Artificial neural networks for hardness prediction of HAZ with chemical composition and tensile test of X70 pipeline steels-Reference-Cited by-同舟云学术

Artificial neural networks for hardness prediction of HAZ with chemical composition and tensile test of X70 pipeline steels

Published:2015-05 Issue:5 Volume:22 Page:446-450
ISSN:1006-706X
Container-title:Journal of Iron and Steel Research International
language:en
Short-container-title:J. Iron Steel Res. Int.

Author:

Pouraliakbar Hesam,Khalaj Mohammad-javad,Nazerfakhari Mohsen,Khalaj Gholamreza

Publisher

Springer Science and Business Media LLC

Subject

Materials Chemistry,Metals and Alloys,Mechanics of Materials

Link

http://link.springer.com/article/10.1016/S1006-706X(15)30025-X/fulltext.html

Reference21 articles.

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4. N. Ishikawa, T. Shinmiya, S. Igi, J. Kondo, in: 2006 International Pipeline Conference, American Society of Mechanical Engineers, USA, 2006, pp. 223–230.

5. Z. X. Li, Z. C. Jing, J. L. Rang, F. Y. Rong, Z. Wenzhen, H. C. Yong, Z. X. Wei, G. S. Tao, in: 2006 International Pipeline Conference, American Society of Mechanical Engineers, USA, 2006, pp. 251–259.

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