Producing aluminum alloy / copper alloy dissimilar materials joint plate by using friction stir welding

2018 ◽  
Vol 2018.55 (0) ◽  
pp. A022
Author(s):  
Shinya FUJIMOTO ◽  
Yukio MIYASHITA ◽  
Hisashi HORI
Keyword(s):  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
Copper Alloy ◽  
Dissimilar Materials ◽  
Friction Stir

Analysis and Correlation of Output Parameters against Input Parameters for Friction Stir Welding of Three Dissimilar Aluminum Alloy

2018 ◽  
Vol 1146 ◽  
pp. 38-43
Author(s):  
Ana Boşneag ◽  
Marius Adrian Constantin ◽  
Eduard Niţu ◽  
Cristian Ciucă
Keyword(s):  
Mechanical Properties ◽  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
Arc Welding ◽  
Welding Process ◽  
Dissimilar Materials ◽  
Friction Stir ◽  
Welding Joints ◽  
Aluminum Plates ◽  
Joining Process

Friction Stir Welding, abbreviated FSW is an innovative joining process. The FSW is a solid-state welding process with a lot of advantages comparing to the traditional arc welding, such as the following: it uses a non-consumable tool, it results of good mechanical properties, it can use dissimilar materials and it have a low environmental impact. First of all, the FSW process was developed to join similar aluminum plates, and now, the technology was developed and the FSW process is used to weld large types of materials, similar or dissimilar. In this paper it is presented an experimental study and the results of it, which includes the welding of three dissimilar aluminum alloy, with different chemical and mechanical properties. This three materials are: AA2024, AA6061 and AA7075. The welding joints and the welding process were analyzed considering: process temperature, micro-hardness, macrostructure and microstructure.

scholarly journals Finite Element Modeling in Friction Stir Welding of Two Dissimilar Pipes

2020 ◽  
Vol 9 (4) ◽  
pp. 377-381
Keyword(s):  
Finite Element ◽  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
Finite Element Modeling ◽  
Dissimilar Materials ◽  
Operating Conditions ◽  
Friction Stir ◽  
Element Modeling ◽  
6063 Aluminum Alloy ◽  
6082 Aluminum Alloy

The Finite Element Modeling has been achieved for two dissimilar pipes welded by friction stir welding for given operating conditions and cases. Moreover, this analysis has been carried out to find the effect of hydrostatic pressure test on the welding area of the pipe by ANSYS Workbench software. In this study dissimilar materials of different pipes were used for FSW, which they were joined as 6063 aluminum alloy pipe with 6082 aluminum alloy pipe and C36000 high-leaded brass pipe with C12200 copper alloy pipe. In this study six parameters were used and with those parameters, eight (8) cases were welded and examined with hydrostatic tests and tensile test. The process was accomplished by varying one of the parameters (rotation speed) and keeping the others as constants.

Defects and tensile properties of 6013 aluminum alloy T-joints by friction stir welding

2014 ◽  
Vol 57 ◽  
pp. 146-155 ◽  
Author(s):  
Yong Zhao ◽  
Lilong Zhou ◽  
Qingzhao Wang ◽  
Keng Yan ◽  
Jiasheng Zou
Keyword(s):  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
Tensile Properties ◽  
T Joints ◽  
Friction Stir

scholarly journals Study on Quality Prediction of 2219 Aluminum Alloy Friction Stir Welding Based on Real-Time Temperature Signal

Materials ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3496
Author(s):  
Haijun Wang ◽  
Diqiu He ◽  
Mingjian Liao ◽  
Peng Liu ◽  
Ruilin Lai
Keyword(s):  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
Prediction Model ◽  
Real Time ◽  
Support Vector ◽  
Weld Quality ◽  
Prediction Ability ◽  
Friction Stir ◽  
Temperature Signal ◽  
2219 Aluminum Alloy

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.

Enhanced aluminum alloy-polymer friction stir welding joints by introducing micro-textures

2021 ◽  
pp. 129872
Author(s):  
Wenquan Wang ◽  
Suyu Wang ◽  
Xinge Zhang ◽  
Yuxin Xu ◽  
Yingtao Tian ◽  
...  
Keyword(s):  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
Friction Stir ◽  
Polymer Friction ◽  
Welding Joints

Dissimilar aluminum alloy joint strength is effected by heat addition in friction stir welding (FSW)

2021 ◽  
Author(s):  
Sharda Pratap Shrivas ◽  
G.K. Agrawal ◽  
Shubhrata Nagpal ◽  
Amit Kumar Vishvakarma ◽  
Ashish Kumar Khandelwal
Keyword(s):  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
Joint Strength ◽  
Friction Stir ◽  
Heat Addition
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