UC Riverside

Flow visualization is one of the main methods of understanding flow behavior in experimental fluid mechanics. Most of the visualization methods provides a good qualitative information about the flow behavior. With The developments in Computer sciences especially in fields of artificial Intelligence and computer vision, Image processing has been used as an important tool in experimental fluid mechanics to quantify the qualitative data obtained by flow visualization. One of the common use of computer vision is in “Particle Image Velocimetry”. PIV uses block matching algorithm to detect motion of the fluid between two frames by calculation the displacement of small particles. PIV has many downsides and is not applicable in many fluid mechanic studies such as two phase flow. Because of the downsides of PIV it is better to use other visualization technics and more advanced image processing algorithms. Therefore, Optical flow measurement is used for the advance image processing algorithm which provides flow properties in more variety of applications. Having these algorithms developed, it was used to study bubble behavior in a turbulent flow. Using the optical flow and edge detection algorithms, perimeter velocity of the bubble, and geometric properties of the bubble was obtained in various frames. It was found that the turbulent intensity of the bubble’s perimeter velocity will reach to a common value when the bubble breaks and reaches its smallest possible size.