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Fly by Feel: Flow Event Detection via Bioinspired Wind-Hairs

Court, A. ORCID: 0000-0002-6302-4961 & Bruecker, C. ORCID: 0000-0001-5834-3020 (2024). Fly by Feel: Flow Event Detection via Bioinspired Wind-Hairs. Fluids, 9(3), article number 74. doi: 10.3390/fluids9030074

Abstract

Bio-inspired flexible pillar-like wind-hairs show promise for the future of flying by feel by detecting critical flow events on an aerofoil during flight. To be able to characterise specific flow disturbances from the response of such sensors, quantitative PIV measurements of such flow-disturbance patterns were compared with sensor outputs under controlled conditions. Experiments were performed in a flow channel with an aerofoil equipped with a 2D array of such sensors when in uniform inflow conditions compared to when a well-defined gust was introduced upstream and was passing by. The gust was generated through the sudden deployment of a row of flaps on the suction side of a symmetric wing that was placed upstream of the aerofoil with the sensors. The resulting flow disturbance generated a starting vortex with two legs, which resembled a horseshoe-type vortex shed into the wake. Under the same tunnel conditions, PIV measurements were taken downstream of the gust generator to characterise the starting vortex, while further measurements were taken with the sensing pillars on the aerofoil in the same location. The disturbance pattern was compared to the pillar response to demonstrate the potential of flow-sensing pillars. It was found that the pillars could detect the arrival time and structural pattern of the flow disturbance, showing the characteristics of the induced flow field of the starting vortex when passing by. Therefore, such sensor arrays can detect the “footprint” of disturbances as temporal and spatial signatures, allowing us to distinguish those from others or noise.

Publication Type: Article
Additional Information: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Publisher Keywords: flow disturbance; PIV; flow characterisation
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Departments: School of Science & Technology
School of Science & Technology > Engineering
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