A Visco‑hyperelastic Model for Prediction of the Brain Tissue Response and the Traumatic Brain Injuries

Document Type : Original Article

Authors

1 Department of Applied Design, Faculty of Mechanical Engineering, University of Kashan

2 Department of Applied Design, Faculty of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran

10.4103/atr.atr_9_17

Abstract

Introduction: Numerous geometrically simplified models may be found in the literature on simulation of the traumatic brain injuries due to the
increased intracranial pressure induced by severe translational accelerations of the brain inside the cranium following the impact waves. While
numerous researchers have utilized viscoelastic models, some have employed specific hyperelastic models for behavior analysis of the brain
tissue. No research has been presented so far based on the more realistic visco‑hyperelastic model. Materials and Methods: In the present
research, a realistic finite element model and four visco‑hyperelastic constitutive models (viscoelastic models on the basis of the polynomial,
Yeoh, Arruda‑Boyce, and Ogden hyperelastic models) are employed to accomplish the outlined task. Therefore, the main motivation of the
present research is checking the accuracy of the modeling procedure rather than presenting clinical results. In this regard, a realistic skull‑brain
model is constructed in CATIA computer code based on the magnetic resonance imaging scans and optimized in the HYPERMESH finite element
software. Results: Influence of the contact and nonlinear characteristics of the brain tissue are considered in the simulation of the relative motions
in LS‑DYNA software to predict time histories of the acceleration and the coup and countercoup pressures by means of ANSYS finite element
analysis software. Discussion: Comparing results of the four proposed visco‑hyperelastic constitutive models with the available experimental
reveals that employing Arruda–Boyce or Ogden‑type viscoelastic models may lead to inaccurate or even erroneous results.

Keywords

References

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History

  • Receive Date: 15 May 2017
  • Revise Date: 15 June 2017
  • Accept Date: 15 July 2017

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