Lagrangian Particle Tracking Challenge
Time-resolved, four-pulse and two-pulse pairs of synthetic particle images with different particles per pixel (PPP) values created by four virtual camera views of tracer particles in the turbulent boundary layers flow are provided along with the calibration data to challenge the latest developments of the LPT code. The challenge synthetic dataset was computed by Large Eddy Simulation (LES) of a cylinder embedded in a turbulent boundary layer flow over a plate. More details of the LPT challenge is available in "http://cfdforpiv.dlr.de/".
For densities higher than 0:08 ppp, a more accurate initialization technique could prevent the 4D-PTV algorithm from failing or improve its convergence speed. We highlighted that KLPT featuring LCTI succeeded in reconstructing tracks at the density of 0:12 ppp, while KLPT featuring NNI failed to converge. Fig 1 shows an example of coherent motion detection by LCTI at the density of 0:12 ppp. The particle trajectories obtained from the proposed method are shown in Video. 1. Questions have been raised about the 4D-PTV sensitivity to the number of initialized particles at the beginning. We illustrated this issue in the LPT challenge case with 0:12 ppp and over 120 000 particles. As shown in Fig. 2, the KLPT-LCTI process reaches no more than 85 000 (i.e., 70%) final tracks if the process starts with any number below 30000 initialized tracks. However, starting with 60 000 initialized tracks leads to cover over 99% of final trajectories after 30 time steps at 0:12 ppp. The evidence from this study indicates that the number of initialized tracks is one deterministic contributor to the 4D-PTV convergence at high-density scenarios. Without a proper track initialization algorithm, a 4D-PTV scheme would not be able to recover the majority of tracks eventually.
VIDEO. 1. LPT challenge results of wall-bounded wake flow behind a cylinder. Tracking over 120000 particles using time-resolved particle tracking velocimetry (4D-PTV).