Dynamic Response of Aeroelastically Tailored Composite Wing: Analysis and Experiment

57th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference ◽

10.2514/6.2016-0469 ◽

2016 ◽

Cited By ~ 1

Author(s):

Jurij Sodja ◽

Noud Werter ◽

Johannes K. Dillinger ◽

Roeland De Breuker

Keyword(s):

Dynamic Response ◽

Composite Wing

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The Influence of Low Energy Impacts on the Static and Dynamic Response of a Foam Core Composite Wing

Journal of Intelligent Material Systems and Structures ◽

10.1177/1045389x08095184 ◽

2009 ◽

Vol 20 (11) ◽

pp. 1351-1361 ◽

Cited By ~ 3

Author(s):

E. Aktaş ◽

M. Seaver ◽

J.M. Nichols ◽

S.T. Trickey ◽

W.R. Davis

Keyword(s):

Dynamic Response ◽

Low Energy ◽

Foam Core ◽

Composite Wing

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Efficient Method for Aeroelastic Tailoring of Composite Wing to Minimize Gust Response

International Journal of Aerospace Engineering ◽

10.1155/2017/1592527 ◽

2017 ◽

Vol 2017 ◽

pp. 1-12 ◽

Cited By ~ 3

Author(s):

Yang Yu ◽

Zhengjie Wang ◽

Shijun Guo

Keyword(s):

Dynamic Response ◽

Efficient Method ◽

Laminated Composite ◽

Optimization Process ◽

Computational Time ◽

Response Analysis ◽

Dynamic Response Analysis ◽

Aeroelastic Tailoring ◽

Gust Response ◽

Composite Wing

Aeroelastic tailoring of laminated composite structure demands relatively high computational time especially for dynamic problem. This paper presents an efficient method for aeroelastic dynamic response analysis with significantly reduced computational time. In this method, a relationship is established between the maximum aeroelastic response and quasi-steady deflection of a wing subject to a dynamic loading. Based on this relationship, the time consuming dynamic response can be approximated by a quasi-steady deflection analysis in a large proportion of the optimization process. This method has been applied to the aeroelastic tailoring of a composite wing of a tailless aircraft for minimum gust response. The results have shown that 20%–36% gust response reduction has been achieved for this case. The computational time of the optimization process has been reduced by 90% at the cost of accuracy reduction of 2~4% comparing with the traditional dynamic response analysis.

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