A new viscoelastic model for human brain tissue using Lode invariants based rate-type thermodynamic framework

IF 2.2 Q2 ENGINEERING, MULTIDISCIPLINARY
Durga Prasad, P. Sreejith, K. Kannan
{"title":"A new viscoelastic model for human brain tissue using Lode invariants based rate-type thermodynamic framework","authors":"Durga Prasad,&nbsp;P. Sreejith,&nbsp;K. Kannan","doi":"10.1016/j.apples.2023.100130","DOIUrl":null,"url":null,"abstract":"<div><p>We develop new rate-type constitutive relations on a set of orthonormal tensor basis and the corresponding set of Lode invariants, which require only 9 material parameters to predict the mechanical response of the human brain tissue. The mode-dependent response of the tissue is captured by invoking the Hill-stable elastic potential of Prasad and Kannan (2020) and constructing a new form for the rate of dissipation, thus introducing the mode-of-deformation dependent modulus terms and the mode-of-deformation-rate dependent viscosities into the rate-type thermodynamic framework of Rajagopal and Srinivasa (2000). Through the analysis-driven construction of the rate of dissipation, we incorporate maximum change in the viscosities with respect to the mode-of-deformation rates and limit the number of material parameters. Our model satisfactorily predicts the complicated load-unload cycles (pre-conditioned and conditioned) and the stress relaxation data under multiple modes of deformation and multiple rates for the Corona Radiata (CR) region of the brain tissue. It also captures the tension–compression asymmetry in the response and the higher relaxation time in compression loading than in shear loading.</p></div>","PeriodicalId":72251,"journal":{"name":"Applications in engineering science","volume":"15 ","pages":"Article 100130"},"PeriodicalIF":2.2000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applications in engineering science","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666496823000055","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

We develop new rate-type constitutive relations on a set of orthonormal tensor basis and the corresponding set of Lode invariants, which require only 9 material parameters to predict the mechanical response of the human brain tissue. The mode-dependent response of the tissue is captured by invoking the Hill-stable elastic potential of Prasad and Kannan (2020) and constructing a new form for the rate of dissipation, thus introducing the mode-of-deformation dependent modulus terms and the mode-of-deformation-rate dependent viscosities into the rate-type thermodynamic framework of Rajagopal and Srinivasa (2000). Through the analysis-driven construction of the rate of dissipation, we incorporate maximum change in the viscosities with respect to the mode-of-deformation rates and limit the number of material parameters. Our model satisfactorily predicts the complicated load-unload cycles (pre-conditioned and conditioned) and the stress relaxation data under multiple modes of deformation and multiple rates for the Corona Radiata (CR) region of the brain tissue. It also captures the tension–compression asymmetry in the response and the higher relaxation time in compression loading than in shear loading.

基于速率型热力学框架的Lode不变量的人脑组织粘弹性模型
我们在一组正交张量基础上开发了新的速率型本构关系和相应的Lode不变量集,它们只需要9个材料参数就可以预测人脑组织的机械响应。通过调用Prasad和Kannan(2020)的Hill稳定弹性势并构建耗散率的新形式来捕捉组织的模式相关响应,从而将变形相关模量项的模式和变形速率相关粘度的模式引入Rajagopal和Srinivasa(2000)的速率型热力学框架中。通过分析驱动的耗散率结构,我们结合了粘度相对于变形率模式的最大变化,并限制了材料参数的数量。我们的模型令人满意地预测了脑组织电晕辐射(CR)区域在多种变形模式和多种速率下的复杂加载-卸载循环(预处理和条件处理)和应力松弛数据。它还捕捉到了响应中的拉伸-压缩不对称性,以及压缩载荷中比剪切载荷中更高的弛豫时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Applications in engineering science
Applications in engineering science Mechanical Engineering
CiteScore
3.60
自引率
0.00%
发文量
0
审稿时长
68 days
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信