Application of Artificial Neural Network to Friction Stir Welding Process of AA7050 Aluminum Alloy

Author(s):  
Aniket K. Dutt ◽  
K. Sindhuja ◽  
Siriyapureddy Vijaya Narasimha Reddy ◽  
Pawan Kumar
Metals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 804
Author(s):  
Sansan Ding ◽  
Qingyu Shi ◽  
Gaoqiang Chen

The purpose of this paper is to report quantitative data and models for the flow stress for the computer simulation of friction stir welding (FSW). In this paper, the flow stresses of the commercial 6061 aluminum alloy at the typical temperatures in FSW are investigated quantitatively by using hot compression tests. The typical temperatures during FSW are determined by reviewing the literature data. The measured data of flow stress, strain rate and temperature during hot compression tests are fitted to a Sellars–Tegart equation. An artificial neural network is trained to implement an accurate model for predicting the flow stress as a function of temperature and strain rate. Two models, i.e., the Sellars–Tegart equation and artificial neural network, for predicting the flow stress are compared. It is found that the root-mean-squared error (RMSE) between the measured and the predicted values are found to be 3.43 MPa for the model based on the Sellars–Tegart equation and 1.68 MPa for the model based on an artificial neural network. It is indicated that the artificial neural network has better flexibility than the Sellars–Tegart equation in predicting the flow stress at typical temperatures during FSW.


Author(s):  
Mahmoud Abbasi ◽  
Amin Abdollahzadeh ◽  
Behrouz Bagheri ◽  
Ahmad Ostovari Moghaddam ◽  
Farzaneh Sharifi ◽  
...  

Various methods have been proposed to modify the friction stir welding. Friction stir vibration welding and underwater friction stir welding are two variants of this technique. In friction stir vibration welding, the adjoining workpieces are vibrated normal to the joint line while friction stir welding is carried out, while in underwater friction stir welding the friction stir welding process is performed underwater. The effects of these modified versions of friction stir welding on the microstructure and mechanical characteristics of AA6061-T6 aluminum alloy welded joints are analyzed and compared with the joints fabricated by conventional friction stir welding. The results indicate that grain size decreases from about 57 μm for friction stir welding to around 34 μm for friction stir vibration welding and about 23 μm for underwater friction stir welding. The results also confirm the evolution of Mg2Si precipitates during all processes. Friction stir vibration welding and underwater friction stir welding processes can effectively decrease the size and interparticle distance of precipitates. The strength and ductility of underwater friction stir welding and friction stir vibration welding processed samples are higher than those of the friction stir welding processed sample, and the highest strength and ductility are obtained for underwater friction stir welding processed samples. The underwater friction stir welding and friction stir vibration welding processed samples exhibit about 25% and 10% higher tensile strength compared to the friction stir welding processed sample, respectively. The results also indicate that higher compressive residual stresses are developed as underwater friction stir welding and friction stir vibration welding are applied.


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