76th Annual Meeting of the Division of Fluid Dynamics
Sunday–Tuesday, November 19–21, 2023;
Washington, DC
Session Index
Session R28: Emerging Trends in Fluid Dynamics: Physics-Informed Machine Learning and Dynamic Modeling
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Show Abstracts |
Chair: Wai Tong Chung, Stanford University
Room: 152A
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Monday, November 20, 2023
1:50PM - 2:03PM
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R28.00001: A Physics-Informed Machine Learning Approach for Predicting Atomized Drop Distributions in Liquid Jet Simulations
Chris J Cundy, Shahab Mirjalili, Charlelie Laurent, Stefano Ermon, Ali Mani
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Monday, November 20, 2023
2:03PM - 2:16PM
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R28.00002: Physics-Informed Neural Networks (PINN) for Enhanced Dynamic Modeling and Reverse Problem Solving in an Electro-Wetting Operated Microfluid Prism
Chihoon Song, Duck Gyu Lee, Jeongsu LEE, Keunhwan Park
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Monday, November 20, 2023
2:16PM - 2:29PM
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R28.00003: Predicting the three-dimensional separating flow in a diffuser using physics-informed neural networks
Ben Steinfurth, Julien Weiss
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Monday, November 20, 2023
2:29PM - 2:42PM
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R28.00004: DNS and physics-informed surrogate models of surfactant-laden dispersed flows
Juan Pablo Valdes, Fuyue Liang, Lyes Kahouadji, Sibo Cheng, Seungwon Shin, Jalel Chergui, Damir Juric, Omar K Matar
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Monday, November 20, 2023
2:42PM - 2:55PM
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R28.00005: Discovering self-similar blow-up solutions using physics-informed neural networks
Yongji Wang, Ching-Yao Lai, Tristan Buckmaster, Javier Gomez Serrano
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Monday, November 20, 2023
2:55PM - 3:08PM
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R28.00006: Semi-supervised machine learning model for Lagrangian state estimation
Reno Miura, Koji Fukagata
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Monday, November 20, 2023
3:08PM - 3:21PM
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R28.00007: Cooperative swimming at low Reynolds numbers using deep reinforcement learning
Yangzhe Liu, Zonghao Zou, On Shun Pak, Alan C. H. Tsang
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Monday, November 20, 2023
3:21PM - 3:34PM
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R28.00008: Reinforcement learning of reconfigurable microswimmers
Alan C. H. Tsang, On Shun Pak
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