2022
DOI: 10.1103/physrevfluids.7.034603
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Analysis of spatiotemporal inner-outer large-scale interactions in turbulent channel flow by multivariate empirical mode decomposition

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Cited by 7 publications
(22 citation statements)
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“…Motivated by such observations of coherent structures and their interactions, there has been intensive efforts in recent years to investigate the scale interactions in wall turbulence by quantifying turbulent energy transfers between different scales [6][7][8][9][10][11][12][13][14][15][16][17][18][19] . Interestingly, both forward (from larger to smaller scales) and inverse (from smaller to larger scales) turbulent energy cascades have been observed in these studies, and the relations of such interscale energy transfers to the dynamics of coherent structures, such as the self-sustaining cycles of each inner and outer structure 9,12,19,20 , the inner-outer interactions 9,10,[17][18][19][21][22][23] , merging/splitting of wall-attached hair-pin vortices 16 , etc. have been discussed.…”
Section: Introductionmentioning
confidence: 88%
“…Motivated by such observations of coherent structures and their interactions, there has been intensive efforts in recent years to investigate the scale interactions in wall turbulence by quantifying turbulent energy transfers between different scales [6][7][8][9][10][11][12][13][14][15][16][17][18][19] . Interestingly, both forward (from larger to smaller scales) and inverse (from smaller to larger scales) turbulent energy cascades have been observed in these studies, and the relations of such interscale energy transfers to the dynamics of coherent structures, such as the self-sustaining cycles of each inner and outer structure 9,12,19,20 , the inner-outer interactions 9,10,[17][18][19][21][22][23] , merging/splitting of wall-attached hair-pin vortices 16 , etc. have been discussed.…”
Section: Introductionmentioning
confidence: 88%
“…The time-resolved spatial velocity fields are decomposed into scale-based modal representations by an extended version of the 2-D EMD (Mäteling & Schröder 2022). Unlike classical Fourier filtering, the EMD is able to process nonlinear and unsteady data, which are both essential characteristics of turbulent flows.…”
Section: Methodical Approachmentioning
confidence: 99%
“…In the present analysis, a 2-D NA-MEMD is applied to the velocity fields (Mäteling & Schröder 2022). In general, the multivariate data can be composed of different fluid-dynamical quantities such as velocity, pressure or density fields.…”
Section: Methodical Approachmentioning
confidence: 99%
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