[en] MODELING THE YOUNG MODULUS OF NANOCOMPOSITES: A NEURAL NETWORK APPROACH

[pt] MARLEY MARIA BERNARDES REBUZZI VELLASCO

[pt] OMAR PARANAIBA VILELA NETO

[pt] MARCO AURELIO CAVALCANTI PACHECO

[pt] JOSE ROBERTO MORAES D ALMEIDA

[pt] LEANDRO FONTOURA CUPERTINO

[en] Composite materials have changed the way of using polymers, as the strength was favored by the incorporation of fibers and particles. This new class of materials allowed a larger number of applications. The insertion of nanometric sized particles has enhanced the variation of properties with a smaller load of fillers. In this paper, we attempt to a better understanding of nanocomposites by using an artificial intelligence’s technique, known as artificial neural networks. This technique allowed the modeling of Young’s modulus of nanocomposites. A good approximation was obtained, as the correlation between the data and the response of the network was high, and the error percentage was low.

2013-02-18

[pt] TEXTO

application/pdf

INGLÊS

https://www.maxwell.vrac.puc-rio.br/colecao.php?strSecao=resultado&nrSeq=21164@2