This research used computational fluid dynamics (CFD) to examine the behavior of airborne droplets released during respiratory events. The CFD model utilizes an Eulerian-Lagrangian approach, with turbulence resolved using the Spalart-Allmaras detached eddy simulation. The first part investigates airborne transmission and how modifying saliva during a sneeze impacts this process. The study employs CFD to simulate these respiratory events in a ventilated room. It finds that larger droplets alone are insufficient for droplet settling due to secondary breakdown processes. Modifiers that increase the Ohnesorge number show resistance to aerosolization from secondary breakup, resulting in more droplets with high settling rates, reducing their likelihood of airborne transmission. Another effective modifier reduces saliva content. The second part of the research develops a linear algebraic function to represent the near-field dispersion of droplets formed during respiratory events. This model facilitates the examination of flow interaction among various sources in different environments without requiring computationally expensive CFD simulations. The final part of the research involves developing a numerical Wells curve considering droplet evaporation, buoyancy, turbulence, breakup, and collision. The study also examines the effect of relative humidity on airborne transmission, finding that higher relative humidity slows the evaporation rate, which typically promotes faster droplet settling. Overall, these findings offer promising strategies for preventing spread of airborne transmission, highlighting the potential of saliva modification and advanced modeling techniques in public health interventions.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2023-1440 |
| Date | 01 January 2024 |
| Creators | Shrestha, Rajendra, Mr. |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Thesis and Dissertation 2023-2024 |
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