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

doi:10.1016/j.msea.2019.04.113

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

Dept. of Materials Science & Engineering

Research output: Contribution to journal › Article › peer-review

58 Scopus citations

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 language	English
Pages (from-to)	56-59
Number of pages	4
Journal	Materials Science and Engineering: A
Volume	758
DOIs	https://doi.org/10.1016/j.msea.2019.04.113
State	Published - 5 Jun 2019

Keywords

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

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10.1016/j.msea.2019.04.113

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

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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year = "2019",

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doi = "10.1016/j.msea.2019.04.113",

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T1 - Microstructure-based prediction of yield ratio and uniform elongation in high-strength bainitic steels using multiple linear regression analysis

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

KW - Multiple linear regression analysis

KW - Prediction

KW - Uniform elongation

KW - Yield ratio

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U2 - 10.1016/j.msea.2019.04.113

DO - 10.1016/j.msea.2019.04.113

M3 - Article

AN - SCOPUS:85065231981

SN - 0921-5093

VL - 758

SP - 56

EP - 59

JO - Materials Science and Engineering: A

JF - Materials Science and Engineering: A

ER -

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

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Keywords

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