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On the applicability of numerical image mapping for PIV image analysis near curved interfaces

Research output: Contribution to journalArticle

Original languageEnglish
Article number075301
Number of pages18
JournalMeasurement Science and Technology
Volume28
Issue number7
Early online date2 Jun 2017
DOIs
DateAccepted/In press - 10 Apr 2017
DateE-pub ahead of print - 2 Jun 2017
DatePublished (current) - Jul 2017

Abstract

This paper scrutinises the general suitability of image mapping for particle image velocimetry (PIV) applications. Image mapping can improve PIV measurement accuracy by eliminating overlap between the PIV interrogation windows and an interface, as illustrated by some examples in the literature. Image mapping transforms the PIV images using a curvilinear interface-fitted mesh prior to performing the PIV cross correlation. However, degrading effects due to particle image deformation and the Jacobian transformation inherent in the mapping along curvilinear grid lines have never been deeply investigated. Here, the implementation of image mapping from mesh generation to image resampling is presented in detail, and related error sources are analysed. Systematic comparison with standard PIV approaches shows that image mapping is effective only in a very limited set of flow conditions and geometries, and depends strongly on a-priori knowledge of the boundary shape and streamlines. In particular, with strongly curved geometries or streamlines that are not parallel to the interface, the image-mapping approach is easily outperformed by more traditional image analysis methodologies invoking suitable spatial relocation of the obtained displacement vector.

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    Rights statement: This is the final published version of the article (version of record). It first appeared online via IOP at http://iopscience.iop.org/article/10.1088/1361-6501/aa6c8f/meta. Please refer to any applicable terms of use of the publisher.

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