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Development of Octree-Based High-Quality Mesh Generation Method for Biomedical Simulation

  • Keisuke Katsushima
  • Kohei Fujita
  • Tsuyoshi Ichimura
  • Muneo Hori
  • Lalith Maddegedara
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10861)

Abstract

This paper proposes a robust high-quality finite element mesh generation method which is capable of modeling problems with complex geometries and multiple materials and suitable for the use in biomedical simulation. The previous octree-based method can generate a high-quality mesh with complex geometries and multiple materials robustly allowing geometric approximation. In this study, a robust mesh optimization method is developed combining smoothing and topology optimization in order to correct geometries guaranteeing element quality. Through performance measurement using sphere mesh and application to HTO tibia mesh, the validity of the developed mesh optimization method is checked.

Keywords

Mesh generation Multiple materials Mesh optimization Biomedical simulation 

References

  1. 1.
    Ichimura, T., Hori, M., Bielak, J.: A hybrid multiresolution meshing technique for finite element three-dimensional earthquake ground motion modelling in basins including topography. Geophys. J. Int. 177(3), 1221–1232 (2009)CrossRefGoogle Scholar
  2. 2.
    Fujita, K., Katsushima, K., Ichimura, T., Hori, M., Lalith, M.: Octree-based multiple-material parallel unstructured mesh generation method for seismic response analysis of soil-structure systems. Procedia Comput. Sci. 80, 1624–1634 (2016)CrossRefGoogle Scholar
  3. 3.
    Fujita, K., Katsushima, K., Ichimura, T., Horikoshi, M., Nakajima, K., Hori, M., Maddegedara, L.: Wave propagation simulation of complex multi-material problems with fast low-order unstructured finite-element meshing and analysis. In: Proceedings of International Conference on High Performance Computing in Asia-Pacific Region (2017)Google Scholar
  4. 4.
    Wu, Z., Sullivan, J.M.: Multiple material marching cubes algorithm. Int. J. Numer. Methods Eng. 58(2), 189–207 (2003)CrossRefGoogle Scholar
  5. 5.
    Xu, K., Cheng, Z.Q., Wang, Y., Xiong, Y., Zhang, H.: Quality encoding for tetrahedral mesh optimization. Comput. Graph. 33(3), 250–261 (2009)CrossRefGoogle Scholar
  6. 6.
    Freitag, L.A., Ollivier-Gooch, C.: Tetrahedral mesh improvement using swapping and smoothing. Int. J. Numer. Methods Eng. 40(21), 3979–4002 (1997)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Klingner, B.M., Shewchuk, J.B.: Aggressive tetrahedral mesh improvement. In: Brewer, M.L., Marcum, D. (eds.) Proceedings of the 16th International Meshing Roundtable, pp. 3–23. Springer, Heidelberg (2007).  https://doi.org/10.1007/978-3-540-75103-8_1
  8. 8.
    Freitag, L.A., Knupp, P.M., Munson, T., Shontz, S.: A comparison of inexact Newton and coordinate descent mesh optimization techniques. In: Proceedings of the 13th International Meshing Roundtable. Sandia National Laboratories, pp. 243–254, September 2004Google Scholar
  9. 9.
    GrabCAD: Tibia TOMOFIX Plate for HTO. https://grabcad.com/
  10. 10.
    GrabCAD: Design of osseointegrated Implant for tibial bone. https://grabcad.com/

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Keisuke Katsushima
    • 1
  • Kohei Fujita
    • 1
    • 2
  • Tsuyoshi Ichimura
    • 1
    • 2
  • Muneo Hori
    • 1
    • 2
  • Lalith Maddegedara
    • 1
    • 2
  1. 1.Department of Civil Engineering, Earthquake Research InstituteThe University of TokyoBunkyoJapan
  2. 2.RIKEN Center for Computational ScienceKobeJapan

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