Low-Reynolds-number investigations on the ability of the strip of e-TellTale sensor to detect the flow features over wind turbine blade section: flow stall and reattachment dynamics - Laboratoire Interdisciplinaire des Sciences du Numérique Access content directly
Journal Articles Wind Energy Science Year : 2021

Low-Reynolds-number investigations on the ability of the strip of e-TellTale sensor to detect the flow features over wind turbine blade section: flow stall and reattachment dynamics

Abstract

Abstract. Monitoring the flow features over wind turbine blades is a challenging task that has become more and more crucial. This paper is devoted to demonstrate the ability of the e-TellTale sensor to detect the flow stall–reattachment dynamics over wind turbine blades. This sensor is made of a strip with a strain gauge sensor at its base. The velocity field was acquired using time-resolved particle image velocimetry (TR-PIV) measurements over an oscillating 2D blade section equipped with an e-TellTale sensor. PIV images were post-processed to detect movements of the strip, which was compared to movements of flow. Results show good agreement between the measured velocity field and movements of the strip regarding the stall–reattachment dynamics.
Fichier principal
Vignette du fichier
wes-6-409-2021.pdf (14.16 Mo) Télécharger le fichier
Origin : Publisher files allowed on an open archive

Dates and versions

hal-03437709 , version 1 (20-11-2021)

Licence

Attribution

Identifiers

Cite

Antoine Soulier, Caroline Braud, Dimitri Voisin, Bérengère Podvin. Low-Reynolds-number investigations on the ability of the strip of e-TellTale sensor to detect the flow features over wind turbine blade section: flow stall and reattachment dynamics. Wind Energy Science, 2021, 6 (2), pp.409-426. ⟨10.5194/wes-6-409-2021⟩. ⟨hal-03437709⟩
73 View
6 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More