Computational Solid Mechanics Laboratory, Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, USA.
Pathobiological Sciences Department, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70803, USA.
J Mech Behav Biomed Mater. 2018 Jan;77:24-33. doi: 10.1016/j.jmbbm.2017.08.037. Epub 2017 Sep 1.
Viscoelastic properties of the white matter brain tissue are systematically studied in this paper utilizing indentation experiments, mathematical modeling, and finite element simulation. It is first demonstrated that the internal stiffness of the instrument needs to be thoroughly obtained and incorporated in the analysis as its contribution to the recorded mechanical response is significant for experiments on very compliant materials. The flat-punch monotonic indentation is then performed indirectly on sagittal plane slices with pushing a large rigid coverslip into the sample surface. The recorded load and displacement data are used for calibrating different viscoelastic models and presenting numerical values for the model elements. Consequently, the accuracy of the findings based on the theoretical models is investigated by performing finite element simulations which suggest a considerable substrate effect that causes violation of the semi-infinite half-space assumption in modeling of the material behavior. Accordingly, correction factors for adjusting the viscoelastic constants are obtained and presented. Since the Maxwell model shows a superior capability in rendering the mechanical response of the brain, an extension of this model to Multimode Maxwell viscoelastic solid is proposed for modeling the tissue behavior under a more complex load-hold-unload indentation cycle that shows acceptable agreement with experimental observations.
本文利用压痕实验、数学建模和有限元模拟系统地研究了脑白质组织的黏弹性特性。首先证明了仪器的内部刚度需要彻底获得并纳入分析中,因为其对记录的机械响应的贡献对于非常柔软的材料的实验非常重要。然后,通过将大刚性盖玻片推入样品表面,在矢状面切片上进行扁平冲头单调压痕。记录的载荷和位移数据用于校准不同的黏弹性模型,并给出模型元素的数值。因此,通过进行有限元模拟来研究基于理论模型的发现的准确性,这些模拟表明存在显著的基底效应,这会导致在对材料行为建模时违反半无限半空间假设。因此,获得并提出了用于调整黏弹性常数的校正因子。由于麦克斯韦模型在呈现大脑的力学响应方面具有卓越的能力,因此提出了将该模型扩展到多模式麦克斯韦黏弹性固体,以对更复杂的加载-保持-卸载压痕循环下的组织行为进行建模,该模型与实验观察结果具有良好的一致性。