4.5 Article

Modeling of braided stents: Comparison of geometry reconstruction and contact strategies

期刊

JOURNAL OF BIOMECHANICS
卷 107, 期 -, 页码 -

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ELSEVIER SCI LTD
DOI: 10.1016/j.jbiomech.2020.109841

关键词

Self-expandable stent; Nitinol; Finite element analysis; 3D parametric equations; Wire interaction

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Braided stents are self-expandable devices widely used in many different clinical applications. In-silico methods could be a useful tool to improve the design stage and preoperative planning; however, numerical modeling of braided structures is not trivial. The geometries are often challenging, and a parametric representation is not always easily achieved. Moreover, in the literature, different options have been proposed to handle the contact among the wires, but an extensive comparison of these modeling techniques is missing. In this work, both the geometry and contact issues are discussed. Firstly, an effective strategy based on parametric equations to draw complex braided geometries is illustrated and exploited to build three beam meshes resembling commercial devices. Secondly, three finite element simulations (bending, crimping and confined release) were carried out to compare simplified contact techniques involving connector elements with the more realistic but computationally expensive option based on the general contact algorithm, which has already been validated in the literature through comparisons with experimental results. Both local (stress distribution) and global quantities (forces/displacements) were analyzed. The results obtained using the connectors are significantly affected by wire interpenetrations and over-constraint. The percentage errors reached considerably high values, exceeding 100% in the confined release test and 50% in the remaining cases study. Moreover, the errors do not show uniform trends but vary according to the stent geometry, boundary conditions, connector type and investigated entity, suggesting that it is not possible to replace the use of the general contact algorithm with simplified approaches. (C) 2020 Elsevier Ltd. All rights reserved.

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