Bulletin of the American Physical Society

75th Annual Meeting of the Division of Fluid Dynamics

Volume 67, Number 19

Sunday–Tuesday, November 20–22, 2022; Indiana Convention Center, Indianapolis, Indiana.

Session Index

Session T29: CFD: Data-Driven and Machine Learning	Show Abstracts
Chair: Jian-Xun Wang, University of Notre Dame Room: 237

Monday, November 21, 2022 4:10PM - 4:23PM		T29.00001: Machine learning framework to predict flows over arbitrarily arranged solid arrays Geunhyeok Choi, Seungwon Shin, Seong Jin Kim
Monday, November 21, 2022 4:23PM - 4:36PM		T29.00002: A Neural Differentiable Solver for Efficient Simulation of Fluid-Structure Interaction Xiantao Fan, Jian-Xun Wang
Monday, November 21, 2022 4:36PM - 4:49PM		T29.00003: Competitive physics-informed networks for high-accuracy solutions to Navier-Stokes problems Yash Kothari, Qi Zeng, Florian Schaefer, Spencer H Bryngelson
Monday, November 21, 2022 4:49PM - 5:02PM		T29.00004: β-Variational autoencoders for nonlinear and ortogonal reduced-order models in turbulence Ricardo Vinuesa, Hamidreza Eivazi, Soledad Le Clainche, Sergio Hoyas
Monday, November 21, 2022 5:02PM - 5:15PM		T29.00005: Accelerating Poisson equation solvers with physics informed neural networks Morgan Kerhouant, Thomas Abadie, Raj Venuturumilli, Andre Nicolle, Omar K Matar
Monday, November 21, 2022 5:15PM - 5:28PM		T29.00006: Efficient high-dimensional variational data assimilation with machine-learned reduced-order models Romit Maulik, Vishwas Rao, Jiali Wang, Gianmarco Mengaldo, Emil Constantinescu, Bethany A Lusch, Prasanna Balaprakash, Ian Foster, Rao Kotamarthi
Monday, November 21, 2022 5:28PM - 5:41PM		T29.00007: Hydrokinetic turbine wake flow reconstruction in large-scale waterways using physics-informed convolutional neural networks Zexia Zhang, Ali Khosronejad
Monday, November 21, 2022 5:41PM - 5:54PM		T29.00008: On the application of data-driven modeling within the rotorcraft design space Nicholas Peters
Monday, November 21, 2022 5:54PM - 6:07PM		T29.00009: Efficient and Robust Training Strategies for Physics and Equality Constrained Artificial Neural Networks shamsulhaq basir, Inanc Senocak
Monday, November 21, 2022 6:07PM - 6:20PM		T29.00010: Prediction and Control of 2D Decaying Turbulence using Generative Adversarial Networks Jiyeon Kim, Junhyuk Kim, Changhoon Lee
Monday, November 21, 2022 6:20PM - 6:33PM		T29.00011: A heterogeneous computing approach to coupled simulation and machine-learning deployment for high-speed flows Charlelie Laurent, Kazuki Maeda
Monday, November 21, 2022 6:33PM - 6:46PM		T29.00012: Machine Learning Flux-Limiters for Compressible Flow Simulations Robert M Chiodi, Nga T Nguyen-Fotiadis, Michael McKerns, Andrew T Sornborger, Daniel Livescu

About APS

The American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics.

Headquarters 1 Physics Ellipse, College Park, MD 20740-3844 (301) 209-3200
Editorial Office 100 Motor Pkwy, Suite 110, Hauppauge, NY 11788 (631) 591-4000
Office of Public Affairs 529 14th St NW, Suite 1050, Washington, D.C. 20045-2001 (202) 662-8700

Bulletin of the American Physical Society

75th Annual Meeting of the Division of Fluid Dynamics

Volume 67, Number 19

Sunday–Tuesday, November 20–22, 2022; Indiana Convention Center, Indianapolis, Indiana.

Session Index

Session T29: CFD: Data-Driven and Machine Learning

Follow Us

Engage

My APS

Information for

About APS