Machine learning strategies applied to the control of a fluidic pinball

C. Raibaudo; P. Zhong; B. Noack; R. Martinuzzi

doi:10.1063/1.5127202

Journal articles

Machine learning strategies applied to the control of a fluidic pinball

C. Raibaudo ¹ P. Zhong ¹ B. Noack ² R. Martinuzzi ¹

1 Schulich School of Engineering, The University of Calgary, Calgary, AB T2N 1N4, Canada

2 LIMSI - Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur

Document type :

Journal articles

Domain :

Engineering Sciences [physics] / Mechanics [physics.med-ph] / Fluids mechanics [physics.class-ph]

Statistics [stat] / Machine Learning [stat.ML]

Mathematics [math] / Optimization and Control [math.OC]

Complete list of metadata

https://hal-univ-orleans.archives-ouvertes.fr/hal-03371787
Contributor : Cédric Raibaudo Connect in order to contact the contributor
Submitted on : Friday, October 8, 2021 - 10:29:50 PM
Last modification on : Wednesday, March 16, 2022 - 3:54:02 AM

Machine learning strategies applied to the control of a fluidic pinball

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Machine learning strategies applied to the control of a fluidic pinball

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