Toward a flow-structure-based wall-modeled large-eddy simulation paradigm

TL;DR

This paper introduces a novel wall-modeled large-eddy simulation approach that couples a near-wall DNS patch with an outer LES flow, leveraging flow structure knowledge for improved predictions of wall-bounded turbulence.

Contribution

It presents a flow-structure-based coupling method for wall modeling in LES, moving beyond RANS-based models by utilizing turbulence structure insights.

Findings

Accurately predicts wall stress and velocity fluctuations.

Captures flow structure across the near-wall layer.

Predicts subgrid-scale quantities effectively.

Abstract

A promising and cost-effective method for numerical simulation of high Re wall-bounded flows is wall-modeled large-eddy simulation. Most wall models are formulated from the Reynolds-averaged Navier-Stokes equations (RANS). These RANS-based wall models are calibrated using mean turbulence data and make no use of the current vast knowledge on turbulent flow structure. Moreover, RANS-based models are limited to predicting the mean velocity profile, and the mean wall shear stress. Using the knowledge of the wall-normal self-similarity of high-$Re_\tau$ wall-bounded turbulent flows, we present a coupling between a near-wall patch of DNS resolution fixed in inner-units and an outer LES flow field. The near-wall patch captures the near-wall self-sustaining cycle as well as the lower portion of the self-similar hierarchy of eddies. Given that both the near-wall patch and the LES capture separate portions of the self-similar hierarchy of eddies an instantaneous top boundary condition for the patch is formulated. The near-wall model is capable of predicting subgrid-scale quantities such as the wall stress, velocity fluctuations, kinetic energy spectra, and flow structure across the entire near-wall layer.