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Bellot JP, Kroll-Rabotin JS, Gisselbrecht M, et al. Toward Better Control of Inclusion Cleanliness in a Gas Stirred Ladle Using Multiscale Numerical Modeling. Materials (Basel). 2018;11(7)doi: 10.3390/ma11071179.
Bellot, J. P., Kroll-Rabotin, J. S., Gisselbrecht, M., Joishi, M., Saxena, A., Sanders, S., & Jardy, A. (2018). Toward Better Control of Inclusion Cleanliness in a Gas Stirred Ladle Using Multiscale Numerical Modeling. Materials (Basel, Switzerland), 11(7), . https://doi.org/10.3390/ma11071179
Bellot, Jean-Pierre, et al. "Toward Better Control of Inclusion Cleanliness in a Gas Stirred Ladle Using Multiscale Numerical Modeling." Materials (Basel, Switzerland) vol. 11,7 (2018). doi: https://doi.org/10.3390/ma11071179
Bellot JP, Kroll-Rabotin JS, Gisselbrecht M, Joishi M, Saxena A, Sanders S, Jardy A. Toward Better Control of Inclusion Cleanliness in a Gas Stirred Ladle Using Multiscale Numerical Modeling. Materials (Basel). 2018 Jul 10;11(7). doi: 10.3390/ma11071179. PMID: 29996521; PMCID: PMC6073398.
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Materials (Basel). 2018 Jul 10;11(7). doi: 10.3390/ma11071179.

Toward Better Control of Inclusion Cleanliness in a Gas Stirred Ladle Using Multiscale Numerical Modeling.

Materials (Basel, Switzerland)

Jean-Pierre Bellot, Jean-Sebastien Kroll-Rabotin, Matthieu Gisselbrecht, Manoj Joishi, Akash Saxena, Sean Sanders, Alain Jardy

Affiliations

  1. Institut Jean Lamour-UMR 7198 CNRS/Université de Lorraine, CS 50840, 54011 Nancy CEDEX, France. [email protected].
  2. Laboratory of Excellence on Design of Alloy Metals for low-mAss Structures (Labex DAMAS), Université de Lorraine, 57073 Metz, France. [email protected].
  3. Institut Jean Lamour-UMR 7198 CNRS/Université de Lorraine, CS 50840, 54011 Nancy CEDEX, France. [email protected].
  4. Laboratory of Excellence on Design of Alloy Metals for low-mAss Structures (Labex DAMAS), Université de Lorraine, 57073 Metz, France. [email protected].
  5. Institut Jean Lamour-UMR 7198 CNRS/Université de Lorraine, CS 50840, 54011 Nancy CEDEX, France. [email protected].
  6. Laboratory of Excellence on Design of Alloy Metals for low-mAss Structures (Labex DAMAS), Université de Lorraine, 57073 Metz, France. [email protected].
  7. Institut Jean Lamour-UMR 7198 CNRS/Université de Lorraine, CS 50840, 54011 Nancy CEDEX, France. [email protected].
  8. Laboratory of Excellence on Design of Alloy Metals for low-mAss Structures (Labex DAMAS), Université de Lorraine, 57073 Metz, France. [email protected].
  9. Department of Chemical & Materials Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada. [email protected].
  10. Department of Chemical & Materials Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada. [email protected].
  11. Institut Jean Lamour-UMR 7198 CNRS/Université de Lorraine, CS 50840, 54011 Nancy CEDEX, France. [email protected].
  12. Laboratory of Excellence on Design of Alloy Metals for low-mAss Structures (Labex DAMAS), Université de Lorraine, 57073 Metz, France. [email protected].

PMID: 29996521 PMCID: PMC6073398 DOI: 10.3390/ma11071179

Abstract

The industrial objective of lowering the mass of mechanical structures requires continuous improvement in controlling the mechanical properties of metallic materials. Steel cleanliness and especially control of inclusion size distribution have, therefore, become major challenges. Inclusions have a detrimental effect on fatigue that strongly depends both on inclusion content and on the size of the largest inclusions. Ladle treatment of liquid steel has long been recognized as the processing stage responsible for the inclusion of cleanliness. A multiscale modeling has been proposed to investigate the inclusion behavior. The evolution of the inclusion size distribution is simulated at the process scale due to coupling a computational fluid dynamics calculation with a population balance method integrating all mechanisms, i.e., flotation, aggregation, settling, and capture at the top layer. Particular attention has been paid to the aggregation mechanism and the simulations at an inclusion scale with fully resolved inclusions that represent hydrodynamic conditions of the ladle, which have been specifically developed. Simulations of an industrial-type ladle highlight that inclusion cleanliness is mainly ruled by aggregation. Quantitative knowledge of aggregation kinetics has been extracted and captured from mesoscale simulations. Aggregation efficiency has been observed to drop drastically when increasing the particle size ratio.

Keywords: aggregation; non-metallic inclusions; simulation; steel ladle

References

  1. Adv Colloid Interface Sci. 2006 Sep 25;122(1-3):79-91 - PubMed
  2. Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Dec;78(6 Pt 1):061404 - PubMed
  3. Langmuir. 2015 Jun 2;31(21):5712-21 - PubMed

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