持续性高过载下人脑的多孔弹性响应

田金; 刘少宝; 卢天健; 徐峰

doi:10.21656/1000-0887.450130

持续性高过载下人脑的多孔弹性响应

doi: 10.21656/1000-0887.450130

田金^{1, 2, 3,},
刘少宝^{4, 5},
卢天健^{4, 5},
徐峰^{2, 3, ,}

1.
西安交通大学第二附属医院，西安 710061
2.
西安交通大学生命科学与技术学院生物医学信息工程教育部重点实验室，西安 710049
3.
西安交通大学仿生工程与生物力学研究所，西安 710049
4.
南京航空航天大学航空航天结构力学及控制全国重点实验室，南京 210016
5.
南京航空航天大学多功能轻量化材料与结构工信部重点实验室，南京 210016

(我刊编委刘少宝、卢天健来稿)

详细信息

作者简介:
田金(1993—)，男，助理教授，博士(E-mail: jintian@xjtu.edu.cn)

通讯作者:
徐峰(1980—)，男，教授，博士，博士生导师(通讯作者. E-mail: fengxu@mail.xjtu.edu.cn)

中图分类号: O34
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- 文章访问数: 120
- HTML全文浏览量: 49
- PDF下载量: 35
- 被引次数: 0
出版历程
- 收稿日期: 2024-05-09
- 修回日期: 2024-05-20
- 刊出日期: 2024-06-01

Poroelastic Responses of Human Brain Under Sustained High Overloads

TIAN Jin^{1, 2, 3
,},
LIU Shaobao^{4, 5},
LU Tianjian^{4, 5},
XU Feng^{2, 3
, ,}

1.
The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, P.R. China
2.
Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P.R.China
3.
Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an 710049, P.R.China
4.
State Key Laboratory of Mechanics and Control for Aerospace Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P.R.China
5.
MIIT Key Laboratory of Multifunctional Lightweight Materials and Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P.R.China

(Contributed by LIU Shaobao, LU Tianjian, M. AMM Editorial Board)

摘要

摘要:
航空航天飞行期间经常出现的持续性高过载，对乘员的脑功能有重要影响，而脑功能受脑组织力学行为的影响，且后者与载荷特点高度相关.为预测持续性高过载下的人脑力学响应，该文采用多孔弹性本构描述了脑组织的力学行为，基于简化的头部一维多层结构模型，推导了脑组织的多孔弹性控制方程、状态量传递矩阵，利用Laplace变换及其逆变换，得到了颅内液体压力、颅内液体渗流速度、脑组织有效应力、脑组织位移的时空分布.结果表明，颅内液体渗流对脑组织在持续性高过荷下的响应有显著影响.该文强调采用多孔弹性本构描述脑组织力学行为的适切性和必要性，为极端载荷条件下人脑生物力学响应研究提供了重要的理论见解.
- 脑组织力学响应 /
- 持续性高过载 /
- 多孔弹性本构
Abstract:
Sustained high overloads often acting during aerospace flights can significantly affect the passenger brain function dependent on the mechanical behavior of brain tissue and highly correlated with load characteristics. To predict the mechanical responses of human brain under sustained high overloads, the poroelastic constitutive model was adopted to characterize the mechanical behaviors of brain tissue. Built on an idealized 1D multi-layer structural model for human heads, the poroelastic control equation and the state transfer matrix for the brain tissue were derived. Through the Laplace transform and its inverse transform, the spatiotemporal distribution of the intracranial fluid pressure, the intracranial fluid seepage velocity, the brain tissue effective stress, and the brain tissue displacement were obtained. The results indicate that, the intracranial fluid infiltration has a significant impact on the responses of the brain tissue under sustained high overloads. The present work emphasizes the appropriateness and necessity of using poroelastic constitutive models to describe the mechanical behavior of brain tissue, providing important theoretical insights for the study of brain biomechanics under extreme load conditions.
- brain tissue mechanical response /
- sustained high overload /
- poroelastic constitutive model
edited-by

edited-by
注释:

1) (我刊编委刘少宝、卢天健来稿)

HTML全文

图 1 头部结构及其简化模型

Figure 1. The head structure and its simplified model

下载: 全尺寸图片幻灯片

图 2 多孔弹性介质的微元体

Figure 2. The microelement of the poroelastic medium

下载: 全尺寸图片幻灯片

图 3 脑组织内代表点响应量随时间的分布

Figure 3. Temporal distributions of response variables for representative points in brain tissue

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图 4 达到稳定状态后，不同量值过载引起的响应量随位置的分布

Figure 4. Under overloads with varying magnitudes, spatial distributions of response variables in stable states

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图 5 脑组织取不同弹性模量时各响应量随时间、空间的分布

Figure 5. Temporal and spatial distributions of response variables for brain tissue with varying elastic moduli

下载: 全尺寸图片幻灯片

图 6 过载和弹性模量对脑组织变形和液体分布的影响

Figure 6. Effects of the overload magnitude and the elastic modulus on the brain tissue deformation and the liquid distribution

下载: 全尺寸图片幻灯片

图 7 脑组织取不同渗透系数时各响应量随时间、空间的分布曲线

Figure 7. Temporal and spatial distributions of response variables for the brain tissue with varying permeability coefficients

下载: 全尺寸图片幻灯片

表 1 头部各层结构的材料参数^[13-15]

Table 1. Material parameters of the layers of the head structure^[13-15]

part	density ρ/(kg·m^-3)	elastic modulus E/MPa	Poisson’s ratio υ
skin	1 200	16.7	0.42
trabecular bone	2 000	15 000	0.22
cancellous bone	1 300	1 000	0.24
dura mater	1 130	31.5	0.45
arachnoid	1 130	22.0	0.45
pia mater	1 130	11.5	0.45
brain tissue	1 060	3.5×10^-4	0.35

下载: 导出CSV

表 2 一维头部模型中的参数

Table 2. Parameters in one-dimensional head model

model parameter	symbol	value	reference
cerebrospinal fluid density	ρ_f/(kg·m^-3)	1 000	estimate
brain tissue solid skeleton density	ρ_sb/(kg·m^-3)	1 060	[14]
brain tissue elastic modulus	E_b/Pa	350	[15]
brain tissue porosity	n_b	0.2	[18]
brain tissue permeability coefficient	κ_b/(m·s^-1)	1.59×10^-7	[19]
meningeal density	ρ_sm/(kg·m^-3)	1 130	[13]
meningeal elastic modulus	E_m/MPa	31.5	[13]
meningeal porosity	n_m	0.2	estimate according to [18]
meningeal permeability coefficient	κ_m/(m·s^-1)	1×10^-7	estimate according to [19]
gravitational acceleration	g/(m·s^-2)	9.8	common knowledge
upper meningeal layer thickness	ΔH₁/mm	0.5	[15]
brain tissue layer thickness	ΔH₂/cm	10	estimate
lower meningeal thickness	ΔH₃/mm	0.5	[15]
initial intracranial pressure	p₀/kPa	0.55	[20]

下载: 导出CSV

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