scholarly journals Welding Parameters Optimization in Plunging and Dwelling Phase of FSW Medium Thickness 2219 Aluminum Alloy

Author(s):  
Xiaohong Lu ◽  
Jinhui Qiao ◽  
Junyu Qian ◽  
Shixuan Sun ◽  
Steven Y. Liang

Abstract The influence of welding parameters on temperature distribution in plunging and dwelling phase of friction stir welding (FSW) medium thickness 2219 aluminum alloy is blank. Improper selection of welding parameters will result in uneven temperature distribution along the thickness of the weldment, which will lead to welding defects and ultimately affect the mechanical properties of the weldment. To realize the prediction of temperature distribution and achieve the optimization of welding parameters, a simulation model of FSW 18mm thick 2219 aluminum alloy is built based on DEFORM. The validity of the simulation model is verified by temperature measurement experiments. With the minimum temperature difference in the core area of the weldment as target value, and weldable temperature range of 2219 aluminum alloy as constraint conditions, orthogonal experiments are conducted considering the rotational speed, the press amount, the tool tilt angle, the plunging traverse speed and the dwelling time. The results of variance analysis show that the rotational speed and the dwelling time are significant factors affecting temperature field during plunging and dwelling phase. Through single factor simulation, the welding parameters in plunging and dwelling phase are optimized. This study provides a reference for realizing high-quality welding of a heavy rocket fuel tank.

Author(s):  
Memduh Murtulmuş

Aluminum alloy Al 2024-T3 were successfully joined using friction stir spot jwelding joining (FSSW). Satisfactory joint strengths were obtained at different welding parameters (tool rotational speed, tool plunge depth, dwell time) and tool pin profile (straight cylindrical, triangular and tapered cylindrical). Resulting joints were welded with welded zone. The different tools significantly influenced the evolution on the stir zone in the welds. Lap-shear tests were carried out to find the weld strength. Weld cross section appearance observations were also done. The macrostructure shows that the welding parameters have a determinant effect on the weld strength (x: the nugget thickness, y: the thickness of the upper sheet and SZ: stir zone). The main fracture mode was pull out fracture modes in the tensile shear test of joints. The results of tensile shear tests showed that the tensile-shear load increased with increasing rotational speed in the shoulder penetration depth of 0.2 mm. Failure joints were obrerved in the weld high shoulder penetration depth and insufficient tool rotation.


2010 ◽  
Vol 44-47 ◽  
pp. 76-80
Author(s):  
Lei Wang ◽  
Jian Jun Zhu

Temperature distribution is the foundation to study friction stir welding technique, influence of welding parameters on temperature was studied through experiment measurement on AA2024-T4 aluminum alloy plates. An instantaneous relative linear velocity based heat source was utilized to build the FEM model of friction stir welding process, good agreement was observed between the measured and simulated thermal profiles. FEM model was also utilized to study effect of welding parameters on temperature distribution.


2021 ◽  
Author(s):  
Xiaohong Lu ◽  
Yihan Luan ◽  
Xiangyue Meng ◽  
Yu Zhou ◽  
Ning Zhao ◽  
...  

Abstract Friction stir welding (FSW) is a solid-state jointing technology, which has the advantages of high joint strength, low residual stress aXnd small deformation after welding. During the process of FSW, the welding temperature has an important effect on the quality of the weldment. Therefore, the heat generation model of FSW of medium thickness 2219 aluminum alloy is established based on the friction heat generation at the interface between the tool and the workpiece and the plastic deformation heat generation of the weldment material near the tool. The heat transfer model is set under the premise of considering heat conduction, thermal convection, and thermal radiation. Using JMatPro technology, the temperature-related material parameters of 2219 aluminum alloy are calculated based on the material composition, and the heat generation model is imported into the ABAQUS simulation software based on the DFLUX subroutine, and the establishment of the FSW thermodynamic model is realized. The effectiveness of the model is verified by FSW experiments. The thermodynamic model takes into account both heat generation (friction heat generation and plastic deformation heat generation) and heat transfer (heat conduction, thermal convection and thermal radiation), so it has a high prediction accuracy. Based on the FSW thermodynamic model, the influence of welding parameters on temperature distribution is explored, subsequently the influence of welding temperature on mechanical properties of welded joint are also studied. The research can provide guidance for predicting and characterizing the temperature distribution and the improvement of mechanical performance of FSW.


Materials ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3496
Author(s):  
Haijun Wang ◽  
Diqiu He ◽  
Mingjian Liao ◽  
Peng Liu ◽  
Ruilin Lai

The online prediction of friction stir welding quality is an important part of intelligent welding. In this paper, a new method for the online evaluation of weld quality is proposed, which takes the real-time temperature signal as the main research variable. We conducted a welding experiment with 2219 aluminum alloy of 6 mm thickness. The temperature signal is decomposed into components of different frequency bands by wavelet packet method and the energy of component signals is used as the characteristic parameter to evaluate the weld quality. A prediction model of weld performance based on least squares support vector machine and genetic algorithm was established. The experimental results showed that, when welding defects are caused by a sudden perturbation during welding, the amplitude of the temperature signal near the tool rotation frequency will change significantly. When improper process parameters are used, the frequency band component of the temperature signal in the range of 0~11 Hz increases significantly, and the statistical mean value of the temperature signal will also be different. The accuracy of the prediction model reached 90.6%, and the AUC value was 0.939, which reflects the good prediction ability of the model.


2019 ◽  
Vol 44 ◽  
pp. 197-206 ◽  
Author(s):  
Shujun Chen ◽  
Hongwei Zhang ◽  
Xiaoqing Jiang ◽  
Tao Yuan ◽  
Yang Han ◽  
...  

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