Turbulence Unsteadiness Drives Extreme Clustering.

We show that the unsteadiness of turbulence has a drastic effect on turbulence parameters and in particle cluster formation. To this end we use direct numerical simulations of particle laden flows with a steady forcing that generates an unsteady large-scale flow. Particle clustering correlates with the instantaneous Taylor-based flow Reynolds number, and anticorrelates with its instantaneous turbulent energy dissipation constant.

Conformal Invariance in Water-Wave Turbulence.

We experimentally investigate the statistics of zero-height isolines in gravity wave turbulence as physical candidates for conformal invariant curves. We present direct evidence that they can be described by the family of conformal invariant curves called stochastic Schramm-Löwner evolution (or SLE_{κ}), with diffusivity κ=2.88(8).

Assimilation of statistical data into turbulent flows using physics-informed neural networks.

When modeling turbulent flows, it is often the case that information on the forcing terms or the boundary conditions is either not available or overly complicated and expensive to implement. Instead, some flow features, such as the mean velocity profile or its statistical moments, may be accessible through experiments or observations. We present a method based on physics-informed neural networks to assimilate a given set of conditions into turbulent states.

Bubble Formation in Pulsed Electric Field Technology May Pose Limitations.

Currently, increasing amounts of pulsed electric fields (PEF) are employed to improve a person's life quality. This technology is based on the application of the shortest high voltage electrical pulse, which generates an increment over the cell membrane permeability. When applying these pulses, an unwanted effect is electrolysis, which could alter the treatment.

Broken Mirror Symmetry of Tracer's Trajectories in Turbulence.

Topological properties of physical systems play a crucial role in our understanding of nature, yet their experimental determination remains elusive. We show that the mean helicity, a dynamical invariant in ideal flows, quantitatively affects trajectories of fluid elements: the linking number of Lagrangian trajectories depends on the mean helicity. Thus, a global topological invariant and a topological number of fluid trajectories become related, and we provide an empirical expression linking them.