ArticleMaterials (Basel, Switzerland)2023
Prediction of Tool Eccentricity Effects on the Mechanical Properties of Friction Stir Welded AA5754-H24 Aluminum Alloy Using ANN Model.
Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Research on Multiscale Characterization and Computational Modeling/Simulation of Metallic Materials.Materials (Basel, Switzerland) · 2026Article
- Friction stir welding of aluminum alloy 6082-T6 using eccentric shoulder tools to eliminate the need for tool tilting.Scientific reports · 2025Article
- Optimization of 2024-T3 Aluminum Alloy Friction Stir Welding Using Random Forest, XGBoost, and MLP Machine Learning Techniques.Materials (Basel, Switzerland) · 2024Article
- Modeling and Experimental Investigation of the Impact of the Hemispherical Tool on Heat Generation and Tensile Properties of Dissimilar Friction Stir Welded AA5083 and AA7075 Al Alloys.Materials (Basel, Switzerland) · 2024Article
- Advanced Analytical Methods of the Analysis of Friction Stir Welding Process (FSW) of Aluminum Sheets Used in the Automotive Industry.Materials (Basel, Switzerland) · 2023Article
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Authors and funding
5 authors.
Funding
Abstract
The current study uses three different pin eccentricities (e) and six different welding speeds to investigate the impact of pin eccentricity on friction stir welding (FSW) of AA5754-H24. To simulate and forecast the impact of (e) and welding speed on the mechanical properties of friction stir welded joints for (FSWed) AA5754-H24, an artificial neural network (ANN) model was developed. The input parameters for the model in this work are welding speed (WS) and tool pin eccentricity (e). The outputs of the developed ANN model include the mechanical properties of FSW AA5754-H24 (ultimate tensile strength, elongation, hardness of the thermomechanically affected zone (TMAZ), and hardness of the weld nugget zone (NG)). The ANN model yielded a satisfactory performance. The model has been used to predict the mechanical properties of the FSW AA5754 aluminum alloy as a function of TPE and WS with excellent reliability. Experimentally, the tensile strength is increased by increasing both the (e) and the speed, which was already captured from the ANN predictions. The R
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