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Mechanical behavior modeling of nanocrystalline NiAl compound by a feed-forward back-propagation multi-layer perceptron ANN

Authors :
Yazdanmehr, M.
Anijdan, S.H. Mousavi
Samadi, A.
Bahrami, A.
Source :
Computational Materials Science. Feb2009, Vol. 44 Issue 4, p1231-1235. 5p.
Publication Year :
2009

Abstract

Abstract: In this paper, an artificial neural network (ANN) model has been developed to predict the yield and tensile strengths of hot pressed NiAl intermetallic compound based on the experimental data from Albiter et al. [A. Albiter, M. Salazar, E. Bedolla, R.A.L. Drew, R. Perez, Mater. Sci. Eng. A 347 (2003) 154]. The predicted results, with a correlation relation between 0.9791 and 0.9921, show a very good agreement with the experimental values. Furthermore, the sensitivity analysis was performed to investigate the importance of the effects of chemical composition and temperature on the mechanical behavior of hot pressed NiAl intermetallic compound. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
09270256
Volume :
44
Issue :
4
Database :
Academic Search Index
Journal :
Computational Materials Science
Publication Type :
Academic Journal
Accession number :
36338240
Full Text :
https://doi.org/10.1016/j.commatsci.2008.08.006