60 citations · 69 across the 2 of their papers we have counts for
3 papers
physics.flu-dyn2022★ 9 cited
Evolution of waves in liquid films on moving substrates
Tsvetelina Ivanova, Fabio Pino, Benoit Scheid +1
Accurate and computationally accessible models of liquid film flows allow for optimizing coating processes such as hot-dip galvanization and vertical slot-die coating. This paper e…
physics.flu-dyn2022
Challenges and Opportunities for Machine Learning in Fluid Mechanics
M. A. Mendez, J. Dominique, M. Fiore +3
Big data and machine learning are driving comprehensive economic and social transformations and are rapidly re-shaping the toolbox and the methodologies of applied scientists. Mach…
physics.flu-dyn2022★ 60 cited
Comparative analysis of machine learning methods for active flow control
Fabio Pino, Lorenzo Schena, Jean Rabault +1
Machine learning frameworks such as Genetic Programming (GP) and Reinforcement Learning (RL) are gaining popularity in flow control. This work presents a comparative analysis of th…