activity
20192026
most citedVelocity and acceleration statistics in particle-laden turbulent swirling flows

16 citations · 54 across the 10 of their papers we have counts for

collaborators
Showing physics.flu-dynShow all

10 papers · 1 filter

physics.flu-dyn2026

Evolution of inertial particle clustering in decaying turbulence

Martín Obligado, Sofía Angriman

Inertial particle dynamics in turbulence are commonly interpreted in terms of the instantaneous particle Stokes number, as supported by studies in statistically stationary homogene…

physics.flu-dyn2026

Ice melting in an oscillatory flow

Sofía Angriman, Tobias de Buck, Roberto Verzicco +1

We investigate the melting dynamics of an ice disk subjected to an external oscillatory flow using two-dimensional direct numerical simulations, in the absence of buoyancy, varying…

physics.flu-dyn2025★ 2 cited

Collective effects of neighbouring melting ice objects

Sofía Angriman, Detlef Lohse, Roberto Verzicco +1

We present a study on the melting dynamics of neighbouring ice bodies by means of idealised simulations, focusing on collective effects, with the goal of obtaining fundamental insi…

physics.flu-dyn2024★ 3 cited

Active grid turbulence anomalies through the lens of physics informed neural networks

Sofía Angriman, Sarah E. Smith, Patricio Clark di Leoni +3

Active grids operated with random protocols are a standard way to generate large Reynolds number turbulence in wind and water tunnels. But anomalies in the decay and third-order sc…

physics.flu-dyn2024

Turbulence unsteadiness drives extreme clustering

Florencia Zapata, Sofía Angriman, Amélie Ferran +3

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 part…

physics.flu-dyn2022★ 2 cited

Generation of Turbulent States using Physics-Informed Neural Networks

Sofia Angriman, Pablo Cobelli, Pablo Mininni +2

When modelling 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…

physics.flu-dyn2022★ 12 cited

Clustering in laboratory and numerical turbulent swirling flows

Sofía Angriman, Amélie Ferran, Florencia Zapata +3

We study the three-dimensional clustering of velocity stagnation points, of nulls of the vorticity and of the Lagrangian acceleration, and of inertial particles in turbulent flows…

physics.flu-dyn2022★ 7 cited

Multi-time structure functions and the Lagrangian scaling of turbulence

Sofía Angriman, Pablo D. Mininni, Pablo J. Cobelli

We define and characterize multi-time Lagrangian structure functions using data stemming from two swirling flows with mean flow and turbulent fluctuations: A Taylor-Green numerical…

physics.flu-dyn2021★ 12 cited

Broken mirror symmetry of tracer's trajectories in turbulence

Sofía Angriman, Pablo J. Cobelli, Mickaël Bourgoin +3

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,…

physics.flu-dyn2019★ 16 cited

Velocity and acceleration statistics in particle-laden turbulent swirling flows

Sofía Angriman, Pablo D. Mininni, Pablo J. Cobelli

We present a comparison of different particles' velocity and acceleration statistics in two paradigmatic turbulent swirling flows: the von Kármán flow in a laboratory experiment, a…