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Journal of Materials Engineering and Performance
Published in: Journal of Materials Engineering and Performance 12/2013

01-12-2013

Prediction of Contact Fatigue Life of Alloy Cast Steel Rolls Using Back-Propagation Neural Network

Authors: Huijin Jin, Sujun Wu, Yuncheng Peng

Published in: Journal of Materials Engineering and Performance | Issue 12/2013

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Abstract

In this study, an artificial neural network (ANN) was employed to predict the contact fatigue life of alloy cast steel rolls (ACSRs) as a function of alloy composition, heat treatment parameters, and contact stress by utilizing the back-propagation algorithm. The ANN was trained and tested using experimental data and a very good performance of the neural network was achieved. The well-trained neural network was then adopted to predict the contact fatigue life of chromium alloyed cast steel rolls with different alloy compositions and heat treatment processes. The prediction results showed that the maximum value of contact fatigue life was obtained with quenching at 960 °C, tempering at 520 °C, and under the contact stress of 2355 MPa. The optimal alloy composition was C-0.54, Si-0.66, Mn-0.67, Cr-4.74, Mo-0.46, V-0.13, Ni-0.34, and Fe-balance (wt.%). Some explanations of the predicted results from the metallurgical viewpoints are given. A convenient and powerful method of optimizing alloy composition and heat treatment parameters of ACSRs has been developed.
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Appendix
Available only for authorised users
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Metadata
Title
Prediction of Contact Fatigue Life of Alloy Cast Steel Rolls Using Back-Propagation Neural Network
Authors
Huijin Jin
Sujun Wu
Yuncheng Peng
Publication date
01-12-2013
Publisher
Springer US
Published in
Journal of Materials Engineering and Performance / Issue 12/2013
Print ISSN: 1059-9495
Electronic ISSN: 1544-1024
DOI
https://doi.org/10.1007/s11665-013-0695-8

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