Computational and Statistical Fitting of Particle Tracking Simulation on Oseen Vortex

Abstract

Visualization methods of fluid data are crucial for studying flows and turbulence, and one of the most common methods of simulation is particle tracking velocimetry (PTV). In this project, the visualization of flow is studied using PTV simulation of an Oseen vortex. For statistically fitting the fluid data, two main methods were used: regressive fitting and spline fitting. Final fits of data were done using Kriging, which is a sophisticated regression method, and thin plate spline fitting. Then, comparisons of the two methods were drawn using statistical methods. Kriging yielded lower mean squared error overall, but thin plate spline fitting method takes smoothness of fit into account.