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Self-similar compressible turbulent boundary layers with pressure gradients. Part 2. Self-similarity analysis of the outer layer

Published online by Cambridge University Press:  09 October 2019

Tobias Gibis*
Affiliation:
Institute of Aerodynamics and Gas Dynamics, University of Stuttgart, 70550 Stuttgart, Germany
Christoph Wenzel*
Affiliation:
Institute of Aerodynamics and Gas Dynamics, University of Stuttgart, 70550 Stuttgart, Germany
Markus Kloker
Affiliation:
Institute of Aerodynamics and Gas Dynamics, University of Stuttgart, 70550 Stuttgart, Germany
Ulrich Rist
Affiliation:
Institute of Aerodynamics and Gas Dynamics, University of Stuttgart, 70550 Stuttgart, Germany
*
Email addresses for correspondence: tobias.gibis@iag.uni-stuttgart.de, wenzel@iag.uni-stuttgart.de
Email addresses for correspondence: tobias.gibis@iag.uni-stuttgart.de, wenzel@iag.uni-stuttgart.de

Abstract

A thorough self-similarity analysis is presented to investigate the properties of self-similarity for the outer layer of compressible turbulent boundary layers. The results are validated using the compressible and quasi-incompressible direct numerical simulation (DNS) data shown and discussed in the first part of this study; see Wenzel et al. (J. Fluid Mech., vol. 880, 2019, pp. 239–283). The analysis is carried out for a general set of characteristic scales, and conditions are derived which have to be fulfilled by these sets in case of self-similarity. To evaluate the main findings derived, four sets of characteristic scales are proposed and tested. These represent compressible extensions of the incompressible edge scaling, friction scaling, Zagarola–Smits scaling and a newly defined Rotta–Clauser scaling. Their scaling success is assessed by checking the collapse of flow-field profiles extracted at various streamwise positions, being normalized by the respective scales. For a good set of scales, most conditions derived in the analysis are fulfilled. As suggested by the data investigated, approximate self-similarity can be achieved for the mean-flow distributions of the velocity, mass flux and total enthalpy and the turbulent terms. Self-similarity thus can be stated to be achievable to a very high degree in the compressible regime. Revealed by the analysis and confirmed by the DNS data, this state is predicted by the compressible pressure-gradient boundary-layer growth parameter $\unicode[STIX]{x1D6EC}_{c}$, which is similar to the incompressible one found by related incompressible studies. Using appropriate adaption, $\unicode[STIX]{x1D6EC}_{c}$ values become comparable for compressible and incompressible pressure-gradient cases with similar wall-normal shear-stress distributions. The Rotta–Clauser parameter in its traditional form $\unicode[STIX]{x1D6FD}_{K}=(\unicode[STIX]{x1D6FF}_{K}^{\ast }/\bar{\unicode[STIX]{x1D70F}}_{w})(\text{d}p_{e}/\text{d}x)$ with the kinematic (incompressible) displacement thickness $\unicode[STIX]{x1D6FF}_{K}^{\ast }$ is shown to be a valid parameter of the form $\unicode[STIX]{x1D6EC}_{c}$ and hence still is a good indicator for equilibrium flow in the compressible regime at the finite Reynolds numbers considered. Furthermore, the analysis reveals that the often neglected derivative of the length scale, $\text{d}L_{0}/\text{d}x$, can be incorporated, which was found to have an important influence on the scaling success of common ‘low-Reynolds-number’ DNS data; this holds for both incompressible and compressible flow. Especially for the scaling of the $\bar{\unicode[STIX]{x1D70C}}\widetilde{u^{\prime \prime }v^{\prime \prime }}$ stress and thus also the wall shear stress $\bar{\unicode[STIX]{x1D70F}}_{w}$, the inclusion of $\text{d}L_{0}/\text{d}x$ leads to palpable improvements.

Information

Type
JFM Papers
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s) 2019
Figure 0

Table 1. Consistent sets of compressible characteristic scales. RC, Rotter–Clauser; ZS, Zagarola–Smits.

Figure 1

Table 2. Summarized properties of DNS results presented by Wenzel et al. (2019) in the domain of interest. Given parameters are the kinematic Rotta–Clauser parameter $\unicode[STIX]{x1D6FD}_{K}$ and parameters evaluated at the beginning (‘$1$’) and the end (‘$2$’) of the region of interest, where $\unicode[STIX]{x1D6FD}_{K}=(\unicode[STIX]{x1D6FF}_{K}^{\ast }/\bar{\unicode[STIX]{x1D70F}}_{w})(\text{d}p_{e}/\text{d}x)$ is almost constant. Here $M_{e}$ is the local Mach number, $\unicode[STIX]{x0394}x/\unicode[STIX]{x1D6FF}_{99,av}$ is the spatial extent of the region of interest in averaged boundary-layer thicknesses (‘$av$’), $\unicode[STIX]{x1D6FF}_{99,2}/\unicode[STIX]{x1D6FF}_{99,1}$ is the ratio of local boundary-layer thickness, and $Re_{\unicode[STIX]{x1D703}}$ is the corresponding Reynolds number. Prefix $i$ is for almost incompressible and $c$ for compressible cases.

