Prediction of heat generation and microstructure of AA7075 friction stir welding using ANN: Effect of process parameters

The presence of residual stresses within a friction stir welded structure commonly results in severe deformation and weakness in the structure's ability to withstand imposed external loads. Coupled Eulerian Lagrangian approach was applied to develop the simulation analysis and investigate the t...

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Bibliographic Details
Published in:Manufacturing letters 2022-04, Vol.32, p.5-9
Main Authors: Salhan, Pranav, Singh, Rupanshu, Jain, Prasoon, Butola, Ravi
Format: Article
Language:English
Subjects:
AA7075 aluminium
Artificial neural network
Friction stir welding
Mechanical properties
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Summary:The presence of residual stresses within a friction stir welded structure commonly results in severe deformation and weakness in the structure's ability to withstand imposed external loads. Coupled Eulerian Lagrangian approach was applied to develop the simulation analysis and investigate the thermal behaviour and stresses occurring during welding. The numerical simulations show that on increasing the rotational speed the weld flow temperature and plastic strain increases. Artificial neural network was developed to predict the output parameters and a regression coefficient value of 0.990 was attained. General insights and trends about the microstructure of similar FSW AA7075 were discussed.
ISSN:2213-8463
2213-8463
DOI:10.1016/j.mfglet.2022.01.004