Research, Application and Future Prospect of Mode Decomposition in Fluid Mechanics

doi:10.3390/sym16020155

CORC > 力学研究所 > 中国科学院力学研究所 > 高温气体动力学国家重点实验室

	Research, Application and Future Prospect of Mode Decomposition in Fluid Mechanics
	Long, Yun 1; Guo, Xi'an 1; Xiao TB(肖天白)2
刊名	SYMMETRY-BASEL
	2024-02-01
卷号	16 期号:2 页码:22
关键词	fluid mechanics modal decomposition technology proper orthogonal decomposition
DOI	10.3390/sym16020155
通讯作者	Long, Yun(longyun@ujs.edu.cn)
英文摘要	In fluid mechanics, modal decomposition, deeply intertwined with the concept of symmetry, is an essential data analysis method. It facilitates the segmentation of parameters such as flow, velocity, and pressure fields into distinct modes, each exhibiting symmetrical or asymmetrical characteristics in terms of amplitudes, frequencies, and phases. This technique, emphasizing the role of symmetry, is pivotal in both theoretical research and practical engineering applications. This paper delves into two dominant modal decomposition methods, infused with symmetry considerations: Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD). POD excels in dissecting flow fields with clear periodic structures, often showcasing symmetrical patterns. It utilizes basis functions and time coefficients to delineate spatial modes and their evolution, highlighting symmetrical or asymmetrical transitions. In contrast, DMD effectively analyzes more complex, often asymmetrical structures like turbulent flows. By performing iterative analyses on the flow field, DMD discerns symmetrical or asymmetrical statistical structures, assembling modal functions and coefficients for decomposition. This method is adapted to extracting symmetrical patterns in vibration frequencies, growth rates, and intermodal coupling. The integration of modal decomposition with symmetry concepts in fluid mechanics enables the effective extraction of fluid flow features, such as symmetrically or asymmetrically arranged vortex configurations and trace evolutions. It enhances the post-processing analysis of numerical simulations and machine learning approaches in flow field simulations. In engineering, understanding the symmetrical aspects of complex flow dynamics is crucial. The dynamics assist in flow control, noise suppression, and optimization measures, thus improving the symmetry in system efficiency and energy consumption. Overall, modal decomposition methods, especially POD and DMD, provide significant insights into the symmetrical and asymmetrical analysis of fluid flow. These techniques underpin the study of fluid mechanics, offering crucial tools for fluid flow control, optimization, and the investigation of nonlinear phenomena and propagation modes in fluid dynamics, all through the lens of symmetry.
分类号	二类
资助项目	China Postdoctoral Science Foundation Funded Project
WOS关键词	PROPER ORTHOGONAL DECOMPOSITION ; ORDER REDUCTION ; POD ANALYSIS ; FLOWS ; TURBULENCE ; SYSTEMS
WOS研究方向	Science & Technology - Other Topics
语种	英语
WOS记录号	WOS:001172496300001
资助机构	China Postdoctoral Science Foundation Funded Project
其他责任者	Long, Yun
内容类型	期刊论文
源URL	[http://dspace.imech.ac.cn/handle/311007/94655]
专题	力学研究所_高温气体动力学国家重点实验室
作者单位	1.Jiangsu Univ, Natl Res Ctr Pumps, Zhenjiang 212013, Peoples R China; 2.Chinese Acad Sci, Inst Mech, State Key Lab High Temp Gas, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Long, Yun,Guo, Xi'an,Xiao TB. Research, Application and Future Prospect of Mode Decomposition in Fluid Mechanics[J]. SYMMETRY-BASEL,2024,16(2):22.
APA	Long, Yun,Guo, Xi'an,&肖天白.(2024).Research, Application and Future Prospect of Mode Decomposition in Fluid Mechanics.SYMMETRY-BASEL,16(2),22.
MLA	Long, Yun,et al."Research, Application and Future Prospect of Mode Decomposition in Fluid Mechanics".SYMMETRY-BASEL 16.2(2024):22.