Modeling Methods I: Closure Models, Automated Discovery of Equations, and Prediction

Presentations

• Closure modeling through the lens of multifidelity operator learning

  ORAL

  Nov. 20, 2023, 1:50 PM – Nov. 20, 2023, 2:03 PM

  Publication: Ahmed, S. E., & Stinis, P. (2023). A multifidelity deep operator network approach to closure for multiscale systems. Computer Methods in Applied Mechanics and Engineering, 414, 116161.

  Presenters

  • Shady E Ahmed

    • Pacific Northwest National Laboratory

  Authors

  • Shady E Ahmed

    • Pacific Northwest National Laboratory

  • Panos Stinis

    • Pacific Northwest National Laboratory

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• A Closed Machine Learning Parametric Reduced Order Model Approach - Application to Turbulent Flows

  ORAL

  Nov. 20, 2023, 2:03 PM – Nov. 20, 2023, 2:16 PM

  Publication: https://arxiv.org/pdf/2304.14183.pdf

  Presenters

  • Rama AYOUB

    • King Abdullah Univ of Sci & Tech (KAUST)

  Authors

  • Rama AYOUB

    • King Abdullah Univ of Sci & Tech (KAUST)

  • Mourad Oulghelou

    • ENSAM

  • Amine AMMAR

    • ENSAM

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• Discovery of viscoelastic constitutive models with complexity-penalized sparse regression

  ORAL

  Nov. 20, 2023, 2:16 PM – Nov. 20, 2023, 2:29 PM

  Presenters

  • Sarah Beetham

    • Oakland University

  Authors

  • Sarah Beetham

    • Oakland University

  • Konstantinos Zinelis

    • Imperial College London

  • Thomas Abadie

    • Department of Chemical Engineering, Imperial College London

  • Gareth H McKinley

    • Massachusetts Institute of Technology

  • Omar K Matar

    • Imperial College London

  • Jesse Capecelatro

    • University of Michigan

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• Neural Operator for Modeling Dynamical Systems with Trajectories and Statistics Matching

  ORAL

  Nov. 20, 2023, 2:29 PM – Nov. 20, 2023, 2:42 PM

  Presenters

  • Chuanqi Chen

    • University of Wisconsin - Madison

  Authors

  • Chuanqi Chen

    • University of Wisconsin - Madison

  • Jinlong Wu

    • University of Wisconsin-Madison
    • University of Wisconsin - Madison
    • University of Wisconsin–Madison

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• Bayesian Identification of Nonlinear Dynamics (BINDy)

  ORAL

  Nov. 20, 2023, 2:42 PM – Nov. 20, 2023, 2:55 PM

  Presenters

  • Lloyd Fung

    • Univ of Cambridge

  Authors

  • Lloyd Fung

    • Univ of Cambridge

  • Urban Fasel

    • Imperial College London

  • Matthew P Juniper

    • Univ of Cambridge

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• Application of Denoising Diffusion Probabilistic Models to Turbulence Prediction

  ORAL

  Nov. 20, 2023, 2:55 PM – Nov. 20, 2023, 3:08 PM

  Presenters

  • Jiyeon Kim

    • Yonsei University

  Authors

  • Jiyeon Kim

    • Yonsei University

  • Changhoon Lee

    • Yonsei University

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• Data-driven observable discovery for reduced-order modeling of turbulence based on the Mori-Zwanzig formalism

  ORAL

  Nov. 20, 2023, 3:08 PM – Nov. 20, 2023, 3:21 PM

  Presenters

  • Joel Barnett

    • University of California, Los Angeles

  Authors

  • Yifeng Tian

    • Los Alamos National Laboratory

  • Joel Barnett

    • University of California, Los Angeles

  • Yen Ting Lin

    • Los Alamos National Labs

  • Daniel Livescu

    • LANL

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• An improved likelihood-weighted sequential sampling method for extreme events statistics

  ORAL

  Nov. 20, 2023, 3:21 PM – Nov. 20, 2023, 3:34 PM

  Presenters

  • Xianliang Gong

    • University of Michigan

  Authors

  • Xianliang Gong

    • University of Michigan

  • Yulin Pan

    • University of Michigan

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