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20th International conference on Microwaves, Radar, and Wireless Communication (MIKON)

作者： Bekasiewicz, A. Zieniutycz, W. Koziel, S. Ogurtsov, S. Gdansk Univ Technol Fac Elect Telecommun & Informat Gdansk Poland Reykjavik Univ Engn Optimizat & Modeling Ctr Reykjavik Iceland

ISBN: (纸本)9788393152520

A methodology for computationally efficient simulation-driven design of microstrip antenna subarrays is presented. Our approach takes into account the effect of the feed (here, a corporate network) on the subarray side-lobe level and allows adjustment of both radiation and reflection responses of the structure under design within a single automated process. This process is realized as surrogate-based optimization that produces designs meeting requirements imposed on both radiation and reflection at the cost of just a few simulations of the high-fidelity model of the structure of interest. Selected optimal designs of microstrip subarrays operating at 10 GHz have been manufactured and validated by measuring their radiation patterns and reflection coefficients.

关键词： Design automation microstrip antenna arrays design optimization patch antennas antenna radiation patterns feeds surrogate-based optimization

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Efficient Design optimization of Compact Dual-Band Microstrip Branch-Line Coupler Using Response Features

Efficient Design Optimization of Compact Dual-Band Microstri...

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IEEE MTT-S International conference on Numerical Electromagnetic and Multiphysics modeling and optimization

作者： Slawomir Koziel Adrian Bekasiewicz Engineering Optimization and Modeling Center Reykjavik University

ISBN: (纸本)9781479968121

In this paper, computationally efficient design optimization of a miniaturized dual-band microstrip branch-line coupler is presented. Our optimization approach relies on suitably extracted features of a highly nonlinear response of the coupler structure under design. By formulating the design objectives in terms of the feature point locations, we carry out iterative optimization of the linear model of the features, embedded in the trust-region framework. Due to only slightly nonlinear dependence of the features on the designable parameters of the circuit, the optimized design satisfying prescribed performance requirements is obtained at the low computational cost of only 24 high-fidelity EM simulations of the structure.

关键词： simulation-driven design Miniaturized microwave circuits Microstrip couplers Dual-band couplers

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modeling and simulation of production of metallothionein and red fluorescent fusion protein by recombinant escherichia coli using LabVIEW

Modeling and simulation of production of metallothionein and...

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2014 International conference on Logistics Engineering, Management and Computer Science, LEMCS 2014

作者： Su, Liangyu School of Electrical and Information Engineering Xu Chang University Xu Chang China

ISBN: (纸本)9789462520103

Genetic algorithm(GA) is a powerful tool for the analysis of the mechanism and dynamic responses of the fermentation process,and for process optimization and automatic *** this research,the structured and unstructured mathematical models and computer simulation of MT production and RFP fluorescence are made,and it is implemented,verified and analyzed in *** result shows that the advantages and the usefulness of the data driven and graphical programming software of LabVIEW in modeling and simulation of biological phenomena. © 2014. The authors - Published by Atlantis Press.

关键词： Genetic algorithms

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Motion simulation and optimization Design of Double-Front Axle Steering System Based on ADAMS

Motion Simulation and Optimization Design of Double-Front Ax...

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IEEE Transportation Electrification conference and Expo (ITEC Asia-Pacific)

作者： Li, Liang Zhang, Chengning Wang, Zhifu Liu, Mingchun Shi, Jianjun Beijing Inst Technol Natl Engn Lab Elect Vehicle Beijing 100081 Peoples R China

ISBN: (纸本)9781479942398

Aiming at the problem that the steering tires were seriously wore on a 8x8 in-wheel motor driven vehicle, a model of McPherson suspension and double-front axle steering system was established by ADAMS. Considering the influences on steering errors caused by wheel jump and using parametric analysis method, the error accumulation between theoretical value and actual value of steering angle, and the sum of variation of toe-in angle were added up for forming the objective optimization function. The simulation and optimization results indicate that this design improves the steering performance and reduces the motion interference between the suspension and steering linkage.

