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Optimizing the welding performance of 2024-T351 aluminum alloy through friction stir welding technology

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study investigates the impact of friction stir welding (FSW) parameters, specifically the rotational speed of the welding tool and the linear welding speed, on the bonding efficiency and mechanical performance of high-strength aluminum alloy joints. The research focuses on alloy 2024-T351, with a thickness of 7.1 mm, widely utilized in aerospace applications due to its excellent strength-to-weight ratio. However, welding this alloy using conventional fusion methods such as TIG, MIG, and laser welding presents considerable challenges, includ ing the formation of defects and loss of mechanical properties.To overcome these limitations, FSW was employed using a conventional milling machine, with two rotational speeds (800 and 1100 RPM) and three linear welding speeds (28, 40, and 56 mm/min). Tensile test specimens were prepared according to standard procedures, and tensile tests were conducted at room temperature to evaluate the welded joints’ mechanical integrity. The obtained results were compared with the tensile strength of the base metal to determine bonding efficiency. The findings revealed that increasing the rotational speed while reducing the linear welding speed negatively impacted the tensile strength and bonding efficiency of the joints. However, improved ductility was observed at specific speed combinations, indicating an optimal balance between heat input and material flow. The highest bonding efficiency of 87.4% was achieved at a rotational speed of 800 RPM and a linear speed of 28 mm/min, highlighting the importance of precise parameter selection for enhancing weld quality in alloy 2024-T351.
Rocznik
Strony
125--129
Opis fizyczny
Bibliogr. 10 poz., rys., tab.
Twórcy
  • Metallurgical Engineering Department, College of Materials Engineering, Babylon University, Babylon, Iraq
  • College of Food Sciences, Department of Dairy Science and Technology, Al-Qasim Green University
Bibliografia
  • 1. Abd-Allateef, N., Mizhir, A., 2010. Friction Stir Welding of Porous Al-Si alloy. Journal of Engineering and Technology, 28(6).
  • 2. Ambriz, R., Mayagoitia, V., 2011. Welding of aluminum alloys. In Recent Trends in Processing and Degradation of Aluminium Alloys (pp. 63-86). Books on Demand.
  • 3. Campbell, F. C., 2006. Manufacturing Technology for Aerospace Structural Materials. Elsevier Ltd.
  • 4. Khaled, T., (2005). An outsider looks at friction stir welding (Federal Avia tion Administration).
  • 5. Kissell, J. R., 2018. Aluminum and Its Alloys. In Marks’ Standard Handbook for Mechanical Engineers (pp. 2.1-2.92).
  • 6. Maamar, H., Mohamed, K., Rafik, R. O., Toufik, F., Nabil, D., Djilali, A., 2008. Heat treatment and welding effects on mechanical properties and microstructure evolution of 2024 and 7075 aluminium alloys. 2nd Inter national Conference on Heat Treatment and Surface Engineering of Tools and Dies.
  • 7. Silva YC, D.; Andrade, T.C.; Júnior, F.O.; Sousa AB, F.; dos Santos, J.F.; Marcondes, F.; Miranda, H.C.; Silva, C.C. Numerical investigation of the influence of friction stir welding parameters on the microstructure of AISI 410S ferritic stainless steel joints. J. Mater. Res. Technol. 2023, 27, 8344–8359. [Google Scholar] [CrossRef]
  • 8. Matitopanum, S.; Pitakaso, R.; Sethanan, K.; Srichok, T.; Chokanat, P. Pre diction of the Ultimate Tensile Strength (UTS) of Asymmetric Friction Stir Welding Using Ensemble Machine Learning Methods. Processes 2023, 11, 391. [Google Scholar] [CrossRef]
  • 9. Nadeau, F.; Thériault, B.; Gagné, M.-O. Machine learning models applied to friction stir welding defect index using multiple joint configurations and alloys. J. Mater. Des. Appl. 2020, 234, 752–765. [Google Scholar] [CrossRef]
  • 10. Verma, S.; Misra, J.P.; Singh, J.; Batra, U.; Kumar, Y. Prediction of tensile behavior of FS welded AA7039 using machine learning. Mater. Today Commun. 2021, 26, 101933. [Google Scholar] [CrossRef]
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-10ddee88-0ef7-463f-89a2-8fa26486a953
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