178 citations
- Aix-Marseille UniversitéFR33 papers
- Centre National de la Recherche ScientifiqueFR33 papers
- Institut Universitaire des Systèmes Thermiques IndustrielsFR20 papers
- Centrale MéditerranéeFR17 papers
- Château GombertFR13 papers
- Laboratoire de Mécanique et d’AcoustiqueFR5 papers
- Institute of Materials, Minerals and MiningGB4 papers
- Northwestern UniversityUS4 papers
- Université de NîmesFR4 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR3 papers
- Conservatoire National des Arts et MétiersFR3 papers
- École Centrale de LyonFR3 papers
77 papers
Fluid transport by a single active filament in a three-dimensional two-phase flow
Qian Mao, Umberto d'Ortona, Julien Favier
Micro-scale cilia play a vital role in mucociliary clearance (MCC) in the human respiratory airways. In this numerical study, we examine fluid transport driven by the active beatin…
Quantum lattice Boltzmann method for several time steps: A local Carleman linearization algorithm
Antonio David Bastida Zamora, Ljubomir Budinski, Valtteri Lahtinen +1
This article presents a novel encoding for quantum Lattice Boltzmann method algorithm using Carleman linearization. In contrast to previous articles \cite{Sanavio2024LatticeBC,sana…
Adaptive Lattice Gas Algorithm: Classical and Quantum implementations
Niccolò Fonio, Ljubomir Budinski, Valtteri Lahtinen +1
Lattice gas algorithms (LGA) are a class of algorithms including, in chronological order, binary lattice gas cellular automata (LGCA), integer lattice gas algorithms (ILGA) and lat…
Machine-Learning Enhanced Predictors for Accelerated Convergence of Partitioned Fluid-Structure Interaction Simulations
Azzeddine Tiba, Thibault Dairay, Florian de Vuyst +2
Stable partitioned techniques for simulating unsteady fluid-structure interaction (FSI) are known to be computationally expensive when high added-mass is involved. Multiple couplin…
Generalizing the SINDy approach with nested neural networks
Camilla Fiorini, Clément Flint, Louis Fostier +4
Symbolic Regression (SR) is a widely studied field of research that aims to infer symbolic expressions from data. A popular approach for SR is the Sparse Identification of Nonlinea…
Physics informed Neural Networks applied to the description of wave-particle resonance in kinetic simulations of fusion plasmas
Jai Kumar, David Zarzoso, Virginie Grandgirard +2
The Vlasov-Poisson system is employed in its reduced form version (1D1V) as a test bed for the applicability of Physics Informed Neural Network (PINN) to the wave-particle resonanc…