In line with recent ongoing efforts to collect crucial information about the mechanisms of virus diffusion and put them in relation to the effective complexity of the several natural or artificial environments where human beings leave and operate, the present study deals with the dispersion of evaporating saliva droplets in the cabin of an interregional train. A relevant physical model is constructed taking into account the state of the art in terms of existing paradigms and their ability to represent some fundamental aspects related to the evolution in time of a cloud of multi-disperse droplets. Conveniently, such a theoretical framework is turned into a computational one that relies on low Mach-number asymptotics and can therefore take advantage of the typical benefits (relatively low computational cost) associated with pressure-based methods. Numerical simulations are used to predict the flow established in the cabin as a result of the ventilation systems and related settings dictated by considerations on passenger comfort. The solution of two-way coupled Lagrangian evolution equations is used to capture the associated dynamics of the dispersed phase and predict its transport in conjunction with the peculiar topology of the considered flow and morphology of solid surfaces, which bound it (including the human beings). Typical physiological processes such as talking or coughing are considered. An analysis on the impact of the multiplicity of droplet sources is also conducted, thereby providing some indications in terms of potential risks for the cabin occupants.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.