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2022

Valle, Cesar L.; Carranza, Gilbert T.; Rumpf, Raymond C.

Conformal Frequency Selective Surfaces for Arbitrary Curvature Journal Article

In: IEEE Transactions on Antennas and Propagation, vol. 71, iss. 1, pp. 612-620, 2022, ISSN: 1558-2221.

Abstract | Links | BibTeX | Tags: arbitrary conformal array, conformal frequency selective surface, finite element analysis, frequency selective surface (FSS), gratings, periodic structures, strain, surface fitting

@article{nokey,
title = {Conformal Frequency Selective Surfaces for Arbitrary Curvature},
author = {Cesar L. Valle and Gilbert T. Carranza and Raymond C. Rumpf},
url = {https://ieeexplore.ieee.org/abstract/document/9933174/keywords#keywords},
doi = {10.1109/TAP.2022.3216960},
issn = {1558-2221},
year = {2022},
date = {2022-10-31},
urldate = {2022-10-31},
journal = {IEEE Transactions on Antennas and Propagation},
volume = {71},
issue = {1},
pages = {612-620},
abstract = {An algorithm is introduced for generating frequency selective surfaces (FSS) capable of conforming to any curvature while maintaining proper size, shape and spacing of the elements. Compared to traditional projection and mapping methods, the presented algorithm maintains the electromagnetic properties of the FSS array despite the curvature. The algorithm can be used to conform to radomes, parts of autonomous vehicles, or any surface. The algorithm is agnostic to both element design and surface curvature. This allows the user to design a FSS for any curved surface while maintaining its response comparable to a flat array. The algorithm outputs two standard tessellation language (STL) files, one describing the curved surface and the other the elements of the FSS placed onto the curved surface. This makes the algorithm suitable for 3D printing using systems with more than three axes or for flexible electronics. Several examples of arbitrary surfaces are shown. Lastly, the algorithm was applied to a Jerusalem-cross FSS on a non-symmetrical parabolic dome. The dimensions of the parabolic dome were chosen to test the response of the array on a rather extreme surface against a projected array on the same surface. Simulations were carried out using Ansys HFSS from the infinite array to finite arrays to confirm operation. Three test surfaces were manufactured with measured results found to be in good agreement with simulation.},
keywords = {arbitrary conformal array, conformal frequency selective surface, finite element analysis, frequency selective surface (FSS), gratings, periodic structures, strain, surface fitting},
pubstate = {published},
tppubtype = {article}
}

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An algorithm is introduced for generating frequency selective surfaces (FSS) capable of conforming to any curvature while maintaining proper size, shape and spacing of the elements. Compared to traditional projection and mapping methods, the presented algorithm maintains the electromagnetic properties of the FSS array despite the curvature. The algorithm can be used to conform to radomes, parts of autonomous vehicles, or any surface. The algorithm is agnostic to both element design and surface curvature. This allows the user to design a FSS for any curved surface while maintaining its response comparable to a flat array. The algorithm outputs two standard tessellation language (STL) files, one describing the curved surface and the other the elements of the FSS placed onto the curved surface. This makes the algorithm suitable for 3D printing using systems with more than three axes or for flexible electronics. Several examples of arbitrary surfaces are shown. Lastly, the algorithm was applied to a Jerusalem-cross FSS on a non-symmetrical parabolic dome. The dimensions of the parabolic dome were chosen to test the response of the array on a rather extreme surface against a projected array on the same surface. Simulations were carried out using Ansys HFSS from the infinite array to finite arrays to confirm operation. Three test surfaces were manufactured with measured results found to be in good agreement with simulation.

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  • https://ieeexplore.ieee.org/abstract/document/9933174/keywords#keywords
  • doi:10.1109/TAP.2022.3216960

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