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Artificial Neural Network Approach to Predict Mechanical Properties of 301 Austenitic Stainless Steel

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Abstract:

In this study, the effect of original thicknesses of plate, the thicknesses of plate after rolling and rolling reduction on the strength in 301 stainless steel was modeled by means of artificial neural network (ANN). The experimental data were collected to obtain training set and testing set. The normalization method was employed for avoiding over-fitting. The optimal ANN method architecture was determined by according to the trial and error procedure. The results of the ANN model were in good agreement with experimental data. As can be seen from the result, we believe that the neural network model can efficiently predict the relationship between mechanical properties and rolling reduction in 301 austenitic stainless steel.

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Periodical:

Materials Science Forum (Volume 658)

Pages:

145-148

DOI:

https://doi.org/10.4028/www.scientific.net/MSF.658.145

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Online since:

July 2010

Authors:

Zhi Yu Chen, De Ning Zou, Jun Hui Yu, Ying Han

Keywords:

Artificial Neural Network (ANN), Austenitic Stainless Steel, Back Propagation, Deformation Rate, Mechanical Property

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© 2010 Trans Tech Publications Ltd. All Rights Reserved

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