A mid-fidelity numerical method for blood flow in deformable vessels

In this work, a novel fluid–structure interaction algorithm for the simulation of blood flow in three-dimensional deformable vessels is addressed. The method extends the mid-fidelity strategy named as Transversally Enriched Pipe Element Method, extensively tested as an efficient approach to simulate...

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Veröffentlicht in:Computer methods in applied mechanics and engineering 2022-03, Vol.392, p.114654, Article 114654
Hauptverfasser: Mansilla Alvarez, L.A., Bulant, C.A., Ares, G.D., Feijóo, R.A., Blanco, P.J.
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Sprache:eng
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Zusammenfassung:In this work, a novel fluid–structure interaction algorithm for the simulation of blood flow in three-dimensional deformable vessels is addressed. The method extends the mid-fidelity strategy named as Transversally Enriched Pipe Element Method, extensively tested as an efficient approach to simulate the blood flow under rigid wall hypothesis, by taking into account the distensibility of the lumen boundary by means of an independent ring structural model. The Navier–Stokes equations, in Arbitrary Lagrangian–Eulerian framework, are used as the governing equations for the blood flow dynamics, the vessel wall mechanics is represented through an elastic constitutive law, and the fluid domain deformation problem is explicitly solved by exploiting the layered structure of the geometry discretization associated to the mid-fidelity model. The result is an approximation strategy able to take into account the wall deformation at nearly zero added cost when compared with a rigid wall model. An extensive numerical validation and verification of the proposed methodology is reported employing simple domains and complex patient-specific geometries to highlight the potential for real applications. •Fluid–structure coupling is mandatory for modeling large vessels.•The TEPEM is extended for FSI by considering an independent ring structural model.•This model incorporate the fluid–structure interaction at zero added cost.•This strategy is an efficient alternative for expensive high-fidelity models.
ISSN:0045-7825
1879-2138
DOI:10.1016/j.cma.2022.114654