Focus Session: Deep Learning in Experimental and Computational Fluid Mechanics (Part II) (5:45pm - 6:30pm CST)

Presentations

• Super-resolution of Finite Element spaces using Physics-informed Deep Learning Networks for Turbulent flows

  POSTER

  Authors

  • Aniruddhe Pradhan

    • University of Michigan

  • Rajarshi Biswas

    • University of Michigan

  • Karthik Duraisamy

    • University of Michigan, Ann arbor
    • University of Michigan

  View abstract →

• Dispersed Multiphase Flow Generation using 3D Steerable Convolutional Neural Network

  POSTER

  Authors

  • Bhargav Sriram Siddani

    • University of Florida

  • S. Balachandar

    • University of Florida
    • Department of Mechanical and Aerospace Engineering, University of Florida

  • Ruogu Fang

    • University of Florida

  • W. C. Moore

    • University of Florida

  • Yunchao Yang

    • University of Florida

  View abstract →

• Deep Reinforcement Learning for Control of Fuel Injection in Compression Ignition Engines

  POSTER

  Authors

  • Nicholas Wimer

    • National Renewable Energy Laboratory

  • Marc Henry de Frahan

    • National Renewable Energy Laboratory

  • Shashank Yellapantula

    • National Renewable Energy Laboratory

  • Ray Grout

    • National Renewable Energy Laboratory

  View abstract →

• Performance Bounds of Data-Driven Reynolds Stress Models via Optimal Tensor Basis Expansions

  POSTER

  Authors

  • Andrew Banko

    • Stanford University

  • Christopher J. Elkins

    • Stanford University

  • John K. Eaton

    • Stanford University

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• Using generative adversarial networks for subfilter modeling of turbulent flows

  POSTER

  Authors

  • Mathis Bode

    • RWTH Aachen University

  View abstract →

• Predictions in Wall-bounded Turbulence Through Convolutional-network Models Using Wall Quantities

  POSTER

  Authors

  • Luca Guastoni

    • KTH Royal Institute of Technology

  • Alejandro G\"uemes

    • Universidad Carlos III de Madrid

  • Andrea Ianiro

    • Universidad Carlos III de Madrid

  • Stefano Discetti

    • Universidad Carlos III de Madrid

  • Philipp Schlatter

    • SimEx/FLOW, KTH Engineering Mechanics
    • KTH Royal Institute of Technology
    • KTH Royal Institute of Technology, Engineering Mechanics
    • SimEx/FLOW, KTH Engineering Mechanics, Stockholm, Sweden

  • Hossein Azizpour

    • KTH Royal Institute of Technology

  • Ricardo Vinuesa

    • SimEx/FLOW, KTH Engineering Mechanics
    • KTH Royal Institute of Technology
    • KTH Royal Institute of Technology, Engineering Mechanics
    • SimEx/FLOW, KTH Engineering Mechanics, Stockholm, Sweden

  View abstract →

• SimNet: A neural network solver for multi-Physics applications

  POSTER

  Authors

  • Oliver Hennigh

    • Nvidia

  • Kaustubh Tangsali

    • Nvidia

  • Akshay Subramaniam

    • Nvidia

  • Susheela Narasimhan

    • Nvidia

  • Mohammad Nabian

    • Nvidia

  • Jose del Aguila Ferrandis

    • Nvidia

  • Sanjay Choudhry

    • Nvidia

  View abstract →

• Generalization of Machine Learning Criteria for Ignition Prediction

  POSTER

  Authors

  • Faustino Martinez

    • San Diego State University

  • Pavel Popov

    • San Diego State University

  View abstract →

• Learning minimal representations for chaotic dynamics of partial differential equations

  POSTER

  Authors

  • Alec J. Linot

    • University of Wisconsin - Madison

  • Michael D. Graham

    • University of Wisconsin - Madison

  View abstract →

• Flowtaxis in the wakes of oscillating airfoils

  POSTER

  Authors

  • Haotian Hang

    • University of Southern California

  • Sina Heydari

    • University of Southern California

  • Brendan Colvert

    • University of California, San Diego

  • Eva Kanso

    • University of Southern California
    • Univ of Southern California
    • Dept. of Aerospace and Mechanical Engineering, University of Southern California

  View abstract →

• Physics-informed Autoencoders for Operator-theoretic decomposition and Model reduction of Complex Flows

  POSTER

  Authors

  • Karthik Duraisamy

    • University of Michigan, Ann arbor
    • University of Michigan

  • Shaowu Pan

    • University of Michigan, Ann arbor
    • University of Michigan

  View abstract →

• Fast solver of the shallow water equations with application to estimation of the riverine surface flow velocity

