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Nat Med. 2022 Jul;28(7):1491-1500. doi: 10.1038/s41591-022-01816-0. Epub 2022 Apr 8.
2
Air exchange rates and advection-diffusion of CO and aerosols in a route bus for evaluation of infection risk.用于评估感染风险的路线巴士中 CO 和气溶胶的空气交换率和对流-扩散。
Indoor Air. 2022 Mar;32(3):e13019. doi: 10.1111/ina.13019.
3
Breathing zone and exhaled air re-inhalation rate under transient conditions assessed with a computer-simulated person.在瞬态条件下,利用计算机模拟人评估呼吸区和呼出空气再吸入率。
Indoor Air. 2022 Feb;32(2):e13003. doi: 10.1111/ina.13003.
4
Viral Load in COVID-19 Patients: Implications for Prognosis and Vaccine Efficacy in the Context of Emerging SARS-CoV-2 Variants.新冠患者的病毒载量:在新型严重急性呼吸综合征冠状病毒2(SARS-CoV-2)变体背景下对预后和疫苗效力的影响
Front Med (Lausanne). 2022 Jan 31;8:836826. doi: 10.3389/fmed.2021.836826. eCollection 2021.
5
An improved numerical model for epidemic transmission and infection risks assessment in indoor environment.一种用于室内环境中疫情传播和感染风险评估的改进数值模型。
J Aerosol Sci. 2022 May;162:105943. doi: 10.1016/j.jaerosci.2021.105943. Epub 2022 Jan 11.
6
Quantitative assessment of the risk of airborne transmission of SARS-CoV-2 infection: Prospective and retrospective applications.定量评估 SARS-CoV-2 感染经空气传播的风险:前瞻性和回顾性应用。
Environ Int. 2020 Dec;145:106112. doi: 10.1016/j.envint.2020.106112. Epub 2020 Sep 6.
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Estimation of airborne viral emission: Quanta emission rate of SARS-CoV-2 for infection risk assessment.空气中病毒排放的估算:用于感染风险评估的 SARS-CoV-2 的定量排放率。
Environ Int. 2020 Aug;141:105794. doi: 10.1016/j.envint.2020.105794. Epub 2020 May 11.
8
Numerical investigation of indoor particulate contaminant transport using the Eulerian-Eulerian and Eulerian-Lagrangian two-phase flow models.使用欧拉-欧拉和欧拉-拉格朗日两相流模型对室内颗粒污染物传输进行数值研究。
Exp Comput Multiph Flow. 2020;2(1):31-40. doi: 10.1007/s42757-019-0016-z. Epub 2019 May 9.
9
Experimental and numerical investigation of micro-environmental conditions in public transportation buses.公共交通巴士内微环境条件的实验与数值研究
Build Environ. 2010 Oct;45(10):2077-2088. doi: 10.1016/j.buildenv.2010.03.004. Epub 2010 Mar 17.
10
Viral load of SARS-CoV-2 in clinical samples.临床样本中新型冠状病毒2的病毒载量
Lancet Infect Dis. 2020 Apr;20(4):411-412. doi: 10.1016/S1473-3099(20)30113-4. Epub 2020 Feb 24.

通勤巴士上空气传播风险的空间分布:使用计算流体和粒子动力学以及计算机模拟人员的数值案例研究。

Spatial distributions of airborne transmission risk on commuter buses: Numerical case study using computational fluid and particle dynamics with computer-simulated persons.

作者信息

Yoo Sung-Jun, Kurokawa Akira, Matsunaga Kazuhiko, Ito Kazuhide

机构信息

Faculty of Engineering Sciences, Kyushu University, 6-1 Kasuga-koen, Kasuga, Fukuoka, 816-8580 Japan.

Interdisciplinary Graduate School of Engineering Science, Kyushu University, 6-1 Kasuga-koen, Kasuga, Fukuoka, 816-8580 Japan.

出版信息

Exp Comput Multiph Flow. 2023;5(3):304-318. doi: 10.1007/s42757-022-0146-6. Epub 2023 Feb 10.

DOI:10.1007/s42757-022-0146-6
PMID:36788805
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9912221/
Abstract

Commuter buses have a high passenger density relative to the interior cabin volume, and it is difficult to maintain a physical/social distance in terms of airborne transmission control. Therefore, it is important to quantitatively investigate the impact of ventilation and air-conditioning in the cabin on the airborne transmission risk for passengers. In this study, comprehensive coupled numerical simulations using computational fluid and particle dynamics (CFPD) and computer-simulated persons (CSPs) were performed to investigate the heterogeneous spatial distribution of the airborne transmission risk in a commuter bus environment under two types of layouts of the ventilation system and two types of passenger densities. Through a series of particle transmission analysis and infection risk assessment in this study, it was revealed that the layout of the supply inlet/exhaust outlet openings of a heating, ventilation, and air-conditioning (HVAC) system has a significant impact on the particle dispersion characteristics inside the bus cabin, and higher infection risks were observed near the single exhaust outlet in the case of higher passenger density. The integrated analysis of CFPD and CSPs in a commuter bus cabin revealed that the airborne transmission risk formed significant heterogeneous spatial distributions, and the changes in air-conditioning conditions had a certain impact on the risk.

摘要

通勤巴士相对于车厢内部容积而言乘客密度较高,就空气传播控制而言,难以保持物理/社交距离。因此,定量研究车厢内通风和空调对乘客空气传播风险的影响很重要。在本研究中,使用计算流体和粒子动力学(CFPD)以及计算机模拟人(CSP)进行了综合耦合数值模拟,以研究在两种通风系统布局和两种乘客密度下通勤巴士环境中空气传播风险的非均匀空间分布。通过本研究中的一系列粒子传播分析和感染风险评估发现,供暖、通风和空调(HVAC)系统的进风口/出风口布局对巴士车厢内的粒子扩散特性有显著影响,在乘客密度较高的情况下,在单个出风口附近观察到较高的感染风险。对通勤巴士车厢内CFPD和CSP的综合分析表明,空气传播风险形成了显著的非均匀空间分布,并且空调条件的变化对风险有一定影响。