Suppr超能文献

受脉冲载荷作用的软凝胶的材料特性分析与模拟。

Material characterization and simulation for soft gels subjected to impulsive loading.

机构信息

U.S. Naval Research Laboratory, Washington, DC, 20375, USA.

U.S. Naval Research Laboratory, Washington, DC, 20375, USA.

出版信息

J Mech Behav Biomed Mater. 2022 Sep;133:105293. doi: 10.1016/j.jmbbm.2022.105293. Epub 2022 May 27.

Abstract

For impact and blast experiments of traumatic brain injury (TBI), soft gel materials are used as surrogates to imitate the mechanical responses of brain tissue. To properly model a viscoelastic gel brain in a surrogate head using a finite element (FE) model, material parameters such as the shear moduli and relaxation time at high strain rates are required. However, such information is scarce in the literature and its applicability for a range of dynamic conditions is unclear. We used an integrated experiment and simulation approach to efficiently determine mechanical properties of soft gels at finite strains, as well as over a wide range of strain rates. A novel impact experiment using a gel block was developed to capture the high strain rate behavior by maximizing the inherent shear wave motion at different impact conditions. A corresponding computational model was used to simulate the gel dynamics of the impact. Parametric simulations utilizing optimization and correlation analyses were used to calibrate multiple material parameters in the nonlinear viscoelastic model to the experimental data. The optimal parameters for gels, including Sylgards 184, 3-6636, and 527, were found. We ascertained the initial shear stiffening effect in gels at high strain rate loadings experimentally and incorporated this effect in the simulation. We have verified the integrated approach by comparing the material properties of the gels with analytical results based on shear wave propagation. This study provides a new approach to calibrate the material behavior of soft gels under high strain rate loading conditions.

摘要

对于创伤性脑损伤 (TBI) 的冲击和爆炸实验,软凝胶材料被用作替代品来模拟脑组织的力学响应。为了在替代头部中使用有限元 (FE) 模型正确模拟粘弹性凝胶脑,需要高应变速率下的剪切模量和松弛时间等材料参数。然而,文献中此类信息很少,其在一系列动态条件下的适用性尚不清楚。我们使用集成的实验和模拟方法,在有限应变下以及在很宽的应变率范围内高效确定软凝胶的力学性能。开发了一种新颖的凝胶块冲击实验,通过在不同冲击条件下最大限度地提高固有剪切波运动来捕获高应变速率行为。相应的计算模型用于模拟冲击的凝胶动力学。利用优化和相关分析的参数模拟用于将非线性粘弹性模型中的多个材料参数校准到实验数据。确定了 Sylgards 184、3-6636 和 527 等凝胶的最佳参数。我们通过实验确定了高应变速率载荷下凝胶中的初始剪切硬化效应,并将其纳入模拟中。我们通过将凝胶的材料性能与基于剪切波传播的分析结果进行比较,验证了这种综合方法。本研究为在高应变速率加载条件下校准软凝胶材料行为提供了一种新方法。

相似文献

1
Material characterization and simulation for soft gels subjected to impulsive loading.
J Mech Behav Biomed Mater. 2022 Sep;133:105293. doi: 10.1016/j.jmbbm.2022.105293. Epub 2022 May 27.
2
Rheological characterization of human brain tissue.
Acta Biomater. 2017 Sep 15;60:315-329. doi: 10.1016/j.actbio.2017.06.024. Epub 2017 Jun 26.
4
On the mechanical characterization and modeling of polymer gel brain substitute under dynamic rotational loading.
J Mech Behav Biomed Mater. 2016 Oct;63:44-55. doi: 10.1016/j.jmbbm.2016.06.008. Epub 2016 Jun 10.
5
Shear wave propagation in anisotropic soft tissues and gels.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:1117-22. doi: 10.1109/IEMBS.2009.5333418.
6
The influence of the specimen shape and loading conditions on the parameter identification of a viscoelastic brain model.
Comput Math Methods Med. 2013;2013:460413. doi: 10.1155/2013/460413. Epub 2013 Jul 9.
7
Method for characterizing viscoelasticity of human gluteal tissue.
J Biomech. 2012 Apr 30;45(7):1252-8. doi: 10.1016/j.jbiomech.2012.01.037. Epub 2012 Feb 22.
8
Multidirectional mechanical properties and constitutive modeling of human adipose tissue under dynamic loading.
Acta Biomater. 2021 Jul 15;129:188-198. doi: 10.1016/j.actbio.2021.05.021. Epub 2021 May 25.
9
Mechanical characterization of brain tissue in simple shear at dynamic strain rates.
J Mech Behav Biomed Mater. 2013 Dec;28:71-85. doi: 10.1016/j.jmbbm.2013.07.017. Epub 2013 Jul 24.
10
Measurement of brain simulant strains in head surrogate under impact loading.
Biomech Model Mechanobiol. 2021 Dec;20(6):2319-2334. doi: 10.1007/s10237-021-01509-6. Epub 2021 Aug 28.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验