Investigation of friction stir welding tool parameters using FEM and neural network

Int. J. Precis. Eng. Manuf.

2014

Self Cite

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.

Section: Simulation Detailsmentioning

confidence: 55%

Section: Introductionmentioning

confidence: 99%

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

Shojaeefard

Int. J. Precis. Eng. Manuf.

2014

Self Cite

“…Their model effectively determines the relationships between the tool forces and process parameters. Shojaeefard et al (2013) studied the influence of pin profile and shoulder diameter on material flow, welding force, temperature, and strain distributions. Marzbanrad et al (2014) investigated the effect of tool pin profile, and Asadi et al (2011a;Tutunchilar et al 2012a) studied the effect of the process parameters on material flow, temperature, and strain distributions during friction stir processing.…”

Section: Introductionmentioning

confidence: 99%

Microstructural simulation of friction stir welding using a cellular automaton method: a microstructure prediction of AZ91 magnesium alloy

Givi

2015

Int J Mech Mater Eng

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Background: Recently, some researchers have simulated FSW using FEM and studied the influence of process parameters and tool geometry on material flow, welding force, and temperature and strain distributions during friction stir processing. Additionally, in terms of microstructure modeling, various approaches such as the Cellular Automaton (CA) model have been developed to simulate microstructural evolution during plastic deformation processes. Method: In this work, a finite element model (FEM) is established to study the microstructure evolution during friction stir welding (FSW) of AZ91 magnesium alloy. To this aim, first, the hot compression tests at different temperatures and strain rates were carried out to achieve the flow stress curves. Then, the hardening parameter, the recovery parameter and the strain rate sensitivity were calculated according to flow stress results and using the Kocks−Mecking model. Next, a continuum based thermo-mechanically coupled rigid-viscoplastic FEM model was proposed in Deform-3D software to simulate the FSW of AZ91 magnesium alloy. To evaluate microstructure of the weld zone a model is proposed based on the combination of Cellular Automaton and Laasraoui-Jonas models.

“…The finer elements in the mean size of 0.5 mm were placed under the tool pin. More details on FEM model can be found in authors' pervious works [7,16,[30][31][32][33][34][35]. …”

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

Int J Adv Manuf Technol

et al. 2016

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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.