A new approach to wall modeling in LES of incompressible flow via function enrichment
For computational fluid dynamics practitioners, this method offers a more general and accurate wall-modeling technique that works on very coarse meshes, particularly under adverse pressure gradients and separated flows.
The paper introduces a wall-modeling approach for LES that enriches polynomial function spaces with Spalding's law-of-the-wall, enabling accurate turbulent boundary layer predictions on extremely coarse meshes (first grid point up to y1+=500). Tested on channel flows up to Reτ=5000, periodic constrictions, and backward-facing step flow, it achieves excellent agreement with DNS and experimental data.
A novel approach to wall modeling for the incompressible Navier-Stokes equations including flows of moderate and large Reynolds numbers is presented. The basic idea is that a problem-tailored function space allows prediction of turbulent boundary layer gradients with very coarse meshes. The proposed function space consists of a standard polynomial function space plus an enrichment, which is constructed using Spalding's law-of-the-wall. The enrichment function is not enforced but "allowed" in a consistent way and the overall methodology is much more general and also enables other enrichment functions. The proposed method is closely related to detached-eddy simulation as near-wall turbulence is modeled statistically and large eddies are resolved in the bulk flow. Interpreted in terms of a three-scale separation within the variational multiscale method, the standard scale resolves large eddies and the enrichment scale represents boundary layer turbulence in an averaged sense. The potential of the scheme is shown applying it to turbulent channel flow of friction Reynolds numbers from $Re_τ=590$ and up to $5,000$, flow over periodic constrictions at the Reynolds numbers $Re_H=10,595$ and $19,000$ as well as backward-facing step flow at $Re_h=5,000$, all with extremely coarse meshes. Excellent agreement with experimental and DNS data is observed with the first grid point located at up to $y_1^+=500$ and especially under adverse pressure gradients as well as in separated flows.