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When binary liquid mixtures are cooled rapidly from a homogeneous phase into a two-phase system, domains of the two equilibrium phases form and grow (coarsen) with time. In the absence of an external forcing due to gravity or an imposed shear flow, a dynamic scaling regime emerges in which the domain morphology is statistically self-similar at different times with a length-scale that grows with time. In the presence of gravity, however, multiple length scales develop, with the system coarsening more rapidly in the direction of the force. The late-time behavior of such a system is characterized in this study by the calculation of anisotropic growth laws. Gravitation effects significantly affect scaling laws, even with small density mismatch, and the growth mechanism has some similarities to the sedimentation process. However, very few numerical studies have been made of such effects; this is one of the first.

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Component-scale modeling of boiling is predominantly based on the Eulerian–Eulerian two-fluid approach. Within this framework, wall boiling is accounted for via the Rensselaer Polytechnic Institute (RPI) model and, within this model, the bubble is characterized using three main parameters: departure diameter (D), nucleation site density (N), and departure frequency (f). Typically, the magnitudes of these three parameters are obtained from empirical correlations. However, in recent years, efforts have been directed toward mechanistic modeling of the boiling process. Of the three parameters mentioned above, the departure diameter (D) is least affected by the intrinsic uncertainties of the nucleate boiling process. This feature, along with its prominence within the RPI boiling model, has made it the primary candidate for mechanistic modeling ventures. Mechanistic modeling of D is mostly carried out through solving of force balance equations on the bubble. Forces incorporated in these equations are formulated as functions of the radius of the bubble and have been developed for, and applied to, low-pressure conditions only. Conversely, for high-pressure conditions, no mechanistic information is available regarding the growth rates of bubbles and the forces acting on them. In this study, we use direct numerical simulation coupled with an interface tracking method to simulate bubble growth under high (up to 45 bar) pressure, to obtain the kind of mechanistic information required for an RPI-type approach. In this study, we compare the resulting bubble growth rate curves with predictions made with existing experimental data

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