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Title: Wall-Shear-Stress-Based Conditional Sampling Analysis of Coherent Structures in a Turbulent Boundary Layer
Abstract Coherent structures are critical for controlling turbulent boundary layers due to their roles in momentum and heat transfer in the flow. Turbulent coherent structures can be detected by measuring wall shear stresses that are footprints of coherent structures. In this study, wall shear stress fluctuations were measured simultaneously in a zero pressure gradient turbulent boundary layer using two house-made wall shear stress probes aligned in the spanwise direction. The wall shear stress probe consisted of two hot-wires on the wall aligned in a V-shaped configuration for measuring streamwise and spanwise shear stresses, and their performance was validated in comparison with a direct numerical simulation result. Relationships between measured wall shear stress fluctuations and streamwise velocity fluctuations were analyzed using conditional sampling techniques. The peak detection method and the variable-interval time-averaging (VITA) method showed that quasi-streamwise vortices were inclined toward the streamwise direction. When events were simultaneously detected by the two probes, stronger fluctuations in streamwise velocity were detected, which suggests that stronger coherent structures were detected. In contrast to the former two methods, the hibernating event detection method detects events with lower wall shear stress fluctuations. The ensemble-averaged mean velocity profile of hibernating events was shifted upward compared to the law of the wall, which suggests low drag status of the coherent structures related with hibernating events. These methods suggest significant correlations between wall shear stress fluctuations and coherent structures, which could motivate flow control strategies to fully exploit these correlations.  more » « less
Award ID(s):
1832976
PAR ID:
10296805
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Journal of Fluids Engineering
Volume:
143
Issue:
4
ISSN:
0098-2202
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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