Multi-objective optimization approach on diffuse sound transmission through poroelastic composite sandwich structure

孔力学 声音传输等级 夹层结构复合材料 流离失所(心理学) 多目标优化 材料科学 优化设计 分类 复合数 结构工程 声学 计算机科学 数学优化 多孔介质 多孔性 算法 数学 工程类 复合材料 物理 机器学习 心理学 心理治疗师
作者
Roohollah Talebitooti,M.R. Zarastvand,Hamed Darvishgohari
出处
期刊:Journal of Sandwich Structures and Materials [SAGE Publishing]
卷期号:23 (4): 1221-1252 被引量:65
标识
DOI:10.1177/1099636219854748
摘要

Multi-objective vibroacoustic optimization of the double-walled doubly curved composite shells having poroelastic lining in its core in a diffuse field is performed based on Non-dominated sorting Genetic Algorithm-II. To present an analytical model on the basis of multi-objective optimization, the summation of sound transmission loss and transverse displacement along with weight of the structure are considered as two cost functions, which should be optimized in a diffuse field. In fact, the significant achievement of this work is to design an optimization algorithm to improve vibroacoustic fitness and weight of the sandwich doubly curved shells. In the first part of the paper, a general formulation is prepared to analyze the dynamic of the poroelastic composite sandwich structures. Likewise, some validation configurations are presented to confirm the accuracy of the current formulation. Consequently, an optimization algorithm is provided on the basis of considering some appropriate design variables including material and porous types as well as stacking sequences. In this regard, a batch of 19 benchmarks of porous core is investigated. Furthermore, a configuration of optimized points in the Pareto front is plotted in which the simultaneous effects of optimizing the weight and vibroacoustic fitness can be observed. As a result, a new approach is made through optimization of the transverse displacement of the structure as a function of various incidence and azimuth angles in three dimensional configurations with respect to different frequencies.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Ava应助满意的灵枫采纳,获得10
2秒前
CodeCraft应助卷发麦麦采纳,获得10
3秒前
3秒前
joinn完成签到,获得积分10
3秒前
4秒前
栗子发布了新的文献求助10
4秒前
huhu完成签到,获得积分20
5秒前
筱喜完成签到,获得积分20
5秒前
6秒前
单纯的若菱完成签到,获得积分20
6秒前
direstyles完成签到,获得积分10
6秒前
7秒前
英勇思山完成签到,获得积分20
7秒前
眯眯眼的乐曲完成签到,获得积分10
8秒前
熹熹完成签到 ,获得积分10
8秒前
8秒前
joinn发布了新的文献求助10
8秒前
哇冰1完成签到 ,获得积分10
10秒前
cao关注了科研通微信公众号
10秒前
11秒前
jerry发布了新的文献求助10
11秒前
迷人靖儿应助清爽的夜绿采纳,获得10
11秒前
王富贵完成签到,获得积分10
11秒前
胡图图图图图图完成签到,获得积分10
11秒前
ktqaiaiai发布了新的文献求助10
12秒前
天天快乐应助刘47采纳,获得10
13秒前
xpqiu完成签到,获得积分10
13秒前
sewqar发布了新的文献求助10
13秒前
14秒前
一只呆发布了新的文献求助10
14秒前
14秒前
青黛完成签到 ,获得积分10
15秒前
15秒前
15秒前
小飞应助lee采纳,获得10
16秒前
17秒前
18秒前
曾hf完成签到 ,获得积分10
18秒前
南北完成签到,获得积分10
19秒前
活力的静曼完成签到,获得积分10
20秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The Effective Clinical Neurologist 3ed 500
The Great Hymn to Šamaš 500
Positive Obsession: The Life and Times of Octavia E. Butler 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7698368
求助须知:如何正确求助?哪些是违规求助? 9258096
关于积分的说明 20012030
捐赠科研通 7273416
什么是DOI,文献DOI怎么找? 3293303
关于科研通互助平台的介绍 2448732
邀请新用户注册赠送积分活动 2299348