Prediction of welding residual stress and deformation in electro-gas welding using artificial neural network

Liu, Fangfang; Tao, Congcong; Dong, Zuomin; Jiang, Kun; Zhou, Shouzhen; Zhang, Zhihang; Shen, Chen

doi:10.1016/j.mtcomm.2021.102786

Cited by 13 publications

(2 citation statements)

References 23 publications

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“…The electro‐gas welding (EGW) experiment device is shown in Figure 1 , which is mainly composed of fixture, welding tool, and cooling device. [ 14 ] The welding material is EH36 steel produced by Ansteel Group whose material composition is shown in Table 1 , indicating that it is a low‐carbon steel. The welding wire used is DW‐S1LG cored wire.…”

Section: Methodsmentioning

confidence: 99%

The Prediction of Ferrite Ratio in HAZ of EH36 Steel Electro‐Gas Welding Joints Based on Leblond Equation

Liu

Zhou

Dong

et al. 2022

steel research int.

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A favorable microstructure is a perquisite for ensuring the quality of welding joints, but grain coarsing inevitably occurs in the heat‐affected zone (HAZ). Controlling the reduction of deterioration as much as possible is a key problem in welding engineering. Based on the welding experiment, a finite element model considering the contact heat transfer of water‐cooled sliders is constructed to obtain key information about the welding heat cycle, such as T8/5, and a prediction algorithm for the microstructure prediction of HAZ is developed based on the Leblond model. The results show that the proportion of ferrite gradually decreases with the increase in cooling rate. The evolution law of the model prediction is the same as that of the experimental results, and the maximum error is within 5%, indicating that the prediction is accurate and reliable. This observation has great significance for the optimization of the electro‐gas welding process.

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Section: Methodsmentioning

confidence: 99%

The Prediction of Ferrite Ratio in HAZ of EH36 Steel Electro‐Gas Welding Joints Based on Leblond Equation

Liu

Zhou

Dong

et al. 2022

steel research int.

Self Cite

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show abstract

“…The shipbuilding industry faces a challenge of high heat input during welding processes, particularly with conventional methods like submerged arc welding (SAW) [1][2][3][4] and electrogas arc welding (EGW) [5][6][7]. To mitigate this issue and improve weld quality, various welding techniques and processes have been suggested, including laser beam welding (LBW) [8,9] and electron beam welding (EBW) [10,11].…”

Section: Introductionmentioning

confidence: 99%

Optimization of hot-wire fraction for enhance quality in GMAW

Suwannatee,

Yamamoto,

Shinohara

2023

Weld World

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The combination of hot-wire insertion technology and gas metal arc welding (GMAW) is proposed to increase deposition rate and reduce power consumption. This study systematically investigated the effect of hot-wire fraction on weld metal properties. The results show that the compensatory deposition rate from hot-wire insertion provides a similar effective height compared with the rate from conventional GMAW, with a lower weld height/width ratio, lower power consumption, and improved mechanical properties. However, an excessive hot-wire fraction can lead to lack of fusion, and this value should be limited to no more than 44% of the total deposition rate. The relative GMAW and hotwire fractions were optimized to maximize total deposition volume while avoiding lack of fusion and providing sufficient penetration. With the optimized condition, hot-wire GMAW could be efficiently used to obtain similar deposition rates with lower power consumption and without sacrificing toughness properties. This proposed process offers a sustainable alternative development to conventional GMAW.

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Developing a visual prediction program for residual stress in girth butt welds using GA-RBF neural network

Jiao,

Jin

2024

Int J Adv Manuf Technol

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Prediction of welding residual stress and deformation in electro-gas welding using artificial neural network

Cited by 13 publications

References 23 publications

The Prediction of Ferrite Ratio in HAZ of EH36 Steel Electro‐Gas Welding Joints Based on Leblond Equation

The Prediction of Ferrite Ratio in HAZ of EH36 Steel Electro‐Gas Welding Joints Based on Leblond Equation

Optimization of hot-wire fraction for enhance quality in GMAW

Developing a visual prediction program for residual stress in girth butt welds using GA-RBF neural network

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