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Simulation-Driven Modeling and Optimization

ASDOM, Reykjavik, August 2014

  • Conference proceedings
  • © 2016

Overview

Editors:
  1. Slawomir Koziel

    1. Engin. Optimization & Modeling Cent, Reykjavik University, Reykjavik, Iceland

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  2. Leifur Leifsson

    1. College of Engineering, Iowa State University, Ames, USA

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  3. Xin-She Yang

    1. School of Science and Technology, Middlesex University, London, United Kingdom

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  • Presents strategies for enhancing automated simulation-driven modeling design practices
  • Highlights invaluable techniques for areas such as engineering, hydrodynamics, ocean science and climate modeling, where design processes are rooted in CPU-heavy computer simulations
  • Accessible with only a working knowledge of calculus and numerical modeling and optimization

Part of the book series: Springer Proceedings in Mathematics & Statistics (PROMS, volume 153)

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Table of contents (15 papers)

  1. Front Matter

    Pages i-viii
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  2. Numerical Aspects of Model Order Reduction for Gas Transportation Networks

    • Sara Grundel, Nils Hornung, Sarah Roggendorf
    Pages 1-28

  3. Parameter Studies for Energy Networks with Examples from Gas Transport

    • Tanja Clees
    Pages 29-54

  4. Fast Multi-Objective Aerodynamic Optimization Using Space-Mapping-Corrected Multi-Fidelity Models and Kriging Interpolation

    • Leifur Leifsson, Slawomir Koziel, Yonatan Tesfahunegn, Adrian Bekasiewicz
    Pages 55-73

  5. Assessment of Inverse and Direct Methods for Airfoil and Wing Design

    • Mengmeng Zhang, Arthur William Rizzi
    Pages 75-109

  6. Performance Optimization of EBG-Based Common Mode Filters for Signal Integrity Applications

    • Carlo Olivieri, Francesco de Paulis, Antonio Orlandi, Slawomir Koziel
    Pages 111-133

  7. Unattended Design of Wideband Planar Filters Using a Two-Step Aggressive Space Mapping (ASM) Optimization Algorithm

    • Marc Sans, Jordi Selga, Ana Rodríguez, Paris Vélez, Vicente E. Boria, Jordi Bonache et al.
    Pages 135-159

  8. Two-Stage Gaussian Process Modeling of Microwave Structures for Design Optimization

    • J. Pieter Jacobs, Slawomir Koziel
    Pages 161-184

  9. Efficient Reconfigurable Microstrip Patch Antenna Modeling Exploiting Knowledge Based Artificial Neural Networks

    • Murat Simsek, Ashrf Aoad
    Pages 185-206

  10. Expedited Simulation-Driven Multi-Objective Design Optimization of Quasi-Isotropic Dielectric Resonator Antenna

    • Adrian Bekasiewicz, Slawomir Koziel, Wlodzimierz Zieniutycz, Leifur Leifsson
    Pages 207-231

  11. Optimal Design of Photonic Crystal Nanostructures

    • Abdel-Karim S. O. Hassan, Nadia H. Rafat, Ahmed S. A. Mohamed
    Pages 233-260

  12. Design Optimization of LNAs and Reflectarray Antennas Using the Full-Wave Simulation-Based Artificial Intelligence Models with the Novel Metaheuristic Algorithms

    • Filiz GüneÅŸ, Salih Demirel, Selahattin Nesil
    Pages 261-298

  13. Stochastic Decision-Making in Waste Management Using a Firefly Algorithm-Driven Simulation-Optimization Approach for Generating Alternatives

    • Raha Imanirad, Xin-She Yang, Julian Scott Yeomans
    Pages 299-323

  14. Linear and Nonlinear System Identification Using Evolutionary Optimisation

    • K. Worden, I. Antoniadou, O. D. Tiboaca, G. Manson, R. J. Barthorpe
    Pages 325-345

  15. A Surrogate-Model-Assisted Evolutionary Algorithm for Computationally Expensive Design Optimization Problems with Inequality Constraints

    • Bo Liu, Qingfu Zhang, Georges Gielen
    Pages 347-370

  16. Sobol Indices for Dimension Adaptivity in Sparse Grids

    • Richard P. Dwight, Stijn G. L. Desmedt, Pejman Shoeibi Omrani
    Pages 371-395

  17. Back Matter

    Pages 397-404
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Keywords

About this book

This edited volume is devoted to the now-ubiquitous use of computational models across most disciplines of engineering and science, led by a trio of world-renowned researchers in the field. Focused on recent advances of modeling and optimization techniques aimed at handling computationally-expensive engineering problems involving simulation models, this book will be an invaluable resource for specialists (engineers, researchers, graduate students) working in areas as diverse as electrical engineering, mechanical and structural engineering, civil engineering, industrial engineering, hydrodynamics, aerospace engineering, microwave and antenna engineering, ocean science and climate modeling, and the automotive industry, where design processes are heavily based on CPU-heavy computer simulations. Various techniques, such as knowledge-based optimization, adjoint sensitivity techniques, and fast replacement models (to name just a few) are explored in-depth along withan array of the latest techniques to optimize the efficiency of the simulation-driven design process.

High-fidelity simulation models allow for accurate evaluations of the devices and systems, which is critical in the design process, especially to avoid costly prototyping stages. Despite this and other advantages, the use of simulation tools in the design process is quite challenging due to associated high computational cost. The steady increase of available computational resources does not always translate into the shortening of the design cycle because of the growing demand for higher accuracy and necessity to simulate larger and more complex systems. For this reason, automated simulation-driven design—while highly desirable—is difficult when using conventional numerical optimization routines which normally require a large number of system simulations, each one already expensive.

Editors and Affiliations

  • Engin. Optimization & Modeling Cent, Reykjavik University, Reykjavik, Iceland

    Slawomir Koziel

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

    Leifur Leifsson

  • School of Science and Technology, Middlesex University, London, United Kingdom

    Xin-She Yang

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