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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

  • Fang WangEmail author
  • Bingyu Wang
  • Yong Han
  • Qian Peng
  • Fan Li
  • Adam Wittek
Conference paper
  • 354 Downloads

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.

Keywords

Brain–skull boundary conditions Brain–skull interface Finite element brain model Explicit finite element modeling Pedestrian accident Accident reconstruction Traumatic brain injury Diffuse axonal injury 

Notes

Acknowledgements

The research was supported by National Natural Science Foundation of China (Grant No. 51605407, 51505403), Fujian Provincial Department of Science and Technology (Grant No. 2017J01652), and State Administration of Foreign Experts Affairs P.R. China (Grant~No.~GDT20173600566). All FE simulations using Total HUman Model for Safety THUMS Version 4.0 human body model and all the simulations for the accident reconstruction using MADYMO multibody code in this research were conducted at Xiamen University of Technology.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Fang Wang
    • 1
    • 2
    Email author
  • Bingyu Wang
    • 1
    • 2
  • Yong Han
    • 1
    • 2
  • Qian Peng
    • 1
    • 2
  • Fan Li
    • 3
  • Adam Wittek
    • 4
  1. 1.School of Mechanical and Automotive EngineeringXiamen University of TechnologyXiamenChina
  2. 2.Fujian Collaborative Innovation Center for R&D of Coach and Special VehicleXiamenChina
  3. 3.College of Mechanical and Vehicle EngineeringHunan UniversityChangshaChina
  4. 4.Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical EngineeringThe University of Western AustraliaCrawley-PerthAustralia

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