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Determination of Impedance Boundary Conditions for the Pulmonary Vasculature

Computational modeling can be used to achieve a better understanding of fluid analysis within the pulmonary circulation. Boundary conditions are used in fluid analysis to determine the pressure and flow profiles of the blood as it moves through the lung. Accurate boundary conditions are critical in providing accurate models of blood pressure and blood flow. An important consideration when determining boundary conditions for the pulmonary vasculature is the effect of respiration on the impedance of the pulmonary vasculature. An additional consideration for the pulmonary vasculature is the physiologic differences between the pulmonary circulation and that of the systemic circulation. This research determines impedance boundary conditions for the pulmonary vasculature that reflect the specific geometry of the lung and correspond to maximal inspiration and maximal expiration. The analysis was performed using an existing one-dimensional finite element analysis system. The boundary conditions were defined by a bifurcating structure tree with a number of variables that were used to change the resistance of the pulmonary vessels. The variables within the structure tree were altered to reflect the differences between the pulmonary circulation and the systemic circulation. These variables include the length to radius ratio of the vessels in the structure tree and the asymmetry as the branches. A respiration factor was used to scale the vessels of the structure tree to reflect the effects of respiration on the geometry of the lung. The compliance of the vessels was also changed to reflect the more distensible vessels found in the pulmonary system. The geometry of the lung was defined with the structured tree parameters at maximal inspiration and the respiration factor was used to scale the defined geometry and reflect maximal expiration. The parameters were determined by utilizing an optimization technique. The Levinberg-Marquardt least-squares non-linear optimization algorithm was used to find a set of non-unique optimal parameters. The computed data was validated using measured pressure and flow data collected in a previous study.

Identiferoai:union.ndltd.org:NCSU/oai:NCSU:etd-03282007-001101
Date27 April 2007
CreatorsClipp, Rachel Betany
ContributorsDr. Brooke N. Steele, Dr. Carol Lucas, Dr. Mette Olufsen
PublisherNCSU
Source SetsNorth Carolina State University
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://www.lib.ncsu.edu/theses/available/etd-03282007-001101/
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