Optimized dynamic similarity models to predict SGS backscatter in 2D decaying turbulence

doi:10.1016/j.compfluid.2024.106497

	Optimized dynamic similarity models to predict SGS backscatter in 2D decaying turbulence
	Wang DD(王丹丹)1,2; Ren, Yuxin 2; Ding MN(丁梦楠)1
通讯作者	Ren, Yu-xin([email protected])
发表期刊	COMPUTERS & FLUIDS
	2025-02-15
卷号	288 页码:14
ISSN	0045-7930
摘要	Large eddy simulation (LES) of two-dimensional (2D) turbulence is often used in the geostrophic flows. However, some basic dynamics underlying traditional SGS models are absent in 2D turbulence, e.g. the vortex stretching. Hence, this research proposes an optimized dynamic similarity model (DSM) for the SGS stress, which is constructed through the dynamic procedure based on the Germano identity. In addition, a modification is made to the dynamic mixed model (DMM) for the sake of realizability condition. The optimized DSM is justified in comparison with the DMM, through the a priori and a posteriori verifications, in the context of the 2D decaying turbulence with turbulent Reynolds number of Re = 3.7 x 104 and turbulent Mach number of Mt = 0.1. Special attention is paid to the consistency of the verification procedure, so that the filtering operations used in the direct numerical simulation (DNS) and LES are optimally equivalent. The SGS transport phenomena, especially the SGS backscatter, predicted by these two models are studied in detail. In addition, the optimized DSM and the DMM are extended for the modified SGS transport vectors of passive scalars to show their capability in calculating 2D turbulent mixing. The numerical results show the optimized DSM provides larger correlation coefficient, better locality, and stronger SGS backscsatter than the DMM does, and therefore it is more suitable for the LES of 2D turbulence.
关键词	2D turbulence SGS backscatter Dynamic similarity model
DOI	10.1016/j.compfluid.2024.106497
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:001374216400001
关键词[WOS]	LARGE-EDDY-SIMULATION ; SUBGRID-SCALE BACKSCATTER ; FORMULATION
WOS研究方向	Computer Science ; Mechanics
WOS类目	Computer Science, Interdisciplinary Applications ; Mechanics
资助项目	NSFC[92152201]
项目资助者	NSFC
论文分区	二类
力学所作者排名	1
RpAuthor	Ren, Yu-xin
引用统计
文献类型	期刊论文
条目标识符	http://dspace.imech.ac.cn/handle/311007/97778
专题	高温气体动力学国家重点实验室
作者单位	1.Chinese Acad Sci, Inst Mech, Beijing 100190, Peoples R China; 2.Tsinghua Univ, Engn Mech, Beijing 100084, Peoples R China
推荐引用方式 GB/T 7714	Wang DD,Ren, Yuxin,Ding MN. Optimized dynamic similarity models to predict SGS backscatter in 2D decaying turbulence[J]. COMPUTERS & FLUIDS,2025,288:14.Rp_Au:Ren, Yu-xin
APA	王丹丹,Ren, Yuxin,&丁梦楠.(2025).Optimized dynamic similarity models to predict SGS backscatter in 2D decaying turbulence.COMPUTERS & FLUIDS,288,14.
MLA	王丹丹,et al."Optimized dynamic similarity models to predict SGS backscatter in 2D decaying turbulence".COMPUTERS & FLUIDS 288(2025):14.