Computational construction and design optimization of a novel tri-tube heart valve.
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| Title: | Computational construction and design optimization of a novel tri-tube heart valve. |
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| Authors: | Li, Jirong1,2 (AUTHOR), Yu, Yijiang1 (AUTHOR), Tranquillo, Robert T.1,3 (AUTHOR) tranquillo@umn.edu |
| Source: | Biomechanics & Modeling in Mechanobiology. Jun2025, Vol. 24 Issue 3, p1103-1121. 19p. |
| Subjects: | Heart valves, Mathematical optimization, Finite element method, Computational mathematics, Flow simulations |
| Abstract: | A finite-element-based algorithm for the in silico construction of a novel tri-tube heart valve was developed to facilitate optimization of the leaflet geometry. An anisotropic hyperelastic model fitted to high-strain rate planar equibiaxial tension and compression data was used to approximate the nonlinear and anisotropic material behavior of biologically-engineered tubes and simulate valve closure under steady back pressure and steady forward flow. Four metrics were considered to evaluate valve performance in simulated closure: coaptation area, regurgitation area, pinwheel index, and prolapse area. Response surfaces revealed competing objectives between metrics for a valve of target 24 mm diameter in terms of two design parameters, tube diameter and leaflet height. A multi-objective genetic algorithm determined an intermediate tube diameter and leaflet height (16 mm and 11 mm, respectively) of the design space as optimal. Additionally, steady flow simulations were performed using two-way fluid–structure interaction with selected designs to examine washout behind leaflets with particle tracking. One design close to the optimal point for valve closure indicated washout for particles initially distributed behind leaflets. Though comprehensive valve design optimization requires flow analysis over multiple valve cycles to capture all effects associated with flow, this methodology based on diastolic state geometry optimization followed by steady washout analysis reduces the space of design variables for further optimization. [ABSTRACT FROM AUTHOR] |
| Copyright of Biomechanics & Modeling in Mechanobiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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