首页 | 本学科首页   官方微博 | 高级检索  
检索        


The Use of Finite Element Methods and Genetic Algorithms in Search of an Optimal Fabric Reinforced Porous Graft System
Authors:M S Yeoman  B D Reddy  H C Bowles  P Zilla  D Bezuidenhout and T Franz
Institution:(1) Centre for Research in Computational and Applied Mechanics, University of Cape Town, Rondebosch, South Africa;(2) Finite Element Analysis Services, Cape Town, South Africa;(3) Cardiovascular Research Unit, Chris Barnard Department of Cardiothoracic Surgery, Faculty of Health Sciences, University of Cape Town, Private Bag X3, Observatory, 7935, South Africa;
Abstract:The mechanics of arteries result from the properties of the soft tissue constituents and the interaction of the wall layers, predominantly media and adventitia. This concept was adopted in this study for the design of a tissue regenerative vascular graft. To achieve the desired structural properties of the graft, most importantly a diametric compliance of 6%/100 mmHg, finite element methods and genetic algorithms were used in an integrated approach to identify the mechanical properties of an adventitial fabric layer that were required to optimally complement an intimal/medial polyurethane layer with interconnected porosity of three different size classes. The models predicted a compliance of 16.0, 19.2, and 31.5%/100 mmHg for the non-reinforced grafts and 5.3, 5.5, and 6.0%/100 mmHg for the fabric-reinforced grafts. The latter, featuring fabrics manufactured according to the required non-linear mechanical characteristics numerically predicted, exhibited an in vitro compliance of 2.1 ± 0.8, 3.0 ± 2.4, and 4.0 ± 0.7% /100 mmHg. The combination of finite element methods and genetic algorithms was shown to be able to successfully optimize the mechanical design of the composite graft. The method offers potential for the application to alternative concepts of modular vascular grafts and the incorporation of tissue ingrowth and biodegradation.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号