A data-driven dynamic nonlocal subgrid-scale model for turbulent flows

TL;DR

This paper introduces a novel data-driven, parameter-free nonlocal turbulence model for LES and VLES of isotropic turbulence, demonstrating high accuracy in reproducing DNS results and promising applications in environmental modeling.

Contribution

The paper presents a new dynamic nonlocal turbulence model based on fractional Laplacian operators, eliminating the need for tuning parameters through three innovative data-driven approaches.

Findings

High correlation with DNS SGS stress components

Accurate probability density functions of SGS forces

Effective in both LES and VLES regimes

Abstract

We developed a novel autonomously dynamic nonlocal turbulence model for the large and very large eddy simulation (LES, VLES) of the homogeneous isotropic turbulent flows (HIT). The model is based on a generalized (integer-to-noninteger) order Laplacian of the filtered velocity field, and a novel dynamic model has been formulated to avoid the need for tuning the model constant. Three data-driven approaches were introduced for the determination of the fractional-order to have a model which is totally free of any tuning parameter. Our analysis includes both the $\textit{a priori}$ and the $\textit{a posteriori}$ tests. In the former test, using a high-fidelity and well-resolved dataset from direct numerical simulations (DNS), we computed the correlation coefficients for the stress components of the subgrid-scale (SGS) stress tensor and the one we get directly from the DNS results. Moreover, we compared the probability density function of the ensemble-averaged SGS forces for different filter sizes. In the latter, we employed our new model along with other conventional models including static and dynamic Smagorinsky into our pseudo-spectral solver and tested the final predicted quantities. The results of the newly developed model exhibit an expressive agreement with the ground-truth DNS results in all components of the SGS stress and forces. Also, the model exhibits promising results in the VLES region as well as the LES region, which could be remarkably important for the cost-efficient nonlocal turbulence modelings e.g., in meteorological and environmental applications.