Simulation and experimental investigation of FSP of AZ91 magnesium alloy

Asadi, Parviz; Mahdavinejad, Ramezanali; Tutunchilar, S.

doi:10.1016/j.msea.2011.05.035

Cited by 123 publications

(60 citation statements)

References 19 publications

(30 reference statements)

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“…The Arrhenius equation was used to describe the relationship between the strain rate, flow stress and temperature. 11 The constant shear friction model was used to model contact between tool and workpiece. 8,11 A comparison between the numerical and experimental results for welding forces is shown in Fig.…”

Section: Simulation Detailsmentioning

confidence: 99%

See 1 more Smart Citation

Multi objective optimization of friction stir welding parameters using FEM and neural network

Shojaeefard

Akbari

Asadi

2014

Int. J. Precis. Eng. Manuf.

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In this study the inuence of rotational and traverse speed on the friction stir welding of AA5083 aluminum alloy has been investigated. For this purpose a thermo-mechanically coupled, 3D FEM analysis was used to study the effect of rotational and traverse speed on welding force, peak temperature and HAZ width. Then, an Articial Neural Network (ANN) model was employed to understand the correlation between the welding parameters (rotational and traverse speed) and peak temperature, HAZ width and welding force values in the weld zone. Performance of the ANN model was found excellent and the model can be used to predict peak temperature, HAZ width and welding force. Furthermore, in order to find optimum values of traverse and rotational speed, the multi-objective optimization was used to obtain the Pareto front. Finally, the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) was employed to obtain the best compromised solution.

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Section: Simulation Detailsmentioning

confidence: 99%

“…11 The constant shear friction model was used to model contact between tool and workpiece. 8,11 A comparison between the numerical and experimental results for welding forces is shown in Fig. 1; showing a good agreement between the predicted force and experimental data.…”

Section: Simulation Detailsmentioning

confidence: 99%

Multi objective optimization of friction stir welding parameters using FEM and neural network

Shojaeefard

Akbari

Asadi

2014

Int. J. Precis. Eng. Manuf.

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show abstract

“…The model is based on ALE method. It has been [15] developed earlier by the several researchers a 3D thermo-mechanical model based on lagrangian technique. They have predicted the temperature and strain evolution that can be used for prediction of stirred zone.…”

Section: Introductionmentioning

confidence: 99%

Finite Element Simulation of Temperature and Strain Distribution during Friction Stir Welding of AA2024 Aluminum Alloy

Jain

Pal

Singh

2016

J. Inst. Eng. India Ser. C

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Friction Stir Welding (FSW) is a solid state joining process and is handy for welding aluminum alloys. Finite Element Method (FEM) is an important tool to predict state variables of the process but numerical simulation of FSW is highly complex due to non-linear contact interactions between tool and work piece and interdependency of displacement and temperature. In the present work, a three dimensional coupled thermo-mechanical method based on Lagrangian implicit method is proposed to study the thermal history, strain distribution and thermomechanical process in butt welding of Aluminum alloy 2024 using DEFORM-3D software. Workpiece is defined as rigid-visco plastic material and sticking condition between tool and work piece is defined. Adaptive remeshing is used to tackle high mesh distortion. Effect of tool rotational and welding speed on plastic strain is studied and insight is given on asymmetric nature of FSW process. Temperature distribution on the workpiece and tool is predicted and maximum temperature is found in workpiece top surface.

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“…For material flow simulation during FSP, Deform-3D TM software was used because of its good capability in modeling severe plastic deformation [1,28]. In the present investigation for problem simplification, some assumptions were made as follow:…”

Section: Simulation Of Friction Stir Processingmentioning

confidence: 99%

“…The constant shear friction model was used for modeling friction between FSP tool and workpiece [28,29],…”

Section: -mentioning

confidence: 99%

The effect of reinforcement type on the microstructure, mechanical properties, and wear resistance of A356 matrix composites produced by FSP

Shojaeefard

Akbari

Asadi

et al. 2016

Int J Adv Manuf Technol

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Fabrication of particle-reinforced aluminum matrix composites has been pursued with a keen interest recently. However, a comparison of the effect of different reinforcements on the mechanical properties and wear resistance of A356 matrix composites fabricated by FSP is of great interest to be considered. In the present work, the microstructural, mechanical, and wear properties of A356 matrix composites reinforced by SiC, TiC, ZrO 2 , and B 4 C particles are investigated. Moreover, the effect of pin profile on distribution of reinforcing particles in the stir zone of the FSPed specimens is investigated. Hardness and wear tests are performed in order to investigate mechanical and wear properties of the composites. The composite reinforced by TiC particles exhibits higher hardness value compared with other reinforcements due to the excellent bonding between TiC and metal matrix as well as higher hardness value of reinforcement itself than other reinforcements. Moreover, wear test results show that the wear resistance of the composite is significantly improved compared with that of the base metal.

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Simulation and experimental investigation of FSP of AZ91 magnesium alloy

Cited by 123 publications

References 19 publications

Multi objective optimization of friction stir welding parameters using FEM and neural network

Multi objective optimization of friction stir welding parameters using FEM and neural network

Finite Element Simulation of Temperature and Strain Distribution during Friction Stir Welding of AA2024 Aluminum Alloy

The effect of reinforcement type on the microstructure, mechanical properties, and wear resistance of A356 matrix composites produced by FSP

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