Image pre-processing method for near-wall PIV measurements over moving curved interfaces

Jia, L C and Zhu, Y D and Jia, Y X and Yuan, H J and Lee, C B (2017) Image pre-processing method for near-wall PIV measurements over moving curved interfaces. Measurement Science and Technology, 28 (3). 035201. ISSN 0957-0233

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Abstract

PIV measurements near a moving interface are always difficult. This paper presents a PIV image pre-processing method that returns high spatial resolution velocity profiles near the interface. Instead of re-shaping or re-orientating the interrogation windows, interface tracking and an image transformation are used to stretch the particle image strips near a curved interface into rectangles. Then the adaptive structured interrogation windows can be arranged at specified distances from the interface. Synthetic particles are also added into the solid region to minimize interfacial effects and to restrict particles on both sides of the interface. Since a high spatial resolution is only required in high velocity gradient region, adaptive meshing and stretching of the image strips in the normal direction is used to improve the cross-correlation signal-to-noise ratio (SN) by reducing the velocity difference and the particle image distortion within the interrogation window. A two dimensional Gaussian fit is used to compensate for the effects of stretching particle images. The working hypothesis is that fluid motion near the interface is 'quasi-tangential flow', which is reasonable in most fluid-structure interaction scenarios. The method was validated against the window deformation iterative multi-grid scheme (WIDIM) using synthetic image pairs with different velocity profiles. The method was tested for boundary layer measurements of a supersonic turbulent boundary layer on a flat plate, near a rotating blade and near a flexible flapping flag. This image pre-processing method provides higher spatial resolution than conventional WIDIM and good robustness for measuring velocity profiles near moving interfaces.

Item Type: Article
Subjects: Article Archives > Computer Science
Depositing User: Unnamed user with email support@articlearchives.org
Date Deposited: 13 Mar 2024 04:34
Last Modified: 13 Mar 2024 04:34
URI: http://archive.paparesearch.co.in/id/eprint/1798

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