Articles | Volume 6, issue 2
Wind Energ. Sci., 6, 409–426, 2021

Special issue: Wind Energy Science Conference 2019

Wind Energ. Sci., 6, 409–426, 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 et al.

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Cited articles

Aubrun, S., Garcia, E. T., Boquet, M., Coupiac, O., and Girard, N.: Wind turbine wake tracking and its correlations with wind turbine monitoring sensors. Preliminary results, J. Phys., 753, 032003,, 2016. a
Batlle, E. C., Pereira, R., and Kotsonis, M.: Airfoil Stall Hysteresis Control with DBD Plasma actuation, 55th AIAA Aerospace Sciences Meeting, Grapevine, Texas, 9–13 January 2017, 1–8, No. 19803,, 2017. a
Bossanyi, E. A., Kumar, A., and Hugues-Salas, O.: Wind turbine control applications of turbine-mounted LIDAR, J. Phys., 555, 012011,, 2014. a
Braud, C. and Liberzon, A.: Real-time processing methods to characterize streamwise vortices, J. Wind Eng. Ind. Aerod., 179, 14–25,, 2018. a
Cahuzac, A., Boudet, J., Borgnat, P., and Lévêque, E.: Smoothing algorithms for mean-flow extraction in large-eddy simulation of complex turbulent flows, Phys. Fluids, 22, 125104,, 2010. a
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.