| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Ilie, Sergiu
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (18/18 displayed)
- 2024Investigating the Origin of Non-Metallic Inclusions in Ti-Stabilized ULC Steels Using Different Tracing Techniquescitations
- 2023Different Approaches to Trace the Source of Non-Metallic Inclusions in Steel
- 2023Application of tracing techniques to determine the source of alumina inclusions in the clogging layer of Ti-stabilized ULC steels
- 2023Classification of peritectic steels by experimental methods, computational thermodynamics and plant data: An Overview
- 2023Impurities and tramp elements in steel: Thermodynamic aspects and the application to solidification processes
- 2023Comparison of tracing deoxidation products with rare earth elements in the industry and on a laboratory scale
- 2022High temperature thermodynamics of the Fe-C-Mn system; new experimental data for the Fe-C-10 and 20 wt.-% Mn system
- 2022Different Approaches to Trace the Source of Non-Metallic Inclusions in Steelcitations
- 2022A Near-Process 2D Heat-Transfer Model for Continuous Slab Casting of Steelcitations
- 2022Selected metallurgical models for computationally efficient prediction of quality-related issues in continuous slab casting of steel
- 2022Thermomechanical and Microstructural Analysis of the Influence of B- and Ti-Content on the Hot Ductility Behavior of Microalloyed Steelscitations
- 2021Investigations on hot tearing in a continuous slab caster: Numerical modelling combined with analysis of plant results
- 2020Utilization of Experimental Data as Boundary Conditions for the Solidification Model Tempsimu-3Dcitations
- 2019Investigation of water droplet impingement under conditions of the secondary cooling zone of a continuous caster
- 2019High precious phase diagrams – a roadmap for a successful casting processing
- 2016HT-LSCM - A valuable tool for surface microstructure investigations
- 2012Hot deformation behaviour of low alloyed steelcitations
- 2012Influence of Strain Rate on Hot Ductility of a V-Microalloyed Steel Slabcitations
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document
Application of tracing techniques to determine the source of alumina inclusions in the clogging layer of Ti-stabilized ULC steels
Abstract
The formation mechanism behind nozzle clogging during continuous casting of Ti-stabilized ultra-low carbon (ULC) steels is not entirely clarified today. One of the main reasons for the clogging layer formation is the deposition of pre-existing deoxidation products and the possibility of re-oxidation of the steel at the steel/refractory interface. By applying tracing techniques, the source of interfering inclusions and the formation of the clogging layer during continuous casting can be studied in detail.<br/>In this work, two different approaches to identify the source behind the alumina inclusions observed in the clogged nozzle are applied. First, direct tracing by means of rare earth elements (REEs) was performed. For this technique, REEs are added to the liquid steel after deoxidation. Hence, pre-existing alumina inclusions are modified. The advantage of this technique is that REE-containing inclusions appear brighter than the steel matrix in backscattered electron images of scanning electron microscopy with energy-dispersive spectroscopy (SEM/EDS) analysis. It is the state-of-the-art method to track the formation of deoxidation products over the process.The second concept that was examined in this work is REE fingerprint analysis. Up to now, this method has been mainly applied in the research field of food chemistry and geology. For REE fingerprint analysis, the pre-existing concentration of REEs for all essential auxiliaries in the production process – such as Al-granules or casting powders – are measured by inductively coupled plasma-mass spectrometry (ICP-MS) and normalized to a reference data set in order to make REE patterns easier to recognize. The resulting pattern is then compared to the detected pattern of the clogging layer and existing mesoscopic inclusions. Similarities in the REE patterns indicate materials that may have contributed to the formation of the clogging layer or inclusions.