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Journal of Mechanical Science and Technology

, Volume 32, Issue 11, pp 5147–5153 | Cite as

Dissimilar material welding and assessing reliability of super alloy for green and high efficiency thermal power plant

  • Jeong Ho Hwang
  • Ju Hwa Lee
  • Ahmad Hafiz Waqar
  • Dong Ho Bae
  • Kyunghoon Kim
Article
  • 5 Downloads

Abstract

This paper studies the prediction of fatigue and corrosion fatigue lives using neural network and accelerated life methods for dissimilar material weld between Alloy617 and 12Cr steel. First, dissimilar material welding between Alloy617 and 12Cr steel was performed using buttering technology. The fatigue and corrosion fatigue strengths, and electrochemical corrosion susceptibility of dissimilar material weld were assessed. After that, on the basis of obtained data, fatigue life and corrosion fatigue life of dissimilar material weld were predicted using the neural network and accelerated life test methods. The predicted results showed good agreement with the actual fatigue and corrosion fatigue lives. Especially, the results of the neural network prediction were more accurate than those of the accelerated life method.

Keywords

Dissimilar material welding Fatigue strength Corrosion fatigue strength Neural network Accelerated life test method 

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Copyright information

© The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Jeong Ho Hwang
    • 1
    • 2
  • Ju Hwa Lee
    • 1
    • 2
  • Ahmad Hafiz Waqar
    • 1
    • 2
  • Dong Ho Bae
    • 2
  • Kyunghoon Kim
    • 2
  1. 1.Graduate School of Mechanical EngineeringSungkyunkwan UniversityJangan-gu, Suwon, Gyeonnggi-doKorea
  2. 2.School of Mechanical EngineeringSungkyunkwan UniversityJangan-gu, Suwon, Gyeonggi-doKorea

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