流体体积法
泥浆
相变材料
计算流体力学
沸腾
材料科学
传热
潜热
机械
相变
热力学
沸腾传热
相(物质)
核沸腾
传热系数
复合材料
化学
物理
有机化学
分手
作者
Zhenyu Tan,Xunfeng Li,Junlin Chen,Keyong Cheng,Xiulan Huai
标识
DOI:10.1080/10407782.2023.2230352
摘要
Two-dimensional (2D) computational fluid dynamics (CFD) simulations of water-based microencapsulated phase change material suspension (MPCMS) on the flow boiling in a gas–liquid–solid flow system was performed with volume of fluid (VOF) method and discrete particle model (DPM). The Lagrangian particles were linked to the Eulerian phases through the interchange terms such as the drag force in the respective momentum equations. Influences of particle properties including mass fraction and core phase transition temperature, fluid properties including liquid surface tension force and viscosity, detachment time and rise velocity of gas bubbles and particle entrainment in the gas–liquid–solid flow under ambient conditions were numerically investigated. The effects of particles on bubble nucleation, growth and rupture during boiling were studied by visualization. The results show that MPCM can enhance the boiling heat transfer ability of the base liquid. The maximum heat transfer enhancement rate of MPCMS (28 °C) is 4.8%, the maximum heat transfer enhancement rate of MPCMS (90 °C) is 5.1%, the maximum heat transfer enhancement rate of MPCMS (110 °C) can reach 6.7%. MPCM can promote the formation of new bubbles and the rupture of large bubbles, reduce the departure diameter of bubbles, and enhance the boiling heat transfer capacity of the base liquid. The MPCM with core phase change temperature higher than the boiling temperature of base fluid has the best enhancement effect. Through the combination of numerical simulation methods such as VOF and DPM, the complex phase transition heat transfer process of gas-liquid-solid particle coupling of latent thermal functional thermal fluid can be accurately simulated. The work lays a foundation for further explorations on the gas–liquid–solid flows and possible industry applications.
科研通智能强力驱动
Strongly Powered by AbleSci AI