비만아 부모의 돌봄 경험: q 방법론

The kinetic modeling for the nucleation, size growth, and compositional evolution of nonmetallic inclusions in steel was extensively reviewed in the present article. The nucleation and initial growth of inclusion in molten steel during deoxidation as well as the collision growth, motion, removal, and entrapment of inclusions in the molten steel in continuous casting (CC) tundish and strand were discussed. Moreover, the recent studies on the prediction of inclusion composition in CC semiproducts were introduced. Since the 1990s, the development of thermodynamic model and relevant databases for inclusion engineering has been initiated by the steel industry. Later, the commercial software FACTSAGE employing the FACT database was widely used to predict the gas (atmosphere/bubble)–liquid (steel/slag/inclusion)–solid (refractory/slag/steel/inclusion) multiphase equilibria. With the help of the comprehensive thermodynamic database and solution models in conjunction with the development of user-friendly computing packages, the kinetics of inclusion evolution in molten steel can be successfully predicted based on several kinetic models such as the coupled reaction (CR) model, reaction zone model, and tank series recirculation (TSR) model. However, some parameters are needed to represent the real processes according to the model employed at different operational or experimental conditions. The effect of reoxidation on the evolution of inclusions in the ladle and tundish, which was experimentally confirmed, can be simulated by the effective equilibrium reaction zone (EERZ) model. The complex slag–steel interfacial reaction phenomena have been successfully explained by the interfacial kinetic model based on the dynamic interfacial tension and oxygen adsorption/desorption characteristics at the slag-steel interface.

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Kinetic Modeling of Nonmetallic Inclusions Behavior in Molten Steel: A Review

The non-metallic inclusions are mostly harmful to the propertiesof the steel products. The effective characterization of the size, morphology, and distribution of the inclusions in steel is a key issue to remove and control the inclusions in the metallurgical process. However, the conventional methods usually characterize the inclusions on the cross sections of polished samples, which could only reveal the local features of the inclusions. Therefore, the three-dimensional (3D) observation of the inclusions would provide critical information of the inclusions in the steel matrix. However, it is rare to find the reports of the quantitative investigation of the 3D morphology of inclusion particles. In this study, the samples containing titanium nitride (TiN), titanium oxides (TixOy), and manganese sulfide (MnS) inclusions were measured by X-ray Micro-computed tomography (Micro-CT) in the beamline of BL13W1 available at Shanghai Synchrotron Radiation Facility (SSRF) to obtain the 3D information of the inclusions. The 3D particles were reconstructed by the commercial software Avizo based on the optimized cross-sectional image slices. A series of parameters were defined to quantitatively express the 3D size and morphology of the inclusions, whose distributions are discussed and analyzed statistically. The method provides a powerful and useful way to observe and analyze inclusion particles in the steel products.

Three-dimensional characterization of typical inclusions in steel by X-ray Micro-CT

A reaction model was developed to investigate evolutions of steel chemistry and inclusion compositions during reoxidation of Ca-treated Al-killed steels in a tundish. The evolutions of Al2O3, CaO, MgO, and CaO in inclusions were accurately predicted using the current reaction model. The reaction model can widely predict the evolution of inclusions during tundish reoxidation of Ca-treated Al-killed steels with varying concentrations of Al, Ca, and absorbed oxygen.

A Reaction Model for Prediction of Inclusion Evolution During Reoxidation of Ca-Treated Al-Killed Steels in Tundish

Control of non-metallic inclusions is essential for the production of high-quality steel. This review summarizes processes that change inclusion compositions and concentrations during secondary steelmaking—slower changes are limited by reaction between bulk steel and slag or refractory, and faster changes involve direct additions to the steel bath. An example of the former is conversion of alumina inclusions to spinels during ladle treatment, while reoxidation and calcium treatment are typical exemplars of the fast changes. For the slower changes, inclusions approach equilibrium with the liquid steel and conceptually simple kinetic models correctly describe inclusion evolution during ladle treatment. Disequilibrium from faster changes persists for several minutes under typical ladle conditions, with small-scale inhomogeneity in the steel. Fast scanning electron microscopy with microanalysis has facilitated detailed study of these inclusion evolution processes by providing information on inclusion composition, size, and shape. Machine learning methods are likely to be increasingly important in analysis of the results. Such methods have already shown promise to improve classification of inclusions and recognizing inclusion clusters, from analyses of polished sections. Several unresolved issues that require future study are noted.

