Simulation-Driven Design by Knowledge-Based Response Correction Techniques

1. Front Matter

   Pages i-xi

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2. Introduction

   • Slawomir Koziel, Leifur Leifsson

   Pages 1-6

3. Simulation-Driven Design

   • Slawomir Koziel, Leifur Leifsson

   Pages 7-13

4. Fundamentals of Numerical Optimization

   • Slawomir Koziel, Leifur Leifsson

   Pages 15-29

5. Introduction to Surrogate Modeling and Surrogate-Based Optimization

   • Slawomir Koziel, Leifur Leifsson

   Pages 31-61

6. Design Optimization Using Response Correction Techniques

   • Slawomir Koziel, Leifur Leifsson

   Pages 63-74

7. Surrogate-Based Optimization Using Parametric Response Correction

   • Slawomir Koziel, Leifur Leifsson

   Pages 75-98

8. Nonparametric Response Correction Techniques

   • Slawomir Koziel, Leifur Leifsson

   Pages 99-129

9. Expedited Simulation-Driven Optimization Using Adaptively Adjusted Design Specifications

   • Slawomir Koziel, Leifur Leifsson

   Pages 131-146

10. Surrogate-Assisted Design Optimization Using Response Features

    • Slawomir Koziel, Leifur Leifsson

    Pages 147-163

11. Enhancing Response Correction Techniques by Adjoint Sensitivity

    • Slawomir Koziel, Leifur Leifsson

    Pages 165-191

12. Multi-objective Optimization Using Variable-Fidelity Models and Response Correction

    • Slawomir Koziel, Leifur Leifsson

    Pages 193-210

13. Physics-Based Surrogate Modeling Using Response Correction

    • Slawomir Koziel, Leifur Leifsson

    Pages 211-243

14. Summary and Discussion

    • Slawomir Koziel, Leifur Leifsson

    Pages 245-247

15. Back Matter

    Pages 249-262

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Focused on efficient simulation-driven multi-fidelity optimization techniques, this monograph on simulation-driven optimization covers simulations utilizing physics-based low-fidelity models, often based on coarse-discretization simulations or other types of simplified physics representations, such as analytical models. The methods presented in the book exploit as much as possible any knowledge about the system or device of interest embedded in the low-fidelity model with the purpose of reducing the computational overhead of the design process. Most of the techniques described in the book are of response correction type and can be split into parametric (usually based on analytical formulas) and non-parametric, i.e., not based on analytical formulas. The latter, while more complex in implementation, tend to be more efficient.

The book presents a general formulation of response correction techniques as well as a number of specific methods, including those based on correcting the low-fidelity model response (output space mapping, manifold mapping, adaptive response correction and shape-preserving response prediction), as well as on suitable modification of design specifications. Detailed formulations, application examples and the discussion of advantages and disadvantages of these techniques are also included. The book demonstrates the use of the discussed techniques for solving real-world engineering design problems, including applications in microwave engineering, antenna design, and aero/hydrodynamics.

• simulation-based optimization
• computer simulation
• multi-fidelity optimization
• simulation-driven design
• numerical optimization
• surrogate modeling
• response correction techniques
• parametric response correction
• adaptively adjusted design specifications
• variable-fidelity models

• Eng. Optimization & Modeling Center, Reykjavik University, Reykjavik, Iceland

  Slawomir Koziel

• College of Engineering, Iowa State University, Ames, USA

  Leifur Leifsson

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