TY  - CONF
AU  - Novell, Alice
AU  - Muñoz, Fernando
AU  - Ntiniakou, Thaleia
AU  - Montagud, Arnau
AU  - Houzeaux, Guillaume
AU  - Eguzkitza, Ane Beatriz
TI  - Lung Digital Twin COVID-19 Infection: A Multiphysics - Multiscale HPC-Modeling Based on CFPD and Agent-Based Model Coupled Simulations
VL  - 69
CY  - Jülich
PB  - Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag
M1  - FZJ-2025-02477
T2  - Schriften des Forschungszentrums Jülich IAS Series
SP  - 147 - 153
PY  - 2025
AB  - The present work is one of the three pieces (upper airways, lower conductive airways and respiratory zone) of a digital twin lung model developed by the Physical and Numerical Modelling research group from the CASE department in Barcelona Supercomputing Center (BSC). In particular, the study presents the solution of fluid flow and SARS-COV-2 particle transport in the lower conductive zone of the lungs, using a geometry based on patient specific images. The specific context of the current work is framed within the European Project: CREXDATA: Critical Action Planning over Extreme-Scale Data. Its general vision is to develop a generic platform for real-time critical situation management, including flexible action planning and agile decision-making over streaming data of extreme scale and complexity. One of the use cases of the project is the COVID-19 pandemic crisis, studying viral evolution in patients. To that end, the first step is to develop a mechanistic multiscale model to build a toolbox aimed at having a digital twin for the treatment of patients.
T2  - 35th Parallel CFD International Conference 2024
CY  - 2 Sep 2024 - 4 Sep 2024, Bonn (Germany)
Y2  - 2 Sep 2024 - 4 Sep 2024
M2  - Bonn, Germany
LB  - PUB:(DE-HGF)8 ; PUB:(DE-HGF)7
DO  - DOI:10.34734/FZJ-2025-02477
UR  - https://juser.fz-juelich.de/record/1042261
ER  -