Large-scale coherent structures in compressible turbulent boundary layers

Bross, Matthew; Scharnowski, Sven; Kähler, Christian J.

doi:10.1017/jfm.2020.993

Cited by 23 publications

(39 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…alternating low- and high-speed streamwise structures of length greater than ) in the logarithmic region of an incompressible turbulent boundary layer, and these logarithmic structures have a modulating effect on the generation of small-scale near-wall motions. Superstructures have also been identified in supersonic adiabatic turbulent boundary layers using data from either PIV (Ganapathisubramani, Clemens & Dolling 2006; Bross, Scharnowski & Kähler 2021) or DNS (Ringuette, Wu & Martin 2008). Bernardini & Pirozzoli (2011 a ) further showed the occurrence of an inner–outer interaction and the importance of amplitude modulation imposed on the smaller-scale motions by the large-scale ones in DNS of a Mach 2 turbulent boundary layer.…”

Section: Introductionmentioning

confidence: 99%

Direct numerical simulation of hypersonic turbulent boundary layers: effect of spatial evolution and Reynolds number

2022

View full text Add to dashboard Cite

Direct numerical simulations (DNS) are performed to investigate the spatial evolution of flat-plate zero-pressure-gradient turbulent boundary layers over long streamwise domains ( ${>}300\delta _i$ , with $\delta _i$ the inflow boundary-layer thickness) at three different Mach numbers, $2.5$ , $4.9$ and $10.9$ , with the surface temperatures ranging from quasiadiabatic to highly cooled conditions. The settlement of turbulence statistics into a fully developed equilibrium state of the turbulent boundary layer has been carefully monitored, either based on the satisfaction of the von Kármán integral equation or by comparing runs with different inflow turbulence generation techniques. The generated DNS database is used to characterize the streamwise evolution of multiple important variables in the high-Mach-number, cold-wall regime, including the skin friction, the Reynolds analogy factor, the shape factor, the Reynolds stresses, and the fluctuating wall quantities. The data confirm the validity of many classic and newer compressibility transformations at moderately high Reynolds numbers (up to friction Reynolds number $Re_\tau \approx 1200$ ) and show that, with proper scaling, the sizes of the near-wall streaks and superstructures are insensitive to the Mach number and wall cooling conditions. The strong wall cooling in the hypersonic cold-wall case is found to cause a significant increase in the size of the near-wall turbulence eddies (relative to the boundary-layer thickness), which leads to a reduced-scale separation between the large and small turbulence scales, and in turn to a lack of an outer peak in the spanwise spectra of the streamwise velocity in the logarithmic region.

show abstract

Section: Introductionmentioning

confidence: 99%

Direct numerical simulation of hypersonic turbulent boundary layers: effect of spatial evolution and Reynolds number

2022

View full text Add to dashboard Cite

show abstract

“…2019; Li et al. 2021) and wall-bounded turbulence (Huang, Coleman & Bradshaw 1995; Pirozzoli & Bernardini 2011; Bross, Scharnowski & Kähler 2021; Xu et al. 2021 b ).…”

Section: Introductionmentioning

confidence: 99%

“…Bross et al. (2021) experimentally investigated compressibility effects on the large-scale coherent structures and their relation to turbulence statistics in compressible boundary layers. They found that compressibility has a clear effect on boundary layer, and that the scale of large-scale coherent structures based on the boundary layer thickness becomes longer and wider for supersonic turbulent boundary layers when compared with subsonic and transonic turbulent boundary layers.…”

Section: Introductionmentioning

confidence: 99%

Compressibility effects on statistics and coherent structures of compressible turbulent mixing layers

Wang

Chen

2022

J. Fluid Mech.

View full text Add to dashboard Cite

The effects of compressibility on the statistics and coherent structures of a temporally developing mixing layer are studied using numerical simulations at convective Mach numbers ranging from $M_c=0.2$ to $1.8$ and at Taylor Reynolds numbers up to 290. As the convective Mach number increases, the streamwise dissipation becomes more effective to suppress the turbulent kinetic energy. At $M_c=1.8$ , the streamwise dissipation increases much faster than the other two components in the transition region, even larger than pressure–strain redistribution, correlating with the streamwise elongated vortical structures at a higher level of compressibility. We confirm the existence of the large-scale high- and low-speed structures in the mixing layers, which accompany the spanwise Kelvin–Helmholtz rollers at low convective Mach number and dominate the mixing layer at higher convective Mach number. Conditional statistics demonstrate that the large-scale low-speed structures are lifted upwards by a pair of counter-rotating quasi-streamwise rollers flanking the structures. The small-scale vortical structures have an apparent preference for clustering into the top of the low-speed regions, which is directly associated with high-shearing motions on top of the low-speed structures. The high-speed structures statistically exhibit central symmetry with the low-speed structures. The statistics and dynamics of large-scale high- and low-speed structures in the compressible mixing layers resemble those in the outer region of the turbulent boundary layers, which reveals the universality of the large-scale structures in free shear and wall-bounded turbulence. A conceptual model is introduced for the large-scale high- and low-speed structures in turbulent mixing layers.

show abstract

“…This is most evident in high-speed, compressible flows (Williams 2014; Williams et al. 2018), but it has been observed at all Mach numbers (see, for example, Bross, Scharnowski & Kähler 2021). Recently, Aultman, Disotell & Duan (2022) used DNS to investigate the spatial resolution of PIV for the wall-normal components and clearly demonstrated the important role played by window size, and how spurious cross-correlations caused by the size of the illumination diameter and the local particle density set limits on the smallest acceptable window size.…”

Section: Future Directionsmentioning

confidence: 98%

Batchelor Prize Lecture: Measurements in wall-bounded turbulence

Smits

2022

J. Fluid Mech.

View full text Add to dashboard Cite

Our understanding of turbulent boundary layer scaling and structure has advanced greatly in the past 20 to 30 years. On the computational side, direct numerical simulations and large-eddy simulations have made extraordinary contributions as numerical methods and computational resources have advanced, while on the experimental side major advances in instrumentation have made available new imaging and quantitative techniques that provide unprecedented accuracy and detail. Here, I illustrate how the development of such experimental methods have aided our progress by reference to some particular topics related to the structure of turbulent boundary layers: the power law scaling of the mean velocity and its relationship to the mesolayer; the scaling of the outer layer with regard to the log law in turbulence; the development of the outer peak; and the scaling of the turbulent stresses in the near-wall region, with an emphasis on the streamwise component.

show abstract

Large-scale coherent structures in compressible turbulent boundary layers

Abstract: Abstract

Cited by 23 publications

References 61 publications

Direct numerical simulation of hypersonic turbulent boundary layers: effect of spatial evolution and Reynolds number

Direct numerical simulation of hypersonic turbulent boundary layers: effect of spatial evolution and Reynolds number

Compressibility effects on statistics and coherent structures of compressible turbulent mixing layers

Batchelor Prize Lecture: Measurements in wall-bounded turbulence

Contact Info

Product

Resources

About