AFS Transactions
2008
Aitor Loizaga, Foundry technologies, Iron foundry, Jon Sertucha, José Manuel Gutiérrez, Modeling, Pello Larrañaga, Prediction, R&D+i, Ramón Suarez, Spheroidal Graphite, Thermolan
The present work develops a new method for pre-evaluating melt quality of ductile irons and for predicting their metallurgical behavior during the solidification step. Based on the characterization of the liquid-solid trasition using the cooling curves and database techniques, this study provides a new effective approach to predict the nucleation ability of the metal and its shrinkage formation tendency. Both factors are considered as critical parameters in order to guarantee the effective manufacturing of sound castings and increase the productivity. Two specific parameters have been defined for this purpose: N (nodule count prediction factor) and k (shrinkage formation tendency factor). A thermal analysis database has been set up by analyzing castings of an extended variety of ductile irons manufactured under fixed production conditions. The database contains more than 600 records obtained form experimental cooling curves, the results of metallographic studies (graphite morphology characterization), the chemical composition of the alloy and X-ray inspections for evaluating the appearance of contraction defects in specific samples. It is found that necessary feeding requirements related to riser design and the contraction defects appearance are strongly correlated to the shape of the cooling curves and the corresponding N and k factors. Therefore, it is possible to predict the metallurgical behavior of alloys by analyzing their solidification before casting. The aim of the present work is to introduce the procedure for evaluating the N and k factors and to describe their effectiveness when compared to the information from the database.
Pello Larrañaga, José Manuel Gutiérrez, Aitor Loizaga, Jon Sertucha, Ramón Suárez.
Predition, castings soundness, graphite formation, graphite index, metallurgical behavior.
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