The increasing demand from consumers for newer, cheaper and more efficient products is increasingly influencing the way products are designed and produced. Virtual manufacturing processes are recognized to be part of the solution to deliver better products. This goes also for casted goods. To accommodate the ever changing placed upon casting processes simulation methods have to evolve as well. This means expanding the simulation scope both in terms of the complexity of the replicated boundary conditions and processes as well as the detail in which physical modelling is done. An overall understanding of the solidification pattern, possible defect distribution must be understood in order to design the casting process efficiently. This also includes that its micro structure is in the specified range, so that structural requirements can be met.
STAR-Cast utilizes STAR-CCM+’s free surface modelling technique combined with the melting and solidification model to study investment casting, high and low pressure die casting, centrifugal casting and tilt die simulation. A number of unique features are available to the user of STAR-Cast including; Mushy Zone & Flow Stop Modeling, Criteria Functions for Defect Prediction - Shrinkage, Porosity& Cooling rates. The newly added dimensionless Niyama Criterion extends the capabilities of the previous dimensional version.
The precision of casting simulation results depends to a high degree on the quality and completeness of the required material data. For this reason, a dedicated material data base is key to assuring quality of simulation: the data stored in STAR-Cast materials database are certified and qualified according to an internal documentation scheme. Integration of data documentation into casting simulation reports is easy. Searches for and retrieval of data stored in STAR-Cast mat is executed via the GUI, which combines easy use with access to full information about datasets. Straightforward data export allows you to assemble the material dataset appropriate to the simulation problem posed and to transfer this dataset to STAR-Cast.