Formation of the periodic material flow behaviour in friction stir welding

Wang, Tao; Chen, Wu

doi:10.1080/13621718.2021.1902605

Cited by 18 publications

(7 citation statements)

References 30 publications

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“…The periodic F x and F y and their amplitudes depict the eccentric motion of the tool [21,49]. The periodic material flow, sticking and slipping contact condition at the tool-workpiece interface and banded structure in the SZ are consistent with the periodic waveforms of F x and F y [26,28,50]. Moreover, the high-frequency harmonics, such as A 2Fx , A 3Fx , A 2Fy and A 3Fy , are close related to the material flow and plastic deformation behavior during FSW [27,47,51,52].…”

Section: Prediction Of M-a Constituent and Impact Toughnesssupporting

confidence: 58%

Prediction of M–A Constituents and Impact Toughness in Stir Zone of X80 Pipeline Steel Friction Stir Welds

Wang

et al. 2022

Acta Metall. Sin. (Engl. Lett.)

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This study explored a strategy for predicting the proportion of martensite-austenite (M-A) constituents and impact toughness of stir zone (SZ) on X80 pipeline steel joints welded by friction stir welding (FSW). It is found that the welding forces, including the traverse force (F x ), the lateral force (F y ) and the plunge force (F z ), are the key variables related to the change of welding parameters and influence remarkably the characteristics of M-A constituents and impact toughness of SZ. The impact toughness of SZ is commonly lower than that of the base material due to the formation of lath bainite and coarsening of austenite. The characteristics of M-A constituents in SZ are sensitive to the variation of welding parameters and respond well to the change of welding forces. The proportion of small island M-A constituents increases with the decrease in rotational speed and the increase in F z . The increase in the amount of island M-A constituents is beneficial to improve the impact toughness of SZ. Based on the above findings, a machine learning (ML) model for predicting the M-A constituents and impact toughness is constructed using the force features as the input data set. The force data-driven ML model can predict the M-A constituents and impact toughness precisely and exhibits higher accuracy than ML built with welding parameters. It is believed that the high accuracy is achieved because the force features include more details of FSW process, such as the heat generation, material flow, plastic deformation, and so on, which govern the microstructural evolution of SZ during FSW.

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Section: Prediction Of M-a Constituent and Impact Toughnesssupporting

confidence: 58%

Prediction of M–A Constituents and Impact Toughness in Stir Zone of X80 Pipeline Steel Friction Stir Welds

Wang

et al. 2022

Acta Metall. Sin. (Engl. Lett.)

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“…Kalling's No.2 solution (12 g CuCl2 + 20 mL HCL + 225 mL C2H5OH) was used as an etching solution for microstructure evaluation [32,33]. An optical microscope took the bead geometry, and the microstructure evaluations were conducted with the aid of a Scanning Electron Microscope (SEM) having an Energy Dispersive X-ray Spectroscopy (EDX) analyzer for finding out the composition of elements in the welded region [34]. IA-FSW's influence on the corrosive behaviour of AISI 410 welded joints was analyzed by 3 hours and 24 hours weight loss method in 1 M HCL solution.…”

Section: Methodsmentioning

confidence: 99%

Assessment of Corrosive Behaviour and Microstructure Characterization of Hybrid Friction Stir Welded Martensitic Stainless Steel

Mohan

Gopi²,

Tomków

et al. 2021

Advances in Materials Science

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This study examined the effect of induction heating on the microstructure and corrosion characteristics of hybrid friction stir welded AISI 410 stainless steel. Five joints have been produced with different friction stir welding parameters like welding speed, spindle speed, plunge depth, and induction power. Their microstructures were evaluated using a scanning electron microscope, and chemical composition was examined using energy-dispersive X-ray spectroscopy (EDX). The rate of corrosion was found out via the weight loss method in a 1 M HCL solution. The hybrid friction stir welding method used for this work is induction assisted friction stir welding; the results show that this method could produce sound AISI 410 stainless steel Joints. The experiment results show that the joint made at a spindle speed of 1150 rpm, welding speed 40 mm/min, plunge depth 0.5 mm, and in-situ heat by induction 480°C show a better corrosion resistance property with a fine grain structure.

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“…Numerical simulation in computational fluid dyna mics (CFD) is a useful quantitative method to investigate thermomechanical conditions [12][13][14]. However, numerical simulation of SSFSW mainly focused on Tjoints of aluminium alloys but excluding titanium alloys [15,16], and the reliability depends on many factors, such as constitutive models, heat models and boundary conditions [17].…”

Section: Introductionmentioning

confidence: 99%

Material flow and viscous slips during stationary shoulder friction stir welding of Ti6Al4V

Wang

Jiang

Yuan

et al. 2022

Science and Technology of Welding and Joining

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The flow and slip rate of material in friction stir welding mainly determined the weld quality, flow rate depended not only on the shape of pin and welding parameters but also on slip, and an instantaneous centre of speed was generated by rotating speed and welding speed. The relative speed of contact interface is generally an important factor in material flow. The material experienced different viscous slips when rotating around the pin, which disengaged pin at a larger slip and adhered to pin at a smaller slip, resulting in large differences in two sides. The first derivative of the dividing line at the boundary of SZ was extracted to investigate material flow.

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Formation of the periodic material flow behaviour in friction stir welding

Cited by 18 publications

References 30 publications

Prediction of M–A Constituents and Impact Toughness in Stir Zone of X80 Pipeline Steel Friction Stir Welds

Prediction of M–A Constituents and Impact Toughness in Stir Zone of X80 Pipeline Steel Friction Stir Welds

Assessment of Corrosive Behaviour and Microstructure Characterization of Hybrid Friction Stir Welded Martensitic Stainless Steel

Material flow and viscous slips during stationary shoulder friction stir welding of Ti6Al4V

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