Low-Order Modeling and Machine Learning in Fluid Dynamics: Flow Control
ORAL · U25 · ID: 3583236
Presentations
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Improving turbulence control through explainable deep learning
ORAL
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Publication: https://arxiv.org/pdf/2504.02354
Presenters
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Miguel Beneitez
- University of Manchester
Authors
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Miguel Beneitez
- University of Manchester
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Andres Cremades
- KTH Royal Institute of Technology
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Luca Guastoni
- Technical University Munich
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Ricardo Vinuesa
- KTH Royal Institute of Technology
- University of Michigan
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Machine learning-assisted flow control based on an Iterative Linear System Identification
ORAL
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Publication: Planned to submit to arXiv
Presenters
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Kazuma Funai
- Keio Univ
Authors
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Kazuma Funai
- Keio Univ
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Koji Fukagata
- Keio Univ
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Data-driven closure for Koopman control of non-linear systems
ORAL
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Presenters
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Priyam Gupta
- Imperial College London
Authors
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Priyam Gupta
- Imperial College London
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Denis Sipp
- DAAA, ONERA, Institut Polytechnique de Paris
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Taraneh Sayadi
- Conservatoire national des arts et métiers
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Peter J Schmid
- King Abdullah University of Science and Technology
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Georgios Rigas
- Imperial College London
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Abstract Withdrawn
ORAL · Withdrawn
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Reinforcement-Learning-Driven Active Flow Control for Airfoil Pitching Moment Trim
ORAL
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Presenters
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Prasanna Thoguluva Rajendran
- University of Arizona
Authors
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Prasanna Thoguluva Rajendran
- University of Arizona
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Laurent Pagnier
- University of Arizona
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Farzad Mashayek
- University of Arizona
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Impulsive control of low-frequency oscillation of subsonic flow around an airfoil
ORAL
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Presenters
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Nobutaka Taniguchi
- Tohoku University
Authors
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Nobutaka Taniguchi
- Tohoku University
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Yuya Ohmichi
- Japan Aerospace Exploration Agency
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Transformer-based reinforcement learning for aerodynamic lift regulation in gust sequences
ORAL
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Publication: Zhecheng Liu and Jeff D. Eldredge (2025). "Attention on flow control: transformer-based reinforcement learning for lift regulation in highly disturbed flows". arXiv, https://arxiv.org/abs/2506.10153.
Presenters
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Zhecheng Liu
- University of California, Los Angeles
Authors
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Zhecheng Liu
- University of California, Los Angeles
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Jeff D Eldredge
- University of California, Los Angeles
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Feedback control of vortex shedding using data driven modelling with minimal sensing
ORAL
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Publication: This work is a sub-set of a larger study which is currently in preparation for submission to the Journal of Fluid Mechanics with the intention to submit in the next 2 months.
Presenters
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Jack Proudfoot
- University of Oxford
Authors
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Jack Proudfoot
- University of Oxford
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Chris James Nicholls
- University of Oxford
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Brian M Tang
- University of Oxford
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Marko Bacic
- University of Oxford
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Deep Reinforcement Learning and Spatiotemporal Transformers for Intelligent Drug Delivery & Flow Control in Thrombosis Prevention
ORAL
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Presenters
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Mohammad Sarabian
- W. L. Gore & Associates
Authors
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Mohammad Sarabian
- W. L. Gore & Associates
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Sudeep Sastry
- W. L. Gore & Associates, Inc
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Non-intrusive model reduction for open-loop control of shock dynamics in scramjet isolators
ORAL
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Presenters
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Cole J Errico
- University of Illinois Urbana-Champaign
Authors
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Cole J Errico
- University of Illinois Urbana-Champaign
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Alberto Padovan
- University of Illinois at Urbana-Champaign
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Daniel Joseph Bodony
- University of Illinois at Urbana-Champaign
- University of Illinois Urbana-Champaign
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Control of viscoelastic turbulence via wall blowing & suction optimised by reinforcement learning
ORAL
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Publication: None yet; manuscript in preparation.
Presenters
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Udit Sharma
- KTH Royal Institute of Technology
Authors
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Udit Sharma
- KTH Royal Institute of Technology
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Miguel Beneitez
- Department of Mechanical and Aerospace Engineering, The University of Manchester, UK
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Lisa Wittberg
- KTH Royal Institute of Technology
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Ricardo Vinuesa
- KTH Royal Institute of Technology
- University of Michigan
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Outi Tammisola
- FLOW and SeRC (Swedish e-Science Research Centre), Department of Engineering Mechanics, KTH Royal Institute of Technology, Stockholm, Sweden
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Seyedshahabaddin Mirjalili
- KTH Royal Institute of Technology
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Abstract Withdrawn
ORAL · Withdrawn
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