Structural Deformation-Based Computational Method for Static Aeroelasticity of High-Aspect-Ratio Wing Model in Pressurized Wind Tunnel

Structural Deformation-Based Computational Method for Static Aeroelasticity of High-Aspect-Ratio Wing Model in Pressurized Wind Tunnel

Year:    2018

Author:    Tongqing Guo, Ennan Shen, Zhiliang Lu, Li Ding

Advances in Applied Mathematics and Mechanics, Vol. 10 (2018), Iss. 5 : pp. 1158–1172

Abstract

In this study, the structural model of a high-aspect-ratio wing is unknown but its structural deformation is measured at some attack angles in a pressured wind tunnel. To implement the static aeroelastic computation at an arbitrary state, an inversion method is proposed to derive the structural stiffness from the known deformation. The wing is simplified into a single-beam model and its bending and torsional flexibility distributions are respectively expressed as a linear combination of several selected basis functions. The bending deformation can be then expressed as a linear combination of the bending deformations of the models structurally characterized by each basis function, which are gradually evaluated by loading the aerodynamic loads computed at the chosen design state. Based on the measured deformation, the bending stiffness distribution is ultimately fitted by a least square method. The torsional stiffness distribution is solved in the same way. Resultantly, a structural deformation-based computational method for static aeroelasticity of a high-aspect-ratio wing model is achieved by combining the structural stiffness inversion method with a coupled computational fluid dynamics (CFD)-computational structural dynamics (CSD) algorithm. The present method is applied to the design and validation states and the numerical results agree well with the experimental data.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/aamm.OA-2017-0342

Advances in Applied Mathematics and Mechanics, Vol. 10 (2018), Iss. 5 : pp. 1158–1172

Published online:    2018-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    15

Keywords:   

Author Details

Tongqing Guo

Ennan Shen

Zhiliang Lu

Li Ding