Inverse design of cylindrical curved shell metasurface for elastic wave modulation based on PSO-BP model

IF 5.7 1区工程技术 Q1 ENGINEERING, CIVIL

Thin-Walled Structures Pub Date : 2025-03-29 DOI:10.1016/j.tws.2025.113253

Jialin Wu , Lingyun Yao , Hui Chen

{"title":"Inverse design of cylindrical curved shell metasurface for elastic wave modulation based on PSO-BP model","authors":"Jialin Wu , Lingyun Yao , Hui Chen","doi":"10.1016/j.tws.2025.113253","DOIUrl":null,"url":null,"abstract":"<div><div>Nowadays, there is a lack of systematic and comprehensive theory regarding the propagation of elastic wave on cylindrical curved shells metasurface, largely due to the complex three-dimensional structural parameters on cylindrical curved shells. As a new powerful tool for predictive modeling, machine learning method can be learned and updated constantly, and is being used to design complex metasurface structures for controlling elastic wave propagation. In this work, an inverse design method was proposed to deal with the design of cylindrical curved shell metasurface with different curvatures. Firstly, machine learning technique was utilized to construct a mapping between structural parameters and properties of elastic wave propagation. Transmittance and phase shift properties under multiple outputs are initially predicted using multiple variable geometric parameters as inputs to machine learning network. Subsequently, particle swarm optimization (PSO) algorithm is utilized on original network to improve the quality of the predictions. Finally, the constructed models are used to design the unitary metasurface with high transmittance and special phase shifts, which are combined to realize the various modulation functions of elastic wave. Experimental results disclose that the network trained based on a large data set has high prediction accuracy. It is demonstrated the proposed method can not only be used to explore more elastic wave propagation laws in cylindrical curved shells, but also lays foundation for future functions of vibration isolation, energy focusing related to these structures.</div></div>","PeriodicalId":49435,"journal":{"name":"Thin-Walled Structures","volume":"213 ","pages":"Article 113253"},"PeriodicalIF":5.7000,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Thin-Walled Structures","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0263823125003477","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}

引用次数: 0

Abstract

Nowadays, there is a lack of systematic and comprehensive theory regarding the propagation of elastic wave on cylindrical curved shells metasurface, largely due to the complex three-dimensional structural parameters on cylindrical curved shells. As a new powerful tool for predictive modeling, machine learning method can be learned and updated constantly, and is being used to design complex metasurface structures for controlling elastic wave propagation. In this work, an inverse design method was proposed to deal with the design of cylindrical curved shell metasurface with different curvatures. Firstly, machine learning technique was utilized to construct a mapping between structural parameters and properties of elastic wave propagation. Transmittance and phase shift properties under multiple outputs are initially predicted using multiple variable geometric parameters as inputs to machine learning network. Subsequently, particle swarm optimization (PSO) algorithm is utilized on original network to improve the quality of the predictions. Finally, the constructed models are used to design the unitary metasurface with high transmittance and special phase shifts, which are combined to realize the various modulation functions of elastic wave. Experimental results disclose that the network trained based on a large data set has high prediction accuracy. It is demonstrated the proposed method can not only be used to explore more elastic wave propagation laws in cylindrical curved shells, but also lays foundation for future functions of vibration isolation, energy focusing related to these structures.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Thin-Walled Structures 工程技术-工程：土木

CiteScore

9.60

自引率

20.30%

发文量

801

审稿时长

66 days

期刊介绍： Thin-walled structures comprises an important and growing proportion of engineering construction with areas of application becoming increasingly diverse, ranging from aircraft, bridges, ships and oil rigs to storage vessels, industrial buildings and warehouses. Many factors, including cost and weight economy, new materials and processes and the growth of powerful methods of analysis have contributed to this growth, and led to the need for a journal which concentrates specifically on structures in which problems arise due to the thinness of the walls. This field includes cold– formed sections, plate and shell structures, reinforced plastics structures and aluminium structures, and is of importance in many branches of engineering. The primary criterion for consideration of papers in Thin–Walled Structures is that they must be concerned with thin–walled structures or the basic problems inherent in thin–walled structures. Provided this criterion is satisfied no restriction is placed on the type of construction, material or field of application. Papers on theory, experiment, design, etc., are published and it is expected that many papers will contain aspects of all three.