Applied Mathematical Modelling of Continuous Casting Processes: A Review
Abstract
:1. Introduction
2. Metallurgical Length
2.1. Pure Metals or Eutectic Alloys
2.2. Alloys
- (A)
- an enthalpy-like formulation just mentioned using the full 2D time-independent equations;
- (B)
- an enthalpy-like formulation using a reduction of the full 2D time-independent equations to a 1D transient-like formulation of the type used in [21];
- (C)
- the proposed new formulation, which is also 1D transient-like but resolves the locations of the solidus and liquidus isotherms explicitly.
3. Air Gap and Mould Taper
4. Oscillation-Mark Formation
5. Macrosegregation
- in [80], numerical issues associated with the use of CFD, of the type mentioned earlier; and
- the fact that the geometry in question, which has an aspect ratio of six, is not slender enough for the asymptotic approach to be valid.
6. Electromagnetic Stirring
7. Conclusions
- For solidification shrinkage-induced macrosegregation in a binary alloy, reasonably good quantitative agreement was achieved for the cross-sectional macrosegregation profile, and even better agreement is to expected when the model has been developed to include superheat [23].
- For oscillation-mark formation, very good agreement was obtained with experimental results for fold-type marks [30].
Funding
Conflicts of Interest
Appendix A. Notes on Practical Asymptotics
- (a)
- Nondimensionalization of the original governing equations;
- (b)
- Analysis of the nondimensionalized governing equations, and identification of the key dimensionless parameters and asymptotic reduction;
- (c)
- Evidence that the computation of the reduced model is cheaper than the computation of the original model would have been (if the reduced model does not have an analytical solution); and
- (d)
- Evidence of agreement between the results of the original model and the asymptotically reduced model.
- Fewer partial differential equations (PDEs) rather than more;
- One-dimensional models rather than two-dimensional models, and two-dimensional models rather than three-dimensional models;
- Ordinary differential equations (ODEs) rather than PDEs; and
- Problems having fewer model parameters rather than more, with regard to the need for parameter studies to obtain a complete understanding of model behaviour.
- After nondimensionalization and asymptotic reduction, the model was one-dimensional and transient-like, consisted of two PDEs (or effectively different representations of the same PDE) and contained six model parameters [21].
- A direct comparison of CPU time and RAM was not carried out, but we note that one computation in [35] required 30 h of CPU time on a Cray J932 Supercomputer—with current computational architectures, this would no doubt take much less, but still would not be as short as the few seconds required for the formulation in [21].
- The agreement between the model results was very good, as shown in Figure 3.
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Vynnycky, M. Applied Mathematical Modelling of Continuous Casting Processes: A Review. Metals 2018, 8, 928. https://doi.org/10.3390/met8110928
Vynnycky M. Applied Mathematical Modelling of Continuous Casting Processes: A Review. Metals. 2018; 8(11):928. https://doi.org/10.3390/met8110928
Chicago/Turabian StyleVynnycky, Michael. 2018. "Applied Mathematical Modelling of Continuous Casting Processes: A Review" Metals 8, no. 11: 928. https://doi.org/10.3390/met8110928
APA StyleVynnycky, M. (2018). Applied Mathematical Modelling of Continuous Casting Processes: A Review. Metals, 8(11), 928. https://doi.org/10.3390/met8110928