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Computational Micromechanics of Trabecular Porcine Skull Bone Using the Material Point Method

[+] Author Affiliations
Ziwen Fang, Allison N. Ranslow, Reuben H. Kraft

Pennsylvania State University, University Park, PA

Paper No. IMECE2016-67748, pp. V003T04A044; 9 pages
doi:10.1115/IMECE2016-67748
From:
  • ASME 2016 International Mechanical Engineering Congress and Exposition
  • Volume 3: Biomedical and Biotechnology Engineering
  • Phoenix, Arizona, USA, November 11–17, 2016
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-5053-4
  • Copyright © 2016 by ASME

abstract

The trabecular bone in the porcine skull is geometrically complex. It can be characterized experimentally, but requires many test configurations, loading rates, and samples to develop trusted constitutive models that fully characterize the complexity. Typically, Lagrangian finite element simulations are used in the bone modeling community to replicate experimental results for model validation and determination of material properties. In this approach, microCT images are used to develop anatomically accurate surfaces that are then volume meshed. While this modeling approach is valuable, there are some limitations. For example, with high-resolution micoCT data, traditional meshing techniques have proven to be insufficient. Specifically with highly porous trabecular bone data, the complexity of the pore architecture is difficult to be replicated by finite element mesh. To overcome this challenge, the application of material point method (MPM) has been investigated for analyzing the material properties of trabecular bone. This meshless method requires a “particle mesh” that can be derived directly from the microCT data. This process is much easier than developing a finite element mesh. Preliminary results have focused on generating the stress-strain curves for quasi-static loading and comparing numerical predictions with experimental results, as well as verifying the MPM against the finite element method. Initial results are promising and we have seen good comparison with experimental results. Parallel scalability of MPM has also been assessed since large-scale simulations can be expected for the future research.

Copyright © 2016 by ASME

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