Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
 
Session Overview
Session
MS01_02: Minisymposium - Data Science and AI in Fluid Mechanics
Time:
Tuesday, 17/September/2024:
2:30pm - 4:30pm

Session Chair: Ricardo Vinuesa, KTH Royal Institute of Technology
Location: H05

C.A.R.L.-Central Auditorium for Research and Learning Claßenstr. 11 52072 Aachen

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Presentations
2:30pm - 2:45pm

Reinforcement-learning-driven active control for drag reduction in wall-bounded turbulence at high Reynolds numbers

Zisong Zhou, Xiaojue Zhu

Max Planck Institute for Solar System Research, Justus-von-Liebig-Weg 3, 37077 Göttingen, Germany

Zhou-Reinforcement-learning-driven active control for drag reduction-950.pdf


2:45pm - 3:00pm

Reinforcement twinning algorithms for dynamic propeller control

Ruben Antonissen, Alessandro Zarri, Christophe Schram, Miguel Alfonso Mendez

von Karman Institute for Fluid Dynamics, Waterloosesteenweg 72, Sint-Genesius-Rode, Belgium

Antonissen-Reinforcement twinning algorithms for dynamic propeller control-838.pdf


3:00pm - 3:15pm

Real time data assimilation for the digital twinning of wind farms

Sebastiano Randino1, Lorenzo Schena1,2, Emmanuel Gillyns1,3, Nicolas Coudou1, Miguel Alfonso Mendez1

1von Karman Institute for Fluid Dynamics, Waterloosesteenweg 72, Sint-Genesius-Rode, Belgium; 2Vrije Universiteit Brussel (VUB), Elsene, Brussels, 1050, Belgium; 3Université Catholique de Louvain (UCLouvain), 1348 Louvain-la-Neuve, Belgium

Randino-Real time data assimilation for the digital twinning-905.pdf


3:15pm - 3:30pm

Physics-informed neural networks for the prediction of hidden fluid mechanics in droplet impingement

Maximilian Dreisbach1, Elham Kiyani2, Jochen Kriegseis1, George Karniadakis3, Alexander Stroh1

1Institute of Fluid Mechanics, Karlsruhe Institute of Technology, Kaiserstraße 10, 76131 Karlsruhe, Germany; 2Division of Applied Mathematics, Brown University, Providence, RI, 02912, USA; 3Division of Applied Mathematics and School of Engineering, Brown University, Providence, RI, 02912, USA

Dreisbach-Physics-informed neural networks for the prediction-1149.pdf


3:30pm - 3:45pm

Optimum control strategies for maximum thrust production in underwater undulatory swimming

Médéric Argentina1, Li Fu2, Sardor Israilov1, Jesus Sanchéz Rodriguéz3, Christophe Brouzet1, Guillaume Allibert1, Christophe Raufaste1

1Université Côte d'Azur; 2Ecole Centrale de Lyon; 3Universidad Nacional de Educacion a Distancia

Argentina-Optimum control strategies for maximum thrust production-1116.pdf


3:45pm - 4:00pm

Multi-fidelity Reinforcement Learning optimisation of coiled chemical reactors

Mosayeb Shams, Nausheen Basha, Antonio del Rio Chanona, Omar K. Matar

Imperial College London

Shams-Multi-fidelity Reinforcement Learning optimisation-1265.pdf


4:00pm - 4:15pm

Learning spatio-temporal wall-shear stress dynamics from outer-layer velocity fields in turbulent wall-bounded flows

Esther Lagemann, Christian Lagemann, Steven L. Brunton

AI Institute in Dynamic Systems, University of Washington, Seattle, United States

Lagemann-Learning spatio-temporal wall-shear stress dynamics-349.pdf


4:15pm - 4:30pm

Physics-Informed Neural Network Framework for Solving Aeroelastic Fluid-Structure Coupling Problems

Hongjie Zhou, Tingwei Ji, Changdong Zheng, Fangfang Xie

Center for Engineering and Scientific Computation, Zhejiang University, Zhejiang 310027, China

Zhou-Physics-Informed Neural Network Framework for Solving Aeroelastic Fluid-Structure-947.pdf


 
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