Microstructure-based prediction of yield ratio and uniform elongation in high-strength bainitic steels using multiple linear regression analysis

Sang In Lee, Joonho Lee, Byoungchul Hwang

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Microstructures of high-strength bainitic steels were quantitatively analyzed using EBSD analysis based on transformation behavior and morphological characteristics. According to multiple linear regression analysis, reliable empirical equations to predict yield ratio and uniform elongation were proposed. From the results, the fraction of the granular bainite and polygonal ferrite microstructure were estimated to be the most influential factors on the yield ratio and uniform elongation of high-strength bainitic steels, respectively.

Original languageEnglish
Pages (from-to)56-59
Number of pages4
JournalMaterials Science and Engineering A
Volume758
DOIs
Publication statusPublished - 2019 Jun 5

Keywords

  • Bainitic steel
  • Microstructure-based
  • Multiple linear regression analysis
  • Prediction
  • Uniform elongation
  • Yield ratio

ASJC Scopus subject areas

  • Materials Science(all)
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering

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