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Abstract

Gust and turbulence events are of primary importance for the analysis of flight incidents, for the design of gust load alleviation systems and for the calculation of loads in the airframe. Gust and turbulence events cannot be measured directly but they can be obtained through direct or optimisation-based methods. In the direct method the discretisation of the Fredholm Integral equation is associated with an ill conditioned matrix. In this work the effects of regularisation methods including Tikhonov regularisation, Truncated Single Value Decomposition (TSVD), Damped Single Value Decomposition (DSVD) and a recently proposed method using cubic B-spline functions are evaluated for aeroelastic gust identification using in flight measured data. The gust identification methods are tested in the detailed aeroelastic model of FFAST and an equivalent low-fidelity aeroelastic model developed by the authors. In addition, the accuracy required in the model for a reliable identification is discussed. Finally, the identification method based on B-spline functions is tested by simultaneously using both low-fidelity and FFAST aeroelastic models so that the response from the FFAST model is used as measurement data and the equivalent low-fidelity model is used in the identification process.

Publication Type:	Article
Additional Information:	© 2021 The Author(s). Published by Elsevier Masson SAS. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Publisher Keywords:	Aeroelasticity, Gust identification, Inverse problem, Regularisation, Cubic B-spline
Subjects:	T Technology > TL Motor vehicles. Aeronautics. Astronautics
Departments:	School of Science & Technology > Engineering
SWORD Depositor:	Symplectic Administrator

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