Low-Order Modeling and Machine Learning in Fluid Dynamics: Methods I

Presentations

• Adaptive Local Domain Decomposition for Learning Large-Scale Multi-physics Numerical Simulations

  ORAL

  Nov. 24, 2024, 10:00 AM – Nov. 24, 2024, 10:13 AM

  Presenters

  • Wenzhuo Xu

    Carnegie Mellon University

  Authors

  • Wenzhuo Xu

    Carnegie Mellon University

  • Christopher McComb

    Carnegie Mellon University

  • Noelia Grande Gutiérrez

    Carnegie Mellon University

  View abstract →

• Robust dominant balance analysis for identifying governing flow physics in experimental settings

  ORAL

  Nov. 24, 2024, 10:13 AM – Nov. 24, 2024, 10:26 AM

  Presenters

  • Samuel Ahnert

    University of Washington

  Authors

  • Samuel Ahnert

    University of Washington

  • Christian Lagemann

    AI Institute in Dynamic Systems, University of Washington, University of Washington

  • Esther Lagemann

    AI Institute in Dynamic Systems, University of Washington

  • Steven L Brunton

    University of Washington

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• SGD-SINDy: Stochastic Gradient-Descent based Framework for Flexible System Identification

  ORAL

  Nov. 24, 2024, 10:26 AM – Nov. 24, 2024, 10:39 AM

  Presenters

  • Amirhossein Arzani

    University of Utah

  Authors

  • Amirhossein Arzani

    University of Utah

  • Siva Viknesh

    University of Utah

  • Younes Tatari

    University of Utah

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• At the intersection of Reduced Order Modelling and Discrete Loss Minimization: Can complicated, high-Re incompressible flow models become edge computable?

  ORAL

  Nov. 24, 2024, 10:39 AM – Nov. 24, 2024, 10:52 AM

  Presenters

  • Sean R Breckling

    Nevada National Security Site (NNSS)

  Authors

  • Sean R Breckling

    Nevada National Security Site (NNSS)

  • Jacob Murri

    University of California Los Angeles

  • Clifford E Watkins

    Special Technologies Laboratory (STL), Nevada National Security Sites

  • Caleb C Monoran

    Nevada National Security Sites, Nevada National Security Site

  • James Watts

    Colorado School of Mines

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• Data-Driven Resolvent Analysis with Residual Information

  ORAL

  Nov. 24, 2024, 10:52 AM – Nov. 24, 2024, 11:05 AM

  Presenters

  • Katherine Cao

    Stanford University

  Authors

  • Katherine Cao

    Stanford University

  • Matthew J Colbrook

    DAMTP, Cambridge University

  • Benjamin Herrmann

    Universidad de Chile

  • Steven L Brunton

    University of Washington

  • Beverley J McKeon

    Stanford University

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• KOopman Operator Learning : A KOOL model for long term stable prediction of dynamical systems

  ORAL

  Nov. 24, 2024, 11:05 AM – Nov. 24, 2024, 11:18 AM

  Presenters

  • Dibyajyoti Chakraborty

    Pennsylvania State University

  Authors

  • Dibyajyoti Chakraborty

    Pennsylvania State University

  • Conrad S Ainslie

    University of California, Santa Cruz

  • Derek F DeSantis

    Los Alamos National Lab

  • Arvind T Mohan

    Los Alamos National Laboratory (LANL)

  • Ashesh K Chattopadhyay

    University of California, Santa Cruz

  • Romit Maulik

    Pennsylvania State University

  View abstract →

• Data-Driven Dimension Reduction Through Symmetry-Promoting Regularization

  ORAL

  Nov. 24, 2024, 11:18 AM – Nov. 24, 2024, 11:31 AM

  Presenters

  • Nicholas Zolman

    University of Washington

  Authors

  • Nicholas Zolman

    University of Washington

  • Samuel E Otto

    University of Washington

  • J. Nathan Kutz

    University of Washington, University of Washington, AI Institute for Dynamic Systems

  • Steven L Brunton

    University of Washington

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• Dynamic Stall Estimation with Transition Networks

  ORAL

  Nov. 24, 2024, 11:31 AM – Nov. 24, 2024, 11:44 AM

  Presenters

  • Ricardo Cavalcanti Linhares

    University of Minnesota

  Authors

  • Ricardo Cavalcanti Linhares

    University of Minnesota

  • Karen Mulleners

    École Polytechnique Fédérale de Lausanne

  • Ellen Kathryn Longmire

    University of Minnesota

  • Melissa A Green

    University of Minnesota

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• A Y-network encoder-decoder model for predicting vorticity fields from kinetic energy spectra in 2D decaying turbulence

  ORAL

  Nov. 24, 2024, 11:44 AM – Nov. 24, 2024, 11:57 AM

  Presenters

  • Mrigank Dhingra

    Virginia Tech

  Authors

  • Mrigank Dhingra

    Virginia Tech

  • Omer San

    University of Tennessee

  • Anne E Staples

    Virginia Tech, Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, 24061

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• Neural Operator Based Coarse-Grid Navier-Stokes / Interface Tracking Model Development

  ORAL

  Nov. 24, 2024, 11:57 AM – Nov. 24, 2024, 12:10 PM

  Presenters

  • Arsen S Iskhakov

    Kansas State University

  Authors

  • Anna Iskhakova

    Kansas State University

  • Arsen S Iskhakov

    Kansas State University

  • Nam T Dinh

    North Carolina State University

  • Igor A Bolotnov

    North Carolina State University

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• Learning Acoustic Scattering in Turbulent Stratified Flows With Neural Operators

  ORAL

  Nov. 24, 2024, 12:10 PM – Nov. 24, 2024, 12:23 PM

  Presenters

  • Christophe Millet

    CEA, DAM, DIF, F-91297 Arpajon, France

  Authors

  • Christophe Millet

    CEA, DAM, DIF, F-91297 Arpajon, France

  View abstract →