Particle image based simultaneous velocity and particle concentration measurement

Abstract

The aim of this study is the expansion of the application of particle image velocimetry (PIV) to include the determination of particle concentration within the visualized area, in addition to velocity analysis. The assessment of particle concentration is valuable in various lab-scale experiments involving particle dispersion. Additionally, it plays a crucial role in evaluating the quality of PIV images. The research investigates two particle image-based concentration techniques: the exponential averaging-based sliding method and the Voronoi cell-based method on the particle images. The exponential averaging method provides a straightforward approach, utilizing a constant length scale for sliding average application to particle images. However, this method may result in broadened interfaces or a ‘marker-shot’ effect at low concentrations, making it less suitable for scenarios involving highly non-uniform particle distributions, such as concentrated jet emissions into ambient environments. Consequently, detecting interfaces in such cases requires additional effort for reliable results. In contrast, the Voronoi cell-based technique offers the advantage of spatially adaptive resolution, making it well-suited for variable concentration distributions and situations where interface detection is crucial. To comprehensively evaluate the performance of these techniques, a synthetic test case was generated to simulate a diffusion problem featuring an initial step in concentration distribution. Both the exponential averaging and Voronoi cell-based methods were applied and compared using this synthetic test case. Additionally, the effect of particle–particle overlap is analyzed theoretically and experimentally with uniform concentration and comparison with particle counter measurements. A modified Voronoi method is introduced, providing flexibility in capturing a wide range of concentration regions and features. An example experimental scenario involving a turbulent puff was considered demonstrating the application of the developed methods. The results demonstrate that the Voronoi method effectively captures small structures with high concentrations while providing reliable results in regions with low concentrations.