生物软组织各向异性超弹性本构模型的研究进展
An in silico-based review on anisotropic hyperelastic constitutive models for soft biological tissues
摘要：
我们回顾了九个不变的和分散型各向异性超弹性本构模型的基础上，他们的拟合性能的实验数据从三个不同的人体组织的软生物组织。为此，我们使用了混合多目标最优化过程。设计了一种遗传算法来生成初始猜测，然后是基于梯度的搜索算法。本构模型，然后适合于一组单轴和双轴拉伸实验进行不同的纤维取向的组织。对于计算机模拟研究，使用了对血管性腹主动脉、白线和腹直肌鞘组织进行的实验。因此，模型相对于客观的归一化拟合质量度量进行排名。最后，对各模型的拟合性能进行了详细的讨论。这项工作提供了一个有价值的定量比较各种各向异性超弹性模型，其研究结果可以帮助那些建模的软组织的行为在选择最佳的本构模型，为他们的特定应用。
英文摘要：
We review nine invariant and dispersion-type anisotropic hyperelastic constitutive models for soft biological tissues based on their fitting performance to experimental data from three different human tissues. For this, we used a hybrid multi-objective optimization procedure. A genetic algorithm is devised to generate the initial guesses followed by a gradient-based search algorithm. The constitutive models are then fit to a set of uniaxial and biaxial tension experiments conducted on tissues with differing fiber orientations. For the in silico investigation, experiments conducted on aneurysmatic abdominal aorta, linea alba, and rectus sheath tissues are utilized. Accordingly, the models are ranked with respect to an objec tive normalized quality of fit metric. Finally, a detailed discussion is carried out on the fitting performance of each model. This work provides a valuable quantitative comparison of various anisotropic hyperelastic models, the findings of which can aid those modeling the behavior of soft tissues in selecting the best constitutive model for their particular application.
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