том 97 издание 6 страницы 383-425

Machine Learning Steel Ms Temperature

Тип публикацииJournal Article
Дата публикации2021-03-01
scimago Q2
wos Q3
БС2
SJR0.382
CiteScore3.8
Impact factor2.0
ISSN00375497, 17413133
Computer Graphics and Computer-Aided Design
Software
Modeling and Simulation
Краткое описание

Empirical equations, thermodynamics frameworks, and neural network modeling have been developed to predict steel martensite start temperature, [Formula: see text], but they might not tend to generalize well when composition includes a wide range of alloying elements. In this study, we develop the Gaussian process regression (GPR) model to shed light on the relationship between alloying elements and [Formula: see text] temperature for steels. A total of 1119 steels with [Formula: see text] ranging from 153 K to 938 K are examined. The model has a high degree of accuracy and stability, contributing to fast low-cost [Formula: see text] temperature estimations.

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ГОСТ |
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Zhang Y., Xu X. Machine Learning Steel Ms Temperature // Simulation. 2021. Vol. 97. No. 6. pp. 383-425.
ГОСТ со всеми авторами (до 50) Скопировать
Zhang Y., Xu X. Machine Learning Steel Ms Temperature // Simulation. 2021. Vol. 97. No. 6. pp. 383-425.
RIS |
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TY - JOUR
DO - 10.1177/0037549721995574
UR - https://doi.org/10.1177/0037549721995574
TI - Machine Learning Steel Ms Temperature
T2 - Simulation
AU - Zhang, Yun
AU - Xu, Xiaojie
PY - 2021
DA - 2021/03/01
PB - SAGE
SP - 383-425
IS - 6
VL - 97
SN - 0037-5497
SN - 1741-3133
ER -
BibTex |
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BibTex (до 50 авторов) Скопировать
@article{2021_Zhang,
author = {Yun Zhang and Xiaojie Xu},
title = {Machine Learning Steel Ms Temperature},
journal = {Simulation},
year = {2021},
volume = {97},
publisher = {SAGE},
month = {mar},
url = {https://doi.org/10.1177/0037549721995574},
number = {6},
pages = {383--425},
doi = {10.1177/0037549721995574}
}
MLA
Цитировать
Zhang, Yun, and Xiaojie Xu. “Machine Learning Steel Ms Temperature.” Simulation, vol. 97, no. 6, Mar. 2021, pp. 383-425. https://doi.org/10.1177/0037549721995574.