Dynamic iterative approximate deconvolution models for large-eddy simulation of turbulence

Yuan, Zelong1,2,3; Wang, Yunpeng1,2,3; Xie, Chenyue1,2,3; Wang, Jianchun1,2,3

2021-08-01

10.1063/5.0059643

PHYSICS OF FLUIDS   影响因子和分区

1070-6631

1089-7666

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.

SCI ; EI

英语

第一 ; 通讯

National Natural Science Foundation of China (NSFC)[91952104,92052301,91752201] ; National Numerical Windtunnel Project[NNW2019ZT1-A04] ; NSFC Basic Science Center Program[11988102] ; Shenzhen Science and Technology Program[KQTD20180411143441009] ; Key Special Project for Introduced Talents Team of the Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)[GML2019ZD0103] ; Department of Science and Technology of Guangdong Province[2020B1212030001]

Mechanics ; Physics

Mechanics ; Physics, Fluids & Plasmas

WOS:000685874800010

AMER INST PHYSICS

20213510820995

Iterative methods ; Numerical methods ; Turbulence ; Turbulent flow

Fluid Flow:631 ; Fluid Flow, General:631.1 ; Mathematics:921 ; Numerical Methods:921.6

PHYSICS

Web of Science

1.Southern Univ Sci & Technol, Dept Mech & Aerosp Engn, Shenzhen 518055, Peoples R China
2.Southern Marine Sci & Engn Guangdong Lab, Guangzhou 511458, Peoples R China
3.Southern Univ Sci & Technol, Guangdong Hong Kong Macao Joint Lab Data Driven F, Shenzhen 518055, Peoples R China

Yuan, Zelong,Wang, Yunpeng,Xie, Chenyue,et al. Dynamic iterative approximate deconvolution models for large-eddy simulation of turbulence[J]. PHYSICS OF FLUIDS,2021,33(8).

Yuan, Zelong,Wang, Yunpeng,Xie, Chenyue,&Wang, Jianchun.(2021).Dynamic iterative approximate deconvolution models for large-eddy simulation of turbulence.PHYSICS OF FLUIDS,33(8).

Yuan, Zelong,et al."Dynamic iterative approximate deconvolution models for large-eddy simulation of turbulence".PHYSICS OF FLUIDS 33.8(2021).