Monday, November 22, 2021
1:10PM - 1:23PM
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M31.00001: Development of closures for coarse-scale modeling of multiphase and free surface flows using machine learning.
Cristina P Martin Linares, Tom Bertalan, Eleni Koronaki, Jiacai Lu, Gretar Tryggvason, Ioannis G Kevrekidis
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Monday, November 22, 2021
1:23PM - 1:36PM
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M31.00002: Analyses of the Differentiable-programming Paradigm for Learning Physics-constrained Surrogate Models
Divya Sri Praturi, Arvind T Mohan
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Monday, November 22, 2021
1:36PM - 1:49PM
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M31.00003: Frequency-time analysis of turbulent flows using spectral POD
Akhil Nekkanti, Oliver T Schmidt
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Monday, November 22, 2021
1:49PM - 2:02PM
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M31.00004: Data-driven coarse graining of many-body systems
Zachary G Nicolaou, Matthew Kafker, Steven L Brunton, J. Nathan Kutz
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Monday, November 22, 2021
2:02PM - 2:15PM
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M31.00005: Optimizing oblique projections for nonlinear systems using trajectories
Samuel E Otto, Alberto Padovan, Clarence W Rowley
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Monday, November 22, 2021
2:15PM - 2:28PM
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M31.00006: Neural Implicit Flow: A mesh-agnostic representation paradigm for spatio-temporal fields
Shaowu Pan, Steven L Brunton, Nathan Kutz
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Monday, November 22, 2021
2:28PM - 2:41PM
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M31.00007: Physics-guided machine learning for surrogate modeling in fluid mechanics
Suraj A Pawar, Omer San, Adil Rasheed
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Monday, November 22, 2021
2:41PM - 2:54PM
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M31.00008: Data-driven estimation of inertial manifold dimension for chaotic Kolmogorov flow and time evolution on the manifold
Carlos E Perez De Jesus, Michael D Graham
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Monday, November 22, 2021
2:54PM - 3:07PM
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M31.00009: Promoting global stability in data-driven models of quadratic nonlinear dynamics
Alan Kaptanoglu, Jared Callaham, Christopher J Hansen, Aleksandr Aravkin, Steven L Brunton
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Monday, November 22, 2021
3:07PM - 3:20PM
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M31.00010: Modeling chaotic spatiotemporal dynamics with a minimal representation using Neural ODEs
Alec Linot, Michael D Graham
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