DescriptionAtherosclerosis and Cardiovascular disease make up the leading cause of death in the United States. The disease occurs when plaque develops on lesions in the arterial lumen causing narrowing and hardening of the vessel walls. When the lumen cross-sectional area continues to decrease, the velocity of blood increases eventually becoming turbulent. This blood flow turbulence is believed to produce a sound in the occluded artery known as a bruit. Carotid auscultations are considered the golden standard for stenosis screening. However, recent studies suggest this is a poor predictor of carotid stenosis (sensitivity: 11% -51%). There are inaccuracies in relationships between vascular bruits and severity of the disease. Bruits can be missed due to loud sounds produced in the arteries and may be out of the range of human hearing. Therefore, an understanding of the fluid dynamics of diseased arteries will provide more accurate noninvasive methods for detecting and classifying arterial stenosis. This thesis proposes that physical models may be used to simulate the fluid dynamics of the diseased artery. In this research, experiments were conducted on three physical models that represent different geometries of stenosis. The models consisted of latex tubing with a bending modulus and cross-sectional area similar to a carotid artery in situ. A constant mean flow was passed through the lumen of the models, and the wall displacements and sounds produced were obtained and analyzed. The recording devices consisted of a piezoelectric material, optical sensor, and electronic stethoscope. The results show that stenosis facing a flexible wall produces greater wall vibrations than a symmetrical rigid stenosis. It was found that increasing the length of a plaque dome results in higher frequencies. The Continuous Wavelet Transforms (CWTs) of the measurements showed that stenosis with rigid symmetry reduces the amount of wall motion and sounds produced in time. The models have shown that wall motion is affected by stenotic geometries and thus provides a useful approach to the study of fluid dynamics of vascular disease. These relationships can be used to increase the sensitivity of classifying and detecting the structure of stenosis using noninvasive devices.