关键词： Double-front axle steering Macpherson suspension optimization design Virtual prototype modeling

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Behaviour of pseudo-random and chaotic sources of stochasticity in nature-inspired optimization methods

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SOFT COMPUTING 2014年第4期18卷 619-629页

作者： Kroemer, Pavel Zelinka, Ivan Snasel, Vaclav VSB Tech Univ Ostrava IT4Innovat Ostrava 70833 Czech Republic VSB Tech Univ Ostrava Dept Comp Sci Ostrava 70833 Czech Republic

Stochasticity, noisiness, and ergodicity are the key concepts behind many natural processes and its modeling is an important part of their implementation. There is a handful of soft-computing methods that are directly inspired by nature or stochastic natural processes. The implementation of such a nature-inspired optimization and search methods usually depends on streams of integer and floating point numbers generated in course of their execution. The pseudo-random numbers are utilized for in-silico emulation of probability-driven natural processes such as arbitrary modification of genetic information (mutation, crossover), partner selection, and survival of the fittest (selection, migration) and environmental effects (small random changes in motion direction and velocity). Deterministic chaos is a well known mathematical concept that can be used to generate sequences of seemingly random real numbers within selected interval in a predictable and well controllable way. In the past, it has been used as a basis for various pseudo-random number generators (PRNGs) with interesting properties. This work provides an empirical comparison of the behavior of selected nature-inspired optimization algorithms using different PRNGs and chaotic systems as sources of stochasticity.

关键词： Pseudo-random number generators Deterministic chaos simulation Genetic algorithms Differential evolution Particle swarm optimization

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Variable-Fidelity optimization of Antennas Using Adjoint Sensitivities 10

Variable-Fidelity Optimization of Antennas Using Adjoint Sen...

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Loughborough Antennas and Propagation conference (LAPC)

作者： Koziel, Slawomir Bekasiewicz, Adrian Reykjavik Univ Sch Sci & Engn Engn Optimizat & Modeling Ctr Reykjavik Iceland Gdansk Univ Technol Fac Elect Telecommun & Informat Gdansk Poland

ISBN: (纸本)9781479936625

Computationally efficient and reliable procedure for antenna design using electromagnetic (EM) simulation models is proposed. Our approach exploits trust-region-based gradient search and adjoint sensitivities for fast derivative evaluation. Derivative data allows for constructing the approximation model of the antenna responses. Computational cost of the design process can be further reduced by utilizing variable-fidelity EM simulations and adaptive procedure of switching between EM antenna models of increasing accuracy. We demonstrated the proposed methodology using a dielectric resonator antenna. The overall design cost using the proposed approach corresponds to less than eight antenna simulations at fine discretization and it is 50 percent lower than direct high-fidelity model optimization (also exploiting adjoint sensitivities).

关键词： antenna optimization simulation-driven design variable-fidelity EM analysis adjoint sensitivity

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conference on Solving Computationally Expensive Engineering Problems: Methods and Applications, 2008

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conference on Solving Computationally Expensive Engineering Problems: Methods and Applications, 2008

ISBN: (纸本)9783319089843

The proceedings contain 14 papers. The special focus in this conference is on Solving Computationally Expensive Engineering Problems. The topics include: Surrogate-based and one-shot optimization methods for PDE-constrained problems with an application in climate models;shape-preserving response prediction for surrogate modeling and engineering design optimization;nested space mapping technique for design and optimization of complex microwave structures with enhanced functionality;automated low-fidelity model setup for surrogate-based aerodynamic optimization;design space reduction for expedited multi-objective design optimization of antennas in highly dimensional spaces;numerically efficient approach to simulation-driven design of planar microstrip antenna arrays by means of surrogate-based optimization;optimal design of computationally expensive EM-based systems;atomistic surrogate-based optimization for simulation-driven design of computationally expensive microwave circuits with compact footprints;knowledge based three-step modeling strategy exploiting artificial neural network;large-scale global optimization via swarm intelligence;evolutionary clustering for synthetic aperture radar images;automated classification of airborne laser scanning point clouds;a novel approach to the common due-date problem on single and parallel machines and on gaussian process NARX models and their higher-order frequency response functions.

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simulation-driven aerodynamic shape optimization with automated low-fidelity model setup 32

Simulation-driven aerodynamic shape optimization with automa...

