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20242026
most citedMulti-Scale Data Assimilation in Turbulent Models

1 citations · 1 across the 19 of their papers we have counts for

collaborators

21 papers

physics.flu-dyn2026

Drift of interfaces in forced stably-stratified turbulence and the role of vertically-sheared helical structures

Niccolò Cocciaglia, Luca Biferale, Fabio Bonaccorso +1

Experimental investigations of forced stably stratified turbulence (SST) have shown that the step-like density profile, made of well-mixed density layers and sharp interfaces alter…

physics.flu-dyn2026

Gappy Reconstruction of Bubbly Flows by Guided Diffusion Models

Hridey Narula, Tianyi Li, Michele Buzzicotti +2

Experiments in multiphase flows are often limited in their ability to simultaneously obtain velocity measurements in different phases. At the same time, flow reconstruction from ph…

physics.flu-dyn2026

Stochastic Multiscale Reconstruction of Lagrangian Turbulence via Guided Diffusion Models

Conghui Wang, Tianyi Li, Luca Biferale +3

Lagrangian turbulence is characterized by intermittent, fat-tailed fluctuations and nontrivial correlations across temporal scales, making a quantitative description of its full mu…

physics.flu-dyn2026

Smart strategies to navigate turbulent odor plumes reorienting to local wind

Lorenzo Piro, Maurizio Carbone, Luca Biferale +4

Olfactory search in turbulent environments is a sensorimotor problem that many animals solve with remarkable efficiency, yet replicating this ability in artificial systems is an en…

physics.flu-dyn2026

Turbulent pair dispersion with Stochastic Generative Diffusion Models

Andrei Pantea, Luca Biferale, Michele Buzzicotti +3

Recent advances in data-driven modeling have shown that diffusion models can successfully generate synthetic Lagrangian trajectories in turbulent flows. Building on this progress,…

cs.RO2026

Olfactory pursuit: catching a moving odor source in complex flows

Maurizio Carbone, Lorenzo Piro, Robin A. Heinonen +3

Locating and intercepting a moving target from possibly delayed, intermittent sensory signals is a paradigmatic problem in decision-making under uncertainty, and a fundamental chal…

physics.flu-dyn2026

Physics-Constrained Diffusion Model for Synthesis of 3D Turbulent Data

Tianyi Li, Michele Buzzicotti, Fabio Bonaccorso +1

Synthesizing fully developed three-dimensional turbulent velocity fields remains a long-standing problem in fluid mechanics and an open challenge for generative modeling. The diffi…

physics.flu-dyn2026

Adaptive shape control for microswimmer navigation in turbulence

Jingran Qiu, Lorenzo Piro, Luca Biferale +3

Navigation in turbulent environments is a fundamental challenge for biological and artificial microswimmers. While most existing studies focus on adapting motility or steering, the…

physics.flu-dyn2026

On the importance of stochasticity in closures of turbulence

André Freitas, Luca Biferale, Mathieu Desbrun +3

Deterministic closures for coarse-grained turbulence models help reproduce mean statistics, but often fail to capture the finite-time growth of uncertainty. Using the framework of…

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…

physics.flu-dyn2024

Energy Flux Decomposition in Magnetohydrodynamic Turbulence

D. Capocci, P. Johnson, S. Oughton +2

In hydrodynamic (HD) turbulence an exact decomposition of the energy flux across scales has been derived that identifies the contributions associated with vortex stretching and str…