Design Optimization in Computational Mechanics
(Sprache: Englisch)
This book provides a comprehensive introduction to the mathematical and algorithmic methods for the Multidisciplinary Design Optimization (MDO) of complex mechanical systems such as aircraft or car engines.
We have focused on the presentation of strategies...
We have focused on the presentation of strategies...
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Klappentext zu „Design Optimization in Computational Mechanics “
This book provides a comprehensive introduction to the mathematical and algorithmic methods for the Multidisciplinary Design Optimization (MDO) of complex mechanical systems such as aircraft or car engines.We have focused on the presentation of strategies efficiently and economically managing the different levels of complexity in coupled disciplines (e.g. structure, fluid, thermal, acoustics, etc.), ranging from Reduced Order Models (ROM) to full-scale Finite Element (FE) or Finite Volume (FV) simulations. Particular focus is given to the uncertainty quantification and its impact on the robustness of the optimal designs. A large collection of examples from academia, software editing and industry should also help the reader to develop a practical insight on MDO methods.
We assume that the audience has some previous exposure to computational mechanics and optimization. Formal coursework in basic optimization algorithms and simulation methods would be helpful, but is not essential, as the concepts are progressively introduced throughout the text.
The book may by used in a graduate-level course on MDO for students, engineers and researchers, and in industrial short courses and seminars for a wide variety of technical backgrounds.
This book provides a comprehensive introduction to the mathematical and algorithmic methods for the Multidisciplinary Design Optimization (MDO) of complex mechanical systems such as aircraft or car engines.
We have focused on the presentation of strategies efficiently and economically managing the different levels of complexity in coupled disciplines (e.g. structure, fluid, thermal, acoustics, etc.), ranging from Reduced Order Models (ROM) to full-scale Finite Element (FE) or Finite Volume (FV) simulations. Particular focus is given to the uncertainty quantification and its impact on the robustness of the optimal designs. A large collection of examples from academia, software editing and industry should also help the reader to develop a practical insight on MDO methods.
We assume that the audience has some previous exposure to computational mechanics and optimization. Formal coursework in basic optimization algorithms and simulation methods would be helpful, but is not essential, as the concepts are progressively introduced throughout the text.
The book may by used in a graduate-level course on MDO for students, engineers and researchers, and in industrial short courses and seminars for a wide variety of technical backgrounds.
We have focused on the presentation of strategies efficiently and economically managing the different levels of complexity in coupled disciplines (e.g. structure, fluid, thermal, acoustics, etc.), ranging from Reduced Order Models (ROM) to full-scale Finite Element (FE) or Finite Volume (FV) simulations. Particular focus is given to the uncertainty quantification and its impact on the robustness of the optimal designs. A large collection of examples from academia, software editing and industry should also help the reader to develop a practical insight on MDO methods.
We assume that the audience has some previous exposure to computational mechanics and optimization. Formal coursework in basic optimization algorithms and simulation methods would be helpful, but is not essential, as the concepts are progressively introduced throughout the text.
The book may by used in a graduate-level course on MDO for students, engineers and researchers, and in industrial short courses and seminars for a wide variety of technical backgrounds.
Inhaltsverzeichnis zu „Design Optimization in Computational Mechanics “
Foreword xvNotes for Instructors xix
Acknowledgements xxi
Chapter 1. Multilevel Multidisciplinary Optimization in Airplane Design 1
Michel RAVACHOL
1.1. Introduction 1
1.2. Overview of the traditional airplane design process and expected MDO contributions 2
1.3. First step toward MDO: local dimensioning by mathematical optimization 4
1.4. Second step toward MDO: multilevel multidisciplinary dimensioning 4
1.5. Elements of an MDO process 7
1.6. Choice of optimizers 9
1.7. Coupling between levels 11
1.8. Post-processing 13
1.9. Conclusion 16
Chapter 2. Response Surface Methodology and Reduced Order Models 17
Manuel SAMUELIDES
2.1. Introduction 17
2.2. Introducing some more notations 20
2.3. Linear regression 21
2.4. Non-linear regression 26
2.5. Kriging interpolation 35
2.6. Non-parametric regression and kernel-based methods 37
2.7. Support vector regression 45
2.8. Model selection 56