Figure 2

Figure 1. Plots of $U_{0}/U_{e}$ (column 1), $F_{0}/F_{e}$ (column 2) and $G_{0}/U_{0}^{2}$ (column 3) for different scalings: (a) edge scaling, (b) friction scaling, (c) RC scaling and (d) ZS scaling. Grey lines denote the induction regions where $\unicode[STIX]{x1D6FD}_{K}$ is not yet constant. Red lines: ——, $iZPG$; —— –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.19}$; — – —, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.58}$; – $\cdot$ – $\cdot$ – $\cdot$ –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=1.05}$. Blue lines: ——, $cZPG$; —— –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.15}$; – – – – –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.55}$. Cyan line: — – – —, $cFPG_{\unicode[STIX]{x1D6FD}_{K}=-0.18}$.

Figure 3

Figure 2. Plots of PG boundary-layer-growth parameter $\unicode[STIX]{x1D6EC}_{c}$ (column 1) and PG parameter $\unicode[STIX]{x1D6FD}$ (column 2) for different scalings: (a) edge scaling, (b) friction scaling, (c) RC scaling and (d) ZS scaling. Symbols mark positions where local profiles are extracted in the following; cases with the same $\unicode[STIX]{x1D6FD}_{K}$ have the same symbol type. Grey lines denote the induction regions, where $\unicode[STIX]{x1D6FD}_{K}$ is not yet constant. Red lines: ——, $iZPG$; —— –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.19}$; — – —, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.58}$; – $\cdot$ – $\cdot$ – $\cdot$ –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=1.05}$. Blue lines: ——, $cZPG$; —— –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.15}$; – – – – –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.55}$. Cyan line: — – – —, $cFPG_{\unicode[STIX]{x1D6FD}_{K}=-0.18}$.

Figure 4

Figure 3. Mean velocity profiles for different characteristic velocity scales: (a) edge scaling, (b) friction scaling, (c) RC scaling, and (d) ZS scaling. Grey lines: profiles extracted at 10 streamwise positions. Coloured lines: average profiles. Red lines: ——, $iZPG$; —— –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.19}$; — – —, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.58}$; – $\cdot$ – $\cdot$ – $\cdot$ –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=1.05}$. Blue lines: ——, $cZPG$; —— –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.15}$; – – – – –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.55}$. Cyan line: — – – —, $cFPG_{\unicode[STIX]{x1D6FD}_{K}=-0.18}$.

Figure 5

Figure 4. Mean mass-flux profiles for different characteristic mass-flux scales: (a) edge scaling, (b) friction scaling, (c) RC scaling, and (d) ZS scaling. Grey lines: profiles extracted at 10 streamwise positions. Coloured lines: average profiles. Red lines: ——, $iZPG$; —— –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.19}$; — – —, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.58}$; – $\cdot$ – $\cdot$ – $\cdot$ –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=1.05}$. Blue lines: ——, $cZPG$; —— –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.15}$; – – – – –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.55}$. Cyan line: — – – —, $cFPG_{\unicode[STIX]{x1D6FD}_{K}=-0.18}$.

Figure 6

Figure 5. Mean total enthalpy profiles for different characteristic enthalpy scales: (a) edge scaling, (b) friction scaling, (c) RC scaling, and (d) ZS scaling. Grey lines: profiles extracted at 10 streamwise positions. Coloured lines: average profiles. Red line: ——, $iZPG$. Blue lines: ——, $cZPG$; —— –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.15}$; – – – – –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.55}$. Cyan line: — – – —, $cFPG_{\unicode[STIX]{x1D6FD}_{K}=-0.18}$.

Figure 7

Figure 6. Favre stress $\bar{\unicode[STIX]{x1D70C}}\widetilde{u^{\prime \prime 2}}$ in (a) edge scaling, (b) friction scaling, (c) RC scaling, and (d) ZS scaling. Grey lines: profiles extracted at 10 streamwise positions. Coloured lines: average profiles. Red lines: ——, $iZPG$; —— –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.19}$; — – —, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.58}$; – $\cdot$ – $\cdot$ – $\cdot$ –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=1.05}$. Blue lines: ——, $cZPG$; —— –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.15}$; – – – – –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.55}$. Cyan line: — – – —, $cFPG_{\unicode[STIX]{x1D6FD}_{K}=-0.18}$.

