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

Department of Materials Science and Engineering

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

21 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 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
Publication status	Published - 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

Access to Document

10.1016/j.msea.2019.04.113

Cite this

@article{db878183adfb42df97a635e8af03a60f,

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",

note = "Funding Information: This work was supported by the Basic Science Research Program ( NRF-2017R1A2B2009336 ) funded by the National Research Foundation of Korea, South Korea and the Technology Innovation Program (Grant No. 10063488 ) funded by the Ministry of Trade, Industry and Energy, South Korea . Publisher Copyright: {\textcopyright} 2019 Elsevier B.V.",

year = "2019",

month = jun,

day = "5",

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

language = "English",

volume = "758",

pages = "56--59",

journal = "Materials Science & Engineering A: Structural Materials: Properties, Microstructure and Processing",

issn = "0921-5093",

publisher = "Elsevier BV",

}

TY - JOUR

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

N1 - Funding Information: This work was supported by the Basic Science Research Program ( NRF-2017R1A2B2009336 ) funded by the National Research Foundation of Korea, South Korea and the Technology Innovation Program (Grant No. 10063488 ) funded by the Ministry of Trade, Industry and Energy, South Korea . Publisher Copyright: © 2019 Elsevier B.V.

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

UR - http://www.scopus.com/inward/record.url?scp=85065231981&partnerID=8YFLogxK

U2 - 10.1016/j.msea.2019.04.113

DO - 10.1016/j.msea.2019.04.113

M3 - Article

AN - SCOPUS:85065231981

VL - 758

SP - 56

EP - 59

JO - Materials Science & Engineering A: Structural Materials: Properties, Microstructure and Processing

JF - Materials Science & Engineering A: Structural Materials: Properties, Microstructure and Processing

SN - 0921-5093

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this