TU Delft COVID-app: A tool to democratize CFD simulations for SARS-CoV-2 infection risk analysis.
TU Delft COVID-app: A tool to democratize CFD simulations for SARS-CoV-2 infection risk analysis.
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DOI：
10.1016/j.scitotenv.2022.154143
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发表时间：
2022-06-20
期刊：
影响因子：
--
通讯作者：
Scarano F
中科院分区：
文献类型：
--
作者：
Faleiros DE;van den Bos W;Botto L;Scarano F
这项工作描述了一种基于实验的SARS-CoV-2扩散的建模方法。主要目标是开发一个集成在Ansys Fluent中的应用程序，使计算流体动力学（CFD）用户能够在相对较短的时间内建立复杂的病毒粒子液滴扩散模拟，以计算真实的生活场景中SARS-CoV-2感染的概率。该软件应用程序被称为TU德尔夫特COVID-app，包括人体呼气活动、不稳定和湍流对流、液滴蒸发和热耦合的建模。描述人类呼气活动的数据已经从选定的研究中获得，这些研究涉及在咳嗽、打喷嚏和呼吸期间对排出的液滴和气流的测量。用粒子图像测速法（PIV）测量了一个人在背诵演讲时排出的瞬态气流，并在有和没有外科口罩的情况下进行了测量。PIV的瞬时速度场用于确定数值模拟中使用的速度流率，而平均速度场用于验证。此外，外科口罩和N95呼吸机对颗粒过滤的影响以及来自剂量反应模型的SARS-CoV-2感染概率也已在应用中实现。最后，这项工作包括一个案例研究的SARS-CoV-2感染风险分析期间的谈话在餐桌/会议桌上，展示了新开发的应用程序的能力。
This work describes a modelling approach to SARS-CoV-2 dispersion based on experiments. The main goal is the development of an application integrated in Ansys Fluent to enable computational fluid dynamics (CFD) users to set up, in a relatively short time, complex simulations of virion-laden droplet dispersion for calculating the probability of SARS-CoV-2 infection in real life scenarios. The software application, referred to as TU Delft COVID-app, includes the modelling of human expiratory activities, unsteady and turbulent convection, droplet evaporation and thermal coupling. Data describing human expiratory activities have been obtained from selected studies involving measurements of the expelled droplets and the air flow during coughing, sneezing and breathing. Particle Image Velocimetry (PIV) measurements of the transient air flow expelled by a person while reciting a speech have been conducted with and without a surgical mask. The instantaneous velocity fields from PIV are used to determine the velocity flow rates used in the numerical simulations, while the average velocity fields are used for validation. Furthermore, the effect of surgical masks and N95 respirators on particle filtration and the probability of SARS-CoV-2 infection from a dose-response model have also been implemented in the application. Finally, the work includes a case-study of SARS-CoV-2 infection risk analysis during a conversation across a dining/meeting table that demonstrates the capability of the newly developed application.
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影响因子：
3.7
作者：
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影响因子：
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通讯作者：
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DOI：
10.1073/pnas.2012156117
发表时间：
2020-10-13
影响因子：
11.1
作者：
Abkarian, Manouk;Mendez, Simon;Stone, Howard A.
通讯作者：
Stone, Howard A.