Zonal model for predicting contaminant distribution in stratum ventilated rooms
Yalin Lu, Yuchun Zhang, Zhang Lin
Abstract
Accurate prediction of the non-uniform contaminant distribution under stratum ventilation (SV) is crucial for optimal design for reducing contaminant exposure risks. Compared with experiments and computational fluid dynamics, zonal models are convenient to implement. This study proposes a zonal model for predicting dynamic non-uniform contaminant distribution in the stratum ventilated room. The zoning method is based on the unique airflow pattern under SV, and the room is divided into the jet zone, entrainment zone, and the mixing zone. The interzonal airflow rate is derived from the profile of the supply air jet. The results show that the proposed zonal model can predict the dynamic contaminant distribution in the stratum ventilated room. Compared with the experimental measurement, the predictions show good accuracy with the mean absolute error (MAE) at 0.51-2.36 ppm and root mean squared error (RMSE) at 0.64-2.53 ppm. The error of the proposed zonal model is influenced by the degree of mixing in each subzone. The proposed zonal model shows better accuracy for non-uniform air distribution under stratum ventilation compared with the existing zonal model.