Numerical Study of the Coalescence-Induced Droplet Jumping with Macrotexture Based on Single-Phase Model

The low energy conversion efficiency in coalescence-induced droplet jumping limits its potential for various applications, such as self-cleaning, anti-icing, and energy harvesting. Fortunately, it has been proven that this efficiency can be significantly increased through a sophisticated macrotexture design. In this study, we propose a single-phase model with a moving mesh to simulate the self-jumping process under a ridge. The effect of the ridge is realized by adopting a pointwise constraint on several surface nodes. This effective model is validated by experimental results of droplet velocity. In comparison with volume-of-fluid, a single-phase flow method enhances computational efficiency by at least 33.3%. The kinematics and dynamics of the self-jumping process have been investigated with respect to the influences of ridge height and Ohnesorge number. With the help of the radial distributions of velocity and internal pressure, the self-propelled process can be divided into coalescence-induced and lobe-induced stages. The high ridge brings more symmetry-breaking, accelerating the droplet in the coalescence-induced stage. In the lobe-induced stage, the slingshot effect is weakened under high Ohnesorge number due to the prolate shape caused by viscous dissipation. Moreover, the study's findings demonstrate promising application prospects for other ridge shapes, thereby expanding the potential practical applications of this research.