Article ID Journal Published Year Pages File Type
1562829 Computational Materials Science 2010 10 Pages PDF
Abstract

A full stochastic multi-scale modeling technique is developed to estimate mechanical properties of carbon nanotube reinforced polymers. Developing a full-range multi-scale technique to consider effective parameters of all nano, micro, meso and macro-scales and full stochastic implementation of integrated modeling procedures are the novelties of the present research. The length, orientation, agglomeration, curvature and dispersion of carbon nanotubes are taken into account as random parameters. It is proven that random distribution of carbon nanotube length and volume fraction can be replaced with corresponding mean values. The results of predictions are in a very good agreement with published experimental observations.

Related Topics
Physical Sciences and Engineering Engineering Computational Mechanics
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