Direct experimental measurement for partitioning of wall heat flux during subcooled flow boiling: Effect of bubble areas of influence factor. (December 2018)

• Record Type: Journal Article
• Authors: Amidu, Muritala Alade; Jung, Satbyoul; Kim, Hyungdae
• Is Part Of: International journal of heat and mass transfer. Volume 127(2018)Part B
• Page Start: 515
• Page End: 533
• Publication Date: 2018-12
• Subjects: Bubble area of influence -- Infrared thermometry -- Subcooled flow boiling -- Total reflection -- Wall heat flux partitioning; Heat -- Transmission -- Periodicals; Mass transfer -- Periodicals; Chaleur -- Transmission -- Périodiques; Transfert de masse -- Périodiques; Electronic journals; 621.4022
• DOI: 10.1016/j.ijheatmasstransfer.2018.07.079
• Languages: English
• ISSNs: 0017-9310

Abstract

Highlights: Direct experimental measurement of wall heat flux partitioning was performed. Bubble area of influence factor significantly affected the wall heat flux partitioning. Optimum value of bubble area of influence factor was found to be 0.5. Correction for overlapping area of influence of merging bubbles was proposed. Abstract: Heat transfer models in liquid-vapor two-phase flow with wall boiling rely on the wall heat flux partitioning to quantify heat transfer to liquid and vapor separately. Several wall heat flux partitioning models have been proposed over the years based on variety of heat transfer mechanisms, but the three basic mechanisms that form the core of these models are liquid convection, surface quenching and evaporation heat transfer. A key parameter commonly used to determine the relative contribution made by each mechanism is area fraction of influence of bubble which is determined by multiplying maximum bubble projected area fraction with bubble area of influence factor (K). In classic wall heat flux partitioning models, K accounts for the area within which heat is transferred to liquid that moves in towards the heated wall as bubbles lift-off. The value of K has been a subject of controversy over the years with no unanimous conclusion among researchers. Therefore, in this paper, advanced diagnostic approach involving the combination of infrared thermometry and total reflection principle was employed to experimentally study nucleate flow boiling. Rigorous data analyses was performed to partition the wall heat flux into the aforementioned three basic heat transfer mechanisms using different values of K. All three heat transfer mechanisms were significantly sensitive to varying values of K, but setting K = 0.5 with percentage uncertainties of −60%/+50% closely predicted the experimental measurements. In addition, overlapping area of influence due to merging bubbles was observed to be significant in the model at high heat flux condition and must be discounted to get the true bubble area of influence. A correction method for the overlapping area of influence was therefore proposed to enhance accuracy of the predictive model.