Process modeling, such as casting simulations, predict how changes in process parameters will result in changes in microstructure and properties. The greater the accuracy of these simulations, the more useful they are as a predictive tool. Detailed knowledge of the specific boundary conditions, material properties, and the resultant change in the phase transformation pathway during the casting process is required to ensure the simulations can predict a defective part before it is cast.
In this work, casting experiments using a vacuum induction furnace provide heat transfer and thermal history data for a model Bi-Sn alloy as well as aluminum. This data, combined with characterization of the resultant microstructure, is used to refine the microstructural model in the casting simulations.
Using the heat transfer and cooling rate data, a greater understanding of the processing – microstructure relationship is obtained.