Simulation-Driven Design by Knowledge-Based Response Correction Techniques

Slawomir Koziel, Leifur Leifsson (Autoren)

Buch | Softcover

XI, 262 Seiten

2018 | Softcover reprint of the original 1st ed. 2016
Springer International Publishing (Verlag)
978-3-319-80726-3 (ISBN)

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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.

Introduction.- Simulation-Driven Design.- Fundamentals of Numerical Optimization.- Introduction to Surrogate-Based Modeling and Surrogate-Based Optimization.- Design Optimization Using Response Correction Techniques.- Surrogate-Based Optimization Using Parametric Response Correction.- Non-Parametric Response Correction Techniques.- Expedited Simulation-Driven Optimization Using Adaptively Adjusted Design Specification.- Surrogate-Assisted Design Optimization Using Response Features.- Enhancing Response Correction Techniques by Adjoint Sensitivity.- Multi-Objective Optimization Using Variable-Fidelity Models and Response Correction.- Physics-Base Surrogate Models Using Response Correction.- Summary and Discussion.- References.

Erscheinungsdatum	05.03.2022
Zusatzinfo	XI, 262 p. 167 illus., 93 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	4219 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
Schlagworte	adaptively adjusted design specifications • computer simulation • multi-fidelity optimization • Numerical optimization • parametric response correction • response correction techniques • Simulation-Based Optimization • Simulation-driven design • Surrogate modeling • variable-fidelity models
ISBN-10	3-319-80726-9 / 3319807269
ISBN-13	978-3-319-80726-3 / 9783319807263
Zustand	Neuware