Abstract
Capillary evaporation has been valued as an effective mass transfer strategy and the equations associated with environmental and physical parameters can be used to guide the industrial application of capillary evaporation. A combined capillary evaporation experimental setup was constructed to determine the evaporation rates of 1,2-Propylene Glycol (PG)-Vegetable Glycerin (VG) binary mixtures in molar ratios of 1:9, 3:7, 5:5, and 7:3 at 170 ℃, 180 ℃, 190 ℃, 200 ℃ and 210 ℃ in capillary tubes with internal diameters of 0.3 mm, 0.5 mm, 0.6 mm and 0.7 mm, respectively. The results show that the Conjugate Evaporation Mass Transfer (CEMT) model which combined the environmental and physical parameters established in this study and its parameters for "training-test" method regression can predict the evaporation rates with an average error of less than 15% between the theoretical prediction and the experimental data. The total evaporation rate increases linearly with the increase of internal diameter, which is related to the increase of curved surface area and the increase of the ratio of saturated vapor pressure between the curved interface and plane. However, the evaporation rate per unit area decreases with the increase in pipe diameter. The evaporation temperature and the proportion of the light component are related to superheat and Marangoni convection, and the Ma number shows a positive correlation with the total evaporation rate. The method and results of this model provide method guidance and data reference for the investigation of capillary evaporation characteristics of binary mixtures.
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The data that support the findings of this study are available from the corresponding author upon reasonable request.
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The authors are grateful to the Major Science and Technology Project of China National Tobacco Group Corporation for the funding of this research: grant numbers 110202001009(XX-05).
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Li, J., Li, B., Gu, S. et al. A "training-test" method for predicting single capillary evaporation rates using a conjugate mass transfer model based on coefficient fitting. Heat Mass Transfer 59, 2057–2072 (2023). https://doi.org/10.1007/s00231-023-03378-4
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DOI: https://doi.org/10.1007/s00231-023-03378-4