摘要
为了研究大客车内携带病毒飞沫的扩散特性,预测客车中空气传播病毒感染乘客的风险概率,基于计算流体力学的数值仿真与Wells-Riley方程相结合,建立夏天制冷空调开启状态下大客车的数值模型.通过对车内流场的组织特性分析,结合拉格朗日方法,计算车内病毒携带者咳嗽产生飞沫的扩散过程,分析对比在4种送风方式下携带病毒的飞沫对车内乘客的感染风险.研究发现,车内纵向气流是影响飞沫扩散的关键因素,相较于非对称布置的圆形送风口,客车采用条缝型送风口能够减少车内的纵向气流;采用置换通风的客车内,仅6%的乘客有高于5%概率感染疾病,置换通风在降低飞沫传播感染的风险方面更有效.研究成果可以为客车送风系统的结构设计和降低飞沫传播感染风险提供指导作用.
In order to study the spread characteristics of virus droplets in the bus and predict the risk probability of airborne virus infecting passengers in the bus, a numerical model of the bus with the refrigeration and air conditioning on in summer is established based on the numerical simulation of computational fluid dynamics(CFD) in combination with the Wells-Riley equation. Through the analysis of the characteristics of the flow field in the bus in combination with the Lagrangian method, the spread process of the droplets produced by the cough of the virus carrier in the bus is calculated. The infection risk of virus-carrying droplets to the passengers in the bus in the four ventilation mades is analyzed. It is found that the longitudinal airflow in the bus is a key factor affecting the spread of droplets. Compared with the asymmetrically arranged circular air outlets, the longitudinal airflow in the bus can be reduced by the use of slit-type air outlets. Only 6% of passengers have a higher than 5% probability of contracting diseases in the bus with displacement ventilation, which is more effective in reducing the risk of droplet-borne infection. The research results can provide guidance for the structural design of bus air supply systems and reduce the risk of droplet-borne infections.
作者
陈志鑫
汪怡平
杨亚锋
苏建军
杨斌
CHEN Zhixin;WANG Yiping;YANG Yafeng;SU Jianjun;YANG Bin(Hubei Key Laboratory of Advanced Technology for Automotive Components,Wuhan University of Technology,Wuhan 430070,China;Hubei Qixing Cabin Manufacturing Co.,Ltd.,Suizhou 441300,Hubei,China;Gansu Construction Investment Heavy Industry Technology Co.,Ltd.,Lanzhou 730000,China)
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2022年第11期1532-1540,共9页
Journal of Shanghai Jiaotong University
基金
国家自然科学基金资助项目(51775395)。