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

1 Citation (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

Fingerprint

bainitic steel
high strength steels
Steel
Linear regression
Regression analysis
elongation
regression analysis
Elongation
bainite
microstructure
Microstructure
Bainite
predictions
Ferrite
ferrites

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

Cite this

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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.",
keywords = "Bainitic steel, Microstructure-based, Multiple linear regression analysis, Prediction, Uniform elongation, Yield ratio",
author = "Lee, {Sang In} and Joonho Lee and Byoungchul Hwang",
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AU - Lee, Sang In

AU - Lee, Joonho

AU - Hwang, Byoungchul

PY - 2019/6/5

Y1 - 2019/6/5

N2 - 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.

AB - 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.

KW - Bainitic steel

KW - Microstructure-based

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KW - Prediction

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KW - Yield ratio

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