  POSTER

  Authors

  • Mojtaba Forghani

    • Stanford Univ

  • Yizhou Qian

    • Stanford Univ

  • Peter Kitanidis

    • Stanford Univ

  • Matthew Farthing

    • US Army Eng Res and Dev Ctr

  • Tyler Hesser

    • US Army Eng Res and Dev Ctr

  • Jonghyun Lee

    • University of Hawaii

  • Eric Darve

    • Stanford Univ

  View abstract →

• Deep learning to predict the effectiveness factor in the closure problems

  POSTER

  Authors

  • Ehsan Taghizadeh

    • Oregon State University

  • Paul Macklin

    • Indiana University

  • Helen Byrne

    • University of Oxford

  • Brian Wood

    • Oregon State University

  View abstract →

• Embedded training of neural-network sub-grid-scale turbulence models

  POSTER

  Authors

  • Justin Sirignano

    • University of Oxford and University of Illinois at Urbana-Champaign

  • Jonathan MacArt

    • University of Notre Dame

  • Jonathan Freund

    • University of Illinois at Urbana-Champaign

  View abstract →

• Deep learning-based assignment of combustion submodels for large-eddy simulation

  POSTER

  Authors

  • Wai Tong Chung

    • Stanford University

  • Aashwin Mishra

    • Center for Turbulence Research, Stanford University

  • Nikolaos Perakis

    • Technical University Munich

  • Matthias Ihme

    • Stanford Univ
    • Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, United States
    • Stanford University

  View abstract →

• Embedding Physics as Hard Constraints in Generative Adversarial Networks for 3D Turbulence

  POSTER

  Authors

  • Dima Tretiak

    • Los Alamos National Laboratory

  • Arvind Mohan

    • Los Alamos National Laboratory, Los Alamos, NM 87545
    • Los Alamos National Laboratory, Los Alamos, NM, USA
    • Los Alamos National Laboratory

  • Daniel Livescu

    • Los Alamos National Laboratory
    • Los Alamos National Laboratory, Los Alamos, NM, USA
    • Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87544

  View abstract →

• Dynamic Masking of PIV Images using Deep Learning

  POSTER

  Authors

  • Bernhard Vennemann

    • Institute of Fluid Dynamics, ETH Zurich

  • Thomas Rösgen

    • ETH Zurich
    • Institute of Fluid Dynamics, ETH Zurich

  View abstract →

• Pollution Source Localization Using Physics-Driven Deep Neural Net

  POSTER

  Authors

  • Roshan D'Souza

    • University of Wisconsin-Milwaukee

  • Isaac Perez-Raya

    • University of Wisconsin-Milwaukee

  View abstract →

• LES Turbulence Model with Learnt Closure; Integration of DNN into a CFD Solver

  POSTER

  Authors

  • Majid Haghshenas

    • University of Massachusetts Amherst

  • Peetak Mitra

    • University of Massachusetts, Amherst, MA 01003
    • University of Massachusetts Amherst

  • Niccolo Dal Santo

    • MathWorks

  • Mateus Dias Ribeiro

    • German Research Center for Artificial Intelligence (DFKI)

  • Shounak Mitra

    • MathWorks

  • David Schmidt

    • University of Massachusetts, Amherst, MA 01003
    • University of Massachusetts Amherst
    • Department of Mechanical and Industrial Engineering, University of Massachusetts, Amherst MA USA

  View abstract →

• Deep learning-based shadowgraph: implementation of Mask R-CNN to bubble detection in complex two-phase

  POSTER

  Authors

  • Yewon Kim

    • Seoul Natl Univ

  • Hyungmin Park

    • Seoul Natl Univ
    • Seoul National University

  View abstract →

• A hybrid data-driven deep learning technique for fluid-structure interaction

  POSTER

  Authors

  • Rajeev Jaiman

    • University of British Colombia
    • Mechanical Engineering, University of British Columbia
    • Department of Mechanical Engineering, University of British Columbia
    • University of British Columbia
    • The University of British Columbia

  • Tharindu Miyanawala

    • University of Moratuwa

  View abstract →

• Learning to write and paint using a liquid rope trick

  POSTER

  Authors

  • Gaurav Chaudhary

    • Harvard University, MIT

  • Stephanie Christ

    • Harvard University

  • A. John Hart

    • MIT

  • Mahadevan Lakshminarayanan

    • Harvard University
    • John A. Paulson School of Engineering and Applied Sciences, Harvard University
    • School of Engineering and Applied Sciences, Harvard University

  View abstract →

• Inference on spatially unstructured flow fields using Graph Neural Networks

  POSTER

  Authors

  • Francis Ogoke

    • Carnegie Mellon University

  • Kazem Meidani

    • Carnegie Mellon Univ
    • Carnegie Mellon University

  • Amirreza Hashemi

    • University of Pittsburgh

  • Amir Barati Farimani

    • Carnegie Mellon Univ
    • Carnegie Mellon University

  View abstract →

• Machine Learning Statistical Lagrangian Geometry of Turbulence

  POSTER

  Authors

  • Criston Hyett

    • Program in Applied Mathematics, University of Arizona, Tucson, AZ 85721

  • Michael Chertkov

    • Program in Applied Mathematics & Department of Mathematics, University of Arizona, Tucson, AZ 85721
    • Program in Applied Mathematics, University of Arizona, Tucson, AZ 85721

  • Yifeng Tian

    • Los Alamos National Laboratory
    • Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87544

