Dyniewicz Bartłomiej, Bajkowski Jacek M, Bajer Czesław I
Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawińskiego 5b, 02-106 Warszawa, Poland.
Faculty of Mechanical and Industrial Engineering, Warsaw University of Technology, Narbutta 85, 02-524 Warszawa, Poland.
Materials (Basel). 2022 Mar 18;15(6):2270. doi: 10.3390/ma15062270.
In this paper, we address the numerical aspects and implementation of a nonlinear viscoplastic model of the mechanical behaviour of brain tissue to simulate the dynamic responses related to impact loads which may cause traumatic injury. Among the various viscoelastic models available, we deliberately considered modifying the Norton-Hoff model in order to introduce non-typical viscoplastic softening behaviour that imitates a brain's response just several milliseconds after a rapid impact. We describe the discretisation and three dimensional implementation of the model, with the aim of obtaining accurate numerical results in a reasonable computational time. Due to the large scale and complexity of the problem, a parallel computation technique, using a space-time finite element method, was used to facilitate the computation boost. It is proven that, after calibrating, the introduced viscoplastic-softening model is better suited for modelling brain tissue behaviour for the specific case of rapid impact loading rather than the commonly used viscoelastic models.
在本文中,我们探讨了一种用于模拟脑组织力学行为的非线性粘塑性模型的数值方面及实现方法,以模拟与可能导致创伤性损伤的冲击载荷相关的动态响应。在现有的各种粘弹性模型中,我们特意考虑修改诺顿 - 霍夫模型,以引入非典型的粘塑性软化行为,这种行为模仿了快速冲击后仅几毫秒内大脑的响应。我们描述了该模型的离散化和三维实现,目的是在合理的计算时间内获得准确的数值结果。由于问题的规模大且复杂,采用了一种使用时空有限元方法的并行计算技术来促进计算加速。结果表明,经过校准后,引入的粘塑性软化模型比常用的粘弹性模型更适合于模拟快速冲击载荷特定情况下的脑组织行为。