Suppr超能文献

从深部肺部咳出的携带新冠病毒的飞沫:单路径全呼吸道几何结构中的数值量化

SARS COV-2 virus-laden droplets coughed from deep lungs: Numerical quantification in a single-path whole respiratory tract geometry.

作者信息

April Si Xiuhua, Talaat Mohamed, Xi Jinxiang

机构信息

Department of Aerospace, Industrial, and Mechanical Engineering, California Baptist University, 8432 Magnolia Ave., Riverside, California 92504, USA.

Department of Biomedical Engineering, The University of Massachusetts at Lowell, 1 University Ave., Lowell, Massachusetts 01854, USA.

出版信息

Phys Fluids (1994). 2021 Feb;33(2):023306. doi: 10.1063/5.0040914. Epub 2021 Feb 22.

Abstract

When an infected person coughs, many virus-laden droplets will be exhaled out of the mouth. Droplets from deep lungs are especially infectious because the alveoli are the major sites of coronavirus replication. However, their exhalation fraction, size distribution, and exiting speeds are unclear. This study investigated the behavior and fate of respiratory droplets (0.1-4 m) during coughs in a single-path respiratory tract model extending from terminal alveoli to mouth opening. An experimentally measured cough waveform was used to control the alveolar wall motions and the flow boundary conditions at lung branches from G2 to G18. The mouth opening was modeled after the image of a coughing subject captured using a high-speed camera. A well-tested turbulence model and Lagrangian particle tracking algorithm were applied to simulate cough flow evolutions and droplet dynamics under four cough depths, i.e., tidal volume ratio (TVR) = 0.13, 0.20. 0.32, and 0.42. The results show that 2-m droplets have the highest exhalation fraction, regardless of cough depths. A nonlinear relationship exists between the droplet exhalation fraction and cough depth due to a complex deposition mechanism confounded by multiscale airway passages, multiregime flows, and drastic transient flow effects. The highest exhalation fraction is 1.6% at the normal cough depth (TVR = 0.32), with a mean exiting speed of 20 m/s. The finding that most exhaled droplets from deep lungs are 2 m highlights the need for more effective facemasks in blocking 2-m droplets and smaller both in infectious source control and self-protection from airborne virus-laden droplets.

摘要

当感染者咳嗽时,许多携带病毒的飞沫会从口腔呼出。来自深部肺部的飞沫尤其具有传染性,因为肺泡是冠状病毒复制的主要部位。然而,它们的呼出分数、尺寸分布和排出速度尚不清楚。本研究在一个从终末肺泡延伸至口腔开口的单路径呼吸道模型中,研究了咳嗽过程中呼吸道飞沫(0.1 - 4μm)的行为和归宿。使用实验测量的咳嗽波形来控制从G2到G18肺分支处的肺泡壁运动和流动边界条件。根据使用高速相机拍摄的咳嗽受试者图像对口腔开口进行建模。应用经过充分测试的湍流模型和拉格朗日粒子追踪算法,模拟了四种咳嗽深度下的咳嗽气流演变和飞沫动力学,即潮气量比(TVR)= 0.13、0.20、0.32和0.42。结果表明,无论咳嗽深度如何,2μm的飞沫呼出分数最高。由于多尺度气道通道、多流态流动和剧烈瞬态流动效应所混淆的复杂沉积机制,飞沫呼出分数与咳嗽深度之间存在非线性关系。在正常咳嗽深度(TVR = 0.32)时,最高呼出分数为1.6%,平均排出速度为20m/s。深部肺部呼出的大多数飞沫为2μm这一发现凸显了在传染源控制和自我防护以抵御携带病毒的空气传播飞沫方面,需要更有效的口罩来阻挡2μm及更小的飞沫。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8cf/7976054/00923cbdacc7/PHFLE6-000033-023306_1-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验