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32nd AIAA Applied Aerodynamics conference 2014

作者： Koziel, Slawomir Leifsson, Leifur Kurgan, Piotr Tesfahunegn, Yonatan A. Engineering Optimization and Modeling Center Reykjavik University Menntavegur 1 101 Reykjavik Iceland School of Science and Engineering Iceland

ISBN: (数字)9781624102882

ISBN: (纸本)9781624102882

Accurate high-fidelity Computational Fluid Dynamics (CFD) models may be computationally too expensive for simulation-driven design optimization. Variable-fidelity optimization algorithms have been utilized to reduce high CPU-cost related to the design process solely based on accurate CFD models. The most critical components of such algorithms are the low-fidelity models. Typically, the low-fidelity models employ the same CFD solver as the high-fidelity one, but with reduced discretization density and reduced number of flow solver iterations. The performance of the optimization algorithm strongly depends on the quality of the low-fidelity models. The low-fidelity model grid setup has been based on hands-on parametric studies. In this work, an automated low-fidelity CFD model setup technique is developed. The model setup task is defined as a constrained nonlinear optimization problem and suitable grid and flow solver parameters are obtained numerically. Comparison of the standard and the proposed approach is carried out in the context of aerodynamic design of transonic airfoils. Two variable-fidelity optimization algorithms are used in the study. One algorithm is based on a single corrected low-fidelity CFD model and the other utilizes a family of such models. The results suggest that the automated model generation may lead to significant computational savings of the CFDbased aerodynamic design process.

关键词： Computational fluid dynamics

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Computationally efficient multi-objective optimization of and experimental validation of Yagi-Uda antenna 4

Computationally efficient multi-objective optimization of an...

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4th International conference on simulation and modeling Methodologies, Technologies and Applications, SIMULTECH 2014

作者： Bekasiewicz, Adrian Koziel, Slawomir Leifsson, Leifur Faculty of Electronics Telecommunications and Informatics Gdansk University of Technology Gdansk80-233 Poland Engineering Optimization & Modeling Center Reykjavik University Menntavegur 1 Reykjavik101 Iceland

ISBN: (纸本)9789897580383

In this paper, computationally efficient multi-objective optimization of antenna structures is discussed. As a design case, we consider a multi-parameter planar Yagi-Uda antenna structure, featuring a driven element, three directors, and a feeding structure. Direct optimization of the high-fidelity electromagnetic (EM) antenna model is prohibitive in computational terms. Instead, our design methodology exploits response surface approximation (RSA) models constructed from sampled coarse-discretization EM simulation data. The RSA model is utilized to determine the Pareto optimal set of the best possible trade-offs between conflicting objectives. In order to alleviate the difficulties related to a large number of designable parameters, the RSA model is constructed in the initially reduced design space, where the lower/upper parameter bounds are estimated by solving appropriate single-objective problems resulting in identifying the extreme point of the Pareto set. The main optimization engine is multi-objective evolutionary algorithm (MOEA). Selected designs are subsequently refined using space mapping technique to obtain the final representation of the Pareto front at the high-fidelity EM antenna model level. The total design cost corresponds to less than two hundred of EM antenna simulations. © 2014 SciTePress. All rights reserved.

关键词： Multiobjective optimization

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Geodesic Density Tracking with Applications to Data driven modeling

Geodesic Density Tracking with Applications to Data Driven M...

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American Control conference

作者： Halder, Abhishek Bhattacharya, Raktim Texas A&M Univ Dept Aerosp Engn College Stn TX 77843 USA

ISBN: (纸本)9781479932740

Many problems in dynamic data driven modeling deals with distributed rather than lumped observations. In this paper, we show that the Monge-Kantorovich optimal transport theory provides a unifying framework to tackle such problems in the systems-control parlance. Specifically, given distributional measurements at arbitrary instances of measurement availability, we show how to derive dynamical systems that interpolate the observed distributions along the geodesics. We demonstrate the framework in the context of three specific problems: (i) finding a feedback control to track observed ensembles over finite-horizon, (ii) finding a model whose prediction matches the observed distributional data, and (iii) refining a baseline model that results a distribution-level prediction-observation mismatch. We emphasize how the three problems can be posed as variants of the optimal transport problem, but lead to different types of numerical methods.

关键词： Data models Joints Mathematical model optimization Predictive models Transportation Vectors Identification modeling and simulation Reduced order modeling

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