期刊
INDOOR AIR
卷 32, 期 11, 页码 -出版社
WILEY
DOI: 10.1111/ina.13151
关键词
airplane cabin; computational fluid dynamics (CFD); convective and turbulent contaminant mass fluxes; large eddy simulation (LES); time-periodic mixing ventilation; ventilation efficiency
类别
资金
- Fonds Wetenschappelijk Onderzoek
- [FWO 1150617?N]
- [EINF-1581]
- [EINF-1938]
Airplane cabin ventilation is crucial for passengers' well-being. This research investigates the effects of time-periodic mixing ventilation on contaminant removal effectiveness and air change efficiency. The study reveals that time-periodic supply can improve ventilation efficiency and reduce contaminant concentrations in the passenger zone.
Airplane cabin ventilation is essential to ensure passengers' well-being. The conventional ventilation method is mixing ventilation with a statistically steady supply, which, according to former studies, has reached its limits regarding, for example, the ventilation efficiency. However, the effect of a statistically unsteady (time-periodic) supply on the mixing ventilation efficiency has remained largely unexplored. This research uses computational fluid dynamics (CFD) with the large eddy simulation (LES) approach to study isothermal time-periodic mixing ventilation in a section of a single-aisle airplane cabin model, in which the air exhaled by the passengers functions as (passive) contaminants. Two time-periodic supply strategies are evaluated. The induced time-periodic airflow patterns promote an efficient delivery of fresh air to the passenger zone and affect the passengers' expiratory plumes. This results in increased mean contaminant mass fluxes, causing a strong reduction of the mean contaminant concentrations in the passenger zone (up to 23%) and an increased contaminant extraction from the cabin. Mean velocities increase with up to 55% but remain within the comfortable range. It is shown that the ventilation efficiency improves; that is, the contaminant removal effectiveness and air change efficiency (in the full cabin volume) increase with up to 20% and 7%, respectively.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据