Property prediction of ductile iron : Artificial neural network approach

Behera, R K and Swain, S K and Sen, S and Mishra, S C (2012) Property prediction of ductile iron : Artificial neural network approach. Journal of Metallurgy and Materials Science,, 54(3). pp. 197-202.

[thumbnail of 197-202.pdf] PDF
197-202.pdf
Restricted to NML users only. Others may use ->
Download (77kB) | Request a copy

Abstract

Mechanical properties of ductile cast iron (DI) depend on its microstructure, which is influenced by addition of alloying elements. Artificial Neural Network (ANN) tech-
nique developed using back propagation algorithm was employed to predict the tensile strength (UTS) & 0.2% yield strength (YS). Effect of Carbon Equivalent (%CE)
and Mg wt% on UTS and 0.2%YS on 3mm & 12mm sections are studied. Comparison between predicted and experimental value shows good correlation with acceptable percentage of error.

Item Type: Article
Uncontrolled Keywords: Ductile iron, Artificial neural network and Mechanical properties.
Subjects: Metallurgy
Divisions: Material Science and Technology
Depositing User: Dr. A K Sahu
Date Deposited: 12 Feb 2013 09:17
Last Modified: 03 Sep 2026 08:07
URI: http://eprints.nmlindia.org/id/eprint/6379

Actions (login required)

View Item
View Item