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Poster communications

Real-time unsteady air flow prediction to reduces mechanic load variations and wind turbine maintenance costs

Abstract : For actively controlling aerodynamic systems – like Wind Turbine (WT) blades -- it can be necessary to estimate in real-time and predict the air flow around those systems. We propose here a new method which combines machine learning, physical models and measurements for this purpose. Very good numerical results have been obtained on wake flows.
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https://hal.inrae.fr/hal-03278863
Contributor : Dominique Heitz Connect in order to contact the contributor
Submitted on : Tuesday, July 6, 2021 - 8:58:38 AM
Last modification on : Tuesday, October 19, 2021 - 10:48:10 AM
Long-term archiving on: : Thursday, October 7, 2021 - 6:13:25 PM

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  • HAL Id : hal-03278863, version 1

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Valentin Resseguier, Matheus Ladvig, Agustin Martin Picard, Etienne Mémin, Dominique Heitz, et al.. Real-time unsteady air flow prediction to reduces mechanic load variations and wind turbine maintenance costs. SEANERGY 2021 - International leading event on offshore wind and marine renewable energy, Sep 2021, Nantes, Saint-Nazaire, France. pp.1. ⟨hal-03278863⟩

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