International Symposium on Symbiotic Nuclear Power (ISSNP2024)

Bubble surface area plays a critical role in understanding multiphase flow dynamics in various engineering applications, including nuclear reactor coolant systems. One key parameter in the Two-Fluid model used for modelling two-phase flow, is the interfacial area concentration which has a relationship with bubble surface area. This study presents a computer vision methodology for calculating the surface area of bubbles from 2D images through a series of image processing and computational techniques. High-speed photography is utilized to capture sequential 2D images of bubbles in 2×2 rod bundle subchannel. Image preprocessing techniques, such as noise reduction, thresholding and edge detection, are applied to enhance image quality and facilitate accurate bubble detection. Detected bubbles in the 2D images are then used for 3D reconstruction employing an algorithm which assumes bubble rotational symmetry to generate 3D point cloud from 2D contours. Once the 3D shapes of the bubbles are reconstructed, surface extraction algorithms, are applied to generate surface meshes. The surface area of these meshes is then computed using computational geometry libraries. This comprehensive approach enables accurate surface area estimation, providing valuable insights into bubble dynamics within rod bundle subchannels, which is essential for the accurate prediction of the interfacial area concentration.