Artificial intelligence control applied to drag reduction of the fluidic pinball-Reference-Cited by-同舟云学术

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Artificial intelligence control applied to drag reduction of the fluidic pinball

Published:2019-11 Issue:1 Volume:19 Page:
ISSN:1617-7061
Container-title:PAMM
language:en
Short-container-title:Proc. Appl. Math. Mech.

Author:

Cornejo Maceda Guy Y.¹,Noack Bernd R.²³⁴,Lusseyran François²,Deng Nan⁵,Pastur Luc⁵,Morzynski Marek⁶

Affiliation:

1. LIMSI, CNRS Univ. Paris-Sud, Université Paris-Saclay F-91405Orsay

2. LIMSI, CNRS Université Paris-Saclay F-91405Orsay

3. Harbin Institute of Technology China

4. Technische Universität Berlin Germany

5. IMSIA - UMR9219 ENSTA ParisTech France

6. Poznan University of Technology Poland

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/pamm.201900268

Reference4 articles.

1. D.Dracopoulos Evolutionary Learning Algorithms for Neural Adaptive Control Springer 1997

2. S.Brunton B. R.Noack Closed-Loop Turbulence Control: Progress and Challenges 2015 Appl. Mech. Rev. 67 050801

3. T.Duriez S.Brunton B. R.Noack Machine Learning Control: Taming Nonlinear Dynamics and Turbulence Springer 2016

4. B. R.Noack M.Morzyński The Fluidic Pinball: A Toolkit for Multiple-Input Multiple-Output Flow Control. Tech. Rep. 02/2017

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4. Machine-learning flow control with few sensor feedback and measurement noise;Physics of Fluids;2022-04

5. Explorative gradient method for active drag reduction of the fluidic pinball and slanted Ahmed body;Journal of Fluid Mechanics;2021-12-06

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