Numerical Simulation and Analysis of Harvesting Atmospheric Water Using Porous Materials

Abstract

The UN reported that in 2020, 26% of people lack safely managed to drink water. Although water covers more than 70% of the Earth's surface, 97.5% of the water on Earth is saltwater. The scientific community explores three main techniques: groundwater extraction, desalination of saltwater, and rainwater collection to resolve water scarcity. All these techniques require the availability of liquid water; however, in areas with a lack of liquid water, such as in Saudi Arabia, harvesting water from the atmosphere could be a viable option for supplying freshwater as water is abundant in the humid air. This study aims to build a robust mathematical model describing the water moisture absorption to simulate and analyze harvesting atmospheric water (HAW) using porous materials. Furthermore, a rigorous mathematical model was developed to describe the dehydration of absorbed moisture from porous materials. The mathematical model consists of a set of governing partial differential equations, including mass conservation equation, momentum equation (Darcy’s law), heat (energy) equation, associated parameterizations, and initial/boundary conditions. Moreover, the model represents a two-phase fluid flow that contains phase-change gas-liquid physics. The mathematical model has been solved numerically. In the simulated model, different times, thicknesses, and other critical parameters are considered. A dataset has been collected from the literature containing 11 porous materials that have been experimentally used in water generation from the air. A group of empirical models to relate the relative humidity and water content have been suggested and combined with the governing to close the mathematical system. Furthermore, a comparison with experimental findings was made to demonstrate the validity of the simulation model, and the relative error was calculated. The results show that the proposed mathematical model well predicts water content during the absorption and dehydration process. Also, the simulation results show that; during the absorption process, when the depth is smaller, the water content reaches a higher saturation point quickly and at a lower time i.e., quick process. However, during the dehydration process, a lower thickness reaches a higher heat faster, as heat increases, the water content decreases; thus, it has an opposite relationship, and water content decreases over time. Finally, the highest average error of the HAW model is around 4.43% compared to experimental data observed in MnO2-2. Thus, the HAW model is applicable.