A Lagrangian particle method to simulate supercooled large droplet impact and freezing on curved hydrophilic/hydrophobic surfaces

The supercooled large droplet (SLD) impact and freezing characteristics are significant for the numerical prediction of ice shapes in deicing industry. However, simulating these processes remains challenging due to the complex and random splashing and coalescence behaviors of the secondary droplets, which are difficult to capture using Eulerian mesh-based methods. Leveraging the inherent advantage in capturing intense development of the free liquid surface of the moving particle semi-implicit (MPS) method, a typical Lagrangian particle method, an MPS-based algorithm for SLD impact and freezing is developed in this paper. A surface tension model for droplet dynamics simulation and a phase change model for water-to-ice transfer are incorporated into this algorithm. Additionally, a novel freezing model is proposed to stably and accurately represent the freezing process. To validate the accuracy of the MPS-based algorithm, two cases are studied: the freezing of a sessile droplet on a horizontal cold plate and the freezing of a falling droplet on an inclined cold plate. The numerical results show good agreement with experimental data. Utilizing the validated algorithm, the effects of the wettability, supercooled temperature, and Weber number on the SLD impact and freezing characteristics on curved hydrophilic/hydrophobic surfaces are investigated.