Refined analysis identifies noise contamination in large-scale turbulence, suggesting new stochastic models for wall-bounded flows.
Uniform momentum zones (UMZs) are widely used to describe and model the coherent structure of wall-bounded turbulent flows, but their detection has traditionally relied on relatively narrow fields of view which preclude fully resolving features at the scale of large-scale motions (LSMs). We refine and extend recent proposals to detect UMZs with moving-window fields of view by including physically motivated coherency criteria. Using synthetic data, we show how this updated moving-window approach can eliminate noise contamination that is likely responsible for the previously reported, high fractal dimension of UMZ interfaces. By applying the approach to channel flow direct numerical simulation (DNS), we identify a significant number of previously undetected, large-scale UMZ interfaces, including a small fraction of highly linear interfaces with well-defined streamwise inclination angles. We show that the inclination angles vary inversely with the size of the UMZ interfaces and that this relationship can be modelled by the opposing effects of shear-induced inclination and vortex-induced lift-up on hairpin packets. These geometric properties of large-scale UMZ interfaces play an important role in the development of improved stochastic models of wall-bounded turbulence.
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Cui et al. (2025) studied this question.
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