Auteri, F., Savino, A., Zanotti, A., Gibertini, G., Zagaglia, D. , Bmegaptche Tekap, Y. and Braza, M. (2022) Experimental evaluation of the aerodynamic performance of a large-scale high-lift morphing wing. Aerospace Science and Technology, 124, 107515. (doi: 10.1016/j.ast.2022.107515)
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Abstract
The Smart Morphing & Sensing (SMS) project was a multi-disciplinary upstream project that investigated the use of intelligent electro-active actuators to modify the lifting surface of an aircraft. In particular, the attention of the project was focused on trailing-edge, high-lift morphing devices aimed to obtain the optimal shapes to improve the aerodynamic performance of the wing of a large passenger aircraft. The present work describes the experimental assessment of the morphed aerodynamic shapes of the high-lift morphing flap developed during the project. Wind-tunnel tests were performed using a large-scale wing prototype reproducing a section of a full-scale wing of a large passenger aircraft. Several quantities were measured during the tests. Pressure measurements performed in the mid-span section of the wing showed an increase of the lift provided by the cambered morphed shape of the flap in take-off configuration and an increase of both the lift coefficient and the wing efficiency in landing configuration. Particle Image Velocimetry surveys enabled us to obtain an insight in the flow physics behind the measured performance of the morphing flap. Moreover, the deformation of the morphing flap was measured by optical systems to check the actual shape. The tests demonstrated that morphing the trailing-edge flap can be useful to optimise the aerodynamic performance of the wing during take-off and landing.
Item Type: | Articles |
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Additional Information: | This project has received funding from the European Union's H2020 program for research, technological development and demonstration under grant agreement no. 723402. |
Keywords: | Morphing, wind tunnel, aerodynamics, high-lift wing. |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Zagaglia, Dr Daniele |
Authors: | Auteri, F., Savino, A., Zanotti, A., Gibertini, G., Zagaglia, D., Bmegaptche Tekap, Y., and Braza, M. |
Subjects: | T Technology > T Technology (General) |
College/School: | College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity |
Journal Name: | Aerospace Science and Technology |
Publisher: | Elsevier |
ISSN: | 1270-9638 |
ISSN (Online): | 1626-3219 |
Published Online: | 30 March 2022 |
Copyright Holders: | Copyright © 2022 Elsevier |
First Published: | First published in Aerospace Science and Technology 124:107515 |
Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
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