Modelling and Pareto optimization of mechanical properties of friction stir welded AA7075/AA5083 butt joints using neural network and particle swarm algorithm

Shojaeefard, Mohammad Hassan; Behnagh, Reza Abdi; Akbari, Mostafa; Givi, Mohammad Kazem Besharati; Farhani, Foad

doi:10.1016/j.matdes.2012.07.025

Cited by 160 publications

(77 citation statements)

References 30 publications

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“…This technique utilizes a non-consumable rotating welding tool to generate frictional heat and cause deformation at the welding zone, thereby affecting the formation of a joint, while the material is in the solid state. 5 Tool rotational and traverse speeds are very important parameters in friction stir welding. The tool rotation results in stirring and mixing of material and the tool translation flows the stirred material from the leading face of the pin to its trailing face and nishes welding process.…”

Section: Introductionmentioning

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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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: Introductionmentioning

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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“…It has gathered wide acceptance in many structural applications due to its high strength to weight ratio, good resistance to corrosion and natural ageing characteristics [3,4]. In addition, AA6061 alloy (Al-Mg-Si alloy) belongs to a significant class of medium strength aluminum alloys widely used in aircraft applications, marine frames and storage tanks [5].…”

Section: Extended Abstractmentioning

confidence: 99%

Mechanical Properties of Dissimilar Friction Stir Welded Joints between AA7075-O and AA6061-O Alloys

Öztoprak¹,

Serіndağ²,

Yeni³

et al. 2016

World Congress on Mechanical, Chemical, and Material Engineering

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Extended AbstractFriction stir welding (FSW) is a new solid-state joining technique that was developed in 1991 by The Welding Institute (TWI) of UK. In particular, this process is utilized for welding high-strength metallic materials such as aluminum alloys, magnesium, copper and metal matrix composites (MMCs) that are hard to weld by traditional welding methods. In FSW process, the frictional heating is generated between the non-consumable tool and the workpiece. As a result of the heating, the workpiece undergoes intensive plastic flow at an elevated temperature that is under the melting point of the material. Attendantly, the plastic deformation introduces grain refinement owing to the dynamic recrystallization of the grains at the weld zone. There are many advantages of FSW process by comparison with conventional fusion welding technology. No additive materials, cover gas or flux is used in the process and this makes FSW technology a strong candidate for joining of the aforementioned materials. In addition, several types of joints such as butt and T butt joints or fillet joints can be simply welded by this significant technology [1].AA7075 alloy (Al-Zn-Mg-Cu alloy), which is one of the strongest aluminum alloys, is precipitation hardened wrought material commonly used in aircraft parts, gears and shafts, missile parts, aerospace and defence applications [2]. It has gathered wide acceptance in many structural applications due to its high strength to weight ratio, good resistance to corrosion and natural ageing characteristics [3,4]. In addition, AA6061 alloy (Al-Mg-Si alloy) belongs to a significant class of medium strength aluminum alloys widely used in aircraft applications, marine frames and storage tanks [5]. However, both alloys suffer from degraded mechanical properties especially in the heat affected zone (HAZ) subsequent to conventional fusion welding techniques [5,6]. Therefore, FSW is considered as an ideal candidate to join these materials which are known as non-weldable alloys by fusion welding processes.Joining of dissimilar monolithic metals is quite important so as to provide good mechanical performance and obtaining cost-effective joints. AA7075-O and AA6061-O alloys have common widespread applications [7]. Therefore, sound welding of these materials is a prerequisite and attractive in various applications. In this research, dissimilar welds were produced in 3.2 mm thick plates of AA7075-O and AA6061-O alloys by friction stir welding. The effect of welding parameters and material position on tensile strength of the joints and microhardness profiles across the welds were investigated. For this purpose, FSW was carried out with the combination of two different rotational speeds and one welding speed to obtain the effect of heat generation on the welding quality. The parameters were chosen by taking into consideration the results of preliminary experimental studies. Temperature distribution around the weld zone was also measured during the process by using a non-contact infrared thermometer and K...

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“…FSP has been invented based on friction stir welding (FSW) for the microstructure modification of materials [7,8], which results in improving their mechanical and wear resistance. FSW as a welding technique has been used to weld different Al [8,[13][14][15][16], Mg [7,17,18], and Cu [13,19] alloys, some of which are classified as practically unweldable alloys in use of conventional welding methods. Different surface composites have been produced with different types of reinforcing particles like SiC [7,20], TiC [21], Al 2 O 3 [22], CNT [23][24][25], TiO 2 [26], and B 4 C [27].…”

Section: Introductionmentioning

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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Modelling and Pareto optimization of mechanical properties of friction stir welded AA7075/AA5083 butt joints using neural network and particle swarm algorithm

Cited by 160 publications

References 30 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

Mechanical Properties of Dissimilar Friction Stir Welded Joints between AA7075-O and AA6061-O Alloys

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

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