• Title/Summary/Keyword: GMA Welding Process

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Evaluation of tensile strength according to welding variables in GMA welding of SAPH440 (SAPH440재료의 GMA용접시 용접변수에 따른 인장 강도 특성 평가)

  • Kim, Won-Seop;Lee, Jong-Hun;LeeSeo, Han-Seop;Park, Sang-Heup
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.8
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    • pp.133-138
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    • 2019
  • This study evaluated the tensile properties of SAPH440, a hot-rolled steel for automotive structural applications, based on GMAW lap welding, the welding current, the welding voltage, and the feed rate. Tensile tests were performed according to the joint parameters of the GMAW process, for which specimens were fabricated according to KS B ISO 9018 by lap welding. The bead appearance was observed in each condition, and the weldability was evaluated by the tensile test. Higher the welding current resulted in a deeper weld, but the tensile strength was not significantly different from when the parameter was fixed due to the fracture of the base material. When the current was higher than the voltage, as in the case of a welding current of 200 A and welding voltage of 17 V, a large amount of spatter is generated, the welding is unstable, and the welded part breaks. Higher the voltage resulted in the bead not causing defects in general, and it also affected the weldability. If the current and voltage were too low, the welding was not performed normally, and the tensile strength could not be measured. However, as the current increased, the increase of the voltage and the feed rate did not affect the tensile strength.

A Study on the Prediction of Welded Residual Stresses using Neural Network (신경회로망을 이용한 용접잔류응력 예측에 관한 연구)

  • 차용훈;김일수;김하식;이연신;김덕중;성백섭;서준열
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.9 no.6
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    • pp.89-95
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    • 2000
  • In order to achieve effective prediction of residual stresses, the series experiment were carried out and the residual stresses were measured using the backgpropagation algorithm from the neural network and the sectional method. Using the experimental results, the optimal control algorithms using a neural network should be developed in order to reduce the effect of the external disturbances on residual stresses during GMA welding processes. The results obtained from the comparison between the measured and calculated results, showed that the neural network based on backpropagation algorithm can be sued in order to control weld quality. This system can not only help to understand the interaction between the process parameters and residual stress, but also, improve the quantity control for welded structures. The development of the system is goal in this study.

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Manufacturing and Characterization of SiC/AI Metal Matrix Composite by Modified Gas Metal Arc Welding Process ; Manufacturing and Microstructure (개조된 GMA용접공정을 이용한 SiC/AI 복합재료의 제조 및 특성)

  • Kim, Gwang-Su
    • Korean Journal of Materials Research
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    • v.6 no.11
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    • pp.1090-1098
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    • 1996
  • 개조한 가스 금속 아아크 용접공정을 이용하여 SiC/AI 금속기 복합재료를 제조하고 그 특성을 조사하였다. AI 모재위에 강화입자의 크기와 부피분율을 변화하여 다양한 SiC/AI 복합재료층을 제조하였고, 만들어진 복합재료층의 특성은 미세조직관찰과 미소경도시험을 통하여 이루어졌다. 복합재료층의 두께는 약 7-8mm로 측정되었고 균일한 강화입자의 분포도를 얻을 수 있었다. 분산입자의 부피분률은 Ar가스의 유량에 의하여 조절하였고 분산입자의 부피분률이 증가하고 크기가 작아짐에 따라 기지의 수지상 응고조직은 더욱 미세화되었다. 복합재료의 부피경도는 분산입자의 부피분률이 감소함에 따라 낮아졌으나 입자 크기에는 크게 변화가 없는 것으로 나타났다.

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The effect of heat input and PWHT on the mechanical properties and microstructure of HSB600 steel weldments with GMAW (HSB600강 가스메탈아크용접부에서 입열량과 용접후 열처리가 기계적 특성과 미세조직에 미치는 영향)

  • Ju, Dong-Hwi;Jang, Bok-Su;Lim, Young-Min;Koh, Jin-Hyun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.5
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    • pp.1939-1946
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    • 2012
  • High performance steel for bridges requires higher performance in tensile and yield strength, toughness, weldability, etc. The purpose of this study is to investigate the weldability of HSB 600 steel. The effects of heat input (1.4~3.2kJ/mm) and postweld heat treatment (PWHT, $600^{\circ}C$, 40hr.) on the TMCP HSB600 steel weldments made by GMAW process were investigated. The tensile strength and hardness of as-welded specimens decreased with increasing heat input. Charpy V-notch impact energy did not show any significant difference by postweld heat treatment. The fine-grained acicular ferrite was mainly formed in the 2.1kJ/mm of heat input while polygonal and side plate ferrites were dominated in the high inputs. Meanwhile, tensile strength and hardness of PWHT weldments decreased due to the coarsening and globularization of ferrite microstructure and reduction of residual stresses with increasing heat inputs. However, there was no significant difference in the impact energy absorption.