Abstract

Developing lifelike vocal fold models is challenging due to various associatedbiomechanical complexities. Nevertheless, the development and analysis of improved vocal foldmodels is worthwhile since they are valuable tools for gaining insight into human vocal foldvibratory, aerodynamic, and acoustic response characteristics. This thesis seeks to contribute tothe development of computational and physical vocal fold modeling in two ways. First is byintroducing a method of obtaining internal deformation fields within vibrating synthetic vocal foldmodels; second is by presenting an optimization algorithm coupled with a computational vocalfold model to optimize geometry and stiffness of a synthetic vocal fold model to achieve morerealistic vibration patterns.The method for tracking the internal deformation of self-oscillating vocal fold models isbased on MR imaging. Silicone models scaled to four times life-size to lower the flow-inducedvibration frequency were imbedded with fiducial markers in a coronal plane. Candidate markermaterials were tested using static specimens, and two materials, cupric sulfate and glass, werechosen for testing in the vibrating VF models. The vibrating models were imaged using a gatedMRI protocol wherein MRI acquisition was triggered using the subglottal pressure signal. Twodimensionalimage slices at different phases during self-oscillation were captured, and in eachphase the fiducial markers were clearly visible. The process was also demonstrated using a threedimensionalscan at two phases. The benefit of averaging to increase signal-to-noise ratio wasexplored. The results demonstrate the ability to use MRI to acquire quantitative deformation datathat could be used, for example, to validate computational models of flow-induced VF vibrationand quantify deformation fields encountered by cells in bioreactor studies.A low fidelity, two-dimensional, finite element model of VF flow-induced vibration wascoupled with a custom MATLAB-based genetic algorithm optimizer. The objective was to achievea closed quotient within the normal human physiological range. The results showed that changesin geometry and stiffness would lead to a model that exhibited the desired characteristics. Aphysical model based on optimized parameters was then fabricated and the closed quotient wastested. The physical model successfully vibrated with nonzero closed quotient as predicted by thecomputational model.

Degree

College and Department

Ira A. Fulton College of Engineering and Technology; Mechanical Engineering

Rights

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