Investigation of dropwise condensation of water through an efficient individual-based model

In recent years, researchers have directed their studies towards solutions aimed at enhancing heat exchangers effectiveness. In this context, dropwise condensation (DWC) has been identified among the most promising solutions to increase the condensation heat transfer coefficient (HTC). In fact, DWC provides heat transfer coefficients up to ten times higher than those achievable during filmwise condensation (FWC), resulting in both economic and energy benefits. The DWC phenomenon is usually modelled by combining the heat exchanged through a single droplet and the drop-size distribution. The latter can be divided into a distribution of large droplets N(r), determinable analytically by semi-empirical models, and a distribution of small droplets n(r), typically determined through statistical approaches called population-based models. Another possibility for the determination of the droplet-size density is to simulate the DWC process by an individual-based model (IBM). In this case, each drop is tracked throughout its entire life cycle (nucleation, growth, coalescence, sliding), and the drop-size distribution is obtained as a result. In this paper, a new IBM for the simulation of DWC of steam is proposed. The developed model allows for the simulation of more than 10 million droplets while keeping an acceptable simulation time thanks to the implementation of parallel computing. The predictions obtained from the model, in terms of drop-size distribution and condensation heat flux, are compared against both PBM results and experimental data.