|Budget Amount *help
¥2,000,000 (Direct Cost : ¥2,000,000)
Fiscal Year 1995 : ¥800,000 (Direct Cost : ¥800,000)
Fiscal Year 1994 : ¥1,200,000 (Direct Cost : ¥1,200,000)
|Keywords||Free surface / Turbulence / Computer Vision / Particle Image Velocimetry / Surface-Flow Interaction / Wavy free surface / Laser / Pattern tracking / Free surface, / Turbulence, / Computer Vision, / Particle Image Velocimetry, / Surface-Flow Interaction, / Wavy free surface, / Laser, / Pattern tracking.|
The sodium coolant in a reactor vessel of a liquid metal fast breeder reactor (LMFBR) has a free surface. The interaction between the free surface and the circulating flow under the free surface may cause undesirable surface phenomena. The turbulent boundary condition on the wavy free surface is very important in order to evaluate the free surface phenomena. However, no models for the surface turbulent boundary conditions in the wavy conditions were proposed, because of the higher non-linearity of the free surface. In order to investigate the interaction between the flow and the free surface, a new technique had been developed and the interaction were experimentally investigated.
A new algorithm for particle tracking, called the Spring Model technique, has been developed. The algorithm can be applied to flow fields which exhibit characteristics such as rotation, shear and expansion. The algorithm is based on pattern matching of particle clusters between the first and second image. The e
ffectiveness of the Spring Model technique was verified with synthetic data from both a two-dimensional flow and three-dimensional flow. It showed a high degree of accuracy, even for the three-dimensional calculation.
The interaction between the flow and free surface was evaluated measuring the velocity distribution and surface movement simultaneously. The jet interacted with the free surface, causing the wavy free surface condition. The flow under the free surface was visualized by a laser light sheet and small tracer particles. With image processing techniques, i.e., computer vision, the movement of the free surface and the movement of the particles were simultaneously measured from the recorded images, resulting in the velocity distributions and surface locations. Then, the interactions between the flow and free surface were evaluated using the form of turbulent energy and surface-related turbulent values. By increasing the turbulent energy near the free surface, the fluctuations of the free surface height and the inclination of the free were increased. The higher fluctuation of horizontal velocity was related to the higher surface position and negative inclination. Less