Numerical simulations on material flow behaviors in whole process of friction stir welding

Gao, En-zhi; Zhang, X.X.; Liu, Chun-zhong; Ma, Z.Y.

doi:10.1016/s1003-6326(18)64877-0

Cited by 18 publications

(9 citation statements)

References 32 publications

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“…Several authors have shown proper matching with experimental data using friction coefficient values below 1, e.g., 0.45 for Pashazadehet al 19 and 0.3 for Gao et al 16 However, it is observed that all CSM models in literature explored only tools with small dimensions (below 6 mm length) and simplified geometries. [16][17][18][19][20][21][22] In these cases, it is hypothesized that the selected low friction values are inaccurate; however, wrongly providing the right temperature according to calculations. These tools provide a simplified material flow that is easily achievable using low friction values.…”

Section: Frictionmentioning

confidence: 98%

“…Computational solid mechanics (CSM) based methods otherwise consider that the welding material remains solid during the process and has been extensively used in research. [16][17][18][19][20][21][22][23][24] The force equilibrium equation based on continuum mechanics and the resulting partial derivative equations (PDE). Long et al 17 presented a 3 D thermal-mechanical coupled finite element model and investigated the tool tilt angle effect during friction stir welding.…”

Section: Introductionmentioning

confidence: 99%

“…This model was able to predict the thermal-mechanical state variables during the welding and the post-welding morphology of the weld. Gao et al 16 reported the downward spiral movement affected by the shoulder, whereas the lower material first moves in an upward spiral mode affected by the pin and then moves downward. Pashazadeh et al, 19 explored FSW experiments and numerical simulation for a pure copper alloy.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Investigation of material flow and thermomechanical behavior during friction stir welding of an AZ31B alloy for threaded and unthreaded pin geometries using computational solid mechanics simulation

Giorjao

Fonseca

Avila³

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part C:

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In the friction stir welding process, the tool role in the material flow and its thermomechanical behavior is still not entirely understood. Several modeling approaches attempted to explain the material and tool relationship, but to this date, insufficient results were provided in this matter. Regarding this issue and the urgent need for trustful friction stir welding models, a computational solid mechanic's model capable of simulating material flow and defect formation is presented. This model uses an Arbitrary Lagrangian-Eulerian code comparing a threaded and unthread pin profile. The model was able to reproduce the tool's torque, temperatures, and material flow along the entire process, including the underreported downward flow effect promoted by threaded pin's. A point tracking analysis revealed that threads increase the material velocity and strain rate to almost 30% compared to unthreaded conditions, promoting a temperature increment during the process, which improved the material flow and avoided filling defects. The presented results showed the model's capability to reproduce the defects observed in real welded joints, material thermomechanical characteristics and high sensitivity to welding parameters and tool geometries. Nevertheless, the outcomes of this work contribute to essential guidelines for future friction stir welding modeling and development, tool design, and defect prediction.

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Section: Frictionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Investigation of material flow and thermomechanical behavior during friction stir welding of an AZ31B alloy for threaded and unthreaded pin geometries using computational solid mechanics simulation

Giorjao

Fonseca

Avila³

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…The frictional shear stress boundary condition results in a greater dispersion of material across the velocity boundary condition when modelling the FSW between Aluminium and Steel across the toolworkpiece contact interface [14]. Gao et al (2018) created a to examine the material movement across the whole FSW procedure with particle tracking technology using ABAQUS. The simulation showed that the monitored particles move in a spiral pattern around the axis and tracking particles speed moving along the perimeter of the mixer is greater than the speed of the bottom of the weld [15].…”

Section: Introductionmentioning

confidence: 99%

“…Gao et al (2018) created a to examine the material movement across the whole FSW procedure with particle tracking technology using ABAQUS. The simulation showed that the monitored particles move in a spiral pattern around the axis and tracking particles speed moving along the perimeter of the mixer is greater than the speed of the bottom of the weld [15]. Salloomi et al (2020) developed modeling of an explicit nonlinear FE to anticipate the temperature distribution and ensuing stresses in AA 7075-T651 alloy.…”

Section: Introductionmentioning

confidence: 99%

Friction Crush Welding of Dissimilar Materials: Numerical Modelling and Experimental Investigation

Kumar,

Brar,

Singh

2023

Preprint

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Several present day applications require joining of dissimilar materials by solid state processes. In this research work, two dissimilar metals – Aluminium and Steel were joined with a newly developed Friction Crush Welding (FCW) process. Macro-structure images along with X-Ray Diffraction (XRD) pattern were used to investigate the prepared samples. This work also aims to develop a novel Finite Element (FE) model based on ABAQUS for FCW of Aluminium-Steel materials. The numerical model was developed as a three-dimensional, explicit non-linear model utilising the Lagrange technique in ABAQUS. The developed FE model was validated by comparing the simulation results with experimental temperature data obtained by infrared thermography. The predicted temperature values from FE model are in excellent agreement with the experimentally measured values. The influence of welding variables, i.e., tool rotational speed (2000, 3000 and 4000 rpm) and welding speed (15, 30 and 45 mm/min) on temperature was also investigated. Results show that best weld structure is obtained when welding is performed at speed of 30 mm/min and tool rotational speed of 3000 rpm. The developed FE model of the FCW process may be used for predicting the temperatures and predicting the weld structure.

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Friction Stir Welding

Akinlabi

Mahamood

2020

Mechanical Engineering Series

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Numerical simulations on material flow behaviors in whole process of friction stir welding

Cited by 18 publications

References 32 publications

Investigation of material flow and thermomechanical behavior during friction stir welding of an AZ31B alloy for threaded and unthreaded pin geometries using computational solid mechanics simulation

Investigation of material flow and thermomechanical behavior during friction stir welding of an AZ31B alloy for threaded and unthreaded pin geometries using computational solid mechanics simulation

Friction Crush Welding of Dissimilar Materials: Numerical Modelling and Experimental Investigation

Friction Stir Welding

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