Abstract: The ongoing Covid-19 pandemic has redefined our understanding of respiratory infectious disease transmission. The primary modes of transmission of the SARS-CoV-2 virus has been identified to be airborne, with human generated respiratory aerosols being the main carrier of the virus. Understanding the dispersion of these aerosols/droplets generated during speaking and coughing, has helped quantify potential for transmission and design effective mitigation strategies.
Through my talk I will present how models at two ends of the spatio-temporal resolution spectrum helped quantify the physics and aid NASA Ames administrators design mitigation strategies. For the higher spatio-temporal resolution I will illustrate how the high-order SEM based Navier-Stokes solver Nek5000/NekRS was utilized to develop the models, including algorithms developed through CEED. I will present the two main modes of respiratory aerosol/droplet dispersal indoors, first at a shorter time-scale through expiratory events like coughing, and second at a longer time-scale through the room ventilation system induced flow and turbulence. At the other end of the spatio-temporal resolution, I will talk briefly about Covid-19 Exposure Assessment Tool (CEAT), a novel tool developed to account for multiple factors that affect transmission. I will end my talk by briefly discussing how we can bridge the scales and heterogeneities in the problem with the aid of cutting edge computing and data-driven methods, so that we are fully prepared for the next pandemic.
The work presented here has been facilitated by funding through DOE’s National Virtual Biotechnology Laboratory (NVBL).
Speaker: Som Dutta (Utah State University)
More info / join link: https://mfem.org/seminar/