Collaborative framework for PIV uncertainty quantification: comparative assessment of methods
Collaborative framework for PIV uncertainty quantification: comparative assessment of methods
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DOI：
10.1088/0957-0233/26/7/074004
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发表时间：
2015-06
影响因子：
2.4
通讯作者：
A. Sciacchitano;D. Neal;Barton L Smith;S. Warner;P. Vlachos;B. Wieneke;F. Scarano
中科院分区：
文献类型：
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作者：
A. Sciacchitano;D. Neal;Barton L Smith;S. Warner;P. Vlachos;B. Wieneke;F. Scarano
粒子图像测速(PIV)数据的后验不确定度量化对于获得与给定实验相关的不确定度的准确估计至关重要。当测量用于验证计算模型或在设计和决策过程中时，这一点尤其相关。尽管这一主题很重要，但第一个PIV不确定度量化(PIV-UQ)方法只是在最近三年才开发出来的。本文对最近文献中提出的四种方法进行了比较评估：不确定面法(Timmins等人)、粒子视差法(Sciacitano等人)、峰值比准则(Charonko和Vlachos)和相关统计法(Wieneke)。该分析是基于为这一特定目的而进行的实验，其中同时使用了几种测量技术。在不同的测量条件和流型下考察了上述方法的性能。
A posteriori uncertainty quantification of particle image velocimetry (PIV) data is essential to obtain accurate estimates of the uncertainty associated with a given experiment. This is particularly relevant when measurements are used to validate computational models or in design and decision processes. In spite of the importance of the subject, the first PIV uncertainty quantification (PIV-UQ) methods have been developed only in the last three years. The present work is a comparative assessment of four approaches recently proposed in the literature: the uncertainty surface method (Timmins et al ), the particle disparity approach (Sciacchitano et al ), the peak ratio criterion (Charonko and Vlachos ) and the correlation statistics method (Wieneke ). The analysis is based upon experiments conducted for this specific purpose, where several measurement techniques are employed simultaneously. The performances of the above approaches are surveyed across different measurement conditions and flow regimes.