Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2156
Title: Property Prediction of Ductile Iron (DI): Artificial Neural Network Approach
Authors: Behera, R K
Swain, S K
Sen, S
Mishra, S C
Keywords: Property Prediction
Ductile Iron
Issue Date: Aug-2013
Publisher: Orissa Journal of Physics
Citation: Orissa Journal of Physics, Vol. 20, No.2 , August 2013, pp.217-224
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 with multilayer back propagation algorithm is used as a predictive tool for predicting UTS & 0.2%YS of ductile iron with respect to variation in wt% of alloying elements. 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.
Description: Copyright for this article belongs Orissa Physical Society
URI: http://hdl.handle.net/2080/2156
ISSN: 0974-8202
Appears in Collections:Journal Articles

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