{"title":"The airflow distribution and aerosol diffusion rules in the negative pressure isolation ward","authors":"Shanbi Peng, Xue Luo, Bin Yu, Li Huang, Enbin Liu","doi":"10.1177/00375497231168628","DOIUrl":null,"url":null,"abstract":"Negative pressure wards are significant in preventing the spread of infectious pathogens which play a crucial role in fighting against COVID-19. Owing to the negative pressure, contaminated air with pathogens is not able to flow from the wards to non-contaminated zones while fresh filtered air will be transported to the ward via the ventilation system. As airflow controlled by ventilation systems affects the motion of pathogens, for example, infectious aerosol particles, the ability of a negative pressure ward to reduce the risk of infection highly relies on an effective ventilation system. In this investigation, impacts of airflow patterns under various human postures and ventilation processes aerosols diffusion are analyzed via the computational fluid dynamics (CFD) simulation. According to the results, among three airflow patterns, the highest contaminant removal efficiency is 57% at 200 s with the top supply and bottom return mode; besides, in three postures, in the case that the patient is in a standing position, the contaminant removal efficiency is the highest. Furthermore, it is found that the best airflow scheme is a slit tuyere in the ward, with a top supply and side return mode and a sitting position for the patient. This study may provide a reference for the design of airflow in negative pressure isolation wards, control of contaminants, and prevention of viral infections, so as to ensure a good working and recovery environment for medical staff and patients.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":"16 1","pages":"917 - 936"},"PeriodicalIF":1.3000,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Simulation-Transactions of the Society for Modeling and Simulation International","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/00375497231168628","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 1
Abstract
Negative pressure wards are significant in preventing the spread of infectious pathogens which play a crucial role in fighting against COVID-19. Owing to the negative pressure, contaminated air with pathogens is not able to flow from the wards to non-contaminated zones while fresh filtered air will be transported to the ward via the ventilation system. As airflow controlled by ventilation systems affects the motion of pathogens, for example, infectious aerosol particles, the ability of a negative pressure ward to reduce the risk of infection highly relies on an effective ventilation system. In this investigation, impacts of airflow patterns under various human postures and ventilation processes aerosols diffusion are analyzed via the computational fluid dynamics (CFD) simulation. According to the results, among three airflow patterns, the highest contaminant removal efficiency is 57% at 200 s with the top supply and bottom return mode; besides, in three postures, in the case that the patient is in a standing position, the contaminant removal efficiency is the highest. Furthermore, it is found that the best airflow scheme is a slit tuyere in the ward, with a top supply and side return mode and a sitting position for the patient. This study may provide a reference for the design of airflow in negative pressure isolation wards, control of contaminants, and prevention of viral infections, so as to ensure a good working and recovery environment for medical staff and patients.
期刊介绍:
SIMULATION is a peer-reviewed journal, which covers subjects including the modelling and simulation of: computer networking and communications, high performance computers, real-time systems, mobile and intelligent agents, simulation software, and language design, system engineering and design, aerospace, traffic systems, microelectronics, robotics, mechatronics, and air traffic and chemistry, physics, biology, medicine, biomedicine, sociology, and cognition.