Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/92233
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Type: Conference paper
Title: MATNEC: an in-house developed tool for electromagnetic simulation and evolutionary optimization of wire antennas
Author: Zhao, S.
Fumeaux, C.
Fickenscher, T.
Citation: 2014 International Conference on Numerical Electromagnetic Modeling and Optimization for RF, Microwave, and Terahertz Applications, NEMO 2014, 2014, pp.1-4
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Issue Date: 2014
ISBN: 9781479928200
Conference Name: Numerical Electromagnetic Modeling and Optimization for RF, Microwave, and Terahertz Applications, NEMO 2014 (NEMO 2014) (14 May 2014 - 16 May 2014 : Pavia, Italy)
Statement of
Responsibility: 
S. Zhao, C. Fumeaux, and T. Fickenscher
Abstract: Various techniques of numerical electromagnetic computation have been widely used for decades in the design of antennas. In particular, the Numerical Electromagnetic Code was developed based on the method of moments to solve integral equations for current distributions, and thus, it is particularly efficient for the modeling and analysis of wire antennas and other metal structures. The computation load can, however, increase significantly with the increase of complexity in structure modeling. Radial basis functions are employed for geometry description to ease such burden by representing structural variations with a minimal number of variables. Evolutionary optimizations are used to explore a wider solution space in a timely manner in the pursuit of near-optimal solution in a multivariable environment. An in-house tool called MATNEC integrating modeling, simulation, analysis, and optimization is developed, which can successfully deliver near-optimal solutions under a pre-defined fitness function, considering both antenna efficiency and bandwidth. Helical antennas with variations in radius and pitch are successfully optimized, which effectively verifies the robustness of MATNEC and methodology applied
Keywords: NEC; Method of Moments; Evoluntionary optimization; Genetic algorithm; Particle swarm algorithm; Small antennas
Rights: © 2014 IEEE
DOI: 10.1109/NEMO.2014.6995661
Appears in Collections:Aurora harvest 7
Electrical and Electronic Engineering publications

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