Skip to main content
Log in

Two-scale elastic parameter identification from noisy macroscopic data

  • Special
  • Published:
Archive of Applied Mechanics Aims and scope Submit manuscript

Abstract

A two-scale parameter identification procedure to identify microscopic elastic parameters from macroscopic data is introduced and thoroughly analyzed. The macroscopic material behavior of microscopically linear elastic heterogeneous materials is described by means of numerical homogenization. The microscopic material parameters are assumed to be unknown and are identified from noisy macroscopic displacement data. Various examples of microscopically heterogeneous materials—with regularly distributed pores, particles, or layers—are considered, and their parameters are identified from different macroscopic experiments by means of a gradient-based optimization procedure. The reliability of the identified parameters is analyzed by their standard deviations and correlation matrices. It was found that the two-scale parameter identification works well for cellular materials, but has to be designed carefully for layered materials. If the homogenized macroscopic material behavior can be described by less material parameters than the microscopic material behavior, as, e.g., for regularly distributed particles, the identification of all microscopic parameters from macroscopic experiments is not possible.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Ainsworth, M.: Essential boundary conditions and multi-point constraints in finite element analysis. Comput. Methods Appl. Mech. Eng. 190(48), 6323–6339 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  2. Avril, S., Grédiac, M., Pierron, F.: Sensitivity of the virtual fields method to noisy data. Comput. Mech. 34(6), 439–452 (2004)

    Article  MATH  Google Scholar 

  3. Bakhtiari-Nejad, F., Rahai, A., Esfandiari, A.: A structural damage detection method using static noisy data. Eng. Struct. 27(12), 1784–1793 (2005)

    Article  Google Scholar 

  4. Becker, R., Vexler, B.: A posteriori error estimation for finite element discretization of parameter identification problems. Numer. Math. 96(3), 435–459 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  5. Bensoussan, A., Lions, J.L., Papanicolaou, G.: Asymptotic methods in periodic structures. Stud. Math. Appl. 5 (1978)

  6. Bocciarelli, M., Bolzon, G., Maier, G.: Parameter identification in anisotropic elastoplasticity by indentation and imprint mapping. Mech. Mater. 37(8), 855–868 (2005)

    Article  Google Scholar 

  7. Bruhns, O., Anding, D.: On the simultaneous estimation of model parameters used in constitutive laws for inelastic material behaviour. Int. J. Plast. 15(12), 1311–1340 (1999)

    Article  MATH  Google Scholar 

  8. Fedele, R., Maier, G., Whelan, M.: Stochastic calibration of local constitutive models through measurements at the macroscale in heterogeneous media. Comput. Methods Appl. Mech. Eng. 195(37–40), 4971–4990 (2006)

    Article  MATH  Google Scholar 

  9. Feyel, F., Chaboche, J.L.: \(\text{ FE }^2\) multiscale approach for modelling the elastoviscoplastic behaviour of long fibre sic/ti composite materials. Comput. Methods Appl. Mech. Eng. 183(3–4), 309–330 (2000)

    Article  MATH  Google Scholar 

  10. Gavrus, A., Massoni, E., Chenot, J.: An inverse analysis using a finite element model for identification of rheological parameters. J. Mater. Process. Technol. 60(1), 447–454 (1996)

    Article  Google Scholar 

  11. Gross, D., Seelig, T.: Bruchmechanik : Mit einer Einführung in die Mikromechanik, 5th edn. Springer, New York (2011)

    Book  Google Scholar 

  12. Haddadi, H., Belhabib, S.: Improving the characterization of a hardening law using digital image correlation over an enhanced heterogeneous tensile test. Int. J. Mech. Sci. 62(1), 47–56 (2012)

    Article  Google Scholar 

  13. Hill, R.: Elastic properties of reinforced solids: some theoretical principles. J. Mech. Phys. Solids 11(5), 357–372 (1963)

    Article  MATH  Google Scholar 

  14. Kelley, C.: Iterative Methods for Optimization. SIAM, Philadelphia (1995)

    Google Scholar 

  15. Kleiber, M.: Parameter Sensitivity in Nonlinear Mechanics. Wiley, Chichester (1997)

    Google Scholar 

  16. Klinge, S.: Inverse analysis for multiphase nonlinear composites with random microstructure. J. Multiscale Comput. Eng. 10, 361–373 (2012)

    Article  Google Scholar 

  17. Kouznetsova, V.: Computational homogenization for the multi-scale analysis of multi-phase materials. Ph.D. thesis, Technical University Eindhoven (2002)

