Abstract
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.
Published Version
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