Nanoindentation of hyperelastic polymer layers at finite deformation and parameter re-identification
Nanoindentation of hyperelastic polymer layers at finite deformation and parameter re-identification
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DOI：
10.1007/s00419-012-0613-9
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发表时间：
2012-02
影响因子：
2.8
通讯作者：
Zhaoyu Chen;S. Diebels
中科院分区：
文献类型：
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作者：
Zhaoyu Chen;S. Diebels
基底上的薄聚合物层在重要领域具有广泛的应用。然而，用传统的测试方法无法测量其力学性能。近年来，纳米压痕技术成为一种新兴的、主要的薄层测试技术。在目前的工作中，接触力学和超弹性材料的有限元模型的基础上，聚合物层的纳米压痕模拟与有限元代码ABAQUS®。研究了三种常用的超弹性模型，即neo-Hookean模型、Mooney-Rivlin模型和Yeoh模型。这三个模型的行为进行了比较，彼此在不同的边界值问题的纳米压痕，以得到一些不同的行为下的各种超弹性模型的纳米压痕的感觉。与传统的分析方法相比，该方法不对穿透深度进行限制，避免了基底的影响。基于生物进化原理，提出了一种参数重识别策略，对材料模型进行了小变形和有限变形下的参数提取。此外，它是调查多大的渗透深度必须选择，以区分不同的模型，在参考的荷载-位移曲线。最后，讨论了用基于新胡克模型的相对简单的方法来描述由非线性复杂模型获得的数据的可能性。
Thin polymer layers on substrates have a wide range of application in important areas. However, it is impossible to measure the mechanical properties with the traditional testing methods. Recently, nanoindentation became a new but primary testing technique of thin layers. In the present work, based on a finite element model of contact mechanics and hyperelastic materials, nanoindentation of polymer layers is simulated with the finite element code ABAQUS®. Three often used hyperelastic models, that is, the neo-Hookean, Mooney–Rivlin and Yeoh models are investigated. The behaviour of these three models is compared to each other in different boundary value problems of nanoindentation in order to get some feeling of the different behaviour of various hyperelastic models under nanoindentation. In contrast to the traditional analytical method, the penetration depth is not restrained to avoid the influence of the substrate. A parameter re-identification strategy is employed to extract the parameters of the material models at small and finite deformation based on the principle of biological evolution. Furthermore, it is investigated how large the penetration depth has to be chosen in order to distinguish different models in reference to the load–displacement curves. Finally, the possibility is discussed of describing the data obtained by a non-linear complex model using the relatively simple approach based on the neo-Hookean model.