A multi-objective optimization framework for designing a double-skin façade in hot-arid climate: Central composite design and CFD simulation
Marzieh Fallahpour, Iman Mousavi Khorshidi, Farzad Ghasempour, Danial Davani Davari, Emad Tavasoli Khoei, Mahdi Tamimi
Abstract
• A 3D quasi-steady computational fluid dynamics (CFD) model was used to assess the impact of the proposed DSF's geometric parameter on interior temperature and airflow. • The interaction effects of DSF's geometry parameter were investigated. • Optimal double-skin façade parameters were derived by a multi-objective optimization method. • Air velocity and air mass-flow rate are affected mainly by room and DSF air outlet height. • Interior glazing and DSF air outlet heights are the most sensitive parameters for indoor temperature, respectively. Double-skin facades (DSFs) play a crucial role in managing heat gain and indoor air quality in hot-arid climates. To optimize DSF design, a novel 3D multi-objective optimization method was employed to evaluate the interactive effects of DSF geometry parameters on an indoor environment. A 2-meter-high box-type DSF was studied, mounted 0.6 m above the air inlet of a 6 × 8 × 2.8 m room. A Computational Fluid Dynamics (CFD) simulation was conducted to assess buoyant airflow and air temperature. The Design of Experiments (DOE) approach and the Response Surface approach (RSM) were used to evaluate the combined impacts of input and output parameters. The essential geometry parameters for the DSF were chosen, including air gap depth (A.G.), room air outlet height (R.O.), DSF air outlet height (F.O.), and interior glazing height (I.G.). Sensitivity analysis revealed that R.O. and F.O. significantly impacted the average air velocity and mass flow rate, while R.O. and I.G. were the most sensitive parameters on indoor temperature. The optimal design achieved a maximum mass flow rate of 0.72 kg/s and an average air velocity of 0.06 m/s while minimizing the temperature difference between indoor and outdoor to 1.04 °C. The validated optimization framework can be adapted for DSF design across various climatic conditions and building types.