A Metallurgical Tool for Rapid Determination of Micro Inclusion Characteristics in Bearingm Steel Production.

Reinholdsson, Fredrik; Lind, A.; Nilsson, R. Henrik; Sjödin, P.; Jönsson, Pär

doi:10.2355/isijinternational.37.637

Cited by 18 publications

(11 citation statements)

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“…The overall fundamental model can now be seen as a system of equations, where every variable has its own row in the system and where every equation is expressed in the form of a "transport equation" (3). In order to solve the resulting system of equations it is necessary to supply the following additional information: • Thermodynamic properties (i.e.…”

Section: Mathematical Modelingmentioning

confidence: 99%

“…Thus, model predictions of changes in inclusion characteristics during the different stages of ladle refining are very helpful in optimizing the process. Even companies that have reported access to on-line methods to determine micro-inclusion characteristics 3,4) have a need for model predictions. The reason, similar to the delay for steel samples, is the response time (approximately 7 min).…”

Section: Introductionmentioning

confidence: 99%

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The Use of Fundamental Process Models in Studying Ladle Refining Operations.

Jönsson

Jonsson

2001

ISIJ International

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Existing fundamental models of ladle refining operations have been reviewed. No fundamental model that takes all the individual parts of ladle refining into account has been found in the open literature. Nor does a model exist which considers all refining in only one part of a refining step such as vacuum treatment. However, separate fundamental models for prediction regarding alloying, temperature, hydrogen, sulfur, reoxidation, and inclusion growth and removal do exist. In one case, a reoxidation model has also been combined with a sulfur-refining model. Predicted values from the separate models for alloying, temperature, sulfur and hydrogen have been found to agree well with corresponding measured data. The verification of the models for reoxidation and the growth and removal of inclusions is currently lacking and separate models for refining operations such as nitrogen or carbon removal need to be developed. Also, more complex models of parts of ladle refining such as vacuum treatment need to be developed, incorporating the sulfur, hydrogen, reoxidation and inclusion growth and removal models. The ultimate goal is, of course, one overall model that can predict desired parameter values for all steps of ladle refining. Even though such a model does not exist today, the usefulness of existing fundamental models is exemplified. This is to illustrate the potential of more complex and more realistic ladle models in process optimization.KEY WORDS: secondary refining; ladle; modeling; fundamental; steel; slag and gas.tration gradient of the element exists at the interface between two phases. This can, for example, be in the steel phase, if the diffusion of the solutes to be removed or added in steel is the rate controling step. Furthermore, it is assumed that the phases on each side of the concentration boundary layer, the steel phase and the refining phase (gas for hydrogen removal and slag for sulfur removal), are steadily and completely mixed. Therefore, the removal rate of an impurity elements from steel can, for example, be described as follows: 5) ................. (1) where x is the element to be refined (i.e. S or H), k is the total mass-transfer coefficient, r is the steel density, M is the steel mass, and [%x] is the actual concentration of the element to be refined. The parameter [%x] e is the hypothetical concentration of the refined element in the steel phase in equilibrium with the actual concentration in the refining phase. "A" is the interfacial area between the steel and the phase to which the element is refined. In the cases of hydrogen refining and sulfur refining, this is the gas phase and slag phase, respectively.One disadvantage with this traditional approach is that due to the assumptions mentioned, more often than not the coefficients in Eq. (1) can only be valid for one specific case at a time. Therefore, this equation tends to be of limited usefulness in prediction for refining processes in general. For example, the interfacial area A, to be used in prediction of desulfurization during gas...

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Section: Mathematical Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Use of Fundamental Process Models in Studying Ladle Refining Operations.

Jönsson

Jonsson

2001

ISIJ International

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“…[1][2][3][4] Some details regarding the analysis equipment, data acquisition and data processing can be found in earlier publications. 5,6) Today the PDA/OES analysis of inclusion characteristics in steel samples may take 3-5 minutes in an industrial practice. Currently, some steelmaking companies of the European Union try to use the PDA/OES method for fast determination of the inclusion characteristics in steel samples taken from different stages of the productions of various steel grades.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Inclusion Characteristics in Low-Alloyed Steels by Mainly Using PDA/OES Method

2015

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The characteristics of non-metallic inclusions (such as number, size and volume fraction) in liquid steel samples taken during ladle treatment and casting of industrial heats of two low-alloyed Ca-treated steel grades were evaluated by using the Pulse Distribution Analysis with Optical Emission Spectroscopy (PDA/OES) method. These results were compared to data obtained by Scanning Electron Microscope observations of inclusions after electrolytic extraction from steel samples (the EE method). It was found that the PDA/OES method can be used for a relative estimation of the homogeneity of the distribution of non-metallic inclusions in steel samples. Bottom and middle parts of the steel samples showed more homogeneous results with respect to the characteristics of the investigated Al 2 O 3 , CaO-Al 2 O 3 and CaOAl 2 O 3 -CaS inclusions. The numbers of inclusions in the size ranges 2.0-5.7 μm and 1.4-5.7 μm in samples taken before and after a Ca addition, respectively, showed a relatively good agreement between both methods. Furthermore, the calculated volume fractions for inclusions in the size range 2-13 μm obtained by the PDA/OES method agreed satisfactorily well with those obtained from the EE method. Finally, the minimum sizes of inclusions in steel samples, which can reliably be detected by the PDA/OES method, were estimated for steels with different concentrations of Al in steel and Al 2 O 3 in inclusions.

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“…9) The information regarding the development of PDA-OES, its advantages and disadvantages are described in detail in literature. [6][7][8][9][10][11][12][13][14] In this paper, we attempted to identify the size evolution © 2011 ISIJ of Al based inclusions in tundish samples in ULC steel with time by means of PDA-OES. The samples taken at the tundish were specifically taken into consideration for three reasons (i) the sampling method at the ladle and tundish is different.…”

Section: Introductionmentioning

confidence: 99%

Determination of Steel Cleanliness in Ultra Low Carbon Steel by Pulse Discrimination Analysis-Optical Emission Spectroscopy Technique

et al. 2011

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Traditional techniques of inclusion size determination are time consuming and cannot be implemented for on-line quality control. With the development of pulse discrimination analysis -optical emission spectroscopy (PDA-OES), the on-line determination of inclusions has become possible. However, PDA-OES measures only the number of inclusions present in the steel irrespective of size. In the present paper, the potential of PDA to determine the inclusion size is evaluated by employing two methodologies: (i) obtaining the average inclusion size by dividing the difference of total and soluble aluminium concentration by the number of Al based inclusions for 200 industrial ULC heats and (ii) measuring the Al concentration for individual peak intensity for specific heats, giving the inclusion size distribution. The methodologies of inclusion size measurement by PDA-OES as well as the possible causes of the discrepancies obtained after comparison with the inclusion extraction technique are explained in detail.KEY WORDS: PDA-OES; non-metallic inclusions; ultra low carbon steel; inclusion extraction.

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A Metallurgical Tool for Rapid Determination of Micro Inclusion Characteristics in Bearingm Steel Production.

Cited by 18 publications

References 0 publications

The Use of Fundamental Process Models in Studying Ladle Refining Operations.

The Use of Fundamental Process Models in Studying Ladle Refining Operations.

Evaluation of Inclusion Characteristics in Low-Alloyed Steels by Mainly Using PDA/OES Method

Determination of Steel Cleanliness in Ultra Low Carbon Steel by Pulse Discrimination Analysis-Optical Emission Spectroscopy Technique

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