Improvement of double-buffer problem in LES–RANS interface region by introducing an anisotropy-resolving subgrid-scale model

Research output: Contribution to journalArticle

Abstract

The “double-buffer problem” has been regarded as a crucial concern for the strategy behind the hybrid large eddy simulation (LES)/Reynolds-averaged Navier–Stokes (RANS) model (or HLR model, for short). Such models are likely to show unphysical mean-velocity distributions in the LES–RANS interface region, where “super-streak structures” also appear that look like low-speed streaks generated in the near-wall region of wall turbulence. To overcome this difficulty, the stochastic backscatter model, in which the vortex structures in the interface region are divided into smaller scales, holds promise due to the effect of random source term imposed in the momentum equation. Although this method is effective, several parameters must be prescribed and their specification process is arbitrary and ambiguous. An alternative advanced HLR model has been proposed, in which an anisotropy-resolving subgrid-scale (SGS) model was adopted in the LES region as well as a one-equation nonlinear eddy viscosity model in the RANS region. Previous investigations indicated that this HLR model did not exhibit or, at least, largely reduced the “double-buffer problem” in the mean-velocity distribution, with no special treatment being applied. The main purpose of the present study is to reveal why this HLR model improves the predictive performance in the LES–RANS interface region. Specifically, we focus on the role of the extra anisotropic term introduced in the SGS model, finding that it plays an important role in enhancing vortex structures in the interface region, leading to a considerable improvement in model performance.

Original languageEnglish
Pages (from-to)263-283
Number of pages21
JournalTheoretical and Computational Fluid Dynamics
Volume32
Issue number3
DOIs
Publication statusPublished - Jun 1 2018

All Science Journal Classification (ASJC) codes

  • Computational Mechanics
  • Condensed Matter Physics
  • Engineering(all)
  • Fluid Flow and Transfer Processes

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