Artificial Neural Network as a numerical formof effective constitutive law for composites with parametrized and hierarchical microstructure

  • Marek Lefik Technical University of Łódź
  • Marek Wojciechowski Technical University of Łódź

Abstract

In the paper, Artificial Neural Network with hidden layers is used to approximate the functional dependence of the effective properties of a composite on the physical properties of its micro-components. Two numerical examples have been examined in order to demostrate this approach. The first one introduces geometrical parameters of the cell of periodicity into ANN training process. It proves the ability of ANN to catch the behaviour of the composite material based on the properties of the components and their spatial arrangement at micro level. The second example deals with a special case of the self-repetitive composite structure. It has been shown that, in the limit, the geometry and behaviour of such a composite is consistent with the fractal form known in the literature as the Sierpinski's carpet.

Keywords

neural network, homogenisation, hierarchical composite,

References

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Published
Nov 30, 2022
How to Cite
LEFIK, Marek; WOJCIECHOWSKI, Marek. Artificial Neural Network as a numerical formof effective constitutive law for composites with parametrized and hierarchical microstructure. Computer Assisted Methods in Engineering and Science, [S.l.], v. 12, n. 2-3, p. 183-194, nov. 2022. ISSN 2956-5839. Available at: <https://cames.ippt.pan.pl/index.php/cames/article/view/988>. Date accessed: 21 may 2024.
Section
Articles

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