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A compressible hyper-viscoelastic material constitutive model for human brain tissue and the identification of its parameters

机译:人脑组织的可压缩超粘弹性材料本构模型及其参数确定

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摘要

In this paper, we have introduced a compressible hyper-viscoelastic constitutive model for human brain tissue. The model is calibrated with the reported experimental data from different regions of the brain. The parameters of the model are determined in a simultaneous calibration for tension, compression, shear, and compression-relaxation tests data. They are obtained in an iterative procedure in conjunction with a finite elements (FE) modeling of the tissue, as well as, with the Nelder-Mead Simplex optimization procedure. In the calibration procedure, the compressibility of the material is taken into account, and the respective time-dependent volumetric parameter is also determined. Additionally, the Drucker stability condition is enforced to assess the physical meaning of the extracted constitutive parameters. This proposed model provides an improved prediction of the experimental data and tissue response under various loading conditions. The results show that, under inhomogeneous deformation, the suggested approach will lead to a better material calibration of brain tissue compared to the simple mathematical model fitting.
机译:在本文中,我们介绍了用于人脑组织的可压缩超粘弹性本构模型。使用来自大脑不同区域的报告实验数据对模型进行校准。该模型的参数是在同时校准中确定张力,压缩,剪切和压缩松弛测试数据的参数。它们是通过迭代过程与组织的有限元(FE)建模以及Nelder-Mead Simplex优化过程结合而获得的。在校准过程中,考虑了材料的可压缩性,并且还确定了各个随时间变化的体积参数。此外,强制执行Drucker稳定性条件以评估提取的本构参数的物理意义。该提出的模型提供了在各种负荷条件下对实验数据和组织反应的改进预测。结果表明,与简单的数学模型拟合相比,在不均匀变形下,建议的方法将导致对脑组织的更好的材料校准。

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