Constitutive Modeling of Brain Parenchyma Taking Account of Strain Rate Dependency with Anisotropy and Application to Brain Injury Analyses

Paper #:
  • 2016-01-1485

Published:
  • 2016-04-05
Citation:
Atsumi, N., Nakahira, Y., Iwamoto, M., Hirabayashi, S. et al., "Constitutive Modeling of Brain Parenchyma Taking Account of Strain Rate Dependency with Anisotropy and Application to Brain Injury Analyses," SAE Technical Paper 2016-01-1485, 2016, https://doi.org/10.4271/2016-01-1485.
Pages:
13
Abstract:
A reduction in brain disorders owing to traumatic brain injury (TBI) caused by head impacts in traffic accidents is needed. However, the details of the injury mechanism still remain unclear. In past analyses, brain parenchyma of a head finite element (FE) model has generally been modeled using simple isotropic viscoelastic materials. For further understanding of TBI mechanism, in this study we developed a new constitutive model that describes most of the mechanical properties in brain parenchyma such as anisotropy, strain rate dependency, and the characteristic features of the unloading process. Validation of the model was performed against several material test data from the literature with a simple one-element model. The model was also introduced into the human head FE model of THUMS v4.02 and validated against post-mortem human subject (PMHS) test data about brain displacements and intracranial pressures during head impacts. Additionally, several parametric studies were performed to investigate the effect of the shapes of sinusoidal angular acceleration curves inputted to the head on strain distribution and cumulative strain damage measure (CSDM) in the brain. As a result, the proposed model accurately reproduced stress-strain curves in experimental data and described the brain displacements and pressures in PMHS test data. Furthermore, the results of parametric studies indicated that not only the peak value of the loaded angular acceleration but also the impact duration affected the strain distribution and CSDM. The proposed constitutive model has the potential to provide a better understanding of the TBI mechanism and more accurate injury prediction.
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