activity
20162026
most citedModeling realistic multiphase flows using a non-orthogonal multiple-relaxation-time lattice Boltzmann method

125 citations · 1k across the 65 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

physics.flu-dyn2024

Minimal droplet shape representation in experimental microfluidics using Fourier series and autoencoders

Mihir Durve, Jean-Michel Tucny, Sibilla Orsini +6

We introduce a two-step, fully reversible process designed to project the outer shape of a generic droplet onto a lower-dimensional space. The initial step involves representing th…

cond-mat.soft2024

Lattice Boltzmann simulations for soft flowing matter

A. Tiribocchi, M. Durve, M. Lauricella +3

Over the last decade, the Lattice Boltzmann method has found major scope for the simulation of a large spectrum of problems in soft matter, from multiphase and multi-component micr…

physics.flu-dyn2024

Droplet shape representation using Fourier series and autoencoders

Mihir Durve, Jean-Michel Tucny, Deepesh Bhamre +4

The shape of liquid droplets in air plays an important role in aerodynamic behavior and combustion dynamics of miniaturized propulsion systems such as microsatellites and small dro…

physics.flu-dyn2024

A high-performance lattice Boltzmann model for multicomponent turbulent jet simulations

Andrea Montessori, Luiz A. Hegele, Marco Lauricella

In this work an optimized multicomponent lattice Boltzmann (LB) model is deployed to simulate axisymmetric turbulent jets of a fluid evolving in a quiescent, immiscible environment…

physics.comp-ph2024

Keldysh-Lattice Boltzmann approach to quantum nanofluidics

Sauro Succi, Andrea Montessori

We present a mathematical and computational framework to couple the Keldysh non equilibrium quantum transport formalism with a nanoscale lattice Boltzmann method for the computatio…

cs.LG2024★ 11 cited

Can physical information aid the generalization ability of Neural Networks for hydraulic modeling?

Gianmarco Guglielmo, Andrea Montessori, Jean-Michel Tucny +2

Application of Neural Networks to river hydraulics is fledgling, despite the field suffering from data scarcity, a challenge for machine learning techniques. Consequently, many pur…

physics.flu-dyn2024

High-order thread-safe lattice Boltzmann model for HPC turbulent flow simulations

Andrea Montessori, Michele La Rocca, Giorgio Amati +3

We present a highly-optimized thread-safe lattice Boltzmann model in which the non-equilibrium part of the distribution function is locally reconstructed via recursivity of Hermite…