Dynamic Subgrid Scale Modeling of Turbulent Flows using Lattice-Boltzmann Method

TL;DR

This paper introduces a dynamic subgrid scale modeling approach within the lattice-Boltzmann method for large-eddy simulation of turbulent flows, enabling automatic coefficient computation and improved turbulence modeling.

Contribution

It presents a novel dynamic SGS modeling framework in LBM that self-adjusts model coefficients, reducing empiricism and enhancing turbulence simulation accuracy.

Findings

Computed Smagorinsky coefficient aligns with prior data.

Model captures turbulence behavior near walls effectively.

Approach works for different Reynolds numbers.

Abstract

In this paper, we discuss the incorporation of dynamic subgrid scale (SGS) models in the lattice-Boltzmann method (LBM) for large-eddy simulation (LES) of turbulent flows. The use of a dynamic procedure, which involves sampling or test-filtering of super-grid turbulence dynamics and subsequent use of scale-invariance for two levels, circumvents the need for empiricism in determining the magnitude of the model coefficient of the SGS models. We employ the multiple relaxation times (MRT) formulation of LBM with a forcing term for simulation of the grid-filtered dynamics of large-eddies. The dynamic procedure is illustrated for use with the common Smagorinsky eddy-viscosity SGS model. We also discuss proper sampling techniques or test-filters that facilitate implementation of dynamic models in the LBM. For accommodating variable resolutions, we employ locally refined grids in this framework. As examples, we consider the canonical fully developed turbulent channel flow at two different shear Reynolds numbers $Re_{*}$ of 180 and 395. The approach is able to automatically and self-consistently compute the values of the Smagorinsky coefficient, $C_S$. In particular, the computed value in the outer or bulk flow region, where turbulence is generally more isotropic, is about 0.155 (or the model coefficient $C=C_S^2=0.024$) which is in good agreement with prior data. The model coefficient is also found to become smaller and approaches towards zero near walls, reflecting the dampening of turbulent length scales near walls and the computed turbulence statistics are also in good agreement with prior data. The paper also discusses a procedure for incorporation of more general scale-similarity based SGS stress models.