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

Eggeling, Eva ; Erdt, Marius ; Chen, Kan ; Settgast, Volker ; Steinhardt, Alexander ; Sander, Bastian ; Lee, Eugene ; Zhang, Xingzi ; Weber, Daniel ; Mueller-Roemer, Johannes ; Shao, Lin ; Schinko, Christoph (2022)
Accelerated Airborne Virus Spread Simulation: Coupling Agent-based Modeling with GPU-accelerated Computational Fluid Dynamics.
17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. virtual Conference (06.-08.02.2022)
doi: 10.5220/0010904500003124
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

The 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.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2022
Autor(en): Eggeling, Eva ; Erdt, Marius ; Chen, Kan ; Settgast, Volker ; Steinhardt, Alexander ; Sander, Bastian ; Lee, Eugene ; Zhang, Xingzi ; Weber, Daniel ; Mueller-Roemer, Johannes ; Shao, Lin ; Schinko, Christoph
Art des Eintrags: Bibliographie
Titel: Accelerated Airborne Virus Spread Simulation: Coupling Agent-based Modeling with GPU-accelerated Computational Fluid Dynamics
Sprache: Englisch
Publikationsjahr: 2022
Verlag: SciTe Press
Buchtitel: Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - IVAPP
Veranstaltungstitel: 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Veranstaltungsort: virtual Conference
Veranstaltungsdatum: 06.-08.02.2022
DOI: 10.5220/0010904500003124
Kurzbeschreibung (Abstract):

The 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.

Freie Schlagworte: Software architectures, Computational fluid dynamics (CFD), Animated agent behavior
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
Hinterlegungsdatum: 03 Mär 2022 09:09
Letzte Änderung: 03 Mär 2022 09:09
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