Abstract

A major challenge in the Computational Fluid Dynamics (CFD) modeling of the human respiratory system is the complex variation of geometric scale from the trachea to the peripheral airways. The current literature on image-based lung flow analysis is limited to a few (typically 5) generations beyond the trachea. Such studies, which are limited largely by computational intensity and computational cost, also have limited accuracy. In this study we propose a hybrid methodology that enables CFD analysis from the middle to the distal airways through to the alveolar level. A hybrid lung model is generated where the middle airways are reconstructed from human CT-scans using open-source image analysis and extended to distal parts utilizing a section of airway branching tree generated based on deterministic algorithm. Such hybrid models allow the application of physiologically relevant boundary conditions instead of the approximation methods often used in previous studies in the region of interest. Two different breathing conditions are investigated, and the results are validated by comparison with previous experimental and numerical data.

Notes

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Graduation Date

2022

Semester

Summer

Advisor

Ilegbusi, Olusegun

Degree

Master of Science in Mechanical Engineering (M.S.M.E.)

College

College of Engineering and Computer Science

Department

Mechanical and Aerospace Engineering

Degree Program

Mechanical Engineering; Mechanical Systems

Identifier

CFE0009194; DP0026790

URL

https://purls.library.ucf.edu/go/DP0026790

Language

English

Release Date

August 2023

Length of Campus-only Access

1 year

Access Status

Masters Thesis (Open Access)

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