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各种本构模型对动脉组织的预测能力。

Predictive capabilities of various constitutive models for arterial tissue.

机构信息

Department of Biofluid Mechanics, Technical University of Applied Sciences (OTH), Regensburg, Germany; Regensburg Center of Biomedical Engineering (RCBE), OTH and Universität Regensburg, Josef Engert Strasse 9, Biopark I, 93053 Regensburg, Germany.

Institute of Solid Mechanics, Mechatronics and Biomechanics, Brno University of Technology, Technicka 2896/2, 616 69 Brno, Czech Republic; Department of Applied Mechanics, VSB-Technical University Ostrava, 17.listopadu 15/2172, 708 33 Ostrava-Poruba, Czech Republic.

出版信息

J Mech Behav Biomed Mater. 2018 Feb;78:369-380. doi: 10.1016/j.jmbbm.2017.11.035. Epub 2017 Nov 22.

Abstract

INTRODUCTION

Aim of this study is to validate some constitutive models by assessing their capabilities in describing and predicting uniaxial and biaxial behavior of porcine aortic tissue.

METHODS

14 samples from porcine aortas were used to perform 2 uniaxial and 5 biaxial tensile tests. Transversal strains were furthermore stored for uniaxial data. The experimental data were fitted by four constitutive models: Holzapfel-Gasser-Ogden model (HGO), model based on generalized structure tensor (GST), Four-Fiber-Family model (FFF) and Microfiber model. Fitting was performed to uniaxial and biaxial data sets separately and descriptive capabilities of the models were compared. Their predictive capabilities were assessed in two ways. Firstly each model was fitted to biaxial data and its accuracy (in term of R and NRMSE) in prediction of both uniaxial responses was evaluated. Then this procedure was performed conversely: each model was fitted to both uniaxial tests and its accuracy in prediction of 5 biaxial responses was observed.

RESULTS

Descriptive capabilities of all models were excellent. In predicting uniaxial response from biaxial data, microfiber model was the most accurate while the other models showed also reasonable accuracy. Microfiber and FFF models were capable to reasonably predict biaxial responses from uniaxial data while HGO and GST models failed completely in this task.

CONCLUSIONS

HGO and GST models are not capable to predict biaxial arterial wall behavior while FFF model is the most robust of the investigated constitutive models. Knowledge of transversal strains in uniaxial tests improves robustness of constitutive models.

摘要

简介

本研究的目的是通过评估它们在描述和预测猪主动脉组织的单轴和双轴行为方面的能力来验证一些本构模型。

方法

使用来自猪主动脉的 14 个样本进行了 2 个单轴和 5 个双轴拉伸测试。进一步存储了横向应变以用于单轴数据。实验数据通过四个本构模型进行拟合: Holzapfel-Gasser-Ogden 模型(HGO)、基于广义结构张量的模型(GST)、四纤维族模型(FFF)和微纤维模型。分别对单轴和双轴数据集进行拟合,并比较了模型的描述能力。以两种方式评估了它们的预测能力。首先,将每个模型拟合到双轴数据中,并评估其在预测两个单轴响应中的准确性(以 R 和 NRMSE 表示)。然后,以相反的方式进行此过程:将每个模型拟合到两个单轴测试中,并观察其在预测 5 个双轴响应中的准确性。

结果

所有模型的描述能力都非常出色。在从双轴数据预测单轴响应时,微纤维模型最准确,而其他模型也表现出合理的准确性。微纤维和 FFF 模型能够从单轴数据合理地预测双轴响应,而 HGO 和 GST 模型完全无法完成此任务。

结论

HGO 和 GST 模型无法预测双轴动脉壁行为,而 FFF 模型是研究的本构模型中最稳健的。在单轴测试中了解横向应变可以提高本构模型的稳健性。

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