Improving the Mechanical Property of Dissimilar Al/Mg Zn‐Added Ultrasound‐Assisted Friction Stir Lap Welding Joint by Back Propagation Neural Network–Gray Wolf Optimization Algorithm

Song, Qing; Ren, Zha; Ji, Shude; Niu, Shiyu; Qi, Weiwei; Chen, Ming-fei

doi:10.1002/adem.201900973

Cited by 9 publications

(3 citation statements)

References 28 publications

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“…One of these effects, called "acoustoplastic," is a temporary softening due to the imposing ultrasound during the plastic deformation of metallic materials. [1] Considering this effect, ultrasound is suitable for use in several manufacturing processes such as welding, [2,3] additive manufacturing, [4,5] surface impact treatment, [6,7] and metal forming. [8,9] The stress reduction caused by acoustoplastic can be divided into stress superposition, dynamic impact, and acoustic softening.…”

Section: Introductionmentioning

confidence: 99%

Microstructural Evolutions under Ultrasonic Treatment in 304 and 316 Austenitic Stainless Steels: Impact of Stacking Fault Energy

Zohrevand

Aghaie-Khafri

Forouzan

et al. 2021

steel research int.

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Herein, the influence of ultrasonic treatment (UST) on the microstructure of AISI-304 and AISI-316 stainless steels as two common commercial grades with similar properties but different levels of stacking fault energy (SFE) is compared. The softening effect of the ultrasonic wave on the predeformed structure is demonstrated by microhardness measurements, and the relaxation of tensile residual stresses is affirmed through the X-ray diffraction (XRD) peak shifting. Electron and optical microscopy reveals a significant impact of ultrasound on the reduction of the deformation twins' fraction. A new mechanism for detwinning under the action of ultrasonic vibration is proposed using electron backscatter diffraction (EBSD) analysis. Reductions of 25% and 34% are detected in dislocation density of the 10% predeformed tensile sample after 300 W UST for the 304SS and 316SS alloys, respectively. The effect of the SFE is discussed, and it turns out that cross-slip is the main mechanism of dislocation annihilation as a result of UST. Observation of the low-deformation regions close to the grain boundaries indicates the occurrence of the recrystallization phenomenon during UST. Dislocation annihilation, detwinning, dislocation absorption to grain boundaries, and recrystallization are regarded as the softening and relaxation mechanisms of UST for austenitic stainless steels.

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Section: Introductionmentioning

confidence: 99%

Microstructural Evolutions under Ultrasonic Treatment in 304 and 316 Austenitic Stainless Steels: Impact of Stacking Fault Energy

Zohrevand

Aghaie-Khafri

Forouzan

et al. 2021

steel research int.

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“…This algorithm was developed in 1995 by Dr Kennedy and Dr Eberhart, inspired by fish and birds that move in flocks. 30 While these animals are moving in herd while meeting their needs in terms of food and safety, it has been observed that the movements they generate randomly have an effect on other individuals in the herd and enable the herd to reach its current goal more easily. The individual in the herd is called a particle, and the population of these particles is called a swarm.…”

Section: Methodsmentioning

confidence: 99%

A new hybrid meta-heuristic optimization method for predicting UTS for FSW of Al/Cu dissimilar materials

Güvenç

Eren

Başar

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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Joining of aluminum (Al) and copper (Cu) materials used in aerospace, automotive, chemistry, nuclear, electrical-electronic and energy sector with traditional fusion welding methods has some negative consequences. One of the major negativities is the serious decrease in the mechanical properties of the materials as a result of the high temperature that occurs during welding. Therefore, Friction Stir Welding (FSW) is of great importance in joining materials which are dissimilar and have low melting temperatures. In this study, a hybrid artificial neural network (ANN) model has been developed to predict the relationship between FSW parameters and ultimate tensile strength and to increase the prediction performance of ANN using heuristic algorithms by welding Al and Cu plates with FSW. The used hybrid approach consists of ANN and Particle Swarm Optimization/Teaching Learning Based Optimization techniques. The welding applications conducted with three different welding parameters. These parameters, rotation speed (525, 1025, 1525 rpm), welding speed (50, 75, 100 mm/min) and tool offset (0–0.75–1.5 mm) were determined as input parameters of the developed ANN model. Tensile and microhardness tests were applied to determine the mechanical properties in the experimental studies after welding process. In addition, Scanning Electron Microscope analysis and X-ray diffraction were used for microstructure and characterization of the fracture surface and the results obtained were interpreted and examined.

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“…Broadening joining interface and achieving a strong interface is important for FSLW [20]. Therefore, the eLW and the boundary length of the Mr in the lower plate are significant indexes for evaluating the formation of lap joint [21]. There are differences in the joint formation when different welding speeds are employed.…”

Section: Joint Formationmentioning

confidence: 99%

Archives of Metallurgy and Materials

Zhao

Gong

et al. 2021

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Enhancing thE StrEngth of al/Mg DiSSiMilar friction Stir lap WElDED Joint by Zn fillEr aDDition coMbinED With an appropriatE hEat input7075-T6 al and aZ31B Mg dissimilar alloys were friction stir lap welded with or without a Zn filler, and the effect of heat input on the joint quality was systematically studied. The experimental and finite element simulation results displayed that the formation characteristics and microstructures of the joint with or without the Zn filler were significantly affected by the heat input. The tensile shear load of joint with or without the Zn filler increased first and then decreased with the decrease of the welding speed from 200 to 50 mm/min. Moreover, the peak temperature in the stir zone was significantly decreased by the Zn filler addition, and the high temperature zone narrowed along the plate thickness direction. These changes of heat input made that longer mixing region boundary length and larger effective lap width were attained as the Zn filler was used. in addition, due to the replacement of al-Mg intermetallic compounds (iMCs) by al-Mg-Zn and Mg-Zn iMCs which were less harmful to the joint, the tensile shear load of the joint with the Zn filler was obviously enhanced compared to that of the joint without the Zn filler at each welding speed. The maximum tensile shear load of 7.2 kn was obtained at the welding speed of 100 mm/min.

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Improving the Mechanical Property of Dissimilar Al/Mg Zn‐Added Ultrasound‐Assisted Friction Stir Lap Welding Joint by Back Propagation Neural Network–Gray Wolf Optimization Algorithm

Cited by 9 publications

References 28 publications

Microstructural Evolutions under Ultrasonic Treatment in 304 and 316 Austenitic Stainless Steels: Impact of Stacking Fault Energy

Microstructural Evolutions under Ultrasonic Treatment in 304 and 316 Austenitic Stainless Steels: Impact of Stacking Fault Energy

A new hybrid meta-heuristic optimization method for predicting UTS for FSW of Al/Cu dissimilar materials

Archives of Metallurgy and Materials

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