Hidden mechanism of dynamic large-eddy simulation models

TL;DR

This paper investigates the underlying mechanisms of dynamic large-eddy simulation models, revealing that focusing on principal directions of the strain tensor suffices for accurate modeling, thus simplifying the approach.

Contribution

It demonstrates that minimizing the Germano-identity error along principal strain directions is as effective as the full tensor approach in wall-bounded flows.

Findings

Principal directions are crucial for dynamic model success.

Reduced component minimization yields comparable results.

Simplifies the dynamic modeling process.

Abstract

The dynamic model is one of the most successful inventions in subgrid-scale (SGS) modeling as it alleviates many drawbacks of the static coefficient SGS stress models. The model coefficient is often calculated dynamically through the minimization of the Germano-identity error (GIE). However, the driving mechanism behind the dynamic model's success is still not well understood. In wall-bounded flows, we postulate that the principal directions of the resolved rate-of-strain tensor play an important role in the dynamic models. Specifically, we find that minimization of the GIE along only the three principal directions (or less), in lieu of its nine components in its original formulation, produces equally comparable results as the original model when examined in canonical turbulent channel flows, a three-dimensional turbulent boundary layer, and a separating flow over periodic hills. This suggests that not all components of the Germano identity are equally important for the success of the dynamic model, and that there might be dynamically more important directions for modeling the subgrid dynamics.