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\iteman{io-port 05663383}
\itemau{Lefik, Marek; Wojciechowski, Marek}
\itemti{Artificial Neural Network as a numerical form of effective constitutive law for composites with parametrized and hierarchical microstructure.}
\itemso{Comput. Assist. Mech. Eng. Sci. 12, No. 2-3, 183-194 (2005).}
\itemab
Summary: An Artificial Neural Network (ANN) 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 are examined in order to demostrate this approach. The first one introduces geometrical parameters of the cell of periodicity into the ANN training process. It proves the ability of the 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 is 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.
\itemrv{~}
\itemcc{}
\itemut{homogenisation; hierarchical composite}
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