## Simulation-Driven Modeling and Optimization: ASDOM, Reykjavik, August 2014This 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 with an 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. |

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### Contents

1 | |

Parameter Studies for Energy Networks with Examples from Gas Transport | 29 |

Fast MultiObjective Aerodynamic Optimization Using SpaceMappingCorrected MultiFidelity Models and Kriging Interpolation | 55 |

Assessment of Inverse and Direct Methods for Airfoil and Wing Design | 75 |

Performance Optimization of EBGBased Common Mode Filters for Signal Integrity Applications | 110 |

Unattended Design of Wideband Planar Filters Using a TwoStep Aggressive Space Mapping ASM Optimization Algorithm | 135 |

TwoStage Gaussian Process Modeling of Microwave Structures for Design Optimization | 160 |

Efficient Reconfigurable Microstrip Patch Antenna Modeling Exploiting Knowledge Based Artificial Neural Networks | 185 |

Optimal Design of Photonic Crystal Nanostructures | 233 |

Design Optimization of LNAs and Reflectarray Antennas Using the FullWave SimulationBased Artificial Intelligence Models with the Novel Metaheu... | 261 |

Stochastic DecisionMaking in Waste Management Using a Firefly AlgorithmDriven SimulationOptimization Approach for Generating Alternatives | 299 |

Linear and Nonlinear System Identification Using Evolutionary Optimisation | 324 |

A SurrogateModelAssisted Evolutionary Algorithm for Computationally Expensive Design Optimization Problems with Inequality Constraints | 347 |

Sobol Indices for Dimension Adaptivity in Sparse Grids | 371 |

396 | |

Expedited SimulationDriven MultiObjective Design Optimization of QuasiIsotropic Dielectric Resonator Antenna | 207 |

### Other editions - View all

Simulation-Driven Modeling and Optimization: ASDOM, Reykjavik, August 2014 Slawomir Koziel,Leifur Leifsson,Xin-She Yang No preview available - 2016 |

Simulation-Driven Modeling and Optimization: Asdom, Reykjavik, August 2014 Slawomir Koziel,Leifur Leifsson,Xin-She Yang No preview available - 2018 |

### Common terms and phrases

aerodynamic AIAA airfoil analysis antenna applied approach approximation ASM algorithm bandgap bandpass filters circuit coarse model coefficient components computational computationally considered constraints conventional ANN convergence data set defined design optimization design space design variables dielectric differential drag coefficient efficient electromagnetic engineering equations error estimate evolutionary evolutionary algorithms example filter schematic firefly flow Frequency GHz function evaluations Gaussian genetic algorithm geometry GPEEC HBMO high-fidelity high-fidelity model IEEE IEEE Trans initial input iteration Koziel Kriging layers layout low-fidelity model matrix mesh metaheuristic metamodel method microstrip Microw microwave minimax multi-objective optimization nodes noise nonlinear objective function obtained optimal design optimization problem optimum output Pareto front Pareto set particle swarm optimization performance photonic crystal predictive procedure reduced refractive index resonators return loss samples Scenario Section simulation solution space mapping sparse grid specifications Springer structure surrogate model Table target techniques training data values vector