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Journal of Metallurgy and Materials Science
Year : 2012, Volume : 54, Issue : 3
First page : ( 197) Last page : ( 202)
Print ISSN : 0972-4257. Online ISSN : 0974-1267.

Property prediction of ductile iron: Artificial neural network approach

Behera R.K.*, Swain S.K., Sen S., Mishra S.C.

Department of Metallurgical and Materials Engineering, National Institute of Technology, Rourkela, Odisha, India

*Corresponding Author Email: ranjanbehera.2419@gmail.com

Online published on 13 February, 2013.

Abstract

Mechanical properties of ductile cast iron (DI) depend on its microstructure, which is influenced by addition of alloying elements. Artificial Neural Network (ANN) technique 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.

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Keywords

Ductile iron, Artificial neural network, Mechanical properties.

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