Structural Analysis of Turbulent Boundary Layers

We leverage integral measurements of a passive scalar to identify structurally important velocity scales in boundary layers

Planar and Stereo Particle Image Velocimetry (PIV) measurements are performed in a thermal boundary layer with simultaneous integral measurements of the density gradient across the boundary layer height. The boundary layer is heated such that temperature acts as a passive scalar and a second laser is used to measure density gradients. Previous work on the topic [1] revealed that large density gradients are linked with specific patterns of coherent structures in both streamwise and wall-normal velocity fluctuations. Specifically, large wall-normal velocity structures extending across the entire boundary layer height were identified and it was postulated that they result from an average of smaller scales, residing at different wall-normal locations, all contributing to the same density change. The proposed model also included a combination of large- and small-scale streamwise velocity modes, varying in the wall-normal direction. Preliminary results from ongoing work support this model and show that, if a second condition on the vertical location of the identified features is imposed, one can indeed extract velocity structures that are localized in the wall-normal sense and convect with different velocities, while a multi-scale behavior of the streamwise fluctuations is also observed (Figure 1). Stereo PIV data in the cross-flow plane of the boundary layer will help unravel the spanwise variation of these features and provide a more complete picture of the phenomena they represent.

image
Figure: Planar PIV measurements. Streamwise (top) and wall-normal (bottom) velocity fluctuations when conditioned on a large negative streamwise density gradient. The conditional averaging is performed over velocity fields where, only structures residing in locations y<0.2δ (left), 0.3δ

Angeliki Laskari, Theresa Saxton-Fox, Beverley McKeon

Funding
ONR Grant # N00014-17-1-3022

References

  1. Saxton-Fox (2018), PhD Thesis, Caltech.