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A 3D stationary particle tracking velocimetry (SPTV) with a unique recursive corrective algorithm has been successfully established to detect the instantaneous regional fluid flow characteristics. The veracity of SPTV is corroborated by conducting actual displacement measurement validation, which gives a maximum percentage deviation of about 0.8%. This supports the accuracy of the current SPTV system in 3D position detection. More importantly, the SPTV detected velocity fluctuations are highly repeatable. In this study, SPTV is proven to be able to express the nature of chaotic fractal grid-induced regional turbulence, namely: the high turbulence intensity attributed to multilength-scale wake interactions, the Kolmogorov's -5/3 law decay, vortex shedding, and the Gaussian flow undulations immediately leeward of the grid followed by non-Gaussian behaviour further downstream. Moreover, by comparing the flow fields between control no-grid and fractal grid-generated turbulence of a plate-fin array, SPTV reveals vigorous turbulence intensity, smaller regional integral-length-scale, and energetic vortex shedding at higher frequency for the latter, particularly between fins. Thereupon, it allows the unravelling of detailed thermofluid interplays of plate-fin heat sink heat transfer augmentation. The novelty of SPTV lies in its simplicity, use of low-cost off-the-shelf components, and most remarkably, low computational complexity in detecting fundamental characteristics of turbulent fluid flow.
Hoi et al. (Fri,) studied this question.