A comparative study on phenomenon and deep belief network models for hot deformation behavior of an Al–Zn–Mg–Cu alloy

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• 作者：Y. C. Lin ; Ying-Jie Liang ; Ming-Song Chen ; Xiao-Min Chen
• 刊名：Applied Physics A
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：123
• 期：1
• 全文大小：
• 刊物类别：Physics and Astronomy
• 刊物主题：Condensed Matter Physics; Optical and Electronic Materials; Nanotechnology; Characterization and Evaluation of Materials; Surfaces and Interfaces, Thin Films; Operating Procedures, Materials Treatment
• 出版者：Springer Berlin Heidelberg
• ISSN：1432-0630
• 卷排序：123

文摘

The high temperature deformation behavior of an Al–Zn–Mg–Cu alloy is studied by isothermal compression tests at the temperature range of 573–723 K and strain rate range of 0.001–0.1 s−1. Considering the coupled influences of deformation temperature, strain, and strain rate on hot deformation behavior, a deep belief network (DBN) model, as well as a phenomenological constitutive model, is developed for the studied alloy. In order to validate the developed models, the average absolute relative error and correlation coefficient are evaluated between the measured and predicted true stresses. The results show that the developed DBN model has the better predictability for the high temperature deformation behavior of the studied Al–Zn–Mg–Cu alloy. Moreover, the average absolute relative error and correlation coefficient of DBN model are 0.57% and 0.9997, respectively. In addition, the developed DBN model can be effectively applied in the intelligent manufacturing, such as intelligent isothermal die forging technology.