<p>A new user function was developed to simulate carbon macrosegregation in medium to large-sized steel ingots, derived for use in the post-processing stage of casting simulations. This new proposed formulation accounts for critical parameters such as cooling rate, thermal gradient, and ingot geometry, and can be implemented within commercial simulation software to estimate steel carbon content. The methodology was first applied to an industrial-scale 36-tonne ingot, comparing simulation and experimental analyses. Characterisation of the industrial ingot, performed by sectioning and chemical analysis, showed good agreement between the carbon segregative index values predicted by the user function and those experimentally measured. To further assess the reliability of the model, a second case study was conducted on a 40-tonne ingot using the same approach. The results confirmed the predictive capability of the developed function, which can be effectively employed to evaluate carbon macrosegregation in medium to large-sized ingots, particularly for medium- to low-alloy steel grades.</p> Graphical Abstract <p></p>

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Modelling and Simulation of Carbon Macrosegregation in a 36-Tonne Steel Ingot

  • Anna Mantelli,
  • Annalisa Pola,
  • Marcello Gelfi,
  • Cristian Viscardi,
  • Flavio Ricchini,
  • Massimo Svanera,
  • Francesco Bergamaschi

摘要

A new user function was developed to simulate carbon macrosegregation in medium to large-sized steel ingots, derived for use in the post-processing stage of casting simulations. This new proposed formulation accounts for critical parameters such as cooling rate, thermal gradient, and ingot geometry, and can be implemented within commercial simulation software to estimate steel carbon content. The methodology was first applied to an industrial-scale 36-tonne ingot, comparing simulation and experimental analyses. Characterisation of the industrial ingot, performed by sectioning and chemical analysis, showed good agreement between the carbon segregative index values predicted by the user function and those experimentally measured. To further assess the reliability of the model, a second case study was conducted on a 40-tonne ingot using the same approach. The results confirmed the predictive capability of the developed function, which can be effectively employed to evaluate carbon macrosegregation in medium to large-sized ingots, particularly for medium- to low-alloy steel grades.

Graphical Abstract