ISIJ International
Online ISSN : 1347-5460
Print ISSN : 0915-1559
ISSN-L : 0915-1559
Regular Article
Modelling of Cr2N Age-precipitation in High Nitrogen Stainless Steels by Neural Networks
N. S. ReddyI. DzhebyanJae Sang LeeYang Mo Koo
Author information
JOURNALS FREE ACCESS

2010 Volume 50 Issue 2 Pages 279-285

Details
Abstract

It is very important to study the incubation time of alloys as it has direct relation to precipitation kinetics and affects morphology of structure. In spite of many efforts of scientists to develop methods to find incubation time, it is still difficult to measure experimentally. In addition, there is need to develop an approach to analyze existing data for many steels. On the other hand, high nitrogen steels have received a lot of attention for their unique properties, however, there is no clear model developed to predict its precipitation kinetics. In present work, Cr2N age-precipitation in high nitrogen austenitic steels is simulated using neural network (NN) analysis. The feed forward neural network with a back propagation algorithm was built to obtain the constitutive relation of Cr2N age precipitation with alloying elements and aging temperature. The simulated results show that the NN model can correctly reproduce the precipitation behavior of the steel. An analysis of model predictions and experimental data is presented.

Information related to the author
© 2010 by The Iron and Steel Institute of Japan
Previous article Next article
feedback
Top