CFD-Driven Optimization of Biosensor Locations for Indoor Air Quality Monitoring in Hospitals
Author(s)
Vijay, Harshin
Lloyd, Annelise Catherine
Sur, Suchir
Advisor(s)
Gomez, Paula
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Abstract
This research paper explores the use of Computational Fluid Dynamics (CFD) simulations to determine the optimal biosensor placement for detecting pathogens in indoor environments. This study incorporated designs from a rehabilitation gym provided by the Mayo Clinic to address indoor air quality management. Utilizing software tools such as Rhino, Grasshopper, and ParaView, we created 3D models, ran simulations, and analyzed airflow patterns. The objective of this study was to introduce CFD to indoor airflow simulation, outline the methodology for the optimal location for a biosensor, and analyze the relationship between airflow patterns and pathogen detection. The findings indicated multiple points that met the required airflow rate for the biosensor intake. We focused on locations in the lower half of the room, considering the likelihood of capturing particulate matter from the human breath. This paper deliberates on challenges faced and future steps, including increasing model complexity and redefining inlet and outlet locations to improve real-world applicability.
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Date
2024-02
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Text
Resource Subtype
Undergraduate Research Paper
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