Learned discretizations for passive scalar advection in a 2-D turbulent flow

Understand

The computational cost of fluid simulations increases rapidly with grid resolution.

• This has given a hard limit on the ability of simulations to accurately resolve small scale features of complex flows.
• Here we use a machine learning approach to learn a numerical discretization that retains high accuracy even when the solution is under-resolved with classical methods.
• We apply this approach to passive scalar advection in a two-dimensional turbulent flow.