Condensation is a physical process that occurs when a vapor is cooled and/or compressed to its saturation limit. Condensation becomes important in a variety of engineering applications such as in heat exchangers used for distillation purposes. In such instances, higher condensation efficiencies are desirable. Research to improve condensation has focused on dropwise condensation as it has been shown that it can be significantly more efficient than filmwise condensation. Recent investigations of dropwise condensation on nanostructured surfaces suggest that enhanced dropwise condensation can be attained as the average droplet sizes are reduced for clusters growing through dropwise condensation. This, in turn, significantly enhances the heat transfer coefficients of dropwise condensation. This paper summarizes a computational model developed to explore the mechanisms leading to this enhanced dropwise condensation. A Direct Simulation Monte Carlo (DSMC) approach is used here to investigate the mechanisms and limitations of enhanced dropwise condensation for these surfaces aiming to reduce the average droplet sizes of condensation. For computational purposes, several idealizations are assumed by the model, which include: (1) The condensation droplet clusters are assumed to have uniform size, corresponding to an average droplet size observed in actual dropwise condensation scenarios; (2) Due to the assumed uniform droplet distribution, symmetry can be observed from the droplet cluster, so a small but symmetrical cross section of the droplet distribution is used for the computational domain; and (3) Supersaturated steam condensing on a cold wall is assumed for most of the simulations. The mechanisms at play that are deliberately explored are: (1) The effects of surface wettability by using a model that considers droplet conduction variations with varying contact angle; (2) The changes of interfacial resistance with droplet curvature by introducing a surface tension model based on the Tolman length; and (3) The dynamic interactions between neighboring droplets by choosing our computational domain to be a symmetrical cross section that encompasses surrounding droplets in an appropriate fashion. The ambient conditions that were investigated were: (1) Varying atmospheric pressure; (2) Varying amounts of wall subcooling for the droplets; (3) Varying accommodation for water molecules condensing on the droplet; and (4) The introduction of air into the assumed supersaturated steam condensing on the cold wall. To investigate the overall and combined effects of the aforementioned mechanisms on enhanced dropwise condensation through reduced droplet sizes, the simulations were run for droplets with radii between 1 micrometer down to 5 nanometers. The model predictions indicate that the larger droplet transport trend of increasing heat transfer with decreasing droplet sizes breaks down as droplet sizes become smaller due to more prominence of the mechanisms hindering condensation for the reduced droplet sizes. As the model breaks down, a peak heat transfer is reached, and heat transfer is further reduced as the average droplet sizes continue to decrease. The predictions of this particular DSMC model are compared to previous work investigating similar effects. The implications of our observations and potential impact to current and future research in the area is discussed in detail.

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