Kinematic Decomposition of Multi-Pulse Shake-the-Box Particle Tracking Velocimetry Data

We have developed a new, comprehensive kinematic decomposition on unstructured Lagrangian data obtained from volumetric particle tracking velocimetry measurements via a 4-pulse technique. We first validate the method by comparing it with two-dimensional and three-dimensional particle tracking data derived from analytical solutions and the JHU turbulent channel flow DNS and then apply it to experimental data. The method applies a Delaunay triangulation technique on the data at a time t during the track duration and calculates linear affine mappings between the evolving control volumes at a later time t + dt. This approach enables us to establish a continuous representation of the flow behavior along the particle trajectories. The processed data can then be further analyzed to identify the four types of fluid motion (i.e., translation, rotation, dilatation, and shear) without using numerical differentiation schemes. The methodology provides insights into the underlying dynamics of the flow and facilitates the identification of Lagrangian coherent structures within the flow without having to resort to the fine scale reconstruction of the VIC# technique from Jeon et al (2018) or the VIC time-segment assimilation from Scarano et al (2022).