Measurement of wall-shear stress via micro-particle tracking velocimetry
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摘要: 采用微粒子追踪测速技术(Micro-Particle Tracking Velocimetry,µ-PTV)对近壁面的流场开展高空间分辨率测量,通过解析黏性底层的速度分布,应用一次线性回归计算得到壁面摩擦应力。测量了不同雷诺数(基于动量损失厚度 )下的湍流边界层壁面摩擦切应力,在Reθ =1200时获得了罕见回流事件的发生概率和流场结构。实验结果表明,采用µ-PTV技术可以实现壁面摩擦应力的准确测量,在Reθ =1634~4070时,摩擦阻力系数测量误差小于2%。回流事件的概率极低,在Reθ =1200时约为0.05%,尺度小于8×30个壁面单位,因此回流事件的测量对测量技术的空间分辨率要求较高;分析结果表明回流事件伴随壁面附近的强展向涡出现。Abstract: Micro-Particle Tracking Velocimetry (µ-PTV) was used to measure the flow field near the wall with high spatial resolution. By analyzing the velocity distribution of the viscous sublayer, the wall-shear stress can be analyzed by one-time linear regression. The wall-shear stress of the turbulent boundary layer at different Reynolds numbers based on momentum loss thickness was measured and the flow structure of reversal flow events was obtained at Reθ=1200. The results show that the micro-particle tracking velocimetry technology can accurately measure the wall-shear stress and the measurement error of wall-shear stress is below 2% for Reθ=1634–4070. Furthermore, the probability of reversal flow is extreme low, i.e., about 0.05% at Reθ=1200. The measured spatial scale of reversal flow structures is around 8×30 wall units, and therefore the measurement of reversal flow events requires high spatial resolution of the measurement technology. The results show that the reversal flow events occur with the appearance of strong spanwise vortices near the wall.es near the wall.
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表 1 零压力梯度湍流边界层流动参数
Table 1. Parameters of the zero-pressure gradient turbulent boundary layers
x Reθ U∞/(m·s–1) θ/mm uτlinear/(m·s–1) uτClauser/(m·s–1) ν· uτ–1/µm δ0.99/mm H12 863 1200 8.00 2.310 0.351 0.333 43.7 19.83 1.412 1400 1009 3.96 3.965 0.183 0.179 84.0 32.37 1.473 1400 1634 5.96 4.355 0.251 0.248 61.1 34.59 1.449 1400 2130 7.93 4.126 0.326 0.320 47.1 32.92 1.435 1400 2565 9.79 4.075 0.395 0.385 38.9 32.05 1.426 1400 2978 11.78 3.920 0.460 0.453 33.4 31.30 1.419 1400 3638 15.70 3.573 0.601 0.607 25.5 28.84 1.402 1400 4070 18.65 3.389 0.709 0.690 21.7 27.53 1.396 -
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