11 citations · 36 across the 10 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…
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…