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Diagnosis and optimisation of continuous casting practices through numerical modelling
KTH, School of Industrial Engineering and Management (ITM), Materials Science and Engineering, Applied Process Metallurgy. Swerea MEFOS AB, Aronstorpsvagen 1, SE-97437 Luleå, Sweden.
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2016 (English)In: La Metallurgia Italiana, ISSN 0026-0843, no 2, 43-49 p.Article in journal (Refereed) PublishedText
Abstract [en]

An advanced numerical model has been used to diagnose casting practices for a peritectic grade in a Scandinavian steel producer. The model solves the Navier-Stokes equations by use of an interface tracking technique known as the Volume of Fluid (VOF). Furthermore, the model considers heat transfer, solidification and uses Discrete Phase Model to simulate a multiple phase system of steel, slag and argon. As a result, it is possible to predict the metal flow and slag infiltration as well as their influence on the heat flux and solidification under the effect of gas injection and for transient conditions. Recent improvements to the model include a separation between mould powder and slag film and the consideration of the effect of crystallization on the interfacial resistance for a peritectic mould powder. The casting parameters analysed consist of the casting speed interlocked with oscillation settings, Submerged Entry Nozzle (SEN) immersion depths and argon injection flow rates. These practices were optimised by performing parametric studies to evaluate the shell growth, lubrication depth, cooling channel heat flux, etc. The application of the model allows for a prediction of trends and the results provide opportunities for further improvement in the form of guidelines for the process and enhanced operational windows. The model has been tested under industrial conditions and the results indicate the improvements of the surface quality and process stability can be obtained.

Place, publisher, year, edition, pages
ASSOC ITALIANA METALLURGIA , 2016. no 2, 43-49 p.
Keyword [en]
National Category
Metallurgy and Metallic Materials
URN: urn:nbn:se:kth:diva-184557ISI: 000371750600006OAI: diva2:917044

QC 20160405

Available from: 2016-04-05 Created: 2016-04-01 Last updated: 2016-04-05Bibliographically approved

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Nazem Jalali, PooriaJönsson, Pär
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