Besides the gating and riser system
Fig. 1. The conventional computer-aided engineering design process is shown surrounded by a blue dashed line. This shows the potential integration of casting process simulation in the design process.
structures of cast irons (GJS-400 and GJV-450), predicted by casting process simulation, with the lifetime predic- tion for castings. Experiments were used to derive S–N curves (Woehler curves), which resulted in the develop- ment of a closed chain between casting process and the prediction of the final lifetime of a cast component. Local properties driven by the production process of a casting now can be trans- ferred into and considered by lifetime prediction tools.
Microstructure Prediction for Cast Iron
Metallurgy and alloying compo-
nents have an essential influence on the final microstructure and resulting mechanical properties of a casting. Te chemical composition and inclu- sions, the melt treatment (charge materials, melting method, treatment, and inoculation), as well as the local cooling conditions are of utmost importance. Foundry engineers use these process variables to dial in the desired microstructure (graphite form, ferrite/pearlite ratio) and avoid unde- sired defects (i.e., porosity or dross) and microstructures (i.e., graphite deformations or chill). Simulation programs need to be able to predict the kinetics of the creation of the different phases locally during the entire solidifica- tion and cooling process. Besides the alloying elements, this requires the consideration of the inoculation and
36 | MODERN CASTING April 2017
melt treatment process. Te impact of these is usually overlapped with the local cooling conditions within the casting. Te calculation of the plain macroscopic solidification and cool- ing behavior cannot consider these parameters. Microstructure simulation is required to calculate at any time in any location inside the casting, the amount and type of phase created based on the parameters.
and geometry of the casting, cast- ing process simulation considers the chemical composition, melt treatment, and inoculation, as well as other rel- evant process parameters. Te program utilizes these input parameters and local cooling conditions to calculate the locally available inoculation sites, growth of all phases, impact of segre- gation to calculate the solidification process and resulting local microstruc- ture, and its properties. Te calculation of all phases during the solidification process allows for the prediction of the final microstructure when the casting is completely solidi- fied. During the following cooling process, the diffusion of alloying ele- ments within the austenite is consid- ered to predict the amount of graph- ite. Te additional consideration of segregation effects of alloying elements allows for the accurate prediction of ferrite and pearlite growth during the eutectoid phase transfer. Te calcula- tion of cooling conditions below the eutectoid phase transformation leads to the prediction of phase ratios of the matrix (ferrite/pearlite ratio, pearlite
Fig. 2. Test piece locations for a ductile iron bedplate (a), test casting (b), CGI crankcase (c), and step casting (d) are depicted.
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