On the effect of free-stream turbulence on boundary-layer transition

被引:45
作者
Fransson, Jens H. M. [1 ]
Shahinfar, Shahab [2 ]
机构
[1] KTH Royal Inst Technol, Dept Engn Mech, Linne Flow Ctr, SE-10044 Stockholm, Sweden
[2] Scania CV AB, SE-15132 Sodertalje, Sweden
基金
瑞典研究理事会;
关键词
boundary layer receptivity; boundary layer structure; transition to turbulence; BYPASS TRANSITION; DISTURBANCE GROWTH; SIMULATIONS; INSTABILITY; SURFACE;
D O I
10.1017/jfm.2020.444
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
Free-stream turbulence (FST) and its effect on boundary-layer transition is an intricate problem. Elongated unsteady streamwise streaks of low and high speed are created inside the boundary layer and their amplitude and spanwise wavelength are believed to be important for the onset of transition. The transitional Reynolds number is often simply correlated with the turbulence intensity (Tu), and the characteristic length scales of the FST are often considered to have a small to negligible influence on the transition location. Here, we present new results from a large experimental measurement campaign, where both the and the integral length scale (Lambda(x)) are varied (1.8 % < Tu < 6.2%; 16 33 < Lambda(x) < 26 mm). In the current experiments it has been noted that on the one hand, for small Tu, an increase in Lambda(x) advances transition, which is in agreement with established results. On the other hand, for large Tu, an increase in Lambda(x) postpones transition. This trend can be explained by the fact that an optimal ratio between FST length scale and boundary-layer thickness at transition onset exists. Furthermore, our results strengthen the fact that the streaks play a key role in the transition process by showing a clear dependence of the FST characteristics on their spanwise scale. Our measurements show that the aspect ratio of the streaky structures correlates with an FST Reynolds number and that the aspect ratio can change by a factor of two at the location of transition. Finally, we derive a semi-empirical transition prediction model, which is able to predict the influence of Lambda(x) for both small and high values of Tu.
引用
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页数:31
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