TY - JOUR
T1 - Study on the Hot Processing Parameters-Impact Toughness Correlation of Ti-6Al-4V Alloy
AU - Shi, Xiaohui
AU - Zeng, Weidong
AU - Sun, Yu
AU - Han, Yuanfei
AU - Zhao, Yongqing
N1 - Publisher Copyright:
© 2016, ASM International.
PY - 2016/5/1
Y1 - 2016/5/1
N2 - In this research, the hot processing parameters-impact toughness correlation of Ti-6Al-4V titanium alloy is studied. Fifty-four groups of hot processing treatments with different forging temperatures (930, 950, 970 °C), deformation degrees (20, 50, 80%), annealing temperatures (600, 700, 800 °C), and annealing time (1 and 5 h) were conducted. The orthogonal design was used to find the primary hot processing parameters influencing the impact toughness of Ti-6Al-4V alloy. The results show that the annealing temperature can exert the biggest influence on impact toughness. Low annealing temperature is essential to achieve high impact toughness value. In addition, the BP neural network was used to describe the quantitative correlation between hot processing parameters and impact toughness. The results show that the BP neural network exhibits good performance in predicting the impact toughness of Ti-6Al-4V alloy. The prediction error is within 5%. The BP neural network and the orthogonal design method are mutually confirmed in the present work. Finally, based on the microstructure analysis, the reasons responsible for above experimental results are explained.
AB - In this research, the hot processing parameters-impact toughness correlation of Ti-6Al-4V titanium alloy is studied. Fifty-four groups of hot processing treatments with different forging temperatures (930, 950, 970 °C), deformation degrees (20, 50, 80%), annealing temperatures (600, 700, 800 °C), and annealing time (1 and 5 h) were conducted. The orthogonal design was used to find the primary hot processing parameters influencing the impact toughness of Ti-6Al-4V alloy. The results show that the annealing temperature can exert the biggest influence on impact toughness. Low annealing temperature is essential to achieve high impact toughness value. In addition, the BP neural network was used to describe the quantitative correlation between hot processing parameters and impact toughness. The results show that the BP neural network exhibits good performance in predicting the impact toughness of Ti-6Al-4V alloy. The prediction error is within 5%. The BP neural network and the orthogonal design method are mutually confirmed in the present work. Finally, based on the microstructure analysis, the reasons responsible for above experimental results are explained.
KW - artificial neural network
KW - orthogonal test
KW - processing parameter
KW - Ti-6Al-4V alloy
UR - http://www.scopus.com/inward/record.url?scp=84963995204&partnerID=8YFLogxK
U2 - 10.1007/s11665-016-2050-3
DO - 10.1007/s11665-016-2050-3
M3 - 文章
AN - SCOPUS:84963995204
SN - 1059-9495
VL - 25
SP - 1741
EP - 1748
JO - Journal of Materials Engineering and Performance
JF - Journal of Materials Engineering and Performance
IS - 5
ER -