Articles | Volume 6, issue 2
https://doi.org/10.5194/wes-6-409-2021
https://doi.org/10.5194/wes-6-409-2021
Research article
 | 
15 Mar 2021
Research article |  | 15 Mar 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

Antoine Soulier, Caroline Braud, Dimitri Voisin, and Bérengère Podvin

Viewed

Total article views: 2,068 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,314 663 91 2,068 103 91
  • HTML: 1,314
  • PDF: 663
  • XML: 91
  • Total: 2,068
  • BibTeX: 103
  • EndNote: 91
Views and downloads (calculated since 26 Mar 2020)
Cumulative views and downloads (calculated since 26 Mar 2020)

Viewed (geographical distribution)

Total article views: 2,068 (including HTML, PDF, and XML) Thereof 1,944 with geography defined and 124 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Dec 2024
Download
Short summary
Monitoring the flow features over wind turbine blades is a challenging task that has become more and more crucial to monitor and/or operate wind turbine blades. This paper demonstrates the ability of an innovative sensor to detect these features over wind turbine blades. The spatiotemporal description of the flow over the surface has been measured over an oscillating blade section and the strip displacement was compared, showing the ability of the sensor to detect stall.
Altmetrics
Final-revised paper
Preprint