Ndlovu Zwelihle, Desai Dawood, Pandelani Thanyani, Ngwangwa Harry, Nemavhola Fulufhelo
Unisa Biomedical Engineering Research Group, Department of Mechanical Engineering, School of Engineering, College of Science Engineering and Technology, University of South Africa, Pretoria 0001, South Africa.
Department of Mechanical and Mechatronics Engineering, Faculty of Engineering and Built Environment, Tshwane University of Technology, South Africa.
Appl Bionics Biomech. 2022 Feb 28;2022:4775595. doi: 10.1155/2022/4775595. eCollection 2022.
This study assesses the modelling capabilities of four constitutive hyperelastic material models to fit the experimental data of the porcine sclera soft tissue. It further estimates the material parameters and discusses their applicability to a finite element model by examining the statistical dispersion measured through the standard deviation. Fifteen sclera tissues were harvested from porcine' slaughtered at an abattoir and were subjected to equi-biaxial testing. The results show that all the four material models yielded very good correlations at correlations above 96%. The polynomial (anisotropic) model gave the best correlation of 98%. However, the estimated material parameters varied widely from one test to another such that there would be need to normalise the test data to avoid long optimisation processes after applying the average material parameters to finite element models. However, for application of the estimated material parameters to finite element models, there would be need to consider normalising the test data to reduce the search region for the optimisation algorithms. Although the polynomial (anisotropic) model yielded the best correlation, it was found that the Choi-Vito had the least variation in the estimated material parameters, thereby making it an easier option for application of its material parameters to a finite element model and requiring minimum effort in the optimisation procedure. For the porcine sclera tissue, it was found that the anisotropy was more influenced by the fiber-related properties than the background material matrix-related properties.
本研究评估了四种本构超弹性材料模型对猪巩膜软组织实验数据的拟合能力。通过检查标准偏差测量的统计离散度,进一步估计了材料参数,并讨论了它们在有限元模型中的适用性。从屠宰场宰杀的猪身上采集了15个巩膜组织,并进行了等双轴测试。结果表明,所有四种材料模型在相关性高于96%时都产生了非常好的相关性。多项式(各向异性)模型的相关性最佳,为98%。然而,估计的材料参数在一次测试到另一次测试之间变化很大,因此在将平均材料参数应用于有限元模型后,需要对测试数据进行归一化,以避免长时间的优化过程。然而,为了将估计的材料参数应用于有限元模型,需要考虑对测试数据进行归一化,以减少优化算法的搜索区域。虽然多项式(各向异性)模型产生了最佳相关性,但发现Choi-Vito模型估计的材料参数变化最小,因此将其材料参数应用于有限元模型更容易,并且在优化过程中需要的工作量最小。对于猪巩膜组织,发现各向异性受纤维相关特性的影响比背景材料基质相关特性的影响更大。