OpenFOAM for optimization of aerodynamics design and fog harvesting technology.

Condensation occurs when the air temperature drops to its dew point, causing water vapors in the air to cool, lose kinetic energy, and transform into liquid droplets. This process is influenced by the relative humidity and temperature fluctuations, where lower temperatures reduce the air's capacity to hold water vapor, resulting in the formation of liquid water droplets on cooler surfaces. The condensation process is fundamental to the operation of fog harvesting systems, where specialized meshes capture the transformed water droplets. However, the behavior of droplets attached to meshes under background airflow is not well understood. Consequently, controlling the motion and merging of these droplets with neighboring ones poses a significant challenge. In this study, for fog airflow, it is demonstrated that droplets on parallel meshes can aerodynamically interact with both downstream and upstream neighbors at different temperatures. These interactions lead to diverse behaviors, including alignment, coalescence, and repulsion. This study explores the key factors influencing the efficiency of material and design used for fog harvesting systems, and environmental conditions such as fog density and wind speed. The dynamical model includes the single-phase transport equation along with the k − Ω SST (Shear Stress Transport (SST) k-omega) a subclass of RAS (Reynolds-Averaged Simulation) model. The computational analysis of fog harvesting mesh for water collection is performed in OpenFOAM (Open-source Field Operation And Manipulation). The Finite Volume Method (FVM) is employed for solution of the model to check the efficiency and effectiveness of fog harvesting computational designs. Using OpenFOAM, condensation, alignment and merging behaviors based on the interactions between wakes and droplets are visualized. The computational design enhances the surface area available for fog capture, thereby increasing the droplets collection efficiency and resulting in a higher yield of liquid water. The computational results obtained in this study can lead to more sustainable and efficient fog water collectors. [ABSTRACT FROM AUTHOR]