Study and Characterization of Small Diameter Woven Tubular Fabrics

medical textiles;textile biomaterials;artificial arteries;vascular grafts;arterial grafts;tubular structures

Moghe, Ajit Keshav ; Dr. Bhupender S. Gupta, Committee Chair,Dr. Marian G. McCord, Committee Member,Dr. Peter L. Mente, Committee Member,Moghe, Ajit Keshav ; Dr. Bhupender S. Gupta ; Committee Chair ; Dr. Marian G. McCord ; Committee Member ; Dr. Peter L. Mente ; Committee Member

University:North Carolina State University

关键词: medical textiles;    textile biomaterials;    artificial arteries;    vascular grafts;    arterial grafts;    tubular structures;   

Others  :  https://repository.lib.ncsu.edu/bitstream/handle/1840.16/1468/etd.pdf?sequence=1&isAllowed=y

美国|英语

来源: null

【 摘 要 】

Woven tubular structures have been used since 1950s as vascular grafts in repairing damaged or diseased arteries and veins. The grafts for large caliber blood vessels have achieved some success, however, an ideal structure for small diameter artery replacement is yet to be developed. Lack of optimum elastic properties has been a major cause for the failure of these structures. In the present work, woven tubes in diameters ranging from 1.5 to 7.5 mm are developed using a narrow width Muller loom. The materials used are textured Polyester multifilament yarns of different sizes (70, 100 & 150 denier) and the structures developed are plain but with different degrees of tightness. The pick density is varied from 28 to 44 picks per inch and end density is varied by using two different levels of denting order (2 and 4 ends per dent). The diameters of the tubular structures are varied by using different number of warp yarns (38, 44 & 50). Accordingly, the experimental work in this thesis involved weaving of 54 different tubular structures and examining their behavior. The effects of structural variables on the size and the mechanical properties of the grafts are studied.Statistical analysis of variance is conducted to identify significant effects and develop predictive models in several instances.