Low-Order Modeling: Applications
ORAL · L28 · ID: 1765197
Presentations
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Application of Machine Learning in non-Newtonian Flows
ORAL
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Presenters
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Dibyajyoti Chakraborty
Penn State Univeristy
Authors
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Dibyajyoti Chakraborty
Penn State Univeristy
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Shivasubramanian Gopalakrishnan
Indian Institute of Technology, Bombay, Indian Institute of Technology Bombay
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Nonlinear parametric models of viscoelastic fluid flows
ORAL
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Presenters
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Cassio M Oishi
São Paulo State University
Authors
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Cassio M Oishi
São Paulo State University
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Alan A Kaptanoglu
New York University
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Nathan Kutz
University of Washington, University of Washington, AI Institute for Dynamic Systems
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Steven L Brunton
University of Washington, Department of Mechanical Engineering, University of Washington
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Using Artificial Intelligence for Transient Heat Transfer
ORAL
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Presenters
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Ayush Garg
Dublin High School
Authors
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Arturo Rodriguez
University of Texas at El Paso
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Ayush Garg
Dublin High School
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Rafael Baez Ramirez
University of Texas at El Paso
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Jose Perez
University of Texas at El Paso
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Rene D Reza
University of Texas at El Paso
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Piyush Kumar
University of Texas at El Paso
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Vinod Kumar
University of Texas at El Paso
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Estimating thermofluid system parameters using a Markov chain Monte Carlo method, with an example of oscillating heat pipes
ORAL
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Presenters
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Yuxuan Li
UCLA
Authors
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Yuxuan Li
UCLA
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Jeff D Eldredge
University of California, Los Angeles
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Adrienne S Lavine
UCLA
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Timothy S Fisher
UCLA
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Bruce L Drolen
Consultant, ThermAvant
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Data-driven dimensional analysis and modelling of two-phase heat-transfer in small-to-micro tubes
ORAL
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Presenters
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Tullio Traverso
The Alan Turing Institute, Imperial College London, Alan Turing Institute, Imperial College London
Authors
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Tullio Traverso
The Alan Turing Institute, Imperial College London, Alan Turing Institute, Imperial College London
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Francesco Coletti
Brunel University London, Hexxcell Ltd.
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Luca Magri
Imperial College London, Alan Turing Institute
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Tassos Karayiannis
Brunel University London
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Omar K Matar
Imperial College London
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Data-Driven Modeling for Optical Wave Reconstruction in Supersonic and Hypersonic Flows
ORAL
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Presenters
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Andrew M Hess
United States Naval Research Laboratory
Authors
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Andrew M Hess
United States Naval Research Laboratory
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Trushant K Patel
Naval Research Laboratory
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David A Kessler
Naval Research Laboratory
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Di Lin
Naval Research Laboratory
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Abstract Withdrawn
ORAL Withdrawn
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Reduced Order Atmospheric Pollution Modelling using Machine Learning with Proper Orthogonal Decomposition
ORAL
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Presenters
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Elliot Chevet
Aix Marseille University, CNRS, Centrale Méditerranée, IRPHE
Authors
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Elliot Chevet
Aix Marseille University, CNRS, Centrale Méditerranée, IRPHE
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Olivier Boiron
Aix Marseille University, CNRS, Centrale Méditerranée, IRPHE, Marseille, France
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Fabien Anselmet
Aix Marseille University, CNRS, Centrale Méditerranée, IRPHE, Marseille, France
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Deep Reinforcement Learning for Autonomous Navigation in Complex Flows
ORAL
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Presenters
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Selim Mecanna
École Centrale Marseille (IRPHE)
Authors
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Selim Mecanna
École Centrale Marseille (IRPHE)
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Aurore Loisy
École Centrale Marseille (IRPHE)
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Christophe Eloy
École Centrale Marseille (IRPHE)
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Deep Learning for flow field and drag force predictions in dispersed particle flows
ORAL
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Presenters
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Neil A Raj
Virginia polytechnic institute and state university
Authors
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Neil A Raj
Virginia polytechnic institute and state university
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Danesh Tafti
Virginia Polytechnic Institute and State University
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Nikhil Muralidhar
Stevens Institute of Technology
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Enhancing Computational Fluid Dynamics Research and Education through AI: The Role of ChatGPT
ORAL
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Presenters
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Yadong Zeng
Altair Engineering Inc.
Authors
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Yadong Zeng
Altair Engineering Inc.
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Leixin Ma
Arizona State Unviersity
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Abstract Withdrawn
ORAL Withdrawn
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