4 papers
HFNO: an interpretable data-driven decomposition strategy for turbulent flows
Marco Cayuela, Vincent Le Chenadec, Peter Schmid +1
Fourier Neural Operators (FNOs) have demonstrated exceptional accuracy in mapping functional spaces by leveraging Fourier transforms to establish a connection with underlying physi…
Learning dissipation and instability fields from chaotic dynamics
Ludovico T Giorgini, Andre N Souza, Domenico Lippolis +2
To make predictions or design control, information on local sensitivity of initial conditions and state-space contraction is both central, and often instrumental. However, it is no…
Improved Greedy Identification of Latent Dynamics with Application to Fluid Flows
R. Ayoub, M. Oulghelou, P. J Schmid
Model reduction is a key technology for large-scale physical systems in science and engineering, as it brings behavior expressed in many degrees of freedom to a more manageable siz…
A Hybrid Discrete Exterior Calculus Discretization and Fourier Transform of the Incompressible Navier-Stokes Equations in 3D
Abdullah Abukhwejah, Pankaj Jagad, Ravi Samtaney +1
The simulation of fluid flow problems, specifically incompressible flows governed by the Navier-Stokes equations (NSE), holds fundamental significance in a range of scientific and…