  18. LLorca, J., Segurado, J.: Three-dimensional multiparticle cell simulations of deformation and damage in sphere-reinforced composites. Mater. Sci. Eng. A 365(1–2), 267–274 (2004)

    Article  Google Scholar 

  19. Macconi, M., Morini, B., Porcelli, M.: Trust-region quadratic methods for nonlinear systems of mixed equalities and inequalities. Appl. Numer. Math. 59(5), 859–876 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  20. Mahnken, R.: Theoretische und numerische Aspekte zur Modellierung und Parameteridentifikation bei metallischen Werkstoffen. Universität Hannover, Habilitation (1996)

    Google Scholar 

  21. Mahnken, R., Stein, E.: A unified approach for parameter identification of inelastic material models in the frame of the finite element method. Comput. Methods Appl. Mech. Eng. 136(3–4), 225–258 (1996)

    Article  MATH  Google Scholar 

  22. Mandel, J.: Contribution téorique à l’étude de l’écrouissage et des lois de l’écoulement plastique. In: Applied Mechanics: Proceedings of the Eleventh International Congress of Applied Mechanics Munich (Germany) 1964, pp. 502–509 (1966)

  23. Miehe, C.: Computational micro-to-macro transitions for discretized micro-structures of heterogeneous materials at finite strains based on the minimization of averaged incremental energy. Comput. Methods Appl. Mech. Eng. 192(5–6), 559–591 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  24. Miehe, C., Koch, A.: Computational micro-to-macro transitions of discretized microstructures undergoing small strains. Arch. Appl. Mech. 72(4), 300–317 (2002)

    Article  MATH  Google Scholar 

  25. Morini, B., Porcelli, M.: TRESNEI, a matlab trust-region solver for systems of nonlinear equalities and inequalities. Comput. Optim. Appl. 51, 27–49 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  26. Oskay, C., Fish, J.: On calibration and validation of eigendeformation-based multiscale models for failure analysis of heterogeneous systems. Comput. Mech. 42, 181–195 (2008)

    Article  MATH  Google Scholar 

  27. Reuß, A.: Berechnung der Fließgrenze von Mischkristallen auf Grund der Plastizitätsbedingung für Einkristalle. ZAMM J. Appl. Math. Mech. 9(1), 49–58 (1929)

    Article  MATH  Google Scholar 

  28. Schmidt, U., Mergheim, J., Steinmann, P.: Multiscale parameter identification. Int. J. Multiscale Comput. Eng. 10(4), 327–342 (2012)

    Article  Google Scholar 

  29. Schmidt, U., Mergheim, J., Steinmann, P.: Identification of elastoplastic microscopic material parameters within a homogenization scheme. Int. J. Numer. Meth. Eng. 104(6), 391–407 (2015)

    Article  MathSciNet  Google Scholar 

  30. Smit, R., Brekelmans, W., Meijer, H.: Prediction of the mechanical behavior of nonlinear heterogeneous systems by multi-level finite element modeling. Comput. Methods Appl. Mech. Eng. 155, 181–192 (1998)

    Article  MATH  Google Scholar 

  31. Sukumar, N., Pask, J.E.: Classical and enriched finite element formulations for bloch-periodic boundary conditions. Int. J. Numer. Math. Eng. 77(8), 1121–1138 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  32. Suquet, P.M.: Plasticity Today, Chap. Local and Global Aspects in the Mathematical Theory of Plasticity. Elsevier Applied Science Publishers, London (1985)

    Google Scholar 

  33. Voigt, W.: Über die Beziehung zwischen den beiden Elasticitätsconstanten isotroper Körper. Ann. Phys. 38, 573–587 (1889)

    Article  MathSciNet  Google Scholar 

  34. Xiao, Q.Z., Karihaloo, B.L.: Two-scale asymptotic homogenisation-based finite element analysis of composite materials. Multiscale Model. Solid Mech. Comput. Approaches 3, 43 (2009)

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to acknowledge the funding of the Deutsche Forschungsgemeinschaft (DFG) through the Cluster of Excellence Engineering of Advanced Materials.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to P. Steinmann.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schmidt, U., Steinmann, P. & Mergheim, J. Two-scale elastic parameter identification from noisy macroscopic data. Arch Appl Mech 86, 303–320 (2016). https://doi.org/10.1007/s00419-015-1096-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00419-015-1096-2

Keywords

Navigation