  • Daniel Livescu

    • Los Alamos National Laboratory
    • Los Alamos National Laboratory, Los Alamos, NM, USA
    • Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87544

  View abstract →

• Modeling active fluids via physically constrained machine learning

  POSTER

  Authors

  • Matthew Golden

    • Georgia Inst of Tech

  • Jyothishraj Nambisan

    • Georgia Inst of Tech

  • Alberto Fernandez-Nieves

    • Georgia Inst of Tech

  • Roman Grigoriev

    • Georgia Institute of Technology

  View abstract →

• Reconstruction of Turbulent High-resolution DNS Data Using Deep Learning

  POSTER

  Authors

  • Pranshu Pant

    • Carnegie Mellon University

  • Amir Barati Farimani

    • Carnegie Mellon Univ
    • Carnegie Mellon University

  View abstract →

• Machine Learning of Reduced Lagrangian Models of Turbulence

  POSTER

  Authors

  • Michael Woodward

    • Program in Applied Mathematics & Department of Mathematics, University of Arizona, Tucson, AZ 85721

  • Yifeng Tian

    • Los Alamos National Laboratory
    • Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87544

  • Michael Chertkov

    • Program in Applied Mathematics & Department of Mathematics, University of Arizona, Tucson, AZ 85721
    • Program in Applied Mathematics, University of Arizona, Tucson, AZ 85721

  • Mikhail Stepanov

    • Program in Applied Mathematics & Department of Mathematics, University of Arizona, Tucson, AZ 85721

  • Daniel Livescu

    • Los Alamos National Laboratory
    • Los Alamos National Laboratory, Los Alamos, NM, USA
    • Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87544

  • Chris Fryer

    • Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87544

  View abstract →

• Physics-informed Machine Learning of the Lagrangian Dynamics of Velocity Gradient Tensor

  POSTER

  Authors

  • Yifeng Tian

    • Los Alamos National Laboratory
    • Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87544

  • Daniel Livescu

    • Los Alamos National Laboratory
    • Los Alamos National Laboratory, Los Alamos, NM, USA
    • Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87544

  • Michael Chertkov

    • University of Arizona

  View abstract →

• Learning Physics-based Galerkin models of turbulence with Neural Differential Equations

  POSTER

  Authors

  • Arvind Mohan

    • Los Alamos National Laboratory, Los Alamos, NM 87545
    • Los Alamos National Laboratory, Los Alamos, NM, USA
    • Los Alamos National Laboratory

  • Kaushik Nagarajan

    • National Aerospace Laboratories, Bengaluru, India

  • Daniel Livescu

    • Los Alamos National Laboratory
    • Los Alamos National Laboratory, Los Alamos, NM, USA
    • Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87544

  View abstract →

• Designing networks to accurately learn 2D turbulence closures

  POSTER

  Authors

  • Keaton Burns

    • MIT
    • Massachusetts Institute of Technology
    • Massachusetts Institute of Technology, Flatiron Institute

  • Ronan Legin

    • University of Montreal & McGill University

  • Adrian Liu

    • McGill University

  • Laurence Perreault-Levasseur

    • Mila, University of Montreal, Flatiron Institute

  • Yashar Hezaveh

    • University of Montreal, Flatiron Institute

  • Siamak Ravanbakhsh

    • Mila, McGill University

  • Gregory Wagner

    • Massachusetts Institute of Technology

  View abstract →

• Turbulence closure modeling with machine-learning methods: Influence of choice of neural network and training procedure

  POSTER

  Authors

  • Salar Taghizadeh

    • Texas A&M University

  • Yassin Hassan

    • Texas A&M University

  • Freddie Witherden

    • Texas A&M University

  • Sharath Girimaji

    • Texas A&M University
    • Texas A&M

  View abstract →

• Turbulence closure modeling with Machine-Learning Methods: Can RANS overcome curse of averaging?

  POSTER

  Authors

  • Sharath Girimaji

    • Texas A&M University
    • Texas A&M

  View abstract →

• A Deep Learning Based Physics Informed Continuous Spatio Temporal Super-Resolution Framework

  POSTER

  Authors

  • Soheil Esmaeilzadeh

    • Stanford University

  • Chiyu Max Jiang

    • UC Berkeley

  • Kamyar Azizzadenesheli

    • California Institute of Technology

  • Karthik Kashinath

    • Lawrence Berkeley National Laboratory

  • Mustafa Mustafa

    • Lawrence Berkeley National Laboratory

  • Hamdi Tchelepi

    • Stanford University

  • Philip Marcus

    • UC Berkeley

  • Mr Prabhat

    • Lawrence Berkeley National Laboratory

  • Anima Anandkumar

    • California Institute of Technology and NVIDIA

  View abstract →

• Developing an automatic calibration tool for turbulence closure models using machine learning techniques

  POSTER

  Authors

  • Ismael Boureima

    • Los Alamos National Laboratory

  • Vitaliy Gyrya

    • Los Alamos National Laboratory

  • Juan Saenz

    • Los Alamos Natl Lab
    • Los Alamos National Laboratory

  • Susan Kurien

    • Los Alamos National Laboratory

  View abstract →