Multi-pathline flow visualization using PIV images

TL;DR

This paper introduces post-processing techniques for PIV images to enhance flow visualization, enabling better observation of flow features without additional experiments, by controlling exposure, color-coding time, and changing reference frames.

Contribution

It presents novel post-processing methods for PIV images that improve flow visualization and feature detection in various flow cases.

Findings

Enhanced flow features visibility in vortex ring, vortex, and turbulent boundary layer cases.

Post-processing methods improve qualitative understanding of flow dynamics.

Visualization techniques augment traditional PIV data analysis.

Abstract

One of the oldest flow visualization techniques is through multiple pathlines generated by the movement of seeding particles spatially distributed in the flow. In the computerized era, particle images are used in quantitative measurements, such as particle image and particle tracking velocimetry (PIV and PTV). Here, we present several methods for post-processing raw particle images to generate enhanced flow visualization without a need for conducting additional experiments. Three post-processing methods will be shown: 1) controlling the exposure time, 2) color-coding temporal information, and 3) changing the frame of reference. We showcase how employing these three methods can highlight different flow features in three canonical flow cases: vortex ring, leading edge vortex, and turbulent boundary layer. In addition to the quantitative flow field, the multi-pathline visualization is expected to augment our ability to observe fluid flow from many different perspectives.