Design of Acoustic Metamaterials Using Gradient Based Optimization

Feruza A. Amirkulova, A. Norris
{"title":"Design of Acoustic Metamaterials Using Gradient Based Optimization","authors":"Feruza A. Amirkulova, A. Norris","doi":"10.1115/IMECE2018-88254","DOIUrl":null,"url":null,"abstract":"We derive formulas for the gradients of the total scattering cross section (TSCS) with respect to positions of a set of cylindrical scatterers. Providing the analytic form of gradients enhances modeling capability when combined with optimization algorithms and parallel computing. This results in reducing number of function calls and time needed to converge, and improving solution accuracy for large scale optimization problems especially at high frequencies and with a large number of scatterers. As application of the method we design acoustic metamaterial structure based on a gradient-based minimization of TSCS for a set of cylindrical obstacles by incrementally re-positioning them so that they eventually act as an effective cloaking device. The method is illustrated through examples for clusters of hard cylinders in water. Computations are performed on Matlab using parallel optimization algorithms and a multistart optimization solver, and supplying the gradient of TSCS.","PeriodicalId":197121,"journal":{"name":"Volume 11: Acoustics, Vibration, and Phononics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 11: Acoustics, Vibration, and Phononics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/IMECE2018-88254","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

We derive formulas for the gradients of the total scattering cross section (TSCS) with respect to positions of a set of cylindrical scatterers. Providing the analytic form of gradients enhances modeling capability when combined with optimization algorithms and parallel computing. This results in reducing number of function calls and time needed to converge, and improving solution accuracy for large scale optimization problems especially at high frequencies and with a large number of scatterers. As application of the method we design acoustic metamaterial structure based on a gradient-based minimization of TSCS for a set of cylindrical obstacles by incrementally re-positioning them so that they eventually act as an effective cloaking device. The method is illustrated through examples for clusters of hard cylinders in water. Computations are performed on Matlab using parallel optimization algorithms and a multistart optimization solver, and supplying the gradient of TSCS.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于梯度优化的声学超材料设计
我们推导了总散射截面(TSCS)随一组圆柱形散射体位置的梯度公式。提供梯度的解析形式,与优化算法和并行计算相结合,增强了建模能力。这减少了函数调用的次数和收敛所需的时间,并提高了大规模优化问题的解决精度,特别是在高频和大量散射体的情况下。作为该方法的应用,我们设计了基于梯度最小化TSCS的声学超材料结构,用于一组圆柱形障碍物,通过逐步重新定位它们,使它们最终成为有效的隐形装置。通过水中硬圆柱体簇的实例说明了该方法。在Matlab上使用并行优化算法和多启动优化求解器进行了计算,并提供了TSCS的梯度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Vibration Absorption in a Nonlinear Metamaterial Beam Incorporating Shape Memory Alloys Mechanical Design and Development of a Payload for Structural Health Monitoring Experiments on the International Space Station Ultrasonic Characterization of the Elastic Constants in an Aging Ti-6Al-4V ELI Alloy An Experimental Approach in Defect Detection of a Single Row Ball Bearing Using Noise Generation Signal Development and Design of the Dynamic Vibration Absorber Using Magneto-Rheological Elastomer for the Weight and Power Consumption Saving
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1