Prediction of corrosion-fatigue behavior of DP steel through artificial neural network

Authors
Haque, ME Sudhakar, KV
Citation
Me. Haque et Kv. Sudhakar, Prediction of corrosion-fatigue behavior of DP steel through artificial neural network, INT J FATIG, 23(1), 2001, pp. 1-4
Citations number
6
Categorie Soggetti
Material Science & Engineering
Journal title
INTERNATIONAL JOURNAL OF FATIGUE
ISSN journal
01421123 → ACNP
Volume
23
Issue
1
Year of publication
2001
Pages
1 - 4
Database
ISI
SICI code
0142-1123(200101)23:1<1:POCBOD>2.0.ZU;2-0
Abstract
Corrosion-fatigue crack growth (da/dN) of dual phase (DP) steel was analyze d using an artificial neural network (ANN) based model. The training data c onsisted of corrosion-fatigue crack growth rates at varying stress intensit y ranges (DeltaK) for martensite contents between 32 and 76%. The ANN model exhibited excellent comparison with the experimental results. Since a larg e number of variables are used during training the model, it will provide a reliable and useful predictor for corrosion-fatigue crack growth (FCG) in DP steels. (C) 2001 Elsevier Science Ltd. All rights reserved.