Critical assessment of models for predicting the Ms temperature of steels

被引：63

作者：

Sourmail, T

Garcia-Mateo, C

机构：

[1] Univ Cambridge, Dept Mat Sci & Met, Cambridge CB2 3QZ, England

[2] Natl Ctr Met Res, CENIM, Madrid 28040, Spain

来源：

COMPUTATIONAL MATERIALS SCIENCE | 2005年 / 34卷 / 04期

关键词：

martensite; thermodynamics; Bayesian neural networks; linear regression;

D O I：

10.1016/j.commatsci.2005.01.002

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Different approaches to predicting the M-s temperatures of steels are reviewed and discussed with the objective of summarising the main characteristics, advantages and difficulties of each method, mostly from a practical point of view. Empirical methods, and methods based on thermodynamics are then assessed against published data. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：323 / 334

页数：12

共 39 条

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