Spring model tracking algorithm for three-dimensional particle image velocimetry
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abstract
The cross correlation tracking technique is widely used to analyze image data, in Particle Image Velocimetry (PIV). The technique assumes that the fluid motion, within small regions of the flow field, is parallel over short time intervals. However, actual flow fields may have some distorted motion. If the distortion of the flow field is great enough the fluid motion can not be tracked well using the cross correlation technique. For example, in bubbly flow, the parallel motion of the fluid may not be assumed, since bubble motion may greatly disturb the flow field. A tracking algorithm should accept any fluid motion, such a rotation or shear. In this study, a new algorithm for particle tracking, called the Spring Model technique, is proposed. This algorithm can be applied to flow fields which exhibit characteristics such as rotation, shear and expansion. With three-dimensional measurements, the particle concentration in space might be low because of the limited resolution of the images. In this case, the Multiple Overlap technique is also proposed to track particles in this sparse particle data field. By combining the Spring Model technique and Multiple Overlap technique, the three-dimensional flow-field can be measured with a high degree of accuracy.
