中文版 | English
Title

A further investigation on the data assimilation-based small-scale reconstruction of turbulence

Author
Corresponding AuthorWang, Jianchun
Publication Years
2023
DOI
Source Title
ISSN
1070-6631
EISSN
1089-7666
Volume35Issue:1
Abstract
Existing works have shown that the small-scale errors of turbulence can be completely eliminated through data assimilation (DA), provided that all the large-scale Fourier modes below a critical wavenumber k(c) asymptotic to 0.2 eta(-1) are continuously enforced, where eta is the Kolmogorov length scale. Here, we further explore the DA-based small-scale reconstruction problem, for which the large-scale data are insufficient. Under such conditions, an unexpected artificial jump in the energy spectrum is observed. To alleviate this issue and improve the reconstruction accuracy, several approaches have been attempted, including ensemble averaged assimilation, temporally sparse data assimilation (TSDA), and filtering the penalty term in the assimilation. It is shown that ensemble averaging can tangibly reduce the reconstruction error, but the resulted energy spectrum is invariably lower than the true spectrum; TSDA can effectively remove the jump in the energy spectrum, but the reduction of the reconstruction error is limited. Filtering the penalty term can also rectify the energy spectrum, but it makes the reconstruction error larger. Based on these observations, we re-scale the ensemble averaged solution according to the rectified energy spectrum. Both the energy spectrum and the small-scale reconstruction accuracy have been improved by the re-scaled ensemble average method. Furthermore, we also test the current approach in the spatial nudging-based reconstruction of turbulence. Again, enhanced predictions are obtained for both the energy spectrum and the instantaneous turbulent field, invariably demonstrating the effectiveness and robustness of the proposed method.
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
First ; Corresponding
Funding Project
National Natural Science Foundation of China["91952104","92052301","12172161","91752201"] ; National Numerical Windtunnel Project[NNW2019ZT1-A04] ; Shenzhen Science and Technology Program[KQTD20180411143441009] ; Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)[GML2019ZD0103] ; Department of Science and Technology of Guangdong Province[2020B1212030001]
WOS Research Area
Mechanics ; Physics
WOS Subject
Mechanics ; Physics, Fluids & Plasmas
WOS Accession No
WOS:000921518000016
Publisher
ESI Research Field
PHYSICS
Data Source
Web of Science
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/501438
DepartmentDepartment of Mechanics and Aerospace Engineering
Affiliation
1.Southern Univ Sci & Technol, Natl Ctr Appl Math Shenzhen NCAMS, Shenzhen 518055, Peoples R China
2.Southern Univ Sci & Technol, Dept Mech & Aerosp Engn, Shenzhen 518055, Peoples R China
3.Southern Univ Sci & Technol, Guangdong Hong Kong Macao Joint Lab Data Driven Fl, Shenzhen 518055, Peoples R China
First Author AffilicationSouthern University of Science and Technology;  Department of Mechanics and Aerospace Engineering;  
Corresponding Author AffilicationSouthern University of Science and Technology;  Department of Mechanics and Aerospace Engineering;  
First Author's First AffilicationSouthern University of Science and Technology
Recommended Citation
GB/T 7714
Wang, Yunpeng,Yuan, Zelong,Wang, Jianchun. A further investigation on the data assimilation-based small-scale reconstruction of turbulence[J]. PHYSICS OF FLUIDS,2023,35(1).
APA
Wang, Yunpeng,Yuan, Zelong,&Wang, Jianchun.(2023).A further investigation on the data assimilation-based small-scale reconstruction of turbulence.PHYSICS OF FLUIDS,35(1).
MLA
Wang, Yunpeng,et al."A further investigation on the data assimilation-based small-scale reconstruction of turbulence".PHYSICS OF FLUIDS 35.1(2023).
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