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Investigating Formability Behavior of Friction Stir-Welded High-Strength Shipbuilding Steel using Experimental, Finite Element, and Artificial Neural Network Methods

Crossref DOI link: https://doi.org/10.1007/s11665-024-09501-8

Published Online: 2024-04-30

Published Print: 2025-03

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Sekban, Dursun Murat https://orcid.org/0000-0002-7493-1081
Yaylacı, Ecren Uzun https://orcid.org/0000-0002-2558-2487
Özdemir, Mehmet Emin https://orcid.org/0000-0001-7983-7265
Yaylacı, Murat https://orcid.org/0000-0003-0407-1685
Tounsi, Abdelouahed
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Text and Data Mining valid from 2024-04-30

Version of Record valid from 2024-04-30
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Article History

Received: 22 January 2024

Revised: 26 February 2024

Accepted: 18 March 2024

First Online: 30 April 2024

Conflict of interest

: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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