Figure 8

Figure 7. Same as figure 6, but for Favre stress $\bar{\unicode[STIX]{x1D70C}}\widetilde{v^{\prime \prime 2}}$.

Figure 9

Figure 8. Favre stress $\bar{\unicode[STIX]{x1D70C}}\widetilde{u^{\prime \prime }v^{\prime \prime }}$ in (a) edge scaling, (b) friction scaling, (c) RC scaling, and (d) ZS scaling. Grey lines: profiles extracted at 10 streamwise positions. Coloured lines: average profiles. Red lines: ——, $iZPG$; —— –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.19}$; — – —, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.58}$; – $\cdot$ – $\cdot$ – $\cdot$ –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=1.05}$. Blue lines: ——, $cZPG$; —— –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.15}$; – – – – –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.55}$. Cyan line: — – – —, $cFPG_{\unicode[STIX]{x1D6FD}_{K}=-0.18}$.

Figure 10

Figure 9. Turbulent heat flux $\bar{\unicode[STIX]{x1D70C}}\widetilde{h^{\prime \prime }u^{\prime \prime }}$ in (a) edge scaling, (b) friction scaling, (c) RC scaling, and (d) ZS scaling. Grey lines: profiles extracted at 10 streamwise positions. Coloured lines: average profiles. Red line: ——, $iZPG$. Blue lines: ——, $cZPG$; —— –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.15}$; – – – – –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.55}$. Cyan line: — – – —, $cFPG_{\unicode[STIX]{x1D6FD}_{K}=-0.18}$.

Figure 11

Figure 10. Same as figure 9, but for turbulent heat flux $\bar{\unicode[STIX]{x1D70C}}\widetilde{h^{\prime \prime }v^{\prime \prime }}$.

Figure 12

Figure 11. Pressure-gradient boundary-layer growth parameter $\unicode[STIX]{x1D6EC}_{c}$ computed according to (4.8) for the (a) edge and (b) ZS scalings. Identical symbols denote cases with similar $\unicode[STIX]{x1D6FD}_{K}$ values. Red: ——, $iZPG$; —— –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.19}$; — – —, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.58}$; – $\cdot$ – $\cdot$ – $\cdot$ –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=1.05}$. Blue lines: ——, $cZPG$; —— –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.15}$; – – – – –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.55}$. Cyan line: — – – —, $cFPG_{\unicode[STIX]{x1D6FD}_{K}=-0.18}$.

Figure 13

Figure 12. Mean velocity profiles for variations of the edge scales: (a) velocity-based edge scaling and (b) mass-flux-based edge scaling. Grey lines: profiles extracted at 10 streamwise positions. Coloured lines: average profiles. Red lines: ——, $iZPG$; —— –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.19}$; — – —, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.58}$; – $\cdot$ – $\cdot$ – $\cdot$ –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=1.05}$. Blue lines: ——, $cZPG$; —— –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.15}$; – – – – –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.55}$. Cyan line: — – – —, $cFPG_{\unicode[STIX]{x1D6FD}_{K}=-0.18}$.

Figure 14

Figure 13. Favre stress $\bar{\unicode[STIX]{x1D70C}}\widetilde{u^{\prime \prime }v^{\prime \prime }}$ without regarding $\text{d}L_{0}/\text{d}x$ in the scaling in (a) edge scaling, (b) friction scaling, (c) RC scaling, and (d) ZS scaling. Grey lines: profiles extracted at 10 streamwise positions. Coloured lines: average profiles. Red lines: ——, $iZPG$; —— –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.19}$; — – —, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.58}$; – $\cdot$ – $\cdot$ – $\cdot$ –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=1.05}$. Blue lines: ——, $cZPG$; —— –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.15}$; – – – – –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.55}$. Cyan line: — – – —, $cFPG_{\unicode[STIX]{x1D6FD}_{K}=-0.18}$.

Figure 15

Figure 14. Scaling success for ‘low-Reynolds-number’ corrected friction scaling. (a) Self-similarity conditions according to figure 1: (a1) $U_{0}/U_{e}$, (a2) $F_{0}/F_{e}$, and (a3) $G_{0}/U_{0}^{2}$. (b) Mean-velocity profiles and (c) mean mass-flux profiles according to figures 3 and 4, respectively. Grey lines: profiles extracted at 10 streamwise positions. Coloured lines: average profiles. Red lines: ——, $iZPG$; —— –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.19}$; — – —, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=0.58}$; – $\cdot$ – $\cdot$ – $\cdot$ –, $iAPG_{\unicode[STIX]{x1D6FD}_{K}=1.05}$. Blue lines: ——, $cZPG$; —— –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.15}$; – – – – –, $cAPG_{\unicode[STIX]{x1D6FD}_{K}=0.55}$. Cyan line: — – – —, $cFPG_{\unicode[STIX]{x1D6FD}_{K}=-0.18}$.