Ebook: Surrogate-Based Modeling and Optimization: Applications in Engineering

Contemporary engineering design is heavily based on computer simulations. Accurate, high-fidelity simulations are used not only for design verification but, even more importantly, to adjust parameters of the system to have it meet given performance requirements. Unfortunately, accurate simulations are often computationally very expensive with evaluation times as long as hours or even days per design, making design automation using conventional methods impractical. These and other problems can be alleviated by the development and employment of so-called surrogates that reliably represent the expensive, simulation-based model of the system or device of interest but they are much more reasonable and analytically tractable.

This volume features surrogate-based modeling and optimization techniques, and their applications for solving difficult and computationally expensive engineering design problems. It begins by presenting the basic concepts and formulations of the surrogate-based modeling and optimization paradigm and then discusses relevant modeling techniques, optimization algorithms and design procedures, as well as state-of-the-art developments. The chapters are self-contained with basic concepts and formulations along with applications and examples. The book will be useful to researchers in engineering and mathematics, in particular those who employ computationally heavy simulations in their design work.

Contemporary engineering design is heavily based on computer simulations. Accurate, high-fidelity simulations are used not only for design verification but, even more importantly, to adjust parameters of the system to have it meet given performance requirements. Unfortunately, accurate simulations are often computationally very expensive with evaluation times as long as hours or even days per design, making design automation using conventional methods impractical. These and other problems can be alleviated by the development and employment of so-called surrogates that reliably represent the expensive, simulation-based model of the system or device of interest but they are much more reasonable and analytically tractable.

This book is about surrogate-based modeling and optimization techniques, and their applications for solving difficult and computationally expensive engineering design problems. It begins by presenting the basic concepts and formulations of the surrogate-based modeling and optimization paradigm and then discusses relevant modeling techniques, optimization algorithms and design procedures, as well as state-of-the-art developments. The chapters are self-contained with basic concepts and formulations along with applications and examples. The book will be useful to researchers in engineering and mathematics, in particular those who employ computationally heavy simulations in their design work.

Contemporary engineering design is heavily based on computer simulations. Accurate, high-fidelity simulations are used not only for design verification but, even more importantly, to adjust parameters of the system to have it meet given performance requirements. Unfortunately, accurate simulations are often computationally very expensive with evaluation times as long as hours or even days per design, making design automation using conventional methods impractical. These and other problems can be alleviated by the development and employment of so-called surrogates that reliably represent the expensive, simulation-based model of the system or device of interest but they are much more reasonable and analytically tractable.

This book is about surrogate-based modeling and optimization techniques, and their applications for solving difficult and computationally expensive engineering design problems. It begins by presenting the basic concepts and formulations of the surrogate-based modeling and optimization paradigm and then discusses relevant modeling techniques, optimization algorithms and design procedures, as well as state-of-the-art developments. The chapters are self-contained with basic concepts and formulations along with applications and examples. The book will be useful to researchers in engineering and mathematics, in particular those who employ computationally heavy simulations in their design work.

Content:
Front Matter....Pages I-VIII
Space Mapping for Electromagnetic-Simulation-Driven Design Optimization....Pages 1-25
Surrogate-Based Circuit Design Centering....Pages 27-49
Simulation-Driven Antenna Design Using Surrogate-Based Optimization....Pages 51-80
Practical Application of Space Mapping Techniques to the Synthesis of CSRR-Based Artificial Transmission Lines....Pages 81-97
The Efficiency of Difference Mapping in Space Mapping-Based Optimization....Pages 99-120
Bayesian Support Vector Regression Modeling of Microwave Structures for Design Applications....Pages 121-145
Artificial Neural Networks and Space Mapping for EM-Based Modeling and Design of Microwave Circuits....Pages 147-169
Model-Based Variation-Aware Integrated Circuit Design....Pages 171-188
Computing Surrogates for Gas Network Simulation Using Model Order Reduction....Pages 189-212
Aerodynamic Shape Optimization by Space Mapping....Pages 213-245
Efficient Robust Design with Stochastic Expansions....Pages 247-284
Surrogate Models for Aerodynamic Shape Optimisation....Pages 285-312
Knowledge-Based Surrogate Modeling in Engineering Design Optimization....Pages 313-336
Switching Response Surface Models for Structural Health Monitoring of Bridges....Pages 337-358
Surrogate Modeling of Stability Constraints for Optimization of Composite Structures....Pages 359-391
Engineering Optimization and Industrial Applications....Pages 393-412

Contemporary engineering design is heavily based on computer simulations. Accurate, high-fidelity simulations are used not only for design verification but, even more importantly, to adjust parameters of the system to have it meet given performance requirements. Unfortunately, accurate simulations are often computationally very expensive with evaluation times as long as hours or even days per design, making design automation using conventional methods impractical. These and other problems can be alleviated by the development and employment of so-called surrogates that reliably represent the expensive, simulation-based model of the system or device of interest but they are much more reasonable and analytically tractable.

This book is about surrogate-based modeling and optimization techniques, and their applications for solving difficult and computationally expensive engineering design problems. It begins by presenting the basic concepts and formulations of the surrogate-based modeling and optimization paradigm and then discusses relevant modeling techniques, optimization algorithms and design procedures, as well as state-of-the-art developments. The chapters are self-contained with basic concepts and formulations along with applications and examples. The book will be useful to researchers in engineering and mathematics, in particular those who employ computationally heavy simulations in their design work.

Content:
Front Matter....Pages I-VIII
Space Mapping for Electromagnetic-Simulation-Driven Design Optimization....Pages 1-25
Surrogate-Based Circuit Design Centering....Pages 27-49
Simulation-Driven Antenna Design Using Surrogate-Based Optimization....Pages 51-80
Practical Application of Space Mapping Techniques to the Synthesis of CSRR-Based Artificial Transmission Lines....Pages 81-97
The Efficiency of Difference Mapping in Space Mapping-Based Optimization....Pages 99-120
Bayesian Support Vector Regression Modeling of Microwave Structures for Design Applications....Pages 121-145
Artificial Neural Networks and Space Mapping for EM-Based Modeling and Design of Microwave Circuits....Pages 147-169
Model-Based Variation-Aware Integrated Circuit Design....Pages 171-188
Computing Surrogates for Gas Network Simulation Using Model Order Reduction....Pages 189-212
Aerodynamic Shape Optimization by Space Mapping....Pages 213-245
Efficient Robust Design with Stochastic Expansions....Pages 247-284
Surrogate Models for Aerodynamic Shape Optimisation....Pages 285-312
Knowledge-Based Surrogate Modeling in Engineering Design Optimization....Pages 313-336
Switching Response Surface Models for Structural Health Monitoring of Bridges....Pages 337-358
Surrogate Modeling of Stability Constraints for Optimization of Composite Structures....Pages 359-391
Engineering Optimization and Industrial Applications....Pages 393-412
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