Anthony Sergnese

SPLASH capsule close-up

Continuous Casting

ArcelorMittal Dofasco, 2023–2024

In collaboration with ArcelorMittal Dofasco, a major steel manufacturer based in Hamilton, Ontario, researchers at the University of Toronto constructed a full-scale continuous casting water model to investigate flow behavior during steel casting. Its purpose was to better understand flow patterns that lead to defect formation during the casting process, using particle image velocimetry (PIV) measurements alongside computational fluid dynamics (CFD) simulations.

I was responsible for conducting a suite of experiments to characterize the effect of nozzle geometry and operating parameters on flow behavior. Working with nine nozzle geometries, I ran trials across three steel casting rates, each with three air injection rates to replicate argon injection used in industry. For every condition we recorded PIV plots and collected anemometer data from built-in sensors. To validate PIV as a reliable measurement technique, I also designed and executed a smaller pipe-flow experiment, compared the PIV results against CFD simulations in ANSYS Fluent, and successfully demonstrated strong agreement. This validation confirmed PIV as a viable tool for studying flow in steel casting models, strengthening its use for future industrial research. The work was written into a manuscript, presented at AISTech 2025, and published in the conference proceedings, where I am listed as second author.