物理
动态模态分解
多元统计
模式(计算机接口)
分解
统计物理学
机械
机器学习
计算机科学
生态学
生物
操作系统
作者
Zihao Wang,Wei Zhao,Zhi Zhong Pan,Guiyong Zhang,Yichen Jiang,Tiezhi Sun
出处
期刊:Physics of Fluids
[American Institute of Physics]
日期:2024-02-01
卷期号:36 (2)
被引量:1
摘要
This paper introduces temporal information shared multi-variable dynamic mode decomposition (TIMDMD), a novel data-driven algorithm for multi-variable modal decomposition. TIMDMD leverages joint singular value decomposition to share temporal information across variables, resulting in multi-variable rather than single-variable optimization. The algorithm effectively addresses several common issues with traditional DMD approaches, such as inconsistent physical interpretations, a lack of phase consistency between variables, and the mixing of frequency components in the reconstructed flow field. To demonstrate its efficacy, TIMDMD is applied to the analysis of wake flows behind a circular cylinder and a pitching airfoil. The results highlight TIMDMD's ability to align modal indices across variables, correct phase relationships, reduce prediction errors, and improve the clarity of frequency components in the reconstructed flow field.
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