Turbulent flows are characterized by the non-linear cascades of energy and other inviscid
invariants across a huge range of scales, from where they are injected to where they are …

In three-dimensional hydrodynamic turbulence forced at large length scales, a constant
energy flux Π u flows from large scales to intermediate scales, and then to small scales. It is …

An intrinsic feature of turbulent flows is an enhanced rate of mixing and kinetic energy
dissipation due to the rapid generation of small-scale motions from large-scale excitation …

We study the applicability of tools developed by the computer vision community for feature
learning and semantic image inpainting to perform data reconstruction of fluid turbulence …

This investigation questions the importance of inverse interscale energy fluxes, the so-called
energy backscatter, for the modelling of the energy cascade in large-eddy simulations (LES) …

Fully developed turbulence is a universal and scale-invariant chaotic state characterized by
an energy cascade from large to small scales at which the cascade is eventually arrested by …

We address the problem of data augmentation in a rotating turbulence set-up, a
paradigmatic challenge in geophysical applications. The goal is to reconstruct information in …

The properties of rotating turbulence driven by precession are studied using direct numerical
simulations and analysis of the underlying dynamical processes in Fourier space. The study …

Turbulence in three dimensions (3D) supports vortex stretching that has long been known to
accomplish energy transfer to small scales. Moreover, net energy transfer from large-scale …

Inference problems for two-dimensional snapshots of rotating turbulent flows are studied.
We perform a systematic quantitative benchmark of point-wise and statistical reconstruction …