Experimental and theoretical study of vapor/air mixture condensation inside an inclined blind-end pipe in natural convection with considering fog formation. (March 2022)

• Record Type: Journal Article
• Authors: Tan, Bing; Cai, Jiejin; Zhao, Jiyun; Hibiki, Takashi; Tian, W.X.; Wu, Y.W.
• Is Part Of: International journal of heat and mass transfer. Volume 184(2022)
• Publication Date: 2022-03
• Subjects: Modeling -- Fog formation -- Suction effect -- Condensation -- Heat and mass transfer; Heat -- Transmission -- Periodicals; Mass transfer -- Periodicals; Chaleur -- Transmission -- Périodiques; Transfert de masse -- Périodiques; Electronic journals; 621.4022
• DOI: 10.1016/j.ijheatmasstransfer.2021.122375
• Languages: English
• ISSNs: 0017-9310

Abstract

Highlight: An empirical correlation was proposed with a broad range of dimensionless mass numbers. Air/vapor condensation in an inclined blind-end pipe was experimental studied. The fog formation phenomenon was observed and fog effect was added to the diffusion layer model Abstract: This study investigated the vapor condensation characteristics in an inclined pipe under natural convection conditions experimentally and numerically. The inclined blind-end concentric pipe had an inner diameter of 134 mm and a length of 680 mm, which is cooled by cooling water. The experimental pressure range was 0.2–0.6 MPa, and the dimensionless mass number range was 0.44 to 202. The fog formation phenomenon was observed in the experiment. An empirical correlation with a broad range of dimensionless mass numbers was developed based on the experimental results to predict the heat transfer coefficient (HTC). When the air mass fraction was large and the HTC was low, the effect of fog formation on the HTC had to be considered. In the numerical simulation, this study aimed to develop an HTC prediction model with broader applicability. Based on the diffusion boundary layer theory, this study improved Peterson's model by adding fog effect and wave effect. The model showed high adaptability to this experiment and other experiments in the natural convection condensation database. The improved model performed significantly better, with 96% of the data falling within an error zone of 30%. The wide range of dimensionless mass number test data might complement the natural convection condensation experimental database.