Artificial neural network modeling on the relative importance of alloying elements and heat treatment temperature to the stability of α and β phase in titanium alloys-Reference-Cited by-同舟云学术

Artificial neural network modeling on the relative importance of alloying elements and heat treatment temperature to the stability of α and β phase in titanium alloys

Published:2015-09 Issue: Volume:107 Page:175-183
ISSN:0927-0256
Container-title:Computational Materials Science
language:en
Short-container-title:Computational Materials Science

Author:

Reddy N.S.,Panigrahi B.B.,Ho Choi Myeong,Kim Jeoung Han,Lee Chong Soo

Publisher

Elsevier BV

Subject

Computational Mathematics,General Physics and Astronomy,Mechanics of Materials,General Materials Science,General Chemistry,General Computer Science

Reference38 articles.

1. Experimental and theoretical studies of intergranular strain in an alpha titanium alloy during plastic deformation

2. Influence of transformation temperature on microtexture formation associated with α precipitation at β grain boundaries in a β metastable titanium alloy

3. Application of artificial neural networks for modelling correlations in titanium alloys

4. Software products for modelling and simulation in materials science

5. Neural Networks in Materials Science.

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