Abstract

Computational modeling is essential for understanding dropwise condensation (DWC) mechanisms, droplet life-cycle, and predicting heat transfer. However, the multiscale nature of DWC increases the computational cost, thus making the study of the droplet distribution more difficult. Population-based models available in the literature rely on empirical or statistical methods for determining the drop-size distribution. Differently, in the present study, a new individual-based model developed in hybrid MATLAB® and C codes and based on parallel computing is developed to simulate the whole dropwise condensation process, addressing the growth of each droplet, without making any assumption on the droplet population and considering a number of drops never reached in previous similar studies. The proposed model's computational efficiency is significantly improved when considering more than 1 million drops in the computational domain. To optimize the calculation time, the effects of time step, computational domain size, and simulation duration on the overall heat flux and drop-size distribution are discussed. The numerical results are compared against predictions from population-based models available in the literature. The proposed model is also used to study the droplet population and the instantaneous heat flux during DWC at different positions along a vertical condensing surface (upper, middle and lower areas). As a final step, a preliminary comparison is carried out between the present model and experimental data acquired during dropwise condensation on a nearly hydrophobic vertical surface. Considering a nucleation size density of 5 × 1012 m−2 (11 × 106 drops in the computational domain), the simulation is able to predict the experimental heat flux and the large drop-size distribution.

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