A two-parameter strain energy function for brain matter: An extension of the Hencky model to incorporate locking

Q3 Engineering Brain multiphysics Pub Date : 2021-01-01 DOI:10.1016/j.brain.2021.100036
Luis Saucedo-Mora , Olatz García-Bañales , Francisco Javier Montáns , José María Benítez
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引用次数: 1

Abstract

By just replacing the infinitesimal strains by logarithmic strains, the Hencky strain energy has proven to extend successfully the infinitesimal framework to moderately large strains, as those found in brain. However, as polymers and soft tissues, brain presents an important strain-stiffening towards locking. Based on both observations, in this paper we propose a simple two-parameter isotropic strain energy function for representing the inviscid (conservative) behavior of brain matter. The two parameters of the model are the Young modulus (or alternatively the shear modulus) and the locking stretch during a test. Through a comparison with experimental data, we show that with this simple model, employing the two material parameters directly measured from a tensile test, we capture the qualitative aspects and quantitative behavior of brain mater in tension, compression and simple shear tests with good accuracy.

Statement of Significance

This paper shows a simple mathematical model capable of reproducing qualitative aspects and quantitative behavior of brain matter in tension, compression and simple shear tests with good accuracy. The model is governed by only two parameters, namely Young's modulus (or alternatively the shear modulus) and the locking stretch.

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脑物质的双参数应变能函数:亨基模型的扩展,以纳入锁定
通过用对数应变替换无限小的应变,henky应变能已被证明成功地将无限小的框架扩展到中等大的应变,就像在大脑中发现的那样。然而,正如聚合物和软组织一样,大脑呈现出一种重要的应变-向锁定方向硬化。基于这两个观察结果,本文提出了一个简单的双参数各向同性应变能函数来表示脑物质的非粘(保守)行为。模型的两个参数是杨氏模量(或者说是剪切模量)和测试期间的锁定拉伸。通过与实验数据的对比,表明该简单模型采用从拉伸试验中直接测得的两种材料参数,能够较准确地捕捉脑膜在拉伸、压缩和简单剪切试验中的定性方面和定量行为。本文给出了一个简单的数学模型,能够很准确地再现脑物质在拉伸、压缩和简单剪切试验中的定性方面和定量行为。该模型仅由两个参数控制,即杨氏模量(或剪切模量)和锁定拉伸。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Brain multiphysics
Brain multiphysics Physics and Astronomy (General), Modelling and Simulation, Neuroscience (General), Biomedical Engineering
CiteScore
4.80
自引率
0.00%
发文量
0
审稿时长
68 days
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