Development of an optimal process for friction stir welding based on GA-RSM hybrid algorithm

Performance of Friction Stir Welding (FSW) as a solid-state process is approved in several engineering applications, especially aluminum industries. Identification of mechanical behavior of the associated welded zone is necessary due to these extensive applications of FSW. In this study, considering...

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Main Authors: Nabi Mehri Khansari, Filippo Berto, Namdar Karimi, S.M.N Ghoreishi, Mahdi Fakoor, Mozhgan Mokari
Format: Article
Language:English
Published: Gruppo Italiano Frattura 2018-04-01
Series:Frattura ed Integrità Strutturale
Subjects:
Online Access:http://www.gruppofrattura.it/pdf/rivista/numero44/numero_44_art_9.pdf
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spelling doaj-f60f8528eed84e0fb943212db7ec9a402020-11-24T23:35:52ZengGruppo Italiano FratturaFrattura ed Integrità Strutturale1971-89932018-04-01124410612210.3221/IGF-ESIS.44.0910.3221/IGF-ESIS.44.09Development of an optimal process for friction stir welding based on GA-RSM hybrid algorithmNabi Mehri KhansariFilippo BertoNamdar KarimiS.M.N GhoreishiMahdi FakoorMozhgan MokariPerformance of Friction Stir Welding (FSW) as a solid-state process is approved in several engineering applications, especially aluminum industries. Identification of mechanical behavior of the associated welded zone is necessary due to these extensive applications of FSW. In this study, considering the effect of rotational and forward speed of welding tool on the mechanical properties of welded region, a hybrid optimization method based on combination of Genetic Algorithm (GA) and Response Surface Method (RSM) named here as GA-RSM is proposed to achieve maximum tensile and ultimate strength. The results of GA-RSM are validated by per-forming necessary experimental tests on two wide-used 2024 and 5050 aluminum alloys. The results show that GA-RSM could be an effective approach to achieve optimized process for FSW with minimum costhttp://www.gruppofrattura.it/pdf/rivista/numero44/numero_44_art_9.pdfFriction Stir Welding (FSW) Optimized mechanical properties Genetic Algorithm (GA) Response Surface Methodology (RSM)
collection DOAJ
language English
format Article
sources DOAJ
author Nabi Mehri Khansari
Filippo Berto
Namdar Karimi
S.M.N Ghoreishi
Mahdi Fakoor
Mozhgan Mokari
spellingShingle Nabi Mehri Khansari
Filippo Berto
Namdar Karimi
S.M.N Ghoreishi
Mahdi Fakoor
Mozhgan Mokari
Development of an optimal process for friction stir welding based on GA-RSM hybrid algorithm
Frattura ed Integrità Strutturale
Friction Stir Welding (FSW)
Optimized mechanical properties
Genetic Algorithm (GA)
Response Surface Methodology (RSM)
author_facet Nabi Mehri Khansari
Filippo Berto
Namdar Karimi
S.M.N Ghoreishi
Mahdi Fakoor
Mozhgan Mokari
author_sort Nabi Mehri Khansari
title Development of an optimal process for friction stir welding based on GA-RSM hybrid algorithm
title_short Development of an optimal process for friction stir welding based on GA-RSM hybrid algorithm
title_full Development of an optimal process for friction stir welding based on GA-RSM hybrid algorithm
title_fullStr Development of an optimal process for friction stir welding based on GA-RSM hybrid algorithm
title_full_unstemmed Development of an optimal process for friction stir welding based on GA-RSM hybrid algorithm
title_sort development of an optimal process for friction stir welding based on ga-rsm hybrid algorithm
publisher Gruppo Italiano Frattura
series Frattura ed Integrità Strutturale
issn 1971-8993
publishDate 2018-04-01
description Performance of Friction Stir Welding (FSW) as a solid-state process is approved in several engineering applications, especially aluminum industries. Identification of mechanical behavior of the associated welded zone is necessary due to these extensive applications of FSW. In this study, considering the effect of rotational and forward speed of welding tool on the mechanical properties of welded region, a hybrid optimization method based on combination of Genetic Algorithm (GA) and Response Surface Method (RSM) named here as GA-RSM is proposed to achieve maximum tensile and ultimate strength. The results of GA-RSM are validated by per-forming necessary experimental tests on two wide-used 2024 and 5050 aluminum alloys. The results show that GA-RSM could be an effective approach to achieve optimized process for FSW with minimum cost
topic Friction Stir Welding (FSW)
Optimized mechanical properties
Genetic Algorithm (GA)
Response Surface Methodology (RSM)
url http://www.gruppofrattura.it/pdf/rivista/numero44/numero_44_art_9.pdf
work_keys_str_mv AT nabimehrikhansari developmentofanoptimalprocessforfrictionstirweldingbasedongarsmhybridalgorithm
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AT namdarkarimi developmentofanoptimalprocessforfrictionstirweldingbasedongarsmhybridalgorithm
AT smnghoreishi developmentofanoptimalprocessforfrictionstirweldingbasedongarsmhybridalgorithm
AT mahdifakoor developmentofanoptimalprocessforfrictionstirweldingbasedongarsmhybridalgorithm
AT mozhganmokari developmentofanoptimalprocessforfrictionstirweldingbasedongarsmhybridalgorithm
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