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A statistical analysis for time-averaged turbulent and fluctuating flow fields using Particle Image Velocimetry

机译:使用粒子图像测速技术对时间平均湍流和脉动流场进行统计分析

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摘要

The significance of the number of vector maps recorded on time-averaged statistics is analysed using Particle Image Velocimetry for a practical application of a radial fan flow. This type of flow has been shown to produce large gradients in both velocity and turbulence intensity, therefore rendering a single-point statistical analysis of the error in time-averaged data unsuitable. First and second order statistics for the entire region of interest have been assessed by varying sample sizes and monitoring the influence on velocity magnitude, turbulence intensities and Reynolds shear stress. Theoretical standard error estimates and an empirical bootstrapping technique have been implemented for determining high confidence levels in the accuracy of the time-averaged quantities. The results illustrate the complex turbulent and fluctuating flows produced by rotating fans, highlighting the requirement to predict sufficient sample numbers during experimentation. In the example presented, and for many practical scenarios where fluctuating flow exists, a trade-off between sample size and accuracy may be necessary using this measurement technique.
机译:使用粒子图像测速仪分析了在时间平均统计数据上记录的矢量图的数量的重要性,以用于径向风扇流的实际应用。已经显示出这种类型的流动会在速度和湍流强度上产生较大的梯度,因此,对时间平均数据中的误差进行单点统计分析是不合适的。通过改变样本大小并监视对速度大小,湍流强度和雷诺剪切应力的影响,可以评估整个目标区域的一阶和二阶统计量。为了确定时间平均量的准确性中的高置信度,已经实施了理论标准误差估计和经验自举技术。结果说明了旋转风扇产生的复杂湍流和波动流,突出了在实验过程中预测足够的样本数量的要求。在给出的示例中,对于存在波动流量的许多实际情况,使用此测量技术可能需要在样本大小和准确性之间进行权衡。

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