Intelligent method to develop constitutive relationship of Ti–6Al–2Zr–1Mo–1V alloy

• Published in: Transactions of Nonferrous Metals Society of China Vol. 22; no. 6; pp. 1457 - 1461
• Main Authors: SUN, Yu, ZENG, Wei-dong, ZHAO, Yong-qing, HAN, Yuan-fei, MA, Xiong
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2012
• Subjects: Alloy development; artificial neural network; constitutive relationship; Deformation; deformation behavior; Learning theory; Mathematical models; Neural networks; Strain rate; Titanium base alloys; Ti–6Al–2Zr–1Mo–1V alloy; Yield strength; deformation behavior; artificial neural network; Ti–6Al–2Zr–1Mo–1V alloy; constitutive relationship
• ISSN: 1003-6326
• DOI: 10.1016/S1003-6326(11)61341-1

The isothermal compression tests were carried out in the Thermecmastor-Z thermo-simulator at temperatures of 800, 850, 900, 950, 1000 and 1050 °C and the strain rates of 0.01, 0.1, 1 and 10 s−1. The influence of deformation temperature and strain rate on the flow stress of Ti–6Al–2Zr–1Mo–1V alloy was studied. Based on the experimental data sets, the high temperature deformation behavior of Ti–6Al–2Zr–1Mo–1V alloy was presented using the intelligent method of artificial neural network (ANN). The results indicate that the predicted flow stress values by ANN model is quite consistent with the experimental results, which implies that the artificial neural network is an effective tool for studying the hot deformation behavior of the present alloy. In addition, the development of graphical user interface is implemented using Visual Basic programming language.