Ductile iron microstructure prediction based on melt thermal analysis using artificial neural networks (CROSBI ID 648472)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Žmak, Irena ; Filetin, Tomislav ; Unkić, Faruk
engleski
Ductile iron microstructure prediction based on melt thermal analysis using artificial neural networks
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.
artificial neural network ; ductile cast iron ; thermal analysis ; graphite
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Podaci o prilogu
289-292.
2016.
objavljeno
Podaci o matičnoj publikaciji
Proceedings, 48th International October Conference on Mining and Metallurgy
Štrbac, Nada ; Živković, Dragana
Bor: Tehnički fakultet u Boru Univerziteta u Beogradu
978-86-6305-047-1
Podaci o skupu
The 48th International October Conference on Mining and Metallurgy
predavanje
28.09.2016-01.10.2016
Bor, Srbija