| Title: |
Dynamic iterative approximate deconvolution models for large-eddy simulation of turbulence |
| Authors: |
Yuan, Zelong; Wang, Yunpeng; Xie, Chenyue; Wang, Jianchun |
| Contributors: |
National Natural Science Foundation of China; National Numerical Wind Tunnel Project of China; National Natural Science Foundation of China Basic Science Center Program; Shenzhen Science and Technology Program; Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory; Department of Science and Technology of Guangdong Province; Center for Computational Science and Engineering of Southern University of Science and Technology |
| Source: |
Physics of Fluids ; volume 33, issue 8 ; ISSN 1070-6631 1089-7666 |
| Publisher Information: |
AIP Publishing |
| Publication Year: |
2021 |
| Description: |
Dynamic iterative approximate deconvolution (DIAD) models with Galilean invariance are developed for subgrid-scale (SGS) stress in the large-eddy simulation (LES) of turbulence. The DIAD models recover the unfiltered variables using the filtered variables at neighboring points and iteratively update model coefficients without any a priori knowledge of direct numerical simulation (DNS) data. The a priori analysis indicates that the DIAD models reconstruct the unclosed SGS stress much better than the classical velocity gradient model and approximate deconvolution model with different filter scales ranging from viscous to inertial regions. We also propose a small-scale eddy viscosity (SSEV) model as an artificial dissipation to suppress the numerical instability based on a scale-similarity-based dynamic method without affecting large-scale flow structures. The SSEV model can predict a velocity spectrum very close to that of DNS data, similar to the traditional implicit large-eddy simulation. In the a posteriori testing, the SSEV-enhanced DIAD model is superior to the SSEV model, dynamic Smagorinsky model, and dynamic mixed model, which predicts a variety of statistics and instantaneous spatial structures of turbulence much closer to those of filtered DNS data without significantly increasing the computational cost. The types of explicit filters, local spatial averaging methods, and initial conditions do not significantly affect the accuracy of DIAD models. We further successfully apply DIAD models to the homogeneous shear turbulence. These results illustrate that the current SSEV-enhanced DIAD approach is promising in the development of advanced SGS models in the LES of turbulence. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| DOI: |
10.1063/5.0059643 |
| DOI: |
10.1063/5.0059643/14149549/085125_1_online.pdf |
| Availability: |
https://doi.org/10.1063/5.0059643; https://pubs.aip.org/aip/pof/article-pdf/doi/10.1063/5.0059643/14149549/085125_1_online.pdf |
| Accession Number: |
edsbas.2A4E9486 |
| Database: |
BASE |