Stratum Ventilation: Enabling Simultaneous Energy Conservation and Air Purification in Subway Cars

The supply of fresh air for underground rail transit systems is not as simple as opening windows, which is a conventional ventilation (CV) measure adopted in aboveground vehicles. This study aims to improve contaminant dilution and air purification in subway car ventilation systems and the safety of rail transit post-coronavirus disease pandemic era. We designed an air conditioning (AC) terminal system combined with stratum ventilation (SV) to enable energy consumption reduction for subway cars. We experimentally tested the effectiveness of a turbulence model to investigate ventilation in subway cars. Further, we compared the velocity fields of CV and SV in subway cars to understand the differences in their airflow organizations and contaminant removal efficiencies, along with the energy savings of four ventilation scenarios, based on the calculations carried out using computational fluid dynamics. At a ventilation flow rate of 7200 m³/h, the CO₂ concentration and temperature in the breathing areas of seated passengers were better in the SV than in the CV at a rate of 8500 m³/h. Additionally, the energy-saving rate of SV with AC cooling was 14.05%. The study provides new ideas for reducing the energy consumption of rail transit and broadens indoor application scenarios of SV technology.

Zonal model for predicting contaminant distribution in stratum ventilated rooms

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.