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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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https://doi.org/10.5194/wes-2020-13
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-2020-13
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 26 Mar 2020

Submitted as: research article | 26 Mar 2020

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This preprint is currently under review for the journal WES.

Ability of the e-TellTale sensor to detect flow features over wind turbine blades: flow stall/reattachment dynamics

Antoine Soulier1,2, Caroline Braud2, Dimitri Voisin1, and Bérengère Podvin3 Antoine Soulier et al.
  • 1Mer Agitée, Port-la-Forêt, 29940 La Forêt-Fouesnant
  • 2LHEEA (CNRS/ECN), Ecole Centrale Nantes 1, rue de la Noë, 44321 Nantes
  • 3LIMSI (CNRS), Campus Univ. bât. 507, Rue John Von Neumann, 91400 Orsay

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 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.

Antoine Soulier et al.

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Status: open (until 07 May 2020)
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Antoine Soulier et al.

Antoine Soulier et al.

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Latest update: 29 Mar 2020
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Short summary
Paper about validation of Electronic TellTale sensors to support their use for wind turbine blade monitoring.
Paper about validation of Electronic TellTale sensors to support their use for wind turbine...
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