Genetic-algorithms based optimization method of building geometric opening configurations for enhancing outdoor wind environment performance

The quality of the outdoor environment is closely linked to urban ventilation performance. Poor wind conditions in high-density urban areas can lead to severe air pollution and reduced thermal comfort. However, the relationship between outdoor wind conditions and building opening configurations is complex. This study aims to optimize building opening designs for improving the urban wind environment. By combining multi-objective optimization using genetic algorithms and computational fluid dynamics (CFD) simulation technology, this research proposes a framework to guide the design and layout of building openings. Various opening schemes were simulated in a digital model based on a real site in Shenzhen, China. Potential opening configurations for high and low permeability scenarios were obtained through Pareto optimization, and an opening probability map was generated. The results demonstrate that at a porosity of 15 %, pedestrian-level mean wind speed, wind speed dispersion, and pressure differences between the front and rear of the downstream building can be improved by up to 20.00 %, 19.35 %, and 183.33 %, respectively. When the porosity is increased to 25 %, these values improve to 42.22 %, 16.13 %, and 483.33 %. Based on the opening probability distribution map, two building façade opening schemes with different permeability were designed and validated through CFD simulations. Our findings suggest that this framework can effectively guide the design of building openings, improve urban airflow, and offer valuable practical applications.