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Approach to select optimal cross-correlation parameters for light field particle image velocimetry

Zhu, Xiaoyu, Xu, Chuanlong, Hossain, Md. Moinul, Li, Jian, Zhang, Biao, Khoo, Boo Cheong (2022) Approach to select optimal cross-correlation parameters for light field particle image velocimetry. Physics of Fluids, . ISSN 1070-6631. (doi:10.1063/5.0098933) (KAR id:95493)


The light field particle image velocimetry (LF-PIV) has shown a great potential for three-dimensional (3D) flow measurement in space-constrained applications. Usually, the parameters of the cross-correlation calculation in the LF-PIV are chosen based on empirical analysis or introduced from conventional planar PIV, which lowers the accuracy of 3D velocity field measurement. This study presents an approach to selecting optimal parameters of the cross-correlation calculation and thereby offers systematic guidelines for experiments. The selection criterion of the interrogation volume size is studied based on the analysis of the valid detection probability of the correlation peak. The optimal seeding concentration and the size of tracer particles are then explored through synthetic Gaussian vortex field reconstruction. The optimized parameters are employed in a cylinder wake flow measurement in a confined channel. A comparative study is conducted between the LF-PIV and a planar PIV system. Results indicate that the LF-PIV along with the optimized parameters can measure the 3D flow velocity of the cylinder wakes accurately. It has been observed that the mean and max errors of velocity decrease by 32.6% and 18.8%, respectively compared to the related LF-PIV techniques without consideration of optimal parameters. Therefore, it is suggested that the optimized cross-correlation parameters in the LF-PIV can improve the accuracy of 3D flow measurement.

Item Type: Article
DOI/Identification number: 10.1063/5.0098933
Uncontrolled keywords: 3D flow measurement, Light field PIV, Cross-correlation parameters, Valid detection probability, Cylinder wake flow
Subjects: Q Science > Q Science (General)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Moinul Hossain
Date Deposited: 18 Jun 2022 10:59 UTC
Last Modified: 20 Jun 2022 08:58 UTC
Resource URI: (The current URI for this page, for reference purposes)

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