL OPTIMIZATION 207 7.4.1 DESCRIPTION OF THE TEST CASE 207 7.4.2 DETAILS OF THE NUMERICAL SIMULATION 207 7.4.3 NUMERICAL RESULTS 209 7.5 ANOTHER POSSIBLE APPLICATION OF CFD-O: AIRPLANE ENGINES 212 7.5.1 GENERAL DESCRIPTION OF THE OPTIMIZATION CASE 212 7.5.2 DETAILS OF THE COMPUTATION 213 7.5.3 OBTAINED RESULTS/ 213 7.6 CONCLUSION ! 214 REFERENCES 214 CONTENTS XI 8 MULTI-OBJECTIVE OPTIMIZATION FOR PROBLEMS INVOLVING CONVECTIVE HEAT TRANSFER 217 MARCO MANZAN, ENRICO NOBILE, STEFANO PIERI AND FRANCESCO PINTO 8.1 INTRODUCTION -. 218 8.2 LITERATURE REVIEW 219 8.3 PROBLEM STATEMENT 222 8.3.1 GOVERNING EQUATIONS 223 8.3.2 FLUID DYNAMIC BOUNDARY CONDITIONS 224 8.3.3 TEMPERATURE BOUNDARY CONDITIONS 225 8.4 NUMERICAL METHODS 228 8.4.1 FLUID DYNAMIC ITERATIVE SOLUTION 228 8.4.2 THERMAL FIELD ITERATIVE SOLUTION 229 8.5 GEOMETRY PARAMETRIZATION 231 8.5.1 WAVY CHANNELS 231 8.5.2 CC MODULE 234 8.6 OPTIMIZATION METHODS 235 8.6.1 DESIGN OF EXPERIMENT 238 8.7 OPTIMIZATION ALGORITHMS 239 8.7.1 GENETIC ALGORITHM 242 8.7.2 MULTI-OBJECTIVE APPROACHES 243 8.7.3 MULTI-CRITERIA DECISION MAKING (MCDM) 246 8.7.4 OPTIMIZATION PROCESS 247 8.8 RESULTS AND DISCUSSION 249 8.8.1 LINEAR PIECEWISE OPTIMIZATION 249 8.8.2 NURBS OPTIMIZATION 250 8.8.3 LINEAR PIECEWISE VERSUS NURBS 255 8.8.4 THREE-DIMENSIONAL ANALYSIS 256 8.8.5 CC MODULE 258 8.9 CONCLUDING REMARKS 262 REFERENCES 263 9 CFD-BASED OPTIMIZATION FOR A COMPLETE INDUSTRIAL PROCESS: PAPERMAKING 267 JARI HAMALAINEN, TAIJA HAMALAINEN, ELINA MADETOJA AND HENRI RUOTSALAINEN 9.1 INTRODUCTION J. 267 9.2 OPTIMAL SHAPE DESIGN OF THE TAPERED HEADER 269 9.3 OPTIMAL CONTROL OF THE FIBER;ORIENTATION IN THE SLICE CHANNEL 1 272 9.3.1 ON MODELING FIBER ORIENTATION 272 9.3.2 HOCS FIBER - A TROUBLE SHOOTING TOOL 273 9.3.3 DEPTH-AVERAGED NAVIER-STOKES EQUATIONS 274 9.3.4 VALIDATION OF THE DEPTH-AVERAGED NAVIER-STOKES EQUATIONS 276 9.4 MULTI-OBJECTIVE OPTIMIZATION OF PAPERMAKING 278 XII CONTENTS 9.4.1 MULTI-OBJECTIVE OPTIMIZATION 279 9.4.2 MODELING AND OPTIMIZING THE COMPLETE PAPERMAKING PROCESS 281 9.4.3 NUMERICAL EXAMPLES 284 9.5 TOWARDS DECISION SUPPORT SYSTEMS 286 9.6 CONCLUSIONS 287 REFERENCES 288 INDEX 291
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id	DE-604.BV023073680
illustrated	Illustrated
index_date	2024-07-02T19:34:05Z
indexdate	2024-07-09T21:10:23Z
institution	BVB
isbn	9783540721529 9783540721536
language	English
oai_aleph_id	oai:aleph.bib-bvb.de:BVB01-016276802
oclc_num	154712288
open_access_boolean
owner	DE-29T DE-703 DE-91 DE-BY-TUM DE-634
owner_facet	DE-29T DE-703 DE-91 DE-BY-TUM DE-634
physical	XIV, 293 S. Ill., graph. Darst.
publishDate	2008
publishDateSearch	2008
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publisher	Springer
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spelling	Optimization and computational fluid dynamics Dominique Thévenin ... ed. Berlin [u.a.] Springer 2008 XIV, 293 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Computação aplicada larpcal Dinâmica dos fluídos larpcal Mathematisches Modell Fluid dynamics Mathematical models Mathematical optimization Numerische Strömungssimulation (DE-588)4690080-9 gnd rswk-swf Technisches System (DE-588)4126276-1 gnd rswk-swf Optimierung (DE-588)4043664-0 gnd rswk-swf Technisches System (DE-588)4126276-1 s Optimierung (DE-588)4043664-0 s Numerische Strömungssimulation (DE-588)4690080-9 s DE-604 Thévenin, Dominique 1966- Sonstige (DE-588)134097807 oth HEBIS Datenaustausch Darmstadt application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016276802&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
spellingShingle	Optimization and computational fluid dynamics Computação aplicada larpcal Dinâmica dos fluídos larpcal Mathematisches Modell Fluid dynamics Mathematical models Mathematical optimization Numerische Strömungssimulation (DE-588)4690080-9 gnd Technisches System (DE-588)4126276-1 gnd Optimierung (DE-588)4043664-0 gnd
subject_GND	(DE-588)4690080-9 (DE-588)4126276-1 (DE-588)4043664-0
title	Optimization and computational fluid dynamics
title_auth	Optimization and computational fluid dynamics
title_exact_search	Optimization and computational fluid dynamics
title_exact_search_txtP	Optimization and computational fluid dynamics
title_full	Optimization and computational fluid dynamics Dominique Thévenin ... ed.
title_fullStr	Optimization and computational fluid dynamics Dominique Thévenin ... ed.
title_full_unstemmed	Optimization and computational fluid dynamics Dominique Thévenin ... ed.
title_short	Optimization and computational fluid dynamics
title_sort	optimization and computational fluid dynamics
topic	Computação aplicada larpcal Dinâmica dos fluídos larpcal Mathematisches Modell Fluid dynamics Mathematical models Mathematical optimization Numerische Strömungssimulation (DE-588)4690080-9 gnd Technisches System (DE-588)4126276-1 gnd Optimierung (DE-588)4043664-0 gnd
topic_facet	Computação aplicada Dinâmica dos fluídos Mathematisches Modell Fluid dynamics Mathematical models Mathematical optimization Numerische Strömungssimulation Technisches System Optimierung
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016276802&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
work_keys_str_mv	AT thevenindominique optimizationandcomputationalfluiddynamics

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