Enhancing computational fluid dynamics with machine learning

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Maziar Raissi, Paris Perdikaris, George Em Karniadakis · Journal of Computational Physics · 2018 · 16.9K citations · Full text

Natural Sciences, Computer Science, Physics +16

GENERAL CIRCULATION EXPERIMENTS WITH THE PRIMITIVE EQUATIONS

Joseph Smagorinsky · Monthly Weather Review · 1963 · 13.8K citations

Natural Sciences, Earth Sciences, Meteorology +16

Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

Cynthia Rudin · Nature Machine Intelligence · 2019 · 9K citations · Full text

Computing, Computer Science, Artificial Intelligence +11

Dynamic mode decomposition of numerical and experimental data

Peter J. Schmid · Journal of Fluid Mechanics · 2010 · 5.7K citations · Full text

Natural Sciences, Visualization, Computational Fluid Dynamics +15

A tensorial approach to computational continuum mechanics using object-oriented techniques

Henry Weller, Gavin Tabor, Hrvoje Jasak et al. · Computers in Physics · 1998 · 5.3K citations

Natural Sciences, Physics, Computational Fluid Dynamics +14