湍流
比例(比率)
模式(计算机接口)
频道(广播)
动态模态分解
流量(数学)
多元统计
空间生态学
生物系统
噪音(视频)
分解
物理
机械
统计物理学
计算机科学
数学
人工智能
化学
统计
生物
图像(数学)
电信
生态学
操作系统
有机化学
量子力学
作者
Esther Mäteling,Wolfgang Schröder
出处
期刊:Physical review fluids
[American Physical Society]
日期:2022-03-15
卷期号:7 (3)
被引量:9
标识
DOI:10.1103/physrevfluids.7.034603
摘要
The two-dimensional noise-assisted multivariate empirical mode decomposition (2D NA-MEMD) simultaneously decomposes multiple spatial velocity fields into physically meaningful modes, which are sorted by the inherent scale size and are continuous in time. Spatial features shared by different velocity components are easily detectable by the 2D NA-MEMD, which is beneficial for the inner-outer interaction analysis. The advantage of this approach is demonstrated empirically based on turbulent channel flow data targeting the influence of outer-layer large-scale structures on the near-wall turbulent dynamics.
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