Skip to main content

Numerical Homogenization of Heterogeneous Anisotropic Linear Elastic Materials

  • Conference paper
  • First Online:
Large-Scale Scientific Computing (LSSC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8353))

Included in the following conference series:

  • 1330 Accesses

Abstract

The numerical homogenization of anisotropic linear elastic materials with strongly heterogeneous microstructure is studied. The developed algorithm is applied to the case of trabecular bone tissue. In our previous work [1], the orthotropic case was considered. The homogenized anisotropic tensor is transformed according to the principle directions of anisotropy (PDA). This provides opportunities for better interpretation of the results as well as for classification of the material properties.

The upscaling procedure is described in terms of six auxiliary elastic problems for the reference volume element (RVE). Rotated trilinear Rannacher-Turek finite elements are used for discretization of the involved subproblems. A parallel PCG method is implemented for efficient solution of the arising large-scale systems with sparse, symmetric, and positive semidefinite matrices. Then, the bulk modulus tensor is computed from the upscaled stiffness tensor and its eigenvectors are used to define the transformation matrix. The stiffness tensor of the material is transformed with respect to the PDA which gives a canonical (unique) representation of the material properties.

Numerical experiments for two different RVEs from the trabecular part of human bones are presented.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Margenov, S., Vutov, Y.: Parallel MIC(0) preconditioning for numerical upscaling of anisotropic linear elastic materials. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds.) LSSC 2009. LNCS, vol. 5910, pp. 805–812. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  2. Wirth, A.J., Mueller, T.L., Vereecken, W., Flaig, C., Arbenz, P., Mller, R., van Lenthe, G.H.: Mechanical competence of bone-implant systems can accurately be determined by image-based micro-finite element analyses. Arch. Appl. Mech. 80(5), 513–525 (2010)

    Article  MATH  Google Scholar 

  3. Fung, Y.C.: Foundations of Solid Mechanics. Prentice-Hall, Englewood Cliffs (1965)

    Google Scholar 

  4. Nayfeh, A., Pai, P.: Linear and Nonlinear Structural Mechanics. Wiley, New York (2004)

    Book  MATH  Google Scholar 

  5. Sokolonikoff, I.: Mathematical Theory of Elasticity. Mc-Graw-Hill, New York (1956)

    Google Scholar 

  6. Hoppe, R.H.W., Petrova, S.I.: Optimal shape design in biomimetics based on homogenization and adaptivity. Math. Comput. Simul. 65(3), 257–272 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  7. Bensoussan, A., Lions, J.L., Papanicolaou, G.: Asymptotic Analysis for Periodic Structures. Elsevier, Amsterdam (1978)

    MATH  Google Scholar 

  8. Rannacher, R., Turek, S.: Simple nonconforming quadrilateral Stokes element. Numer. Meth. Partial Differ. Equ. 8(2), 97–112 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  9. Arnold, D.N., Brezzi, F.: Mixed and nonconforming finite element methods: Implementation, postprocessing and error estimates. RAIRO. Model. Math. Anal. Numer. 19, 7–32 (1985)

    MATH  MathSciNet  Google Scholar 

  10. Malkus, D., Hughes, T.: Mixed finite element methods – reduced and selective integration techniques: an uniform concepts. CMAME 15, 63–81 (1978)

    MATH  Google Scholar 

  11. Blaheta, R.: Displacement decomposition-incomplete factorization preconditioning techniques for linear elasticity problems. NLAA 1(2), 107–128 (1994)

    MATH  MathSciNet  Google Scholar 

  12. Arbenz, P., Margenov, S., Vutov, Y.: Parallel MIC(0) preconditioning of 3D elliptic problems discretized by Rannacher-Turek finite elements. Comput. Math. Appl. 55(10), 2197–2211 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  13. Rand, O., Rovenski, V.: Analytical Methods in Anisotropic Elasticity: With Symbolic Computational Tools. Birkhauser, Boston (2004)

    Google Scholar 

  14. Walker, D., Dongarra, J.: MPI: a standard Message Passing Interface. Supercomputer 63, 56–68 (1996)

    Google Scholar 

  15. Beller, G., Burkhart, M., Felsenberg, D., Gowin, W., Hege, H.-C., Koller, B., Prohaska, S., Saparin, P.I., Thomsen, J.S.: Vertebral body data set esa29-99-l3. http://bone3d.zib.de/data/2005/ESA29-99-L3/

  16. Cowin, S.: Bone poroelasticity. J Biomech. 32, 217–238 (1999)

    Article  Google Scholar 

  17. Wolff, J.: The Law of Bone Remodeling. Springer, Heidelberg (1986)

    Book  Google Scholar 

  18. Kosturski, N., Margenov, S.: Numerical homogenization of bone microstructure. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds.) LSSC 2009. LNCS, vol. 5910, pp. 140–147. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

Download references

Acknowledgments

This work is supported in part by Grants DFNI I01/5 and DCVP-02/1 from the Bulgarian NSF and the Bulgarian National Center for Supercomputing Applications (NCSA), giving access to the IBM Blue Gene/P computer.

The research is also partly supported by the project AComIn “Advanced Computing for Innovation”, grant 316087, funded by the FP7 Capacity Programme (Research Potential of Convergence Regions)

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Y. Vutov .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Margenov, S., Stoykov, S., Vutov, Y. (2014). Numerical Homogenization of Heterogeneous Anisotropic Linear Elastic Materials. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2013. Lecture Notes in Computer Science(), vol 8353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43880-0_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-43880-0_39

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-43879-4

  • Online ISBN: 978-3-662-43880-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics