DYNAMIC SHAPE RECONSTRUCTION OF THREE-DIMENSIONAL FRAME STRUCTURES USING THE INVERSE FINITE ELEMENT METHOD

作者
Marco Gherlone,Priscilla Cerracchio,Massimiliano Mattone,Marco Di Sciuva,Alexander Tessler
出处
期刊:Politecnico di Torino - PORTO Publications Open Repository TOrino 卷期号:: 1717-1737 被引量:23
摘要

A robust and efficient computational method for reconstructing the three-dimensional displacement field of truss, beam, and frame structures, using measured surface-strain data, is presented. Known as "shape sensing", this inverse problem has important implications for real-time actuation and control of smart structures, and for monitoring of structural integrity. The present formulation, based on the inverse Finite Element Method (iFEM), uses a least-squares variational principle involving strain measures of Timoshenko theory for stretching, torsion, bending, and transverse shear. Two inverse-frame finite elements are derived using interdependent interpolations whose interior degrees-of-freedom are condensed out at the element level. In addition, relationships between the order of kinematic-element interpolations and the number of required strain gauges are established. As an example problem, a thin-walled, circular cross-section cantilevered beam subjected to harmonic excitations in the presence of structural damping is modeled using iFEM; where, to simulate strain-gauge values and to provide reference displacements, a high-fidelity MSC/NASTRAN shell finite element model is used. Examples of low and high-frequency dynamic motion are analyzed and the solution accuracy examined with respect to various levels of discretization and the number of strain gauges.

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
刚刚
an慧儿完成签到,获得积分10
刚刚
stt完成签到,获得积分10
1秒前
Accept发布了新的文献求助20
1秒前
阿耒完成签到,获得积分20
1秒前
淡淡听安发布了新的文献求助10
2秒前
一朵琼花完成签到,获得积分10
2秒前
2秒前
jiejie321完成签到,获得积分10
3秒前
小蘑菇应助神经元neuron采纳,获得10
3秒前
3秒前
悦耳的怀寒应助初景采纳,获得10
3秒前
落寞的绯完成签到 ,获得积分10
4秒前
黄莲上清丸完成签到 ,获得积分10
4秒前
打打应助阿耒采纳,获得10
5秒前
Denmark发布了新的文献求助50
5秒前
无殇完成签到,获得积分10
5秒前
zyy完成签到,获得积分10
5秒前
谢挽风完成签到,获得积分10
6秒前
PP关闭了PP文献求助
7秒前
7秒前
恒驰完成签到,获得积分10
7秒前
ding应助欢欢欢乐乐乐乐采纳,获得10
7秒前
7秒前
豆豆发布了新的文献求助10
7秒前
7秒前
寒冷的芙完成签到,获得积分10
7秒前
淡墨完成签到,获得积分10
7秒前
lindollar完成签到,获得积分10
8秒前
香蕉觅云应助AAA论文批发采纳,获得10
8秒前
8秒前
8秒前
JJ应助陈高兴采纳,获得30
8秒前
帅气网络完成签到,获得积分10
8秒前
8秒前
9秒前
zy完成签到,获得积分10
9秒前
Zurini完成签到,获得积分10
10秒前
10秒前
科研通AI6.4应助杨敬业采纳,获得10
10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
Rosenblum, Global Change Biology 800
自動車の空力技術 800
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7779149
求助须知:如何正确求助?哪些是违规求助? 9319396
关于积分的说明 20371417
捐赠科研通 7366536
什么是DOI,文献DOI怎么找? 3319361
关于科研通互助平台的介绍 2467388
邀请新用户注册赠送积分活动 2334884