Water scarcity remains a pressing global issue, particularly in arid and coastal regions, necessitating the development of energy-efficient and sustainable desalination technologies. This study presents a novel humidification-dehumidification desalination system enhanced by the M-Cycle, which utilizes ambient thermal energy to minimize power consumption and eliminate reliance on fossil fuels. A coupled computational approach involving CFD simulations and PSO was employed to model and optimize system performance. The CFD analysis captured detailed temperature and humidity distributions across the heat and mass exchanger, while the PSO algorithm optimized three key parameters: air velocity, heat exchanger width, and dry air split ratio. Notably, the optimized configuration-an airflow velocity of 6.89 m/s, a device width of 0.63 m, and a 35.97% dry air split-resulted in a freshwater production rate of 3.04 kg per kWh of electricity consumed, 360.5 L per day, and an outlet relative humidity of 99%, with total power consumption of 4.94 kW. Compared to previous M-Cycle-based desalination systems, the proposed configuration demonstrates over a threefold improvement in energy efficiency, as measured by the GOR, highlighting its superior thermodynamic performance. Additionally, the study uniquely resolved the spatial distribution of relative humidity and evaporation rates, without relying on simplifications such as assuming saturated air at the outlet. The results confirm the potential of the proposed M-Cycle HDH system as a highly efficient, scalable, and eco-friendly desalination technology suitable for decentralized and off-grid applications.
Keywords: Computational fluid dynamics (CFD); Humidification-dehumidification (HDH); M-cycle; Optimization; Particle Swarm Optimization (PSO); Water desalination.
© 2025. The Author(s).