Moran Richard, Smith Joshua H, García José J
Escuela de Ingeniería Civil y Geomática. Universidad del Valle. Colombia; Department of Mechanical Engineering. Lafayette College, Easton, PA, USA; Escuela de Ingeniería Civil y Geomática. Universidad del Valle. Colombia.
J Biomech. 2014 Nov 28;47(15):3762-6. doi: 10.1016/j.jbiomech.2014.09.030. Epub 2014 Oct 7.
The mechanical properties of human brain tissue are the subject of interest because of their use in understanding brain trauma and in developing therapeutic treatments and procedures. To represent the behavior of the tissue, we have developed hyperelastic mechanical models whose parameters are fitted in accordance with experimental test results. However, most studies available in the literature have fitted parameters with data of a single type of loading, such as tension, compression, or shear. Recently, Jin et al. (Journal of Biomechanics 46:2795-2801, 2013) reported data from ex vivo tests of human brain tissue under tension, compression, and shear loading using four strain rates and four different brain regions. However, they do not report parameters of energy functions that can be readily used in finite element simulations. To represent the tissue behavior for the quasi-static loading conditions, we aimed to determine the best fit of the hyperelastic parameters of the hyperfoam, Ogden, and polynomial strain energy functions available in ABAQUS for the low strain rate data, while simultaneously considering all three loading modes. We used an optimization process conducted in MATLAB, calling iteratively three finite element models developed in ABAQUS that represent the three loadings. Results showed a relatively good fit to experimental data in all loading modes using two terms in the energy functions. Values for the shear modulus obtained in this analysis (897-1653Pa) are in the range of those presented in other studies. These energy-function parameters can be used in brain tissue simulations using finite element models.
由于人脑组织的力学特性在理解脑损伤以及开发治疗方法和程序方面的应用，其成为了研究的热点。为了描述该组织的行为，我们开发了超弹性力学模型，其参数根据实验测试结果进行拟合。然而，文献中大多数现有研究仅使用单一类型载荷（如拉伸、压缩或剪切）的数据来拟合参数。最近，Jin等人（《生物力学杂志》46:2795 - 2801，2013年）报告了在拉伸、压缩和剪切载荷下，使用四种应变率和四个不同脑区的人脑组织体外测试数据。然而，他们并未报告可直接用于有限元模拟的能量函数参数。为了描述准静态载荷条件下的组织行为，我们旨在确定ABAQUS中可用的超泡沫、奥格登和多项式应变能函数的超弹性参数对于低应变率数据的最佳拟合，同时考虑所有三种加载模式。我们使用了在MATLAB中进行的优化过程，迭代调用在ABAQUS中开发的代表三种载荷的三个有限元模型。结果表明，在能量函数中使用两项时，所有加载模式下与实验数据的拟合效果相对较好。在此分析中获得的剪切模量值（897 - 1653Pa）在其他研究报告的范围内。这些能量函数参数可用于使用有限元模型的脑组织模拟。
