Numerical Simulation of Temperature Distribution and Material Flow During Friction Stir Welding of Dissimilar Aluminum Alloys

Padmanaban, R.; Velamati, Ratna Kishore; Balusamy, V.

doi:10.1016/j.proeng.2014.12.360

Cited by 82 publications

(41 citation statements)

References 27 publications

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“…To clarify the point, as the stirring phenomena increases, the material becomes more ductile, and consequently, the material resistance, the welding force, and the pressure at the contact interfaces decrease. Moreover, the use of higher rotational velocities resulting in higher mixing of the material happened at the lower half part of the welding nugget zone and this issue enhances the quality of the join, similar to what had been reported in the previous literature [17][18][19].…”

Section: Methodssupporting

confidence: 86%

“…As a function of temperature, the friction coefficient values in a variety of 0.207089 to 0.00058 are applied to the model [15,16]. Past studies claimed that, the welding rotational and transverse velocities affect the heat generation during process [1,[17][18][19]. The results of the paper indicated that the model in which the temperature dependent Young's modulus values are applied is more accurate.…”

Section: Methodsmentioning

confidence: 99%

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A comparison between temperature dependent and constant Young's modulus values in investigating the effect of the process parameters on thermal behaviour during friction stir welding

Meyghani

Awang

Emamian

et al. 2018

Materialwissenschaft Werkst

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One of the most intriguing joining techniques in aerospace and automotive industries is friction stir welding. In this welding, temperature has an important effect on the quality and the integrity of the weld. Welding parameters, on the other hand, highly affect the temperature. Many authors used finite element methods to study the effect of the process parameters on thermal behavior by using constant Young's modulus, while, it should decrease as the temperature increases. Therefore, the proper definition of the Young's modulus during the study of the effect of the process parameters on thermal behavior, will increase the accuracy of the model. In this paper, to properly investigate thermal behavior, temperature dependent and constant Young's modulus values are applied in different models to examine the accuracy of those models. In addition, the influence of the process parameters on thermal behavior is studied. More accurate results are obtained from the model in which temperature dependent values of the Young's modulus is used. The effect of the welding parameters and different Young's modulus values on the size, shape and temperature of the welding string zone is studied and reported in detail.

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Section: Methodssupporting

confidence: 86%

Section: Methodsmentioning

confidence: 99%

A comparison between temperature dependent and constant Young's modulus values in investigating the effect of the process parameters on thermal behaviour during friction stir welding

Meyghani

Awang

Emamian

et al. 2018

Materialwissenschaft Werkst

View full text Add to dashboard Cite

show abstract

“…The phase diagram of Al-Mg alloy system is shown in Figure 10 and it is observed that Al 2 Mg 3 precipitates at a temperature of 683 K. The nominal plasticizing temperature obtained during FSP is 400°C (approximately) [11,25]. The heat generation and strain developed during FSP causes recovery, recrystallization and grain growth in the neighborhood of the processing zone.…”

Section: Surface Morphology Analysismentioning

confidence: 99%

Soft computing model for analysing the effect of friction stir processing parameters on the intergranular corrosion susceptibility of aluminium alloy AA5083

Vignesh

Padmanaban

Chinnaraj

2018

Koroze a Ochrana Materialu

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Aluminium alloy AA5083 is prone to intergranular corrosion in marine environments. In an attempt to reduce the intergranular corrosion, AA5083 was subjected to friction stir processing (FSP). The FSP experimental trials were conducted as per face-centered central composite design with three levels of variation in FSP process parameters viz. tool rotation speed (TRS), tool traverse speed (TTS) and tool shoulder diameter (SD). Intergranular corrosion susceptibility of the processed specimens was assessed by performing nitric acid mass loss test. The mass loss of the specimens was correlated with the intergranular corrosion susceptibility as per the standard ASTM G67-13. The experimental results indicate that FSP had significantly reduced the intergranular corrosion susceptibility of the AA5083 alloy. Soft computing techniques namely Artificial Neural Network, Mamdani Fuzzy system, and Sugeno Fuzzy system were used to predict the intergranular corrosion (IGC) susceptibility (mass loss) of the friction stir processed specimens. Among the developed models, Sugeno fuzzy system displayed minimum percentage error in prediction. So Sugeno fuzzy system was used to analyze the effect of friction stir processing process parameters on the IGC of the processed specimens. The results suggest that stir processing of AA5083 at a TRS of 1300 rpm, TTS of 60 mm/min and SD of 21 mm would make the alloy least susceptible to intergranular corrosion.

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“…FSW has many other significant advantages including controlled properties and microstructure, improved material utilization (light weight structures), improved energy utilization (only 2.5% of energy needed for fusion welding), and reduced harmful effects on environment [2][3][4]. Research in FSW has focused on developing experimental, analytical, and numerical models in order to characterize the different zones in FSW [5][6][7][8][9][10][11]. They include the heat affected zone (HAZ), the thermomechanically affected zone (TMAZ), and the base metal.…”

Section: Introductionmentioning

confidence: 99%

“…The parameters that influence the performance of FSW are displayed in Figure 1. They include tool rotational speed, travel speed of the tool, plunge force, plunge depth, and tool design [2][3][4][5][6][7][8][9][10][11][12][13]. These parameters affect the thermo-mechanical and metallurgical changes established during FSW which in turn are related to the evolved properties, microstructure, and process-induced damage in the course of the welding process.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Modeling Approach for Management of Process-Induced Properties in Friction Stir Welding Processes

Ase¹,

S²,

B³

2015

J Appl Mech Eng

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Numerical and physical modeling techniques are used to predict process behavior in friction stir welding (FSW) high strength aluminum alloys. The numerical approach uses a non-linear finite element method to characterize thermal and deformation behavior along the welded structure during FSW. Coupled temperature-displacement analysis is applied in order to determine temperature, displacement, and mechanical responses simultaneously. The physical modeling approach uses the response surface methodology (RSM) to evaluate the effects of the process controlling parameters on the properties of the welded joints. The results obtained, offer insights into the effects of the major process parameters in establishing successful FSW joints that satisfy further processing requirements and product service conditions.

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Numerical Simulation of Temperature Distribution and Material Flow During Friction Stir Welding of Dissimilar Aluminum Alloys

Cited by 82 publications

References 27 publications

A comparison between temperature dependent and constant Young's modulus values in investigating the effect of the process parameters on thermal behaviour during friction stir welding

A comparison between temperature dependent and constant Young's modulus values in investigating the effect of the process parameters on thermal behaviour during friction stir welding

Soft computing model for analysing the effect of friction stir processing parameters on the intergranular corrosion susceptibility of aluminium alloy AA5083

An Integrated Modeling Approach for Management of Process-Induced Properties in Friction Stir Welding Processes

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