利用二元粒子群优化算法设计宽带跨极化转换元面

IF 7.6 2区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Jiao Wang , Wei-Qi Gu , Xin-Cheng Zhao , Yan-Nan Jiang , Kai-Da Xu
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引用次数: 0

摘要

传统的线性极化鉴别方法包括相位差Δφ、椭圆度角β或轴向比,由于这些方法存在宽带不连续性、数值无穷大或无法区分交叉极化转换和共极化转换等缺点,因此不适用于由子块组成的宽带交叉极化转换元表面(CPM)的软件优化设计。因此,我们引入了伪椭圆度角 β' 来表征跨极化转换。基于编码元曲面和 β',本研究首先采用 Python 编程的二元粒子群优化算法来完成反射式宽带 CPM 的优化设计。然后,通过对相对孤立的子块进行再处理,进一步简化得到的 CPM,从而得到最终的 CPM。仿真结果表明,最终的 CPM 实现了宽带跨极化转换,β'≥ 0.4π,相对带宽从 11.66 GHz 到 16.79 GHz 为 36.1%。此外,测量结果与模拟结果非常吻合,验证了所提出的设计方法。它将宽带 CPM 设计从手工方法推进到了自动化方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Designing broadband cross-polarization conversion metasurfaces using binary particle swarm optimization algorithm

Designing broadband cross-polarization conversion metasurfaces using binary particle swarm optimization algorithm
Owing to their disadvantages of broadband discontinuity, infinite value, or incapability of distinguishing cross-polarization conversions from co-polarization conversions, the traditional linear polarization discrimination methods relating to the phase difference Δφ, the ellipticity angle β, or the axial ratio are inapplicable to the software-based optimal design of broadband cross-polarization conversion metasurfaces (CPMs) consisting of subblocks. Therefore, we introduce the pseudo ellipticity angle β' to characterize the cross-polarization conversion. And based upon the coding metasurfaces and β', this work first employs the Python-programmed binary particle swarm optimization algorithm to accomplish the optimal design of reflective broadband CPMs. Then, the obtained CPM is further simplified by reprocessing the relatively isolated subblocks, which results in the final CPM. The simulated results show that the final CPM realizes the broadband cross-polarization conversion with β' ≥ 0.4π and a relative bandwidth of 36.1 % from 11.66 GHz to 16.79 GHz. Moreover, the measured results are in excellent agreements with the simulated ones, which validates the proposed design method. It advances the broadband CPMs design from manual to automated method.
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来源期刊
Materials & Design
Materials & Design Engineering-Mechanical Engineering
CiteScore
14.30
自引率
7.10%
发文量
1028
审稿时长
85 days
期刊介绍: Materials and Design is a multi-disciplinary journal that publishes original research reports, review articles, and express communications. The journal focuses on studying the structure and properties of inorganic and organic materials, advancements in synthesis, processing, characterization, and testing, the design of materials and engineering systems, and their applications in technology. It aims to bring together various aspects of materials science, engineering, physics, and chemistry. The journal explores themes ranging from materials to design and aims to reveal the connections between natural and artificial materials, as well as experiment and modeling. Manuscripts submitted to Materials and Design should contain elements of discovery and surprise, as they often contribute new insights into the architecture and function of matter.
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