CFD analysis of cross-ventilation and heat transfer of buildings

Abstract

The rapid growth of population in urban, industrial, and commercial areas has contributed to an increase in heat production. This has intensified the Urban Heat Island (UHI) effect, where urban areas experience high temperatures. Given that individuals spend approximately 80–90% of their time indoors, the indoor thermal environment is crucial for occupant well-being. Despite its significance, research on the interaction between indoor and outdoor thermal conditions remains limited, with a lack of simulation studies establishing correlations between these environments. The study aimed to explore the relationship between indoor and outdoor thermal conditions through the application of passive cross-ventilation. This research specifically examined buildings arranged in a tandem configuration. Computational Fluid Dynamics (CFD) was employed to simulate and analyse cross-ventilation, with a focus on airflow patterns, heat transfer, and indoor air quality. A preliminary model was first developed to assess mesh resolution and analyse methods for implementing a temperature-dependent heat flux boundary condition on an isolated building. The results revealed that the custom boundary condition offered significant advantages over the constant heat flux boundary condition, such as capturing roof temperature fluctuations and accurately representing real-world heat flux magnitudes. The methodologies established in the preliminary model were integrated into the final model. The mesh resolution was reassessed to ensure its suitability for the configuration of the two buildings in tandem. The study examined the impact of wind-driven and wind and buoyancy-driven flows in buildings in tandem. The results demonstrated that the first building impeded airflow to the second, generating a wake zone characterised by stagnant air. However, in wind-driven flow, despite the second building having the lowest Air Renovation per Hour (ARH), it achieved the highest Air Exchange Efficiency (AEE). This highlighted that AEE alone does not reliably indicate effective airflow. In flow driven by both wind and buoyancy effects, flow patterns enhanced airflow distribution in the second building. Furthermore, the application of heat flux to the building resulted in an improved ARH and a higher AEE compared to the first building.