Bulletin of the American Physical Society
76th Annual Meeting of the Division of Fluid Dynamics
Sunday–Tuesday, November 19–21, 2023; Washington, DC
Session L17: Machine Learning for Inference and Analysis of Fluid Flows
8:00 AM–10:36 AM,
Monday, November 20, 2023
Room: 145B
Chair: Aaron Towne, University of Michigan
Abstract: L17.00002 : Overview of a database for reduced-complexity modeling of fluid flows
8:13 AM–8:26 AM
Presenter:
Aaron S Towne
(University of Michigan)
Authors:
Aaron S Towne
(University of Michigan)
Scott T Dawson
(Illinois Institute of Technology)
Guillaume Bres
(Cascade Technologies)
Adrian Lozano-Duran
(MIT)
Theresa A Saxton-Fox
(University of Illinois Urbana Champaign)
Aadhy S Parthasarathy
(University of Illinois at Urbana-Champai)
Anya R Jones
(U Maryland)
Hulya Biler
(University of Maryland)
Chi-An Yeh
(North Carolina State University)
Het D Patel
(North Carolina State University)
Kunihiko Taira
(UCLA)
[1] Towne, A., Dawson, S.T.M., Brès, G.A, Lozano-Durán, A., Saxton-Fox, T., Parthasarathy, A., Jones, A.R., Biler, H., Yeh, C.-A. Patel, H.D., Taira, K. (2023). A Database for Reduced-Complexity Modeling of Fluid Flows. AIAA Journal, 61 (7), 2867-2892.
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