Fog harvesting is a novel way of reducing water scarcity, especially in arid areas with limited access to conventional water sources. This article describes a computational study that models and optimizes a fog harvester's performance using OpenFOAM. A mesh netting system is incorporated into the design of the fog harvester to collect suspended water droplets from the fog-filled air. With consideration for variables including mesh geometry, airflow velocity, and droplet coalescence, the computer models the airflow and droplet dynamics inside the harvester. OpenFOAM is used to simulate the droplet trajectories and airflow patterns of the fog harvester that exist between the fog droplets and the mesh structure. This enables the optimization of mesh settings to maximize the effectiveness of water capture while reducing airflow resistance. The performance of the fog harvester is then further improved by examining design changes and operating tactics using the validated model. Graphical results illustrating velocity and pressure profiles are presented, offering a visual representation of the fluid flow behavior.
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Muhammad et al. (2026) studied this question.
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