Indoor airflows and risk of airborne contagion of diseases : Using CHAMÁN for assessing modelling strategies.
The study of Indoor Air Quality (IAQ) has been shown time and again to be of the utmost importance for engineering safe and comfortable indoor spaces. Among many aspects, it comprises the risk assessment for airborne transmission of infectious diseases. Novel risk assessment methodologies have been...
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| Format: | masterThesis |
| Language: | English Spanish |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/20.500.12008/45666 |
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| Summary: | The study of Indoor Air Quality (IAQ) has been shown time and again to be of the utmost importance for engineering safe and comfortable indoor spaces. Among many aspects, it comprises the risk assessment for airborne transmission of infectious diseases. Novel risk assessment methodologies have been recently proposed on the basis of Computational Fluid Dynamics (CFD) simulations for predicting pathogen dispersion. Their use is incipient and computationally expensive, and it is unclear if the benefits they provide outweigh the modelling cost when compared to classical analytic approaches. In this thesis, two models for estimating the risk of long-distance airborne transmission of diseases are compared. On the one hand, a CFD-based approach has been implemented by combining high-resolution Large Eddy Simulations (LES) with Wells’ contagion hypothesis. On the other hand, the classical Wells-Riley approach is considered, which relies on the perfect mix hypothesis. Both models are applied to several natural ventilation scenarios in school classrooms. The implemented CFD-based model uses simulations performed with CHAMÁN, an in-house LES solver with a hybrid computation approach. By leveraging the computational power of Graphic Porcessing Units (GPUs), it allows to conduct LES simulations with unprecedented high resolutions and domain sizes in the context of IAQ. For this thesis, CHAMÁN’s capabilities are extended and the solver is validated for indoor airflows by means of a reference experimental case. Results show that classical models attain a satisfactory average risk prediction when compared to the CFD-based approach, which are robust in terms of boundary conditions sensitivity. Nonetheless, the spatial distribution of the pathogen predicted by the CFD simulations depicts evident inhomogeneities, which foretell local risk minima and maxima that are unrecognised by classical models. |
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