A hybrid PIV/PSV approach for a large dynamic velocity range

IF 2.3 3区 工程技术 Q2 ENGINEERING, MECHANICAL
Dapeng Zhang, Wu Zhou, Cameron Tropea, Haoqin Huang, Xiangrui Dong, Tianyi Cai, Xiaoshu Cai
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Abstract

Particle image velocimetry (PIV), particle tracking velocimetry (PTV) and particle streak velocimetry (PSV) are well-established image-based measurement techniques for flow velocity fields; the main difference among the techniques lies in the timing sequence, i.e., the choice of illumination/exposure times and the time between image frames. These are chosen with respect to the expected range of seeding particle movement in time and the desired temporal resolution of flow fluctuations. Difficulties arise when very large differences in velocity occur within a single planar field of view, such that any single timing sequence is inappropriate for certain regions of the observed field. If for instance, the illumination time is adjusted to suit a PIV measurement at low velocities, high velocities in other flow regions will result in streaks. One question to be addressed is therefore, to what extent PIV processing algorithms can properly cope with streaks, which are possibly truncated in either of the consecutive images? In this context, the notion of ‘truncation bias’ will be introduced and evaluated. The present study investigates the possibility of combining image processing algorithms of PIV and PSV in a hybrid manner, while using a single timing sequence for image recording. After image recording, the images are segmented into regions according to which processing algorithm is most appropriate—PIV or PSV—and the respective algorithm is applied to each of the segments. This is followed by a recombination of the computed velocity field from each segment to obtain a result for the total field of view. The performance of this hybrid approach will be evaluated by generating and processing synthetic input data from a direct numerical simulation of a transitional boundary layer. An example laboratory flow is then used to demonstrate the hybrid technique in practice.

大动态速度范围的PIV/PSV混合方法
粒子图像测速(PIV)、粒子跟踪测速(PTV)和粒子条纹测速(PSV)是基于图像的流场测量技术。这些技术之间的主要区别在于时序,即照明/曝光时间的选择和图像帧之间的时间。这些是根据种子粒子在时间上的预期运动范围和流量波动的期望时间分辨率来选择的。当在单个平面视场内出现非常大的速度差异时,就会出现困难,以至于任何单一的时序都不适合观测视场的某些区域。例如,如果在低流速下调整照明时间以适应PIV测量,那么在其他流区域的高流速将导致条纹。因此,需要解决的一个问题是,PIV处理算法在多大程度上可以适当地处理条纹,这些条纹可能在任意一个连续图像中被截断?在这种情况下,将引入并评估“截断偏差”的概念。本研究探讨了PIV和PSV混合图像处理算法的可能性,同时使用单一时序进行图像记录。图像记录完成后,根据最适合的处理算法(piv或psv)对图像进行分割,并对每个片段应用各自的算法。然后对每个片段的计算速度场进行重组,以获得整个视场的结果。这种混合方法的性能将通过生成和处理来自过渡边界层直接数值模拟的合成输入数据来评估。并以实验室流程为例,对该混合技术进行了实践验证。
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来源期刊
Experiments in Fluids
Experiments in Fluids 工程技术-工程:机械
CiteScore
5.10
自引率
12.50%
发文量
157
审稿时长
3.8 months
期刊介绍: Experiments in Fluids examines the advancement, extension, and improvement of new techniques of flow measurement. The journal also publishes contributions that employ existing experimental techniques to gain an understanding of the underlying flow physics in the areas of turbulence, aerodynamics, hydrodynamics, convective heat transfer, combustion, turbomachinery, multi-phase flows, and chemical, biological and geological flows. In addition, readers will find papers that report on investigations combining experimental and analytical/numerical approaches.
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