Predicting the Fatigue Life of Different Composite Materials Using Artificial Neural Networks |
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Authors: | M Al-Assadi H El Kadi I M Deiab |
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Affiliation: | (1) College of Engineering, American University of Sharjah, Sharjah, UAE; |
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Abstract: | Artificial Neural Networks (ANN) have been recently used in modeling the mechanical behavior of fiber-reinforced composite
materials including fatigue behavior. The use of ANN in predicting fatigue failure in composites would be of great value if
one could predict the failure of materials other than those used for training the network. This would allow developers of
new materials to estimate in advance the fatigue properties of their material. In this work, experimental fatigue data obtained
for certain fiber-reinforced composite materials is used to predict the cyclic behavior of a composite made of a different
material. The effect of the neural network architecture and the training function used were also investigated. In general,
ANN provided accurate fatigue life prediction for materials not used in training the network when compared to experimentally
measured results. |
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