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Reconstruction of Real-World Car-to-Pedestrian Accident Using Computational Biomechanics Model: Effects of the Choice of Boundary Conditions of the Brain on Brain Injury Risk

  • 2019
  • OriginalPaper
  • Chapter
Published in:
Authors
Fang Wang
Bingyu Wang
Yong Han
Qian Peng
Fan Li
Adam Wittek
Published in
Computational Biomechanics for Medicine
Publisher
Springer International Publishing

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Abstract

In the current study, the effects of the approach for modelling the brain–skull interface on prediction of the brain injury risk are investigated using a previously validated computational head-brain model. Four types of brain–skull interface modelling approaches (1): the method used in original Total HUman Model for Safety THUMS Head-brain model, (2): brain rigidly attached to the skull, (3): frictionless contact between the brain and skull, and (4): cohesive layer (spring-type) between the brain and skull are employed in numerical reconstruction of a real-world car-to-pedestrian impact accident. The results indicate that the predicted brain injury risk is strongly affected by the approach for modelling the brain–skull interface. The comparison of the predicted risk of diffuse axonal injury DAI and brain contusions with the injuries sustained by the pedestrian involved in the accident seems to suggest that accurate prediction of the brain injury risk using computational biomechanics models requires direct representation of the meninges and subarachnoidal space with the CSF.

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previous chapter Atlas of Acceleration-Induced Brain Deformation from Measurements In Vivo
next chapter Computational Modeling of Fluid–Structure Interaction Between Blood Flow and Mitral Valve
Title
Reconstruction of Real-World Car-to-Pedestrian Accident Using Computational Biomechanics Model: Effects of the Choice of Boundary Conditions of the Brain on Brain Injury Risk
Authors
Fang Wang
Bingyu Wang
Yong Han
Qian Peng
Fan Li
Adam Wittek
Copyright Year
2019
Book
Computational Biomechanics for Medicine

Print ISBN: 978-3-319-75588-5

Electronic ISBN: 978-3-319-75589-2

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-319-75589-2_3
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