Validation and sensitivity analysis of simulations of particle deposition in human airways
Abstract/Contents
- Abstract
- The airway is a major entry port into our body. Airborne particles such as tobacco smoke, dust, pollen, bacteria are breathed with every breath. Particles are also used for medical treatment in the form of inhaled aerosols to treat diseases such as asthma. The effect of these particles on our health is highly dependent on where they deposit in our airway. Where particles deposit depends on many different factors including the particles' size, how we breath and differences in our airway geometry. We study the sensitivity of deposition to these factors through simulation. First, we start with the surface of a realistic human airway obtained from segmenting an MRI scan, breathing in from the mouth. The flow field is computed using an unstructured LES fluids solver and is validated against an Magnetic Resonance Velocimetry experiment. We can vary the flow field intensity to model different breathing conditions. Particles of size 1 to 10 microns are injected as Lagrangian point particles after the flow field is developed. Their trajectories are integrated until they either exit the airway into high generations of the bronchial tree or they are deposited on the airway wall. The deposition statistics are then analyzed. Finally, to study the sensitivity to perturbations in airway geometry, we constructed a parameterized synthetic airway that can perturbed. We studied the effects of constrictions and expansions in the main bronchi to particle distribution.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2014 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Lin, Eleanor Yang |
|---|---|
| Associated with | Stanford University, Department of Computational and Mathematical Engineering. |
| Primary advisor | Iaccarino, Gianluca |
| Primary advisor | Shaqfeh, Eric S. G. (Eric Stefan Garrido) |
| Thesis advisor | Iaccarino, Gianluca |
| Thesis advisor | Shaqfeh, Eric S. G. (Eric Stefan Garrido) |
| Thesis advisor | Darve, Eric |
| Advisor | Darve, Eric |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Eleanor Yang Lin. |
|---|---|
| Note | Submitted to the Department of Computational and Mathematical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2014. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2014 by Yang Lin
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...