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新冠疫情及未来大流行期间,为更安全地规划学术设施而对呼吸道飞沫演变进行预测:一种数值方法。

Prediction of respiratory droplets evolution for safer academic facilities planning amid COVID-19 and future pandemics: A numerical approach.

作者信息

Quiñones Jhon J, Doosttalab Ali, Sokolowski Steven, Voyles Richard M, Castaño Victor, Zhang Lucy T, Castillo Luciano

机构信息

School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47907, United States.

Department of Mechanical, Aerospace and Nuclear Engineering, Rensselaer Polytechnic Institute, Troy, NY, 12180, United States.

出版信息

J Build Eng. 2022 Aug 15;54:104593. doi: 10.1016/j.jobe.2022.104593. Epub 2022 May 14.

DOI:10.1016/j.jobe.2022.104593
PMID:40477575
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9107331/
Abstract

Airborne dispersion of the novel SARS-CoV-2 through the droplets produced during expiratory activities is one of the main transmission mechanisms of this virus from one person to another. Understanding how these droplets spread when infected humans with COVID-19 or other airborne infectious diseases breathe, cough or sneeze is essential for improving prevention strategies in academic facilities. This work aims to assess the transport and fate of droplets in indoor environments using Computational Fluid Dynamics (CFD). This study employs unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations with the Euler-Lagrange approach to visualize the location of thousands of droplets released in a respiratory event and their size evolution. Furthermore, we assess the dispersion of coughing, sneezing, and breathing saliva droplets from an infected source in a classroom with air conditioning and multiple occupants. The results indicate that the suggested social distancing protocol is not enough to avoid the transmission of COVID-19 since small saliva droplets ( ≤ 12 m) can travel in the streamwise direction up to 4 m when an infected person coughs and more than 7 m when sneezes. These droplets can reach those distances even when there is no airflow from the wind or ventilation systems. The number of airborne droplets in locations close to the respiratory system of a healthy person increases when the relative humidity of the indoor environment is low. This work sets an accurate, rapid, and validated numerical framework reproducible for various indoor environments integrating qualitative and quantitative data analysis of the droplet size evolution of respiratory events for a safer design of physical distancing standards and air cleaning technologies.

摘要

新型严重急性呼吸综合征冠状病毒2(SARS-CoV-2)通过呼气活动产生的飞沫进行空气传播,是该病毒在人与人之间传播的主要机制之一。了解感染新冠病毒(COVID-19)或其他空气传播传染病的人呼吸、咳嗽或打喷嚏时这些飞沫如何传播,对于改进学术机构的预防策略至关重要。这项工作旨在使用计算流体动力学(CFD)评估室内环境中飞沫的传输和归宿。本研究采用非定常雷诺平均纳维-斯托克斯(URANS)模拟和欧拉-拉格朗日方法,以可视化呼吸事件中释放的数千个飞沫的位置及其尺寸演变。此外,我们评估了在有空调且有多名 occupants 的教室中,受感染源咳嗽、打喷嚏和呼出的唾液飞沫的扩散情况。结果表明,建议的社交距离协议不足以避免 COVID-19 的传播,因为当感染者咳嗽时,小唾液飞沫(≤12微米)可沿流向传播至4米,打喷嚏时可传播超过7米。即使没有来自风或通风系统的气流,这些飞沫也能到达这些距离。当室内环境相对湿度较低时,靠近健康人呼吸系统位置的空气传播飞沫数量会增加。这项工作建立了一个准确、快速且经过验证的数值框架,可重现用于各种室内环境,整合了呼吸事件飞沫尺寸演变的定性和定量数据分析,以更安全地设计物理距离标准和空气净化技术。

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