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Equivalent Circuit-Assisted Multi-Objective Particle Swarm Optimization for Accelerated Reverse Design of Multi-Layer Frequency Selective Surface.
- Source :
-
Nanomaterials (2079-4991) . Nov2022, Vol. 12 Issue 21, p3846. 15p. - Publication Year :
- 2022
-
Abstract
- In this paper, a fast reverse design method of multi-layer frequency selective surface (FSS) based on the equivalent circuit (EC)-assisted multi-objective particle swarm optimization (MOPSO) algorithm is proposed. Converting the desired frequency response requirements into an EC and then determining structural parameters via building blocks' EC and MOPSO simplifies the inverse design process of the FSS. The layer-by-layer building blocks of EC are used instead when dealing with the problem of complicated EC computation associated with multi-layer FSS. By converting factors that are difficult to calculate, such as interlayer coupling, into an MOPSO seeking process, the computational complexity is reduced while the design accuracy can be improved. To begin with, it is necessary to determine the distribution of zeros and poles according to the design goals in order to calculate the appropriate EC. Then, the preliminary design of the FSS has been completed in accordance with the EC and the associated building block structure. Finally, the objective function of the optimization algorithm is determined according to the desired frequency response, and the FSS structure parameters are optimized. Taking dual band-stop FSS and triple band-pass FSS structures as examples, the transmission coefficient results obtained by the proposed reverse design method are consistent with the transmission coefficient results based on the ECs, which verifies the effectiveness of the proposed method. The optimized triple band-pass FSS demonstrates strong stability even at oblique incident angles of up to 45° in both TE and TM polarizations. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20794991
- Volume :
- 12
- Issue :
- 21
- Database :
- Academic Search Index
- Journal :
- Nanomaterials (2079-4991)
- Publication Type :
- Academic Journal
- Accession number :
- 160206798
- Full Text :
- https://doi.org/10.3390/nano12213846