Aorta zero-stress state modeling with T-spline discretization

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dc.citation.journalTitleComputational Mechanicsen_US
dc.contributor.authorSasaki, Takafumien_US
dc.contributor.authorTakizawa, Kenjien_US
dc.contributor.authorTezduyar, Tayfun E.en_US
dc.date.accessioned2019-01-08T15:37:43Zen_US
dc.date.available2019-01-08T15:37:43Zen_US
dc.date.issued2018en_US
dc.description.abstractThe image-based arterial geometries used in patient-specific arterial fluid–structure interaction (FSI) computations, such as aorta FSI computations, do not come from the zero-stress state (ZSS) of the artery. We propose a method for estimating the ZSS required in the computations. Our estimate is based on T-spline discretization of the arterial wall and is in the form of integration-point-based ZSS (IPBZSS). The method has two main components. (1) An iterative method, which starts with a calculated initial guess, is used for computing the IPBZSS such that when a given pressure load is applied, the image-based target shape is matched. (2) A method, which is based on the shell model of the artery, is used for calculating the initial guess. The T-spline discretization enables dealing with complex arterial geometries, such as an aorta model with branches, while retaining the desirable features of isogeometric discretization. With higher-order basis functions of the isogeometric discretization, we may be able to achieve a similar level of accuracy as with the linear basis functions, but using larger-size and much fewer elements. In addition, the higher-order basis functions allow representation of more complex shapes within an element. The IPBZSS is a convenient representation of the ZSS because with isogeometric discretization, especially with T-spline discretization, specifying conditions at integration points is more straightforward than imposing conditions on control points. Calculating the initial guess based on the shell model of the artery results in a more realistic initial guess. To show how the new ZSS estimation method performs, we first present 3D test computations with a Y-shaped tube. Then we show a 3D computation where the target geometry is coming from medical image of a human aorta, and we include the branches in our model.en_US
dc.identifier.citationSasaki, Takafumi, Takizawa, Kenji and Tezduyar, Tayfun E.. "Aorta zero-stress state modeling with T-spline discretization." <i>Computational Mechanics,</i> (2018) Springer: https://doi.org/10.1007/s00466-018-1651-0.en_US
dc.identifier.digitalSasaki2018en_US
dc.identifier.doihttps://doi.org/10.1007/s00466-018-1651-0en_US
dc.identifier.urihttps://hdl.handle.net/1911/104977en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.titleAorta zero-stress state modeling with T-spline discretizationen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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