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时变叠加的应用 - 第二部分:脑组织频变行为的预测。

Application of the time-strain superposition - Part II: Prediction of the frequency-dependent behaviour of brain tissue.

机构信息

University of Novo mesto Faculty of mechanical engineering, Na Loko 2, 8000 Novo mesto, Slovenia.

出版信息

J Mech Behav Biomed Mater. 2018 Oct;86:325-335. doi: 10.1016/j.jmbbm.2018.07.007. Epub 2018 Jul 4.

DOI:10.1016/j.jmbbm.2018.07.007
PMID:30007181
Abstract

Knowing the real material properties of brain tissue is of great importance when it comes to the precise prediction of its mechanical response. The efficiency of these procedures depends on the adequacy of experimental data and the analytical and numerical tools utilized. In this study, we combine existing approaches within the theory of viscoelasticity in order to predict the frequency-dependent behaviour of the porcine brain from the known stress relaxation data. Time-strain superposition is applied to the brain shear relaxation segments for the construction of the long-term master curve in the linear viscoelastic range. A widely-used and well-established numerical procedure is then utilized for the prediction of the frequency-dependent modulus based on the constructed master curve. The demonstrated methodology is evaluated using the porcine brain experimental data available from the literature. The results show reasonably good agreement between the predicted and the previously measured and published storage modulus data in the whole frequency range investigated. On the other hand, prediction of the loss modulus is only possible within certain frequency ranges related to the time frame of experimentally known relaxation behaviour. Nevertheless, the outcomes of the paper speak in favour of the validity of the linear viscoelastic interconversion relations between the time- and frequency-dependent material functions of the porcine brain tissue exposed to strain up to the tissue's linear viscoelastic limit.

摘要

当涉及到对脑组织机械响应的精确预测时,了解脑组织的真实材料特性非常重要。这些过程的效率取决于实验数据的充分性以及所使用的分析和数值工具。在这项研究中,我们结合了粘弹性理论中的现有方法,以便根据已知的应力松弛数据来预测猪脑的频率相关行为。时-应变叠加应用于脑剪切松弛段,以便在线性粘弹性范围内构建长期主曲线。然后,利用一种广泛使用且成熟的数值方法,基于构建的主曲线来预测频率相关的模量。所展示的方法使用文献中可获得的猪脑实验数据进行了评估。结果表明,在整个研究的频率范围内,预测的存储模量数据与之前测量和发表的存储模量数据之间具有相当好的一致性。另一方面,损耗模量的预测仅在与实验上已知的松弛行为时间范围相关的某些频率范围内才有可能。尽管如此,本文的结果还是支持了在所研究的应变范围内直到组织的线性粘弹性极限,猪脑组织的时变和频变材料函数之间的线性粘弹性转换关系的有效性。

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