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An artificial neural network approach to fatigue crack growth

Journal Article


Abstract


  • This paper proposes a new three-layer artificial neural network (ANN) to predict the fatigue crack length under constant amplitude mode I cyclic loading. It is shown that the proposed model predicts the crack length with an error of less than 0.05%, and more accurately than the current commonly-used models. © (2011) Trans Tech Publications, Switzerland.

Publication Date


  • 2011

Citation


  • Zarrabi, K., Lu, W. W., & Hellier, A. K. (2011). An artificial neural network approach to fatigue crack growth. Advanced Materials Research, 275, 3-6. doi:10.4028/www.scientific.net/AMR.275.3

Scopus Eid


  • 2-s2.0-79960435507

Start Page


  • 3

End Page


  • 6

Volume


  • 275

Abstract


  • This paper proposes a new three-layer artificial neural network (ANN) to predict the fatigue crack length under constant amplitude mode I cyclic loading. It is shown that the proposed model predicts the crack length with an error of less than 0.05%, and more accurately than the current commonly-used models. © (2011) Trans Tech Publications, Switzerland.

Publication Date


  • 2011

Citation


  • Zarrabi, K., Lu, W. W., & Hellier, A. K. (2011). An artificial neural network approach to fatigue crack growth. Advanced Materials Research, 275, 3-6. doi:10.4028/www.scientific.net/AMR.275.3

Scopus Eid


  • 2-s2.0-79960435507

Start Page


  • 3

End Page


  • 6

Volume


  • 275