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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2018-04-01
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Online Access: | http://www.gruppofrattura.it/pdf/rivista/numero44/numero_44_art_9.pdf |
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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 AT filippoberto developmentofanoptimalprocessforfrictionstirweldingbasedongarsmhybridalgorithm AT namdarkarimi developmentofanoptimalprocessforfrictionstirweldingbasedongarsmhybridalgorithm AT smnghoreishi developmentofanoptimalprocessforfrictionstirweldingbasedongarsmhybridalgorithm AT mahdifakoor developmentofanoptimalprocessforfrictionstirweldingbasedongarsmhybridalgorithm AT mozhganmokari developmentofanoptimalprocessforfrictionstirweldingbasedongarsmhybridalgorithm |
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1725524251399684096 |