Maqola

Hybrid Response Surface–Genetic Algorithm Optimization of Passive Subsurface Cooling for High-Yield Atmospheric Water Harvesting: Parametric Tuning and Energy Analysis under Hot–Humid Conditions

Lotfi Ben SaidDepartment of Mechanical Engineering, College of Engineering, University of Ha’il, Ha’il City 81451, Saudi ArabiaPooya GhodratallahDepartment of Civil Engineering, College of Engineering, Cihan University-Erbil, Erbil, IraqBasem Abu ZneidFaculty of Technical Education, Hourani Center for Applied Scientific Research (HCASR), Al-Ahliyya Amman University, Amman, JordanMehraj‐ud‐din NaikDepartment of Chemical Engineering, College of Engineering and Computer Science, Jazan University, Jazan, Saudi ArabiaSaif AlshammariDepartment of Mechanical Engineering, College of Engineering, Jouf University, Sakakah, 72388, Saudi ArabiaAbdellatif M. SadeqFaculty of Agricultural Mechanization, TIIAME National Research University, Kori Niyoziy 39, Tashkent, 100000, UzbekistanNarinderjit Singh Sawaran SinghFaculty of Data Science and Information Technology, INTI International University, Persiaran Perdana BBN, Putra Nilai, Nilai 71800, MalaysiaHusam RajabCollege of Engineering, Department of Mechanical Engineering, Najran University, King Abdulaziz Road, P.O Box 1988, Najran, Saudi ArabiaMohamed ShabanPhysics Department, Faculty of Science, Islamic University of Madinah, P. O. Box: 170, Madinah, 42351, Saudi ArabiaWalid AichDepartment of Mechanical Engineering, College of Engineering, University of Ha’il, Ha’il City 81451, Saudi Arabia

2026en

Ochiq kirishOltin

Litsenziya: cc-by

Manbada oʻqishdoi.org(yangi oynada ochiladi)

ABI

Annotatsiya

This study presents the development, experimental validation, and multi-objective optimization of a novel solar-assisted atmospheric water harvesting system (AWHS) that employs passive subsurface cooling via buried rectangular stainless steel coils as a sustainable alternative to conventional vapor compression cycle (VCC) systems. Powered autonomously by a 40 W photovoltaic panel, the system exploits the natural thermal gradient of the earth to condense atmospheric moisture without compressors or chemical refrigerants. Comprehensive parametric optimization was conducted using Response Surface Methodology (RSM) with a Central Composite Design (CCD) to model the interactive effects of five critical parameters burial depth (1–4 m), coil length (2–8 m), number of coils (2–8), coil perimeter (200–800 mm), and inlet air velocity (0.5–4.0 m/s) on daily water yield. A Genetic Algorithm (GA) with a population of 100 individuals over 200 generations was then applied for global optimization. The system achieves exceptional energy performance, with an average coefficient of performance (COP) of 14.12 surpassing VCC systems by 9–18 times a moisture harvesting index (MHI) of 0.364, and a minimum unit power consumption (UPC) of only 0.00248 kWh/L, approaching the thermodynamic minimum for water vapor condensation. GA convergence analysis revealed that burial depth contributes 31.8% to total yield, followed by air velocity (29.2%), number of coils (15.4%), coil length (12.8%), and coil perimeter (10.8%), while the Pareto-optimal front identified a trade-off between maximum yield and minimum energy consumption. This sustainable, off-grid solution demonstrates that passive underground cooling particularly in hot and humid coastal desert climates such as Jeddah, Saudi Arabia offers a transformative, energy-efficient alternative to active refrigeration, delivering decentralized potable water without grid dependency or environmental hazards. The hybrid RSM–GA optimization framework proves highly effective for designing scalable AWHS systems, with the optimized configuration achieving 70–133 times lower energy consumption than conventional VCC systems.

Hali tarjima qilinmagan

Identifikatorlar

DOI: 10.1016/j.rineng.2026.114157

Iqtiboslar va manbalar

0 ta iqtibos51 ta foydalanilgan manba