Minimal error partially resolving simulation methods for turbulent flows: A dynamic machine learning approach

A significant extension of previously introduced continuous eddy simulation methods is presented by introducing minimal error partially and fully resolving for turbulent flows. This approach represents a machine learning strategy the hybridization modeling-focused resolution-focused methods. It can be applied to well-known equation structures (Spalart–Allmaras type equations, usually two-equation models), it used different types in computational versions. Physically, implement mode interplay, which ensures that resolution imposed model equals actual flow resolution. Differently formulated reveal two typical errors, they cannot expected provide reliable predictions under conditions where validation data are unavailable. These problems avoided formulations considered.