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使用矢状面和横断面有限元模型研究头部和大脑对爆炸的反应。

Head and brain response to blast using sagittal and transverse finite element models.

机构信息

University of Waterloo, Waterloo, ON, Canada.

出版信息

Int J Numer Method Biomed Eng. 2014 Apr;30(4):470-89. doi: 10.1002/cnm.2612. Epub 2013 Nov 30.

DOI:10.1002/cnm.2612
PMID:24293124
Abstract

Mild traumatic brain injury caused by blast exposure from Improvised Explosive Devices has become increasingly prevalent in modern conflicts. To investigate head kinematics and brain tissue response in blast scenarios, two solid hexahedral blast-head models were developed in the sagittal and transverse planes. The models were coupled to an Arbitrary Lagrangian-Eulerian model of the surrounding air to model blast-head interaction, for three blast load cases (5 kg C4 at 3, 3.5 and 4 m). The models were validated using experimental kinematic data, where predicted accelerations were in good agreement with experimental tests, and intracranial pressure traces at four locations in the brain, where the models provided good predictions for frontal, temporal and parietal, but underpredicted pressures at the occipital location. Brain tissue response was investigated for the wide range of constitutive properties available. The models predicted relatively low peak principal brain tissue strains from 0.035 to 0.087; however, strain rates ranged from 225 to 571 s-1. Importantly, these models have allowed us to quantify expected strains and strain rates experienced in brain tissue, which can be used to guide future material characterization. These computationally efficient and predictive models can be used to evaluate protection and mitigation strategies in future analysis.

摘要

爆炸物引起的轻度创伤性脑损伤在现代冲突中越来越普遍。为了研究爆炸场景中的头部运动学和脑组织响应,在矢状面和横断面上开发了两个实心六面体爆炸头模型。这些模型与周围空气的任意拉格朗日-欧拉模型相结合,模拟了爆炸头的相互作用,用于三种爆炸负荷情况(3、3.5 和 4 米处的 5 公斤 C4)。使用实验运动学数据对模型进行了验证,预测的加速度与实验测试吻合良好,并且在大脑的四个位置预测了颅内压力迹线,模型在额叶、颞叶和顶叶位置提供了良好的预测,但在枕叶位置预测的压力较低。对各种可用的本构性质进行了脑组织响应的研究。模型预测的主要脑组织应变峰值相对较低,范围在 0.035 到 0.087 之间;然而,应变率范围在 225 到 571 s-1 之间。重要的是,这些模型使我们能够量化脑组织中经历的预期应变和应变率,这可以用于指导未来的材料特性研究。这些计算效率高且具有预测性的模型可用于未来分析中的保护和缓解策略评估。

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