@article{Mehade_Hussain_S-2022_94895,
title = {A short review of vapour droplet dispersion models used in CFD to study the airborne spread of COVID19},
author = {Mehade Hussain, S. and Goel, S. and Kadapa, C. and Aristodemou, E.},
month = {apr},
year = {2022},
abstract = {The use of computational fluid dynamics (CFD) to simulate the spread of COVID19 and many other airborne diseases, especially in an indoor environment needs accurate understanding of dispersion models. Modelling the transport/dispersion of vapour droplets within the atmosphere is a complex problem, as it involves the motion of more than one phase, as well as the interphase interactions between the phases. This paper reviews the current canon of research on dispersion modelling of vapour droplets by looking at three specific aspects: (i) physical definition/specification of the initial droplet size distribution; (ii) physics of evaporation/condensation models and (iii) transport equations (with molecular/turbulent dispersion models) to describe the movement of the vapour droplets as they propagate through the air. This review found that the state of modelling implements a wide range of models which shows variances in results thus leading to a state where it is difficult to know which model is most accurate. The authors suggest that further studies in this direction should focus on developing a principle set of equations by benchmarking the previously developed models to establish model uncertainty of the previously developed models with reference to a fixed theoretical model and be compared under identical conditions. However, it must be noted that due to the complex nature of microdroplet evaporation and dispersion coupled with the unpredictable way droplet size distributions are produced, current experimental methodologies that are available to validate such simulations, such as particle image velocimetry, are still not robust enough to provide detailed data to verify minute aspects of the simulations.},
pages = {1349-1356},
volume = {64},
issue = {3},
journal = {Materialstoday: Proceedings},
publisher = {Elsevier},
url = {https://doi.org/10.1016/j.matpr.2022.03.724},
}
