Measurements of the wall shear stress distribution in a fully developed turbulent channel flow have been performed using a film-based sensor. The sensor, as a direct method for measuring the wall shear stress, enables the conduction of measurements in a relatively large domain with high spatial resolution. From the experimental data, instantaneous velocity components in the region of y+<5 were approximated using the instantaneous wall shear stress distribution, the application of the continuity condition, and Taylor expansion of the velocity at the wall. In addition, a direct numerical simulation of a turbulent channel flow at the same Reynolds number range was used to assess the experimental results and to extend the analysis to the buffer layer. The investigated Reynolds numbers are in the range of 2,100-2,900 based on the friction velocity and the half channel height. The distribution of the fluctuating wall shear stress reveals the presence of low- and high-shear regions oriented in the streamwise direction. This indicates the imprint of existing streaky structures in the near-wall region. The conditionally averaged field of low-shear stress regions exhibits the existence of a counter-rotating vortex pattern elongated in the streamwise direction. The averaged map conjectures the signature of long quasi-streamwise vortices or stretched legs of hairpins as the dominant structures in the immediate vicinity of the wall.
|Original language||English (US)|
|Title of host publication||International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2013|
|State||Published - 2013|
|Event||8th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2013 - Poitiers, France|
Duration: Aug 28 2013 → Aug 30 2013
|Name||International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2013|
|Other||8th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2013|
|Period||8/28/13 → 8/30/13|
Bibliographical noteFunding Information:
edged. This research was undertaken with the assistance of resources provided at the National Computational Infrastructure (NCI) and Multi-modal Australian Sciences Imaging and Visualisation Environment (MASSIVE) facilities through the National Computational Merit Allocation Scheme supported by the Australian Government.
The financial support to perform this research by the Australian Research Council is gratefully acknowl-