Accelerated Airborne Virus Spread Si­mu­la­tion: Coupling Agent-based Modeling with GPU-accelerated Computational Fluid Dynamics

AuthorSchinko, Christoph; Shao, Lin; Mueller-Roemer, Johannes Sebastian; Weber, Daniel; Zhang, Xingzi; Lee, Eugene; Sander, Bastian; Steinhardt, Alexander; Settgast, Volker; Eggeling, Eva; Erdt, Marius; Chen, Kan
TypeConference Paper
AbstractThe Coronavirus Disease 2019 (COVID-19) has shown us the necessity to understand its transmission mechanisms in detail in order to establish practice in controlling such infectious diseases. An important instrument in doing so are mathematical models. However, they do not account for the spatiotemporal heterogeneity introduced by the movement and interaction of individuals with their surroundings. Computational fluid dynamics (CFD) simulations can be used to analyze transmission on micro- and mesostructure level, however become infeasible in larger scale scenarios. Agent-based modeling (ABM) on the other hand is missing means to simulate airborne virus transmission on a micro- and mesostructure level. Therefore, we present a system that combines CFD simulations with the dynamics given by trajectories from an ABM to form a basis for producing deeper insights. The proposed system is still work in progress; thus we focus on the system architecture and show preliminary results.
ConferenceInternational Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) 2022