Deep Learning Closure Models for Large-Eddy Simulation of Flows around Bluff Bodies. (arXiv:2208.03498v2 [physics.flu-dyn] UPDATED)

A deep learning (DL) closure model for large-eddy simulation (LES) is
developed and evaluated for incompressible flows around a rectangular cylinder
at moderate Reynolds numbers. Near-wall flow simulation remains a central
challenge in aerodynamic modeling: RANS predictions of separated flows are
often inaccurate, while LES can require prohibitively small near-wall mesh
sizes. The DL-LES model is trained using adjoint PDE optimization methods to
match, as closely as possible, direct numerical simulation (DNS) data. It is
then evaluated out-of-sample (i.e., for …

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