Articles | Volume 5, issue 2
https://doi.org/10.5194/wes-5-819-2020
https://doi.org/10.5194/wes-5-819-2020
Research article
 | 
29 Jun 2020
Research article |  | 29 Jun 2020

Cartographing dynamic stall with machine learning

Matthew Lennie, Johannes Steenbuck, Bernd R. Noack, and Christian Oliver Paschereit

Related authors

Modern methods for investigating the stability of a pitching floating platform wind turbine
Matthew Lennie, David Marten, George Pechlivanoglou, Christian Navid Nayeri, and Christian Oliver Paschereit
Wind Energ. Sci., 2, 671–683, https://doi.org/10.5194/wes-2-671-2017,https://doi.org/10.5194/wes-2-671-2017, 2017
Short summary

Related subject area

Aerodynamics and hydrodynamics
FLOW Estimation and Rose Superposition (FLOWERS): an integral approach to engineering wake models
Michael J. LoCascio, Christopher J. Bay, Majid Bastankhah, Garrett E. Barter, Paul A. Fleming, and Luis A. Martínez-Tossas
Wind Energ. Sci., 7, 1137–1151, https://doi.org/10.5194/wes-7-1137-2022,https://doi.org/10.5194/wes-7-1137-2022, 2022
Short summary
High-Reynolds-number investigations on the ability of the full-scale e-TellTale sensor to detect flow separation on a wind turbine blade section
Antoine Soulier, Caroline Braud, Dimitri Voisin, and Frédéric Danbon
Wind Energ. Sci., 7, 1043–1052, https://doi.org/10.5194/wes-7-1043-2022,https://doi.org/10.5194/wes-7-1043-2022, 2022
Short summary
Experimental investigation of mini Gurney flaps in combination with vortex generators for improved wind turbine blade performance
Jörg Alber, Marinos Manolesos, Guido Weinzierl-Dlugosch, Johannes Fischer, Alexander Schönmeier, Christian Navid Nayeri, Christian Oliver Paschereit, Joachim Twele, Jens Fortmann, Pier Francesco Melani, and Alessandro Bianchini
Wind Energ. Sci., 7, 943–965, https://doi.org/10.5194/wes-7-943-2022,https://doi.org/10.5194/wes-7-943-2022, 2022
Short summary
Parked and operating load analysis in the aerodynamic design of multi-megawatt-scale floating vertical-axis wind turbines
Mohammad Sadman Sakib and D. Todd Griffith
Wind Energ. Sci., 7, 677–696, https://doi.org/10.5194/wes-7-677-2022,https://doi.org/10.5194/wes-7-677-2022, 2022
Short summary
High-Reynolds-number wind turbine blade equipped with root spoilers – Part 1: Unsteady aerodynamic analysis using URANS simulations
Thomas Potentier, Emmanuel Guilmineau, Arthur Finez, Colin Le Bourdat, and Caroline Braud
Wind Energ. Sci., 7, 647–657, https://doi.org/10.5194/wes-7-647-2022,https://doi.org/10.5194/wes-7-647-2022, 2022
Short summary

Cited articles

Abbott, I. H. and Doenhoff, A. E. V.: Theory of Wing Sections, Including a Summary of Airfoil Data, 1st Edn., Dover Publications, Dover, 1959. a, b, c, d, e
Andersen, P. B., Gaunaa, M., Bak, C., and Hansen, M. H.: A Dynamic Stall Model for Airfoils with Deformable Trailing Edges, J. Phys.: Conf. Ser., 75, 012028, https://doi.org/10.1088/1742-6596/75/1/012028, 2007. a
Bak, C., Madsen, H. A., Fuglsang, P., and Rasmussen, F.: Double stall, in: vol. 1043, available at: http://orbit.dtu.dk/fedora/objects/orbit:90308/datastreams/file_7731788/content (last access: 13 September 2019), 1998. a, b
Bak, C., Madsen, H. A., Paulsen, U. S., Gaunaa, M., Fuglsang, P., Romblad, J., Olesen, N. A., Enevoldsen, P., Laursen, J., and Jensen, L.: DAN-AERO MW: Detailed aerodynamic measurements on a full scale MW wind turbine, in: European Wind Energy Conference and Exhibition (EWEC), 20–23 April 2010, Warsaw, Poland, 1–10, 2010. a
Balduzzi, F., Bianchini, A., Church, B., Wegner, F., Ferrari, L., Ferrara, G., and Paschereit, C. O.: Static and Dynamic Analysis of a NACA 0021 Airfoil Section at Low Reynolds Numbers Based on Experiments and Computational Fluid Dynamics, J. Eng. Gas Turb. Power, 141, 1–10, https://doi.org/10.1115/1.4041150, 2019. a
Download
Short summary
This study presents a marriage of unsteady aerodynamics and machine learning. When airfoils are subjected to high inflow angles, the flow no longer follows the surface and the flow is said to be separated. In this flow regime, the forces experienced by the airfoil are highly unsteady. This study uses a range of machine learning techniques to extract infomation from test data to help us understand the flow regime and makes recomendations on how to model it.
Altmetrics
Final-revised paper
Preprint