• Title of article

    Modeling diffusion-governed solidification of ternary alloys – Part 2: Macroscopic transport phenomena and macrosegregation

  • Author/Authors

    Wu، نويسنده , , M. and Li، نويسنده , , Hyoung J. and Ludwig، نويسنده , , A. and Kharicha، نويسنده , , A.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2014
  • Pages
    19
  • From page
    267
  • To page
    285
  • Abstract
    Part 1 of this two-part investigation presented a multiphase solidification model incorporating the finite diffusion kinetics and ternary phase diagram with the macroscopic transport phenomena (Wu et al., 2013). In Part 2, the importance of proper treatment of the finite diffusion kinetics in the calculation of macrosegregation is addressed. Calculations for a two-dimensional (2D) square casting (50 × 50 mm2) of Fe–0.45 wt.%C–1.06 wt.%Mn considering thermo-solutal convection and crystal sedimentation are performed. The modeling result indicates that the infinite liquid mixing kinetics as assumed by classical models (e.g., the Gulliver–Scheil or lever rule), which cannot properly consider the solute enrichment of the interdendritic or inter-granular melt at the early stage of solidification, might lead to an erroneous estimation of the macrosegregation. To confirm this statement, further theoretical and experimental evaluations are desired. The pattern and intensity of the flow and crystal sedimentation are dependent on the crystal morphologies (columnar or equiaxed); hence, the potential error of the calculated macrosegregation caused by the assumed growth kinetics depends on the crystal morphology. Finally, an illustrative simulation of an engineering 2.45-ton steel ingot is performed, and the results are compared with experimental results. This example demonstrates the model applicability for engineering castings regarding both the calculation efficiency and functionality.
  • Keywords
    solidification , macrosegregation , steel ingot , Microsegregation , Ternary alloy
  • Journal title
    Computational Materials Science
  • Serial Year
    2014
  • Journal title
    Computational Materials Science
  • Record number

    1693068