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dc.contributor.authorSekban, Dursun Murat
dc.contributor.authorYaylacı, Ecren Uzun
dc.contributor.authorÖzdemir, Mehmet Emin
dc.contributor.authorÖztürk, Şevval
dc.contributor.authorYaylacı, Murat
dc.contributor.authorPanda, Subrata Kumar
dc.date.accessioned2024-06-13T08:23:32Z
dc.date.available2024-06-13T08:23:32Z
dc.date.issued2024en_US
dc.identifier.citationSekban, D. M., Uzun Yaylacı, E., Özdemir, M. E., Öztürk, Ş., Yaylacı, M., & Panda, S. K. (2024). Formability behavior of AH-32 shipbuilding steel strengthened by friction stir process. Theoretical and Applied Fracture Mechanics, 132, 104485. https://doi.org/10.1016/j.tafmec.2024.104485en_US
dc.identifier.issn0167-8442
dc.identifier.urihttps://doi.org/10.1016/j.tafmec.2024.104485
dc.identifier.urihttps://hdl.handle.net/11436/9094
dc.description.abstractShips are built by bringing materials into various forms and then joining them. Although materials such as wood, composite materials, polyethylene, and aluminum alloys are used in shipbuilding, it is known that commercial ships are generally produced from steel materials. Relatively strong steels used in shipbuilding couse problems such as reduced formability and weldability due to their chemical content. In this context, increasing the strength of such steels without changing their chemical composition is extremely important. Although many methods are used to increase the mechanical properties of steels without changing their chemical composition, the friction stir process (FSP) comes to the fore in terms of the increased rate in strength, reasonable decrease in elongation values, and its application to plate-type materials. In this study, FSP was applied to AH-32 steel used in shipbuilding, and the strength and formability values of the steel after the process were examined comparatively with mechanical tests, finite element method, and artificial neural network model. The results determined that steel's strength improved significantly after the FSP, while the formability behavior decreased very limitedly. The results also showed that the mechanical test results, the model results created with finite elements, and the artificial neural networks are highly consistent.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAH-32 steelen_US
dc.subjectArtificial neural networken_US
dc.subjectFinite element analysis approachen_US
dc.subjectFriction stir processen_US
dc.titleFormability behavior of AH-32 shipbuilding steel strengthened by friction stir processen_US
dc.typearticleen_US
dc.contributor.departmentRTEÜ, Mühendislik ve Mimarlık Fakültesi, İnşaat Mühendisliği Bölümüen_US
dc.contributor.institutionauthorYaylacı, Ecren Uzun
dc.contributor.institutionauthorÖztürk, Şevval
dc.contributor.institutionauthorYaylacı, Murat
dc.identifier.doi10.1016/j.tafmec.2024.104485en_US
dc.identifier.volume132en_US
dc.identifier.startpage104485en_US
dc.relation.journalTheoretical and Applied Fracture Mechanicsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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