Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session W53: Data Science for Climate
3:00 PM–5:48 PM,
Thursday, March 9, 2023
Room: Room 307
Sponsoring
Units:
GDS GPC DFD
Chair: William Ratcliff, National Institute of Standards and Technology
Abstract: W53.00010 : Numerical proof of shell model turbulence closure
5:36 PM–5:48 PM
Presenter:
Giulio Ortali
(Eindhoven University of Technology)
Authors:
Giulio Ortali
(Eindhoven University of Technology)
Alessandro Corbetta
(Eindhoven University of Technology)
Gianluigi Rozza
(SISSA - International School for Advanced Studies)
Federico Toschi
(Eindhoven University of Technology)
Our method employs a novel custom-made Deep Learning architecture comprising a classical 4th order Runge-Kutta integration scheme for the large scales of turbulence augmented with a Recurrent Artificial Neural Network, modelling the subgrid closure term. Using this approach we are able to reproduce, within statistical error bars, the intermittent behavior found in the full model, obtaining the correct scaling laws for Eulerian and Lagrangian structure functions and outperforming classical physics based methods.
This work demonstrates the capability of Machine Learning to capture complex multiscale dynamics and reproduce complex multi-scale and multi-time non-gaussian behaviors, opening up the possibility to tackle turbulence modelling in Navier-Stokes Equations.
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