Near-net-shape castings are the foundation of Ontario’s manufacturing sector. The focus of this project is the application of SOLID to Al shape castings. This software, which predicts heat and mass transfer, and defects, has been used previously to improve casting of large ingots but not shaped products. We will study the degree of macrosegregation that occurs when shape casting Al-Si alloys. Macrosegregation refers to variations in composition that occur in alloys, ranging in scale from mm-cm. These variations have a strong impact on mechanical properties and lead to part rejection.
Impact
Near-net-shape castings are the most cost-effective methods for manufacturing light metal alloy parts of complex shapes. The prediction of casting defects remains of utmost importance to this industry, and improved models are needed in order to increase the usage of Al, Mg and Ti alloys in the automotive and aerospace sectors. Ultimately, this increased usage will result in a cleaner environment through vehicle weight reduction.
Student Experience
This project will provide research-based training and networking opportunities to graduate students at McMaster and l’Ecole des Mines de Nancy. Participating students will gain advanced technical knowledge of solidification, become proficient in numerical modelling of industrial processes, gain expertise in using emerging commercial software, and experience in international collaborations.
