Assessment of predictive methods for the heat transfer coefficient during flow boiling of R50 and R170 mixtures. Issue 1 (1st April 2022)

• Record Type: Journal Article
• Authors: Ferretto, William; Lucchini, Andrea; Colombo, Luigi P.M.
• Is Part Of: Journal of physics. Volume 2177:Issue 1(2022)
• Publication Date: 2022-04-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2177/1/012042
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Liquefied natural gas (LNG) is a binary mixture of methane (R50) and ethane (R170). Proper evaluation of the heat transfer coefficient during flow boiling of such a mixture is very important to design LNG facilities. Pure fluid correlations have been tested with and without the adoption of corrections to account for the lowered performance due to mass transfer resistances arising both in the nucleate boiling and in the convective boiling regimes. In total, the prediction of 13 correlations has been compared with a new data set from the literature. Results show that the correction related to nucleate boiling has the greatest impact though, in general, the adoption of the corrections leads to under predict the data.