Experimental investigation for heat and mass transfer characteristics of R124-DMAC bubble absorption in a vertical tubular absorber. (May 2017)

• Record Type: Journal Article
• Authors: Jiang, Mengnan; Xu, Shiming; Wu, Xi
• Is Part Of: International journal of heat and mass transfer. Volume 108:Part B(2017)
• Page Start: 2198
• Page End: 2210
• Publication Date: 2017-05
• Subjects: R124-DMAC mixture -- Vertical tube -- Bubble absorption -- Heat transfer -- Mass transfer; Heat -- Transmission -- Periodicals; Mass transfer -- Periodicals; Chaleur -- Transmission -- Périodiques; Transfert de masse -- Périodiques; Electronic journals; 621.4022
• DOI: 10.1016/j.ijheatmasstransfer.2017.01.082
• Languages: English
• ISSNs: 0017-9310

Abstract

Highlights: The bubble absorption experiment in a vertical tube for R124-DMAC was done. The factors influencing on heat and mass transfer characteristics were discussed. Correlations of Nusselt number for heat transfer coefficient were proposed. A correlation of Sherwood number for mass transfer coefficient was proposed. Abstract: Experimental investigation for a copper vertical tubular bubble absorber was done with R124 (2-chloro-l, l, l, 2, -tetrafluoroethane)-DMAC (N′, N′-dimethylacetamide) as working fluid. The objective of the investigation was to explore key parameters affecting heat and mass transfer characteristics of the bubble absorber and propose new correlations for heat and mass transfer coefficients respectively for the R124-DMAC bubble absorption. The parameters include vapor and solution flow rates, solution inlet temperatures and mass fractions, nozzle orifice diameters and cooling water inlet temperatures. The results showed that to reduce the solution, cooling water inlet temperature and nozzle orifice diameter or to increase vapor and solution flow rate could enhance the heat and mass transfer performance of the absorber. Finally, correlations of Nusselt number and Sherwood number for calculating heat and mass transfer coefficients were proposed, respectively. Both correlations could predict about 90% of the experimental values at a margin of error less than 20%.