Speaker
Description
In steel industry, ensuring high steel quality is essential to guarantee superior performance of final components. However, defects such as shrinkage porosity, macrosegregation and non-metallic inclusions in steel ingots can adversely affect mechanical properties. Various software tools are currently used to simulate ingot filling and solidification. However, while these tools are known to be reliable in predicting some defects, accurately modeling macrosegregation remains challenging due to the complex and concurrent phenomena occurring during the process. A dedicated user-defined function was created to simulate carbon macrosegregation in steel ingots of medium to large dimensions to be applied during the post-processing phase of casting simulations. The function integrates key solidification factors such as cooling rate, thermal gradient, and ingot geometry and can be incorporated into commercial simulation software to estimate local carbon distribution. The approach was initially tested on a 36-tonne industrial ingot, whose simulation results were compared with experimental data obtained through sectioning and chemical analysis. The comparison revealed a strong correlation between the simulated segregation index and the measured values. A second validation was then performed on a 40-tonne ingot using the same methodology, confirming the consistency and reliability of the model. Overall, the study demonstrates that the developed function is an effective tool for assessing carbon macrosegregation in medium- to large-scale ingots, with relevance for medium- and low-alloy steel grades.
| Speaker Company/University | Anna Mantelli (University of Brescia) |
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