Fluid flow pattern analysis in a trough region: a nonparametric approach

This paper aims at identifying statistically different circulation patterns characterising fluid flow in the trough region between two adjacent asymmetric waveforms, using the velocity data collected by 3D acoustic Doppler velocimeter. Statistical clustering has been performed using ideas originating from information theory and scale space theory in computer vision for splitting the trough region into different spatially connected segments (identifying the circulation bubble in the process) on the basis of circulation patterns. The paper attempts to visualise the fluid fluctuations in the trough region, with emphasis on the circulation region, by simulating the directional fluctuations of fluid particles from the kernel density estimates learned from the experimental data. The image representation of the estimate of the spatial turbulent kinetic energy (TKE) function reveals interesting features corresponding to the regions of high TKE, suggesting the possibilities for further research in this area along the lines of feature extraction and image analysis.