Ductile iron microstructure prediction based on melt thermal analysis using artificial neural networks

Žmak, Irena and Filetin, Tomislav and Unkić, Faruk (2016) Ductile iron microstructure prediction based on melt thermal analysis using artificial neural networks. = Ductile iron microstructure prediction based on melt thermal analysis using artificial neural networks. In: The 48th International October Conference on Mining and Metallurgy, 28.09.-01.10.2016., Bor, Srbija.

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Abstract

The paper presents the results of application of artificial neural networks in predicting the ductile iron graphite microstructure, i.e. nodularity and nodule count. The input parameters are the data acquired through thermal analysis of the melt, namely the ones that affect nodule formation the most: liquidus temperature, eutectic undercooling temperature, recalescence, solidus temperature, graphite factor 1 and graphite factor 2, near-solidus cooling rate, and eutectoid temperature. Good accordance between measured and predicted data is observed so the proposed neural network method can be successfully applied for predicting the graphite formation in ductile iron based on melt thermal analysis.

Item Type:	Conference or Workshop Item (Lecture)
Keywords (Croatian):	artificial neural network ; ductile cast iron ; thermal analysis ; graphite
Subjects:	TECHNICAL SCIENCE > Metallurgy
Divisions:	1000 Department of Materials > 1010 Chair of Materials and Tribology
Indexed in Web of Science:	No
Indexed in Current Contents:	No
Date Deposited:	10 Jan 2018 08:56
Last Modified:	10 Jan 2018 08:56
URI:	http://repozitorij.fsb.hr/id/eprint/8214

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