alexa Establishing Mathematical Models to Predict Grain Size and Hardness of the Friction Stir-Welded AA 7020 Aluminum Alloy Joints


International Journal of Sensor Networks and Data Communications

Author(s): A Rahimzadeh Ilkhichi, Ramin Soufi, Ghulam Hussain, Akbar Heidarzadeh

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In this study, response surface methodology in conjunction with a central composite design was applied to predict the grain size and hardness of friction stir-welded AA 7020 aluminum alloy joints. For this purpose, three welding parameters, including tool rotational speed, traverse speed, and tool axial force, at five levels and 20 runs were considered. In order to validate the predicted models, the analysis of variance was performed. Hardness and microstructural features of the joints were investigated using microhardness test and optical microscopy, respectively. In addition, the influences of friction stir welding parameters on grain size and hardness of the joints were examined thoroughly. The analysis of variance results revealed that the developed models were significant and accurate to predict the responses. Furthermore, with increasing the heat input, the hardness of the joints decreased, where the grain size increased continuously. In addition, the optimized condition for achieving the lowest grain size and highest hardness of the joints was reached as 800 rpm, 125 mm/min and 8 kN.

This article was published in Metallurgical and Materials Transactions B and referenced in International Journal of Sensor Networks and Data Communications

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