Description du projet
Améliorer la compréhension des turbulences grâce à l’intelligence artificielle
Les turbulences sont omniprésentes, elles se manifestent dans pratiquement tous les systèmes qui impliquent des fluides en mouvement. Les flux turbulents posent problème dans les applications hors équilibre de physique fondamentale ou d’ingénierie. Pour mieux comprendre les turbulences, le projet Smart-TURB, financé par l’UE, explorera de nouvelles pistes qui recoupent ingénierie théorique et physique appliquée. Les chercheurs auront recours à des algorithmes d’intelligence artificielle pour étudier et contrôler les turbulences de manière innovante. L’accent sera mis sur le suivi et l’exploitation de structures cohérentes en mouvement et de fluctuations turbulentes statistiques, sur l’optimisation de la navigation des objets flottants et sur la conception de protocoles de recherche collective pour localiser les émissions de sources fixes ou flottantes. Des efforts seront également déployés pour minimiser la dispersion turbulente d’un essaim d’explorateurs sous-marins autonomes. Enfin, de nouvelles expériences in silico seront menées pour l’assimilation des données.
Objectif
Where is it difficult to control, predict and model a flowing system? to search and navigate inside it? to be prepared against extreme events? to tame them? It is in turbulent flows.
Turbulence is ubiquitous and unsolved from the point of view of out-of-equilibrium fundamental physics, uncontrollable from the engineering aspects, and a deadlock for brute-force numerical and experimental investigations. Indeed, progress by using conventional methods has been slow.
In this project, I propose to explore new avenues crossing the boundaries between Theoretical Engineering and Applied Physics using algorithms from Artificial Intelligence (AI) to study and control turbulence in an innovative way using smart Lagrangian objects in a vast array of flows. I am committed to: (i) develop original applications of AI algorithms to track and harness moving coherent structures and/or statistical turbulent fluctuations, (ii) optimise flow navigation of buoyant objects and active surface drifter, (iii) invent collective search protocols to locate emissions from fixed or floating sources, (iv) minimise turbulent dispersion of a swarm of autonomous underwater explorer and (v) perform new in-silico experiments for data-assimilation, to predict extreme-events, or to control turbulent fluctuations by novel Lagrangian injection/adsorption mechanisms.
The unifying fil-rouge of my project is to gain a Deep Understanding of turbulence by performing cutting-edge Lagrangian numerical studies. The project is both methodology oriented, with the grand challenge of developing fully unconventional applications of (Deep) Reinforcement Learning for fluid dynamics, and problem driven, delivering a series of specific optimal control strategies for important realistic flow set-ups and applications to the geophysical fields. With my experience and the impact of my contributions in the discipline, I am confident that I offer the highest chances to carry out this ambitious project with success.
Champ scientifique
Programme(s)
Thème(s)
Régime de financement
ERC-ADG - Advanced GrantInstitution d’accueil
00133 Roma
Italie