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20242026
most citedMulti-Scale Data Assimilation in Turbulent Models

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physics.flu-dyn2025

Long-time evolution of density layers and interfaces in forced stably-stratified flows

Niccolo Cocciaglia, Fabio Bonaccorso, Alessandra Sabina Lanotte +1

Stably stratified fluids subject to sustained forcing are known to develop step-like density "staircases", where nearly homogeneous layers alternate with thin interfaces of strong…

physics.ao-ph2025

Super-resolution of satellite-derived SST data via Generative Adversarial Networks

Claudia Fanelli, Tiany Li, Luca Biferale +4

In this work, we address the super-resolution problem of satellite-derived sea surface temperature (SST) using deep generative models. Although standard gap-filling techniques are…

physics.flu-dyn2025

TURB-Scalar. A large database of passive scalar fields advected by 2D Navier-Stokes in the turbulent inverse cascade regime

Chiara Calascibetta, Luca Biferale, Fabio Bonaccorso +1

We introduce TURB-Scalar, an open-access database comprising approximately uncorrelated snapshots of two-dimensional turbulent velocity and passive scalar fields, obtained fr…

physics.flu-dyn2025

TURB-Smoke. A database of Lagrangian pollutants emitted from point-sources and dispersed in turbulent flows

Luca Biferale, Fabio Bonaccorso, Niccolò Cocciaglia +2

Identifying the location and characteristics of pollution sources in turbulent flows is challenging, especially for environmental monitoring and emergency response, due to sparse,…

physics.flu-dyn2025

Deterministic diffusion models for Lagrangian turbulence: robustness and encoding of extreme events

Tianyi Li, Flavio Tuteri, Michele Buzzicotti +2

Modeling Lagrangian turbulence remains a fundamental challenge due to its multiscale, intermittent, and non-Gaussian nature. Recent advances in data-driven diffusion models have en…

physics.flu-dyn2025★ 1 cited

Multi-Scale Data Assimilation in Turbulent Models

Francesco Fossella, Luca Biferale, Alberto Carrassi +2

We explore the potential of Data-Assimilation (DA) within the multi-scale framework of a shell model of turbulence, with a focus on the Ensemble Kalman Filter (EnKF). The central o…

physics.flu-dyn2025

Lagrangian analysis of turbulent blood flow in the human left heart

Fabio Guglietta, Martino Andrea Scarpolini, Francesco Viola +1

We present a Lagrangian analysis of turbulent blood flow in the human left heart using high-fidelity simulations based on a patient-specific anatomical model. Leveraging a fully co…

physics.flu-dyn2025

Hidden symmetry in passive scalar advected by 2D Navier-Stokes turbulence

Chiara Calascibetta, Luca Biferale, Fabio Bonaccorso +2

Here we show that passive scalars possess a hidden scaling symmetry when considering suitably rescaled fields. Such a symmetry implies (i) universal probability distribution for sc…

physics.flu-dyn2025

Scale invariance of intermittency in LES turbulence

B. Magacho, S. Thalabard, M. Buzzicotti +3

Turbulent flows exhibit large intermittent fluctuations from inertial to dissipative scales, characterized by multifractal statistics and breaking the statistical self-similarity.…

physics.flu-dyn2025

TURB-MHD: an open-access database of forced homogeneous magnetohydrodynamic turbulence

Damiano Capocci, Luca Biferale, Fabio Bonaccorso +1

We present TURB-MHD, a database formed by six datasets of three-dimensional incompressible homogeneous magnetohydrodynamic turbulence maintained by a large-scale random forcing wit…

physics.flu-dyn2025

A posteriori closure of turbulence models: are symmetries preserved?

André Freitas, Kiwon Um, Mathieu Desbrun +2

Turbulence modeling remains a longstanding challenge in fluid dynamics. Recent advances in data-driven methods have led to a surge of novel approaches aimed at addressing this prob…