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铁道科学与工程学报

JOURNAL OF RAILWAY SCIENCE AND ENGINEERING

Vol. 11    No. 1    February 2001

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Prediction of flow stress of Ti-15-3 alloy with artificial neural network
LI Ping(李  萍)1,SHAN De-bin(单德彬)1,XUE Ke-min(薛克敏)1,
LÜ Yan(吕  炎)1, XU Yi(许  沂)2

1. School of Materials Science and Engineering, Harbin Institute of Technology,
Harbin 150001, P.R.China;
 2. Institute of Metal Research, The Chinese Academy of Sciences,
 Shenyang 110015, P.R.China

Abstract:Hot compression experiments were conducted on Ti-15-3 alloy specimens using Gleeble-1500 Thermal Simulator.These tests were focused to obtain the flow stress data under various conditions of strain,strain rate and temperature. On thebasis of these data,the predicting model for the nonlinear relation between flow stress and deformation strain,strain rate and temperature for Ti-15-3 alloy was developed with a back-propagation artificial neural network method. Results show that the neural network can reproduce the flow stress in the sampled data and predict the nonsampled data well. Thus the neural network method has been verified to be used to tackle hot deformation problems of Ti-15-3 alloy.

 

Key words: artificial neural network;  Ti-15-3 alloy; flow stress

ISSN 1672-7029
CN 43-1423/U

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