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Startseite > Forschung > Computational testing of microheterogeneous solids

Computational testing of microheterogeneous solids (finished)

Computational testing of microheterogeneous solids

Researchers

T. Zohdi

Applications

Reliable structural-scale material data

Keywords

materials testing, statistics

Research Context

Constitutive Modelling of Materials, Micromechanics

Publications

  • Zohdi, T. I. and Wriggers, P. (1999). A domain decomposition method for bodies with microstructure based upon material regularization. The International Journal of Solids and Structures. 36, No. 17, 2507-2526.
  • Zohdi, T. I. and Wriggers, P. (1999). Microstructural decomposition error estimates. Zeitschrift für Angewandte Mathematik und Mechanik (ZAMM special issue). 79 S155-S158.
  • Zohdi, T. I., Wriggers, P. and Huet, C. (under review). A method of substructuring large-scale computational micromechanical problems.
  • Zohdi, T. I. and Wriggers, P. (under review). Some aspects of the computational testing of the mechanical properties of microheterogeneous material samples.
  • Zohdi, T. I. and Wriggers, P. (under review). On the reliability of homogenized poro-elastic material responses at infinitesimal and finite strains.


Contents

On a practical level, when computing effective or homogenized mechanical responses of materials possessing heterogeneous microstructure, one can only test finite sized samples. Therefore, aggregate responses computed from various equal, but finite, sized samples, exhibit deviations from one another. In this work we analyze the magnitude of perturbations of computed aggregate infinitesimal strain and finite strain responses of microheterogeneous materials.

Tests for the effective bulk response with increasingly larger particulate samples.
Example configuration of a particulate sample (20 particles), with matrix material not shown.
Convergence behaviour of the effective material property (effective bulk modulus) correlated to enlargements of sample sizes.
Results of the variation in responses for a fixed sample size.


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