The European Physical Journal E (EPJ E)

Open Access

Editorial

Topical issue on quantitative AI in complex fluids and complex flows: challenges and benchmarks

L. Biferale, M. Buzzicotti and M. Cencini

Published online: 23 October 2023

DOI: 10.1140/epje/s10189-023-00356-w

Regular Article - Flowing Matter

Toward accelerated data-driven Rayleigh–Bénard convection simulations

Ayya Alieva, Stephan Hoyer, Michael Brenner, Gianluca Iaccarino and Peter Norgaard

Published online: 28 July 2023

DOI: 10.1140/epje/s10189-023-00302-w

Regular Article – Flowing Matter

Flow reconstruction by multiresolution optimization of a discrete loss with automatic differentiation

Petr Karnakov, Sergey Litvinov and Petros Koumoutsakos

Published online: 24 July 2023

DOI: 10.1140/epje/s10189-023-00313-7

Regular Article – Soft Matter

Neural networks for large eddy simulations of wall-bounded turbulence: numerical experiments and challenges

Mark Benjamin, Stefan P. Domino and Gianluca Iaccarino

Published online: 17 July 2023

DOI: 10.1140/epje/s10189-023-00314-6

Open Access

Regular Article - Flowing Matter

Optimal navigation of a smart active particle: directional and distance sensing

Mischa Putzke and Holger Stark

Published online: 19 June 2023

DOI: 10.1140/epje/s10189-023-00309-3

Regular Article - Flowing Matter

Inference of relative permeability curves in reservoir rocks with ensemble Kalman method

Xu-Hui Zhou, Haochen Wang, James McClure, Cheng Chen and Heng Xiao

Published online: 12 June 2023

DOI: 10.1140/epje/s10189-023-00296-5

Regular Article – Flowing Matter

Steering undulatory micro-swimmers in a fluid flow through reinforcement learning

Zakarya El Khiyati, Raphaël Chesneaux, Laëtitia Giraldi and Jérémie Bec

Published online: 12 June 2023

DOI: 10.1140/epje/s10189-023-00293-8

Open Access

Regular Article - Flowing Matter

Benchmarking YOLOv5 and YOLOv7 models with DeepSORT for droplet tracking applications

Mihir Durve, Sibilla Orsini, Adriano Tiribocchi, Andrea Montessori, Jean-Michel Tucny, Marco Lauricella, Andrea Camposeo, Dario Pisignano and Sauro Succi

Published online: 08 May 2023

DOI: 10.1140/epje/s10189-023-00290-x

Open Access

Regular Article - Flowing Matter

Generative adversarial networks to infer velocity components in rotating turbulent flows

Tianyi Li, Michele Buzzicotti, Luca Biferale and Fabio Bonaccorso

Published online: 04 May 2023

DOI: 10.1140/epje/s10189-023-00286-7

Regular Article - Flowing Matter

Machine learning for optimal flow control in an axial compressor

M. A. Elhawary, Francesco Romanò, Jean-Christophe Loiseau and Antoine Dazin

Published online: 12 April 2023

DOI: 10.1140/epje/s10189-023-00284-9

Open Access

Regular Article - Flowing Matter

Deep reinforcement learning for turbulent drag reduction in channel flows

Luca Guastoni, Jean Rabault, Philipp Schlatter, Hossein Azizpour and Ricardo Vinuesa

Published online: 11 April 2023

DOI: 10.1140/epje/s10189-023-00285-8

Regular Article - Flowing Matter

Deep reinforcement learning for the olfactory search POMDP: a quantitative benchmark

Aurore Loisy and Robin A. Heinonen

Published online: 20 March 2023

DOI: 10.1140/epje/s10189-023-00277-8

Regular Article - Flowing Matter

Reconstructing Rayleigh–Bénard flows out of temperature-only measurements using Physics-Informed Neural Networks

Patricio Clark Di Leoni, Lokahith Agasthya, Michele Buzzicotti and Luca Biferale

Published online: 20 March 2023

DOI: 10.1140/epje/s10189-023-00276-9

Regular Article - Flowing Matter

Assimilation of statistical data into turbulent flows using physics-informed neural networks

Sofía Angriman, Pablo Cobelli, Pablo D. Mininni, Martín Obligado and Patricio Clark Di Leoni

Published online: 09 March 2023

DOI: 10.1140/epje/s10189-023-00268-9

Regular Article - Flowing Matter

Curriculum learning for data-driven modeling of dynamical systems

Michele Alessandro Bucci, Onofrio Semeraro, Alexandre Allauzen, Sergio Chibbaro and Lionel Mathelin

Published online: 08 March 2023

DOI: 10.1140/epje/s10189-023-00269-8

Open Access

Regular Article - Flowing Matter

Toward learning Lattice Boltzmann collision operators

Alessandro Corbetta, Alessandro Gabbana, Vitaliy Gyrya, Daniel Livescu, Joost Prins and Federico Toschi

Published online: 06 March 2023

DOI: 10.1140/epje/s10189-023-00267-w

Regular Article - Flowing Matter

Taming Lagrangian chaos with multi-objective reinforcement learning

Chiara Calascibetta, Luca Biferale, Francesco Borra, Antonio Celani and Massimo Cencini

Published online: 03 March 2023

DOI: 10.1140/epje/s10189-023-00271-0

Regular Article - Flowing Matter

Optimizing airborne wind energy with reinforcement learning

N. Orzan, C. Leone, A. Mazzolini, J. Oyero and A. Celani

Published online: 19 January 2023

DOI: 10.1140/epje/s10189-022-00259-2

Regular Article - Flowing Matter

Inferring turbulent environments via machine learning

Michele Buzzicotti and Fabio Bonaccorso

Published online: 31 December 2022

DOI: 10.1140/epje/s10189-022-00258-3

EPJ

The European Physical Journal E - Soft Matter and Biological Physics

Quantitative AI in Complex Fluids and Complex Flows: Challenges and Benchmarks

Topical issue on quantitative AI in complex fluids and complex flows: challenges and benchmarks

Toward accelerated data-driven Rayleigh–Bénard convection simulations

Flow reconstruction by multiresolution optimization of a discrete loss with automatic differentiation

Neural networks for large eddy simulations of wall-bounded turbulence: numerical experiments and challenges

Optimal navigation of a smart active particle: directional and distance sensing

Inference of relative permeability curves in reservoir rocks with ensemble Kalman method

Steering undulatory micro-swimmers in a fluid flow through reinforcement learning

Benchmarking YOLOv5 and YOLOv7 models with DeepSORT for droplet tracking applications

Generative adversarial networks to infer velocity components in rotating turbulent flows

Machine learning for optimal flow control in an axial compressor

Deep reinforcement learning for turbulent drag reduction in channel flows

Deep reinforcement learning for the olfactory search POMDP: a quantitative benchmark

Reconstructing Rayleigh–Bénard flows out of temperature-only measurements using Physics-Informed Neural Networks

Assimilation of statistical data into turbulent flows using physics-informed neural networks

Curriculum learning for data-driven modeling of dynamical systems

Toward learning Lattice Boltzmann collision operators

Taming Lagrangian chaos with multi-objective reinforcement learning

Optimizing airborne wind energy with reinforcement learning

Inferring turbulent environments via machine learning

Conference announcements