Learned discretizations for passive scalar advection in a two-dimensional turbulent flow

Calculating the evolution of a passive scalar in turbulent flow requires resolving intricate stretching and folding field. Traditionally, this that computational mesh is much smaller than smallest scale concentration Here we demonstrate use machine learning to learn discretizations governing equation give accurate computations with coarser mesh. The model learns universal small structures field stretching, allowing it accurately interpolate less information.