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Metals 2015, 5(2), 836-849; doi:10.3390/met5020836

A Mathematical Formulation to Estimate the Effect of Grain Refiners on the Ultimate Tensile Strength of Al-Zn-Mg-Cu Alloys

1
Technical Sciences, University of Gaziantep, Gaziantep 27310, Turkey
2
Department of Metallurgical and Materials Engineering, Engineering Faculty, Fırat University, Elazığ 23119, Turkey
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Hugo F. Lopez
Received: 13 February 2015 / Accepted: 13 May 2015 / Published: 22 May 2015
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Abstract

In this study, the feed-forward (FF) neural networks (NNs) with back-propagation (BP) learning algorithm is used to estimate the ultimate tensile strength of unrefined Al-Zn-Mg-Cu alloys and refined the alloys by Al-5Ti-1B and Al-5Zr master alloys. The obtained mathematical formula is presented in great detail. The designed NN model shows good agreement with test results and can be used to predict the ultimate tensile strength of the alloys. Additionally, the effects of scandium (Sc) and carbon (C) rates are investigated by using the proposed equation. It was observed that the tensile properties of Al-Zn-Mg-Cu alloys improved with the addition of 0.5 Sc and 0.01 C wt.%. View Full-Text
Keywords: Al-Zn-Mg-Cu alloys; ultimate tensile strength; modeling; ANN Al-Zn-Mg-Cu alloys; ultimate tensile strength; modeling; ANN
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Kurt, H.I.; Oduncuoglu, M.; Kurt, M. A Mathematical Formulation to Estimate the Effect of Grain Refiners on the Ultimate Tensile Strength of Al-Zn-Mg-Cu Alloys. Metals 2015, 5, 836-849.

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