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Mathematical and Computational Applications is published by MDPI from Volume 21 Issue 1 (2016). Previous articles were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with Association for Scientific Research (ASR).
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Article

Determination Of Yield Strenght of 2014 Aluminium Alloy under Aging Conditions by Means of Artifical Neural Networks Method

by
Enver AtiK
*,
Cevdet Meriç
and
Bekir Karlik
C.B.U. Engineering Faculty, 45040 Manisa, Turkey
*
Author to whom correspondence should be addressed.
Math. Comput. Appl. 1996, 1(2), 16-20; https://doi.org/10.3390/mca1020016
Published: 1 December 1996
Versions Notes

Abstract

As known, 2XXX and 7XXX Aluminum process alloys can have high strength values by means of precipitation hardening heat treatment. Determination of the precipitation hardening conditions which can give the most suitable strength values of an alloy, requires numerous tests. But the results of this process which require long time and high cost can be obtained in a shorter time and at a lower cost with less data by means of Artificial Neural Networks method. Since this method is used, less number of experiments and therefore less data is needed. Then other values are found by means of Artificial Neural Networks method.In this study, Artificial Neural Networks were educated with yield strength values of 2014 Aluminum alloy obtained at different aging times and at 150, 190, 232, and 260 °C after taken into solution at 500 °C. Afterwards, yield strengths of alloy at different temperatures were
determined by means of Artificial Neural Networks method.

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MDPI and ACS Style

AtiK, E.; Meriç, C.; Karlik, B. Determination Of Yield Strenght of 2014 Aluminium Alloy under Aging Conditions by Means of Artifical Neural Networks Method. Math. Comput. Appl. 1996, 1, 16-20. https://doi.org/10.3390/mca1020016

AMA Style

AtiK E, Meriç C, Karlik B. Determination Of Yield Strenght of 2014 Aluminium Alloy under Aging Conditions by Means of Artifical Neural Networks Method. Mathematical and Computational Applications. 1996; 1(2):16-20. https://doi.org/10.3390/mca1020016

Chicago/Turabian Style

AtiK, Enver, Cevdet Meriç, and Bekir Karlik. 1996. "Determination Of Yield Strenght of 2014 Aluminium Alloy under Aging Conditions by Means of Artifical Neural Networks Method" Mathematical and Computational Applications 1, no. 2: 16-20. https://doi.org/10.3390/mca1020016

APA Style

AtiK, E., Meriç, C., & Karlik, B. (1996). Determination Of Yield Strenght of 2014 Aluminium Alloy under Aging Conditions by Means of Artifical Neural Networks Method. Mathematical and Computational Applications, 1(2), 16-20. https://doi.org/10.3390/mca1020016

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