2.9. Introduction to design of computer experiments (DoCE) 59
2.10. Bibliography 62
Chapter 3. PDE Metamodeling using Principal Component Analysis 65
Florian DE VUYST
3.1. Principal component analysis (PCA) 68
3.2. Truncation rank and projector error 71
3.3. Application: POD reduction of velocity fields in an engine combustion chamber 74
3.4. Reduced-basis methods, numerical analysis 78
3.5. Intrusive/non-intrusive aspects 86
3.6. Double reduction in both space and parameter dimensions 87
3.7. The weighted residual method 88
3.8. Non-linear problems 90
3.9. General discussion and comparison of surrogates 99
3.10. A numerical example 102
3.11. Time-dependent problems 107
3.12. Numerical analysis of a linear spatio-temporal PDE problem 110
3.13. Related works and complementary bibliography 114
3.14. Bibliography 115
Chapter 4. Reduced-order Models for Coupled Problems 119
Rajan FILOMENO COELHO, Manyu XIAO, Piotr BREITKOPF, Catherine KNOPF-LENOIR, Pierre VILLON and
... mehr
Maryan SIDORKIEWICZ
4.1. Introduction 119
4.2. Model reduction methods for coupled problems 122
4.3. Application 1: MDO of an aeroelastic 2D wing demonstrator 129
4.4. Application 2: MDO of an aeroelastic 3D wing in transonic flow 156
4.5. Application 3: Multiobjective shape optimization of an intake port 173
4.6. Conclusions 193
4.7. Bibliography 194
Chapter 5. Multilevel Modeling 199
Pierre-Alain BOUCARD, Sandrine BUYTET, Bruno SOULIER, Praveen CHANDRASHEKARAPPA and Régis DUVIGNEAU
5.1. Introduction 199
5.2. Notations and vocabulary 200
5.3. Parallel model optimization 204
5.4. Multilevel parameter optimization 205
5.5. Multilevel model optimization 210
5.6. General resolution strategy 215
5.7. Use of the multiscale approach in multilevel optimization 218
5.8. A multilevel method for aerodynamics using an inexact pre-evaluation approach 231
5.9. Numerical examples 237
5.10. Conclusion 258
5.11. Bibliography 260
Chapter 6. Multiparameter Shape Optimization 265
Abderrahmane BENZAOUI and Régis DUVIGNEAU
6.1. Introduction 265
6.2. Multilevel optimization 267
6.3. Validation 270
6.4. Applications 275
6.5. Conclusion 283
6.6. Bibliography 284
Chapter 7. Two-discipline Optimization 287
Jean-Antoine DESIDERI
7.1. Pareto optimality, game strategies, and split of territory in multiobjective optimization 288
7.2. Aerostructural shape optimization of a business-jet wing 306
7.3. Conclusions 315
7.4. Bibliography 318
Chapter 8. Collaborative Optimization 321
Yogesh PARTE, Didier AUROUX, Joël CLÉMENT, Mohamed MASMOUDI and Jean HERMETZ
8.1. Introduction 321
8.2. Definition of parameters 322
8.3. Notations and terminology 326
8.4. Different frameworks for multidisciplinary design optimization 332
8.5. Reduced order models and approximations 355
8.6. Application of MDO to conceptual design of supersonic business jets (SSBJ) 356
8.7. Comments and conclusions 3
4.1. Introduction 119
4.2. Model reduction methods for coupled problems 122
4.3. Application 1: MDO of an aeroelastic 2D wing demonstrator 129
4.4. Application 2: MDO of an aeroelastic 3D wing in transonic flow 156
4.5. Application 3: Multiobjective shape optimization of an intake port 173
4.6. Conclusions 193
4.7. Bibliography 194
Chapter 5. Multilevel Modeling 199
Pierre-Alain BOUCARD, Sandrine BUYTET, Bruno SOULIER, Praveen CHANDRASHEKARAPPA and Régis DUVIGNEAU
5.1. Introduction 199
5.2. Notations and vocabulary 200
5.3. Parallel model optimization 204
5.4. Multilevel parameter optimization 205
5.5. Multilevel model optimization 210
5.6. General resolution strategy 215
5.7. Use of the multiscale approach in multilevel optimization 218
5.8. A multilevel method for aerodynamics using an inexact pre-evaluation approach 231
5.9. Numerical examples 237
5.10. Conclusion 258
5.11. Bibliography 260
Chapter 6. Multiparameter Shape Optimization 265
Abderrahmane BENZAOUI and Régis DUVIGNEAU
6.1. Introduction 265
6.2. Multilevel optimization 267
6.3. Validation 270
6.4. Applications 275
6.5. Conclusion 283
6.6. Bibliography 284
Chapter 7. Two-discipline Optimization 287
Jean-Antoine DESIDERI
7.1. Pareto optimality, game strategies, and split of territory in multiobjective optimization 288
7.2. Aerostructural shape optimization of a business-jet wing 306
7.3. Conclusions 315
7.4. Bibliography 318
Chapter 8. Collaborative Optimization 321
Yogesh PARTE, Didier AUROUX, Joël CLÉMENT, Mohamed MASMOUDI and Jean HERMETZ
8.1. Introduction 321
8.2. Definition of parameters 322
8.3. Notations and terminology 326
8.4. Different frameworks for multidisciplinary design optimization 332
8.5. Reduced order models and approximations 355
8.6. Application of MDO to conceptual design of supersonic business jets (SSBJ) 356
8.7. Comments and conclusions 3
... weniger
Bibliographische Angaben
- Autoren: Piotr Breitkopf , Coelho R. Filomeno
- 2010, 1. Auflage, 550 Seiten, Maße: 16,5 x 23,7 cm, Gebunden, Englisch
- Verlag: Wiley & Sons
- ISBN-10: 1848211384
- ISBN-13: 9781848211384
Sprache:
Englisch
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