Buoyancy-driven natural ventilation: The role of thermal stratification and its impact on model accuracy

Abstract

Since the invention of mechanical ventilation systems, natural ventilation has been deemed inferior compared to active systems for ventilation of buildings. The recent COVID-19 pandemic and raising awareness of climate change issues have rekindled the interests in natural ventilation as a sustainable method for ventilation and pollutant removal. Modelling natural ventilation is challenging due to uncontrollable outdoor conditions. Simple models such as the well-mixed air model assume uniform indoor air temperature. However, thermal stratification can induce significant temperature differences in the vertical direction, thereby violating the well-mixed assumption. This study evaluates the performance of the well-mixed model, the two-layer stratification model, and computational fluid dynamics (CFD) models in predicting the indoor air temperature under buoyancy-driven displacement ventilation. Compared to experimental measurements, the well-mixed model significantly overpredicts the indoor air temperature without thermal stratification since it assumes a uniform indoor air temperature. The two-layer stratification model overpredicts the upper layer air temperature and underpredicts the lower layer air temperature. The CFD models can capture the trend of the thermal stratification of a gradual increase in temperature with height. However, the CFD models underpredict the indoor air temperature, possibly due to errors introduced by the assumption of adiabatic indoor surfaces. Since simplified models cannot resolve thermal stratification, high-fidelity models, such as CFD models, should be used to model natural ventilation. Experimental studies of natural ventilation should include measurements of the thermal stratification, as well as the temperatures or heat fluxes on the indoor surfaces so the results can be used to develop and evaluate numerical models.