TU Delft COVID-app: A tool to democratize CFD simulations for SARS-CoV-2 infection risk analysis

David Engler Faleiros, Wouter van den Bos*, Lorenzo Botto, Fulvio Scarano

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

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.

Original languageEnglish
Article number154143
Number of pages17
JournalScience of the Total Environment
Volume826
DOIs
Publication statusPublished - 2022

Keywords

  • Application
  • COVID-19 simulation
  • COVID-app
  • Infection probability
  • SARS-CoV-2 dispersion
  • Unsteady speaking

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