Title of article :
Critical assessment of models for predicting the Ms temperature of steels
Author/Authors :
Sourmail، نويسنده , , T. and Garcia-Mateo، نويسنده , , C.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2005
Pages :
12
From page :
323
To page :
334
Abstract :
Different approaches to predicting the Ms 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.
Keywords :
martensite , Thermodynamics , Bayesian neural networks , Linear regression
Journal title :
Computational Materials Science
Serial Year :
2005
Journal title :
Computational Materials Science
Record number :
1680968
Link To Document :
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