Inverse Identification of the Dynamic Recrystallization Parameters for AZ31 Magnesium Alloy Using BP Neural Network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Mechanical Engineering,Mechanics of Materials,General Materials Science
Link
http://link.springer.com/content/pdf/10.1007/s11665-011-0015-0.pdf
Reference32 articles.
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2. J. Liu, Z. Cui, and C. Li, Modelling of Flow Stress Characterizing Dynamic Recrystallization for Magnesium Alloy AZ31B, Comput. Mater. Sci., 2008, 41, p 375–382
3. A. Galiyev, R. Kaibyshev, and G. Gottstein, Correlation of Plastic Deformation and Dynamic Recrystallization in Magnesium Alloy ZK60, Acta Mater., 2001, 49, p 1199–1207
4. Y. Zhang, X. Zeng, C. Lu, and W. Ding, Deformation Behavior and Dynamic Recrystallization of a Mg-Zn-Y-Zr Alloy, Mater. Sci. Eng. A, 2006, 428, p 91–99
5. X. Zhao, K. Zhang, X. Li et al., Deformation Behavior and Dynamic Recrystallization of Mg-Y-Nd-Gd-Zr Alloy, J Rare Earths, 2008, 26(6), p 846–850
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