Editorial: Machine Learning and Physical Review Fluids : An Editorial Perspective
Michael P. Brenner, Petros Koumoutsakos · Physical Review Fluids · 2021
Machine learning (ML) has become an important tool for modeling, prediction, and control of fluid flows.Increases in computational power, novel algorithms, and open-source software have facilitated the incorporation of ML in numerous experimental and computational studies and have created a fertile ground for new ideas in fluid mechanics.In turn, an ever-increasing number of papers are submitted to Physical Review Fluids (PRFluids) with ML content.At PRFluids, we welcome research on advances in fluid mechanics achieved through ML, and the goal of this editorial is to assist authors in the preparation of their papers.