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

Yazdanmehr, M ; Sharif University of Technology | 2009

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  1. Type of Document: Article
  2. DOI: 10.1016/j.commatsci.2008.08.006
  3. Publisher: 2009
  4. Abstract:
  5. 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. © 2008 Elsevier B.V. All rights reserved
  6. Keywords:
  7. Intermetallic ; Mechanical properties ; Backpropagation ; Intermetallics ; Mechanical engineering ; Nanocrystalline alloys ; Nanocrystalline materials ; Semiconducting intermetallics ; Sensitivity analysis ; Back propagation (BP) ; Chemical compositions ; Intermetallic ; Intermetallic compound (IMC) ; Layer perceptron ; Mechanical behaviors ; Nano crystalline ; Nanocrystalline compounds ; Neural network
  8. Source: Computational Materials Science ; Volume 44, Issue 4 , 2009 , Pages 1231-1235 ; 09270256 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S0927025608003868