Aerosol Transmission of COVID-19 and other Airborne Diseases in office environments using Computational Fluid Dynamic Modeling and Machine Learning

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dc.contributor.advisorFreire-Gormaly, Marina
dc.contributor.authorWebb, Kishon Winston
dc.date.accessioned2023-12-08T14:42:01Z
dc.date.available2023-12-08T14:42:01Z
dc.date.issued2023-12-08
dc.date.updated2023-12-08T14:42:01Z
dc.degree.disciplineMechanical Engineering
dc.degree.levelMaster's
dc.degree.nameMASc - Master of Applied Science
dc.description.abstractThe COVID-19 pandemic has shown the world how quickly airborne diseases can spread and the lasting impact they can have. Computational fluid dynamic (CFD) models and simulations and machine learning (ML) are powerful tools that allow engineers to create models to predict and advance tools to fight these airborne diseases. The research in this thesis studied the effects of heating, air conditioning and ventilation (HVAC) strategies in small office spaces. A novel methodology was developed to utilize ML, CFD and parallel computing by utilizing the user defined function (UDF) tool of ANSYS Fluent. It was shown that the resulting risk models were quick and effective at predicting high risk areas using spatial data or predicting regions of high risk over time. Future research will refine this method by creating higher fidelity ML models and investigating a wider range of input and output parameters.
dc.identifier.urihttps://hdl.handle.net/10315/41735
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectMechanical engineering
dc.subjectComputer science
dc.subject.keywordsCFD
dc.subject.keywordsCOVID-19
dc.subject.keywordsHVAC
dc.subject.keywordsML
dc.subject.keywordsAI
dc.subject.keywordsNeural Network
dc.subject.keywordsRisk Model
dc.titleAerosol Transmission of COVID-19 and other Airborne Diseases in office environments using Computational Fluid Dynamic Modeling and Machine Learning
dc.typeElectronic Thesis or Dissertation

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