Effects of synthetic data applied to artificial neural networks for fatigue life prediction in nodular cast iron

2021 ◽  
Vol 43 (1) ◽  
Author(s):  
Moises Jimenez-Martinez ◽  
Mariel Alfaro-Ponce
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Cast Iron ◽  
Fatigue Life ◽  
Life Prediction ◽  
Synthetic Data ◽  
Nodular Cast Iron ◽  
Fatigue Life Prediction ◽  
Artificial Neural

Fatigue Life Prediction of Composite Materials: Artificial Neural Networks vs. Polynomial Classifiers

2011 ◽  
Vol 471-472 ◽  
pp. 221-226 ◽  
Author(s):  
Hany A. El Kadi
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Fatigue Life ◽  
Composite Materials ◽  
Life Prediction ◽  
Fatigue Behavior ◽  
Fatigue Life Prediction ◽  
Advantages And Disadvantages ◽  
Artificial Neural ◽  
Polynomial Classifiers

Artificial neural networks (ANN) and polynomial classifiers (PC) have been successfully used to predict the fatigue failure of fiber reinforced composite materials. This includes predicting the behavior of the same material subjected to different loading conditions as well as predicting the fatigue behavior of different materials. In this work, the fatigue life prediction obtained using both methods will be compared. The effect of the various parameters influencing the prediction will be presented and the advantages and disadvantages of each of the methods will be discussed.

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