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Artificial neural network prediction to the hot compressive deformation behavior of Al–Cu–Mg–Ag heat-resistant aluminum alloy

Authors :
Lu, Zhilun
Pan, Qinglin
Liu, Xiaoyan
Qin, Yinjiang
He, Yunbin
Cao, Sufang
Source :
Mechanics Research Communications. Apr2011, Vol. 38 Issue 3, p192-197. 6p.
Publication Year :
2011

Abstract

Abstract: The behavior of the flow stress of Al–Cu–Mg–Ag heat-resistant aluminum alloys during hot compression deformation was studied by thermal simulation test. The temperature and the strain rate during hot compression were 340–500°C, 0.001s−1 to 10s−1, respectively. Constitutive equations and an artificial neural network (ANN) model were developed for the analysis and simulation of the flow behavior of the Al–Cu–Mg–Ag alloys. The inputs of the model are temperature, strain rate and strain. The output of the model is the flow stress. Comparison between constitutive equations and ANN results shows that ANN model has a better prediction power than the constitutive equations. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
00936413
Volume :
38
Issue :
3
Database :
Academic Search Index
Journal :
Mechanics Research Communications
Publication Type :
Academic Journal
Accession number :
60379003
Full Text :
https://doi.org/10.1016/j.mechrescom.2011.02.015