A generally applicable hybrid unsteady Reynolds-averaged Navier–Stokes closure scaled by turbulent structures

This work demonstrates a strategy for hybrid turbulence modeling that relies on parameters identifying flow structures to regulate the model's level of scale resolution, independent computational grid and user input. The approach can be classified as second-generation unsteady Reynolds-averaged Navier–Stokes (URANS), where it is assumed increased resolution inside rapidly deformed regions consistently reduce error compared basic URANS closures. methodology selects by evaluating second invariant velocity gradient tensor in resolved field. functions used this purpose are similar techniques applied topology studies identify coherent structures. proposed formulation extends baseline nonlinear eddy-viscosity model achieves completeness means differential Lagrangian operator approximates locally computed average. addresses lack general applicability deriving from globally filtering at small scales reverting locations with low acceleration, which solution best accuracy. Three test cases presented, demonstrating substantial accuracy enhancement over same sizes. Results obtained new closure demonstrate robust internal flows, showing large-eddy simulation (LES)-like statistics coarse RANS grids. observed increase cost only 3% 24%, represents almost two orders magnitude reduction LES.