大应变水平压缩试验生物力学的计算机优化

Na Li, Jianxin Liu
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引用次数: 0

摘要

在美国,创伤性脑损伤(TBI)是车祸中最常见的死亡原因。对脑组织进行生物力学分析是必要的,因为实验费用大,建模实现了车辆碰撞的力学模拟。为了获得人脑组织的力学特性,近35年来人们进行了压缩、剪切、振荡加载等试验。材料建模和参数报告因研究而异。本文利用非支配排序遗传算法- ii (NSGA-II)获得材料均匀性的方法。超弹性部分采用Ogden能量命运函数作为主要构式函数,应力-应变曲线随应变速率不同而变化,G和beta表示该材料性能中应力与速度的关系。通过Estes的测试,该优化方法得到mu为882 Pa, alpha为4.852,G为29300 Pa。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computer Optimization in Biomechanics in Large Strain Level Compression Test
In the united states, traumatic brain injury (TBI) is the most common cause of death in vehicular crash. Biomechanical analysis of brain tissue is necessary because the experiment cost too much and the modeling achieved the mechanical simulation in vehicular crash. In order to obtain the mechanical properties of human brain tissue, in last 35 years, people did compression, shear, and oscillatory loading. The material modeling and the parameter reported vary from study to study. In this paper a method was utilizing to obtain uniform material properties by using Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Ogden energy destiny function was utilized as the main constructive function in hyperelastic part, as the stress-strain curve vary with different strain rate, the G and beta present the relationship between stress and velocity in this material properties. Through Estes’s test, this optimization method obtain the mu is 882 Pa and alpha is 4.852, G is 29300 Pa.
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