Thermo-mechanical analysis of linear welding stage in friction stir welding: Influence of welding parameters

Veljic, M Darko; Rakin, P Marko; Sedmak, Aleksandar; Radović, A.; Medjo, Bojan; Mrdak, Mihailo; Bajić, Darko

doi:10.2298/tsci210216186v

Cited by 2 publications

(2 citation statements)

References 26 publications

(42 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also, the evolutions of force and temperature values during the welding are considered in [22]. Influence of welding parameters on the process itself or the joint properties is shown in [16,[23][24][25], while the effect of heat input, as another important topic for FSW, is considered in [26,27].…”

Section: Fig 1 Schematic Illustration Of Fsw Process [9]mentioning

confidence: 99%

See 1 more Smart Citation

Influence of temperature and plastic deformation on AA2024 T3 friction stir welded joint microstructure

et al. 2023

View full text Add to dashboard Cite

This paper deals with analysis and comparison of the equivalent plastic strain and temperature fields in the aluminium alloy 2024 T3 welded joint, with macro/microstructure appearance and hardness profile. In the alloys hardened by heat treatment, grain size and particle size of the precipitate are functions of equivalent plastic strain, strain rate and temperature. By analyzing the equivalent plastic strain fields and temperature fields it is possible, to some extent, to capture the effect of welding parameters and thermo-mechanical conditions on grain structure, and therefore hardness and strength in the welded joint. A coupled thermo-mechanical model is applied to study the material behaviour during the linear welding stage of friction stir welding (FSW). Three-dimensional finite element (FE) model has been created in ABAQUS/Explicit software using the Johnson-Cook material law. The values of thermo-mechanical quantities during the welding stage are obtained from the numerical model and shown as distributions across the joint. The obtained values of these quantities are related to the microstructure of the joint zones and hardness distribution, and this relation is discussed.

show abstract

Section: Fig 1 Schematic Illustration Of Fsw Process [9]mentioning

confidence: 99%

“…The welding tool model has a cylindrical pin, which is an often used simplification in published studies dealing with FSW. The model (and different groups of the results, as mentioned in the Introduction section) are described in [13,[20][21][22][23], and some main notes are given here.…”

Section: Numerical Modelmentioning

confidence: 99%

Influence of temperature and plastic deformation on AA2024 T3 friction stir welded joint microstructure

et al. 2023

View full text Add to dashboard Cite

show abstract

Prediction of the tensile strength of friction stir welded joints based on one-dimensional convolutional neural network

Lü

Yang

et al. 2023

IFS

View full text Add to dashboard Cite

Friction stir welding (FSW) is a complex thermo-mechanical coupling process. Tensile strength is an important evaluation index of the mechanical properties of welded joints. How to realize the real-time prediction of tensile strength of the friction stir welded joints to reflect the dynamic change of welding state is a problem in the field. To solve this problem, this paper presents a multi-scale one-dimensional convolutional neural network (Multi-scale 1D CNN) prediction model using time series data of temperature and axial force as inputs to realize the online prediction of tensile strength of welded joints. Firstly, FSW experiments are carried out to obtain time series data of temperature and axial force. Tensile strength values of the welded joints is obtained by tensile tests. The time series data and tensile strength values are fused as a dataset. Then Multi-scale 1D CNN, traditional 1D CNN and Multi-channel 1D CNN prediction models are established and trained with the dataset, respectively. Finally, by comparing the prediction performance of the three models, Multi-scale 1D CNN is proved to be more suitable for analyzing time series data to feedback the dynamic change of tensile strength of the joints during welding.

show abstract

Thermo-mechanical analysis of linear welding stage in friction stir welding: Influence of welding parameters

Cited by 2 publications

References 26 publications

Influence of temperature and plastic deformation on AA2024 T3 friction stir welded joint microstructure

Influence of temperature and plastic deformation on AA2024 T3 friction stir welded joint microstructure

Prediction of the tensile strength of friction stir welded joints based on one-dimensional convolutional neural network

Contact Info

Product

Resources

About