Special Issue: CFD and Covid-19

Abstract

The Covid-19 outbreak has caused significant human and economic loss across the world. While rules-ofthumb for social distancing and masking are thought to be effective measures at inhibiting the spread of the virus, the science behind them is still in its infancy and is often limited to quiescent air conditions. Because airborne diseases such as Covid-19 are transported primarily via aerosolized respiratory droplets, fluid dynamics plays a fundamental role in its spread and, subsequently, mitigation. This is where CFD can play a critical role in understanding how Covid-19 and other airborne diseases spread. With the powerful insight that CFD can provide, simple and effective engineering controls can be implemented therefore reducing the burden of compliance with other measures such as masking, social distancing, and vaccination. CFD has been used in the past to study the spread of airborne diseases in close quarters such as school buses, hospital wards, schools, and other crowded venues. Most of the existing work, however, was limited to low order RANS-type models due to technological limitations. With our modern computational power, it seems natural to seek advanced CFD calculations for Covid-19 and airborne disease transmission. More importantly, therewas little technology exchange between those studying the science of viral transmission and engineering fluid mechanics, in part because CFD was not very popular or was considered as an interesting gadget at best. Recent advances in computational science, however, and their impact on health sciences has created a newfound trust in tools such as CFD to study the spread of airborne disease. There is no better time to capitalise on that opportunity than the present. CFD for airborne transmission has two major components: modelling respiratory disease sources (e.g. mouth) and subsequently tracking their motion with the air. In general, it is not possible to do bothwith very high-fidelity because the former requires DNSlevel calculations while the latter can generally be well managed with LES or RANSmodels. In addition, CFD applied to understanding respiratory sources must at some point rely on observational data of particle size distributions and their properties at the source. On the other hand, if sources are properlymodelled, those can be effectively input to the CFD model to capture their bulk motion with the air. The objective of this special issue is to bring-in world experts in CFD and fluid mechanics to contribute to the scientific understanding of the spread of Covid-19 using advanced computational techniques. The list of contributors was carefully curated from active CFD practitioners and pioneers who were among the first to apply their expertise to study the spread of Covid-19 in close quarters. Contributions to this special issue include high-fidelity calculations of respiratory droplet transport accounting for deposition, evaporation, and transmission, within an LES framework. In addition, the use of HPC and modern software stacks permeates across all submitted articles. Case studies include transmission in a restaurant, city bus, and generic indoor spaces. It is our hope that CFD plays a critical role in public health decisions when it comes to pandemics and the spread of airborne diseases. Continued work in the area to improve both high-fidelity and low-ordermodels is critical and we are excited to see this special issue contain much needed CFD results in this area.