Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/47728
Title: Artificial Neural Network (ANN) approach to hardness prediction of aged aluminium 2024 and 6063 Alloys
Authors: Meyveci A.
Karacan I.
Durmuş H.
Çaligülü U.
Keywords: Aluminum
Deep neural networks
Hardness
Neural networks
AA 2024
AA 6063
Aging heat treatment
Experimental values
Hardness prediction
Aluminum alloys
Publisher: Carl Hanser Verlag
Abstract: In this study, the effect of aging heat treatment on the hardness of AA 2024 and AA 6063 aluminum alloys was investigated by experimental and an Artificial Neural Network (ANN). AA 2024 and AA 6063 aluminum alloys were solution treated at two different temperatures of 490° C and 520° C. Then both samples were cooled to room temperature. After this process, the samples were aged at three different temperatures (140° C, 180° C, 220° C) for ten different periods of time (2, 4, 6, 8, 10, 12, 14, 16, 18, and 20 h.). The experimental results were trained in an ANNs program, and the results were compared with experimental values. It is observed that the experimental results coincided with the ANNs results. © Carl Hanser Verlag, München.
URI: https://doi.org/10.3139/120.110290
https://hdl.handle.net/11499/47728
ISSN: 0025-5300
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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