When considering drop impact on a superhydrophobic surface, it has been shown that drop rebound can occur faster on surfaces with millimetric-micrometric scale features in respect to flat surfaces. Numerous studies, mostly experimental, have dealt with the role of surface patterns in reducing the contact time between the solid surface and the liquid drop. On the other hand, only limited numerical work has been done on this topic, especially in conjunction with the Volume of Fluid (VoF) method.

Since more than 20 years, the Institute of Aerospace Thermodynamics of the University of Stuttgart is developing its own, VoF-based program for the direct numerical simulation (DNS) of multi-phase flows: Free Surface 3D (FS3D). Since FS3D is based on a Cartesian grid, we are currently implementing a method to represent the interaction of multi-phase flows with solid bodies embedded in a Cartesian geometry. In particular, we represent the embedded boundaries with an additional volume of fluid variable and, in each cell intersected by the boundary, we approximate the boundary surface with a plane (PLIC-scheme). We also deal with critical cells by merging them with one of their neighbors by means of a cell-linking strategy. In this work, we validate the method by comparing simulations of drop impact onto superhydrophobic featured walls with data from literature [1]

We simulate the case investigated by Chantelot et al. [1] of a water drop impacting on a superhydrobhobic surface with a spherical singularity. As in [1], we firstly study the drop impact at the top of the spherical singularity at different Weber numbers and then we carry out a set of simulations in which the centres of the drop and the sphere are horizontally shifted. We present the numerical setup, the grid and the used computational resources for each of our simulations. Our results show a very good agreement for contact time and impact morphology, demonstrating the capability of FS3D in capturing the physics of the phenomenon.

[1] P. Chantelot, A. M. Moqaddam, A. Gauthier, S. S. Chikatamaria, C. Clanet, I. V. Karlin, D. Que´re´, Soft Matter, 2018, 14, 2227.