Effect of U-bend on void fraction in subcooled boiling flow. (April 2023) - Pan, Yue; Zhai, Yuling; Li, Zhouhang
Abstract: U-bend is very common in heat exchangers to facilitate the pipe arrangement, whereas studies on boiling heat transfer in such a bend pipe flow are quite scare, hindering the accurate design of this heat exchanger type. This work studied subcooled boiling flow in U-bend pipes with emphasis on the point of net vapor generation (PNVG) and the void fraction distribution. A Eulerian−Eulerian two fluid numerical scheme was established and Rensselaer Polytechnic Institute wall boiling model was incorporated. After verifying the model by experimental data, numerical runs were conducted at 10.81 MPa, mass flux of 100–3000 kg/m 2 s, and heat flux of 100–3000 kW/m 2 . Results show that net vapor generation was postponed when PNVG located outside of bend section, while close to that of straight tube when it is within the bend. Compared with straight pipe, void fraction in U-bend pipe was initially smaller and eventually larger. This transition occurred at different axial positions as the location or curvature of U-bend varied. The delayed PNVG leading to reduction of void fraction. After PNVG, turbulent kinetic energy induced by secondary flow accelerated bubble departure from the wall thus yielded larger void fraction. A modified Saha-Zuber model was proposed by properly considering the bend influence on PNVG and distribution parameter. The modified model is competent to the prediction of void fraction distribution, and can serve the thermal-hydraulic design of heat exchanger involving U-bend. Highlights: Studied effect of U-bend on point of net vapor generation (PNVG) and void fraction distribution. Bend enhances partially developed subcooled boiling heat transfer while delays PNVG. Decrease in wall temperature is the major contribution to the delay of PNVG. Void fraction in U-bend pipe was initially smaller and eventually larger than straight pipe. Void fraction model performs better with modified PNVG and distribution parameter.