1 code implementation • 27 Feb 2024 • Jonathan Viquerat, Philippe Meliga, Pablo Jeken, Elie Hachem
Recently, the increasing use of deep reinforcement learning for flow control problems has led to a new area of research, focused on the coupling and the adaptation of the existing algorithms to the control of numerical fluid dynamics environments.
3 code implementations • 25 Oct 2019 • Junfeng Chen, Jonathan Viquerat, Elie Hachem
Machine learning is a popular tool that is being applied to many domains, from computer vision to natural language processing.
Computational Physics Image and Video Processing
4 code implementations • 23 Aug 2019 • Jonathan Viquerat, Jean Rabault, Alexander Kuhnle, Hassan Ghraieb, Aurélien Larcher, Elie Hachem
Deep Reinforcement Learning (DRL) has recently spread into a range of domains within physics and engineering, with multiple remarkable achievements.
Computational Engineering, Finance, and Science
1 code implementation • 12 Aug 2019 • Paul Garnier, Jonathan Viquerat, Jean Rabault, Aurélien Larcher, Alexander Kuhnle, Elie Hachem
In this work, we conduct a detailed review of existing DRL applications to fluid mechanics problems.
3 code implementations • 11 Jul 2019 • Jonathan Viquerat, Elie Hachem
Despite the significant breakthrough of neural networks in the last few years, their spreading in the field of computational fluid dynamics is very recent, and many applications remain to explore.
Computational Physics