Abstract

Traumatic aortic rupture (TAR) resulting due to motor vehicle crashes (MVC) accounts for about 10%–20% fatalities. This article presents the outcome of our findings of the non-linear stress–strain response and strain rate-dependent behaviour of the aortic tissue under crash like impacts. This study uses both finite element (FE) modelling and experimental testing to enhance the understanding of injury mechanisms associated with TAR. Accurate material properties are essential for correct FE model predictions. Therefore, the objective of the current study was to experimentally characterise and identify a suitable constitutive model and model parameters for aortic tissue that can be incorporated into FE human body models for studying aortic rupture. Inverse characterisation and genetic algorithms (GA) were used to train the FE model to simulate real-life scenarios applying loading in multiple directions. A total of 32 uniaxial tensile tests were conducted on human aortic tissues along with the longitudinal and circumferential directions by loading at different strain rates ranging up to 200/s. The engineering stress–strain relationship obtained for human aorta in the longitudinal and circumferential directions via uniaxial tensile tests demonstrated an approximately bilinear behaviour and strain rate dependency in both directions. The higher stresses and modulus in the circumferential direction as compared to longitudinal direction demonstrates the anisotropic behaviour of the tissue. A constitutive model has been developed and implemented via user subroutine (UMAT) in LS-DYNA that accounts for the strain rate-dependent effects and bilinear behaviour observed in the aortic tissue. A FE model of the experimental set-up was developed, and the parameters of the model were estimated using a GA-based inverse mapping technique. The developed model enables investigation of the mechanical response of the aortic tissue under crashes and other high rate loading conditions. The work is based on the premise that a reliable constitutive model coupled with a FE model of the aorta shall help predict TARs.

摘要

由于机动车辆碰撞 (MVC) 导致的创伤性主动脉破裂 (TAR) 约占死亡人数的 10%–20%。本文介绍了我们发现的非线性应力-应变响应和主动脉组织在类似碰撞冲击下的应变率相关行为的结果。本研究使用有限元 (FE) 建模和实验测试来增强对与 TAR 相关的损伤机制的理解。准确的材料属性对于正确的 FE 模型预测至关重要。因此，当前研究的目的是通过实验表征和确定适合主动脉组织的本构模型和模型参数，以将其纳入 FE 人体模型以研究主动脉破裂。逆表征和遗传算法 (GA) 用于训练有限元模型，以模拟在多个方向上施加载荷的真实场景。在高达 200/s 的不同应变速率下，对人体主动脉组织沿纵向和圆周方向进行了 32 次单轴拉伸试验。通过单轴拉伸试验获得的人体主动脉在纵向和圆周方向上的工程应力-应变关系证明了在两个方向上的近似双线性行为和应变率依赖性。与纵向相比，在圆周方向上更高的应力和模量表明了组织的各向异性行为。已通过 LS-DYNA 中的用户子程序 (UMAT) 开发并实施了本构模型，该模型解释了在主动脉组织中观察到的应变率依赖性效应和双线性行为。开发了实验装置的有限元模型，并使用基于 GA 的逆映射技术估计了模型的参数。开发的模型能够研究在碰撞和其他高速负载条件下主动脉组织的机械响应。这项工作的前提是可靠的本构模型与主动脉的有限元模型相结合将有助于预测 TAR。开发的模型能够研究在碰撞和其他高速负载条件下主动脉组织的机械响应。这项工作的前提是可靠的本构模型与主动脉的有限元模型相结合将有助于预测 TAR。开发的模型能够研究在碰撞和其他高速负载条件下主动脉组织的机械响应。这项工作的前提是可靠的本构模型与主动脉的有限元模型相结合将有助于预测 TAR。