Spanwise velocity statistics in high-Reynolds-number turbulent boundary layers

被引:14
作者
Baidya, R. [1 ]
Philip, J. [1 ]
Hutchins, N. [1 ]
Monty, J. P. [1 ]
Marusic, I. [1 ]
机构
[1] Univ Melbourne, Dept Mech Engn, Melbourne, Vic 3010, Australia
基金
澳大利亚研究理事会;
关键词
boundary layer structure; turbulent boundary layers; DIRECT NUMERICAL-SIMULATION; AMPLITUDE-MODULATION; COHERENT STRUCTURES; DRAG REDUCTION; CHANNEL FLOW; PIPE-FLOW; WALL; STREAMWISE; LAW; CONVECTION;
D O I
10.1017/jfm.2020.1129
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
Spanwise velocity statistics from high-Reynolds-number turbulent boundary layers are reported. The dataset combines efforts spanning over a decade at the University of Melbourne to accurately capture Reynolds number (Re) trends for the spanwise velocity, nominally over one order of magnitude change in Re, using custom subminiature cross-wire probes that minimise spatial resolution effects and misalignment errors. The spanwise velocity (v) variance is found to exhibit an Re invariant logarithmic slope in the log region, in a similar manner to the streamwise velocity (u), which is consistent with the existence of self-similar features within wall-bounded flows. However, unlike the u-variance, it appears that the logarithmic v-variance trend continues to extend towards the wall. The increase in the v-variance with Re in the log region is found to be due to `intermediate-scale eddies', which follow distance-from-the-wall scaling. This results in the v-spectrogram exhibiting a dominant energetic ridge across the intermediate-scales, a trend that is not clearly observed in the u-spectrogram. Other features of the v-spectrogram are found to be similar to the u-spectrogram, such as showing small-scale near-wall features that scale universally with viscous units, and the influence of large-scale v signals residing in the log region that extend to the wall, resulting in a large-scale v footprint in the near-wall region. The observed behaviour of the v-spectrogram with changing Re is used to construct a model for the v-variance based on contributions from small-, intermediateand large-scales, leading to a predictive tool at asymptotically high Re.
引用
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页数:25
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