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CFD modelling of most probable bubble nucleation rate from binary mixture with estimation of components� mole fraction in critical cluster

Hong, B.Z. and Keong, L.K. and Shariff, A.M. (2016) CFD modelling of most probable bubble nucleation rate from binary mixture with estimation of components� mole fraction in critical cluster. Continuum Mechanics and Thermodynamics, 28 (3). pp. 655-668.

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Abstract

The employment of different mathematical models to address specifically for the bubble nucleation rates of water vapour and dissolved air molecules is essential as the physics for them to form bubble nuclei is different. The available methods to calculate bubble nucleation rate in binary mixture such as density functional theory are complicated to be coupled along with computational fluid dynamics (CFD) approach. In addition, effect of dissolved gas concentration was neglected in most study for the prediction of bubble nucleation rates. The most probable bubble nucleation rate for the water vapour and dissolved air mixture in a 2D quasi-stable flow across a cavitating nozzle in current work was estimated via the statistical mean of all possible bubble nucleation rates of the mixture (different mole fractions of water vapour and dissolved air) and the corresponding number of molecules in critical cluster. Theoretically, the bubble nucleation rate is greatly dependent on components� mole fraction in a critical cluster. Hence, the dissolved gas concentration effect was included in current work. Besides, the possible bubble nucleation rates were predicted based on the calculated number of molecules required to form a critical cluster. The estimation of components� mole fraction in critical cluster for water vapour and dissolved air mixture was obtained by coupling the enhanced classical nucleation theory and CFD approach. In addition, the distribution of bubble nuclei of water vapour and dissolved air mixture could be predicted via the utilisation of population balance model. © 2014, Springer-Verlag Berlin Heidelberg.

Item Type:Article
Impact Factor:cited By 7
Uncontrolled Keywords:Binary mixtures; Computation theory; Computational fluid dynamics; Density functional theory; Dissolution; Estimation; Mixtures; Molecules; Water vapor, Bubble nucleation; Bubble nuclei; Classical nucleation theory; Critical cluster; Dissolved gas concentrations; Mole fraction; Population balance modeling; Statistical mean, Nucleation
ID Code:25607
Deposited By: Ms Sharifah Fahimah Saiyed Yeop
Deposited On:27 Aug 2021 09:59
Last Modified:27 Aug 2021 09:59

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