Measuring the velocity field around a complex object by volumetric PIV is hindered by shadow formation (illumination) as well as camera occlusion (imaging). These have been recently dealt with by multiplying illumination and imaging directions (redundancy) and by the integration of ray-tracing techniques to include the effect of visual blockage caused by the object (object-aware particle reconstruction, Wieneke & Rockstroh, 2024). The problem of light reflections blinding regions of the images has not been afforded yet. The latter pertains to interactions between illumination and imaging through the object surface and it poses additional challenges to ghost particle formation, particle detection and tracking in general. This study proposes a method to effectively detect such regions, and measures to modify the particle triangulation algorithm.
The viability of this novel reflection-aware Lagragian particle tracking (RA-LPT) approach is examined by application to two experiments of varying complexity. The first case is the flow around a stationary wall-mounted cube as imaged with a redundant number of cameras. The second experiment tackles an elite runner sprinting across the measurement region obtained with the Ring-of-Fire technique. A considerable reduction of ghost particles (false positives) is attained, while the formation of voids (false negatives) is also minimized. The overall result of the method maximizes the measurement region around and in proximity of the object of interest. ... Read more

Laser light reflection mitigation in Particle Image Velocimetry (PIV) is crucial for accurate flow field measurements. While numerous methods exist for planar PIV, fewer have been developed for volumetric PIV systems, and in particular for coaxial setups like robotic volumetric PIV. Light reflections in volumetric PIV experiments result in high-intensity regions that corrupt particle detection and analysis. This study presents a novel approach for treating light reflections in robotic volumetric PIV experiments. The proposed method uses image filtering and masking techniques in the wavenumber space to separate particle images from reflection regions. The process involves decomposing the image signal into low- and high-wavenumber components using the 2D discrete Fourier transform (DFT) to then use a high-pass filter to attenuate the intensity of the reflection regions. Finally, a step of automated adaptive masking is applied to remove residual reflection areas that the filtering is not able to eliminate. The proposed approach is tested on experimental data obtained from experiments performed using robotic volumetric PIV on two different geometries: a side-view mirror and a rotating two-blade propeller. Comparison between raw and pre-processed images, as well as particle tracking results, is presented. The results from this data comparison show successful removal of reflection-induced artifacts in instantaneous images by using the spatial Fourier filter automated masking approach. The developed image pre-processing strategy effectively removes unsteady light reflection regions in robotic volumetric PIV images, preventing the appearance of spurious particle tracks and improving the accuracy of flow field measurements. The spatial gaps introduced by the masking procedure can be easily filled in via measurements from multiple directions, which are promptly achieved via the robotic volumetric PIV approach. ... Read more