The discrete direct deconvolution model in the large eddy simulation of turbulence

TL;DR

This paper introduces a discrete direct deconvolution model (D3M) for large-eddy simulation of turbulence, demonstrating improved accuracy over traditional models in predicting turbulence statistics and flow structures.

Contribution

The paper develops a fully local discrete deconvolution model (D3M-2) for LES of turbulence, enhancing accuracy and computational efficiency compared to existing models.

Findings

D3M-1 and D3M-2 outperform traditional models in correlation and error metrics.

Both models accurately predict turbulence statistics and flow structures.

D3M effectively captures spatial features like Q-criterion iso surfaces.

Abstract

The discrete direct deconvolution model (D3M) is developed for the large-eddy simulation (LES) of turbulence. The D3M is a discrete approximation of previous direct deconvolution model studied by Chang et al. ["The effect of sub-filter scale dynamics in large eddy simulation of turbulence," Phys. Fluids 34, 095104 (2022)]. For the first type model D3M-1, the original Gaussian filter is approximated by local discrete formulation of different orders, and direct inverse of the discrete filter is applied to reconstruct the unfiltered flow field. The inverse of original Gaussian filter can be also approximated by local discrete formulation, leading to a fully local model D3M-2. Compared to traditional models including the dynamic Smagorinsky model (DSM) and the dynamic mixed model (DMM), the D3M-1 and D3M-2 exhibit much larger correlation coefficients and smaller relative errors in the a priori studies. In the a posteriori validations, both D3M-1 and D3M-2 can accurately predict turbulence statistics, including velocity spectra, probability density functions (PDFs) of sub-filter scale (SFS) stresses and SFS energy flux, as well as time-evolving kinetic energy spectra, momentum thickness, and Reynolds stresses in turbulent mixing layer. Moreover, the proposed model can also well capture spatial structures of the Q-criterion iso surfaces. Thus, the D3M holds potential as an effective SFS modeling approach in turbulence simulations.