2022
DOI: 10.1017/jfm.2022.316
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Objective momentum barriers in wall turbulence

Abstract: We use the recent frame-indifferent theory of diffusive momentum transport to identify internal barriers in wall-bounded turbulence. Formed by the invariant manifolds of the Laplacian of the velocity field, the barriers block the viscous part of the instantaneous momentum flux in the flow. We employ the level sets of single-trajectory Lagrangian diagnostic tools, the trajectory rotation average and trajectory stretching exponent, to approximate both vortical and internal wall-parallel momentum transport barrie… Show more

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Cited by 10 publications
(28 citation statements)
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“…We have additionally used the described algorithm to extract objectively defined instantaneous momentum transport barriers in a 3-D turbulent channel flow in an almost-automated fashion. Such barriers are streamsurfaces of an incompressible barrier equation defined by the Laplacian of the velocity field (Haller et al 2020;Aksamit & Haller 2022). We have extracted vortical momentum transport barriers without the need to advect arrays of trajectories and found such barriers across multiple spatial scales.…”
Section: Discussionmentioning
confidence: 99%
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“…We have additionally used the described algorithm to extract objectively defined instantaneous momentum transport barriers in a 3-D turbulent channel flow in an almost-automated fashion. Such barriers are streamsurfaces of an incompressible barrier equation defined by the Laplacian of the velocity field (Haller et al 2020;Aksamit & Haller 2022). We have extracted vortical momentum transport barriers without the need to advect arrays of trajectories and found such barriers across multiple spatial scales.…”
Section: Discussionmentioning
confidence: 99%
“…This provides a natural way out of the occlusion quandary that besets many visualization approaches while retaining the algorithm's capacity to capture the smallest structures, delineated in the aFTLE plots, by using finer partitions. In the next subsection, we will demonstrate this capacity by pinpointing structures that the active diagnostics-based methods in Haller et al (2020) and Aksamit & Haller (2022) would likely miss. We conclude this section with figure 19 depicting a well-formed spectral gap between the smallest and the second smallest eigenvalue of A for all the computational boxes.…”
Section: Channel Partition Into Small Subdomainsmentioning
confidence: 97%
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