Helicity subgrid-scale models and their numerical validation

TL;DR

This paper investigates helicity-based subgrid-scale models in large-eddy simulations, demonstrating that incorporating helicity improves turbulence modeling accuracy through DNS validation.

Contribution

It introduces and validates a helicity SGS model that enhances standard Smagorinsky models by including turbulence helicity information.

Findings

Helicity SGS models better capture turbulence dynamics in LES.

Inclusion of helicity reduces over-dissipation in SGS models.

DNS validation confirms improved accuracy with helicity effects.

Abstract

Large-eddy simulations (LES) with an appropriate subgrid-scale (SGS) model provide a powerful tool for investigating real-world turbulence. The Smagorinsky model, one of the simplest and most used SGS models, often shows an over-dissipative behavior even when using dynamic procedures to adjust the model coefficient. By incorporating the structural or geometrical information of turbulence provided by helicity (velocity-vorticity correlations), the helicity SGS model is expected to alleviate these issues in the standard Smagorinsky framework, in which only information of turbulence intensity is considered through the turbulent energy. The validity of helicity SGS models is investigated here with the aid of direct numerical simulations (DNSs). Using configurations with and without net rotation, and with large-scale helicity gradients sustained by a mechanical forcing, we show that to better model SGS turbulence, SGS helicity effects should be incorporated into the model together with the Smagorinsky-like eddy viscosity.