Led by Charles Monroe

thinwallPredicting the flow length of high performance castings with thin-wall sections is important for a variety of materials and casting conditions. This project focuses on the development of a model to predict filling in thin-wall casting geometries.

Thin-wall castings are the focus of foundries looking to satisfy the demand for improved casting performance and efficiency. Successful casting designs are generally created based on well-established design rules and procedures such as Chvorinov’s Rule, which relates solidification time to local casting geometry. Unfortunately, the design of thin-wall castings cannot be evaluated reliably with these same methods. For sand casting processes, thin-walled castings are generally those that are designed with sections thinner than ¼ inch or 6 mm; sections are thinner still for die casting. The model developed in this project evaluates filling in thin-wall castings based on the heat energy extracted out of the fluid metal. A visualization of filling length and defects is produced by applying the model to three dimensional meshed casting geometries with temperature and velocity fields.  

The current focus of the project is determining valid model correlations and expected parameter ranges over a wide spectrum of casting conditions. To do this, the model is benchmarked against experimental filling results from landmark fluidity studies in literature. From here, the model will be used to predict and solve current thin-wall filling defects found in industry where complex flow patterns will require refinement of the current result interpretation. The ultimate goal is to develop a broadly applicable model that can be programmed into one of the already commercially available casting simulation software packages.

This is one model case study involving zinc die cast plates with the current model version. The experimental filling of the plates (below) is shown as a function of metal injection velocity from 0.7 to 2.0 m/s. Red areas in the model results (above) indicate regions of filling risk.