/pdf/a-review-of-steel-processing-considerations-for-oxide-521wjj2xgz.pdf

A Review of Steel Processing Considerations for Oxide Cleanliness

This work investigated the use of FactSage macros to simulate steel–slag and steel–inclusion reaction kinetics in silicon-manganese killed steels, and predict oxide inclusion composition changes during ladle treatment. These changes were assessed experimentally using an induction furnace to simulate deoxidation and slag addition. The average steel mass transfer coefficient for the experimental setup was calculated from the analyzed aluminum pick-up by steel. Average oxide inclusion composition was measured using scanning electron microscopy and energy-dispersive X-ray spectroscopy. Confocal laser scanning microscopy was used to assess the physical state (solid or liquid) of oxide inclusions in selected samples. The changes in the chemical compositions of the oxide inclusions and the steel agreed with the FactSage macro simulations.

Modeling Manganese Silicate Inclusion Composition Changes during Ladle Treatment Using FactSage Macros

This paper examines the consistency between experiments and thermodynamic predictions of the modification of non-metallic inclusions by dissolved Ca in liquid Fe-Al alloys. Current thermodynamic predictions made with FactSage (version 7.2) were found to overestimate the amount of dissolved Ca and the Ca in non-metallic inclusions. This was demonstrated in two ways. First, Al-deoxidized Fe was held in CaO-3 pct ZrO2 crucibles for 100-136 minutes at 1873 K (1600 °C) and then reoxidized to precipitate dissolved Ca as oxide inclusions. The amount of Ca in the inclusions after reoxidation was quantified and considered equal to the dissolved Ca in the liquid Fe prior to reoxidation. Although experimental data were limited, the results suggested that the dissolved Ca was low and that the thermodynamic behavior of Ca could be best described by excluding Ca-O interaction. The assumption of no Ca-O interaction was compared with the associate solution model employed in FactSage by simulating the evolution of inclusion compositions in Fe—2, 1, 0.5, 0.1 wt pct Al alloys exposed to CaO (sat.)-MgO (sat.)-Al2O3 slags. The assumption of no Ca-O interaction led to predictions that were much closer to experimental results. More work is needed to ensure dissolved Ca behavior is accurately described and to ensure the sources for Ca modification of inclusions in industrial samples are properly identified.

https://link.springer.com/content/pdf/10.1007/s11663-020-01774-3.pdf

Calcium Modification of Inclusions via Slag/Metal Reactions

This work aims to clarify the rate and mechanism of MgO pickup by alumina inclusions and the effect of oxide impurities in MgO crucibles on this transformation. Two MgO crucibles from different batches from the same supplier were used in laboratory experiments with Al-killed steel. A kinetic model was developed, based on mass-transfer control in the liquid steel. Rate constants were fitted using inclusion analysis. The rate of magnesium transfer from the two types of crucibles was found to differ by a factor of 20; faster magnesium transfer was associated with formation of a slag layer on the inner surface of the crucible wall (rather than a solid spinel product layer). The kinetic model was also used to simulate industrial scale ladle refining (1) to illustrate the effects of total oxygen concentration and (2) to evaluate the contribution of steel-refractory reaction (in addition to steel-slag reaction) on the rate of MgO pickup in alumina inclusion. The rate of MgO pickup was higher with a lower inclusion concentration. For ladle desulfurization, the extent of MgO pickup in inclusions is directly linked to the extent of desulfurization; both reactions are controlled by the oxygen potential at the steel-slag interface.

Rate of MgO Pickup in Alumina Inclusions in Aluminum-Killed Steel

Kinetic modeling of ladle refining can be used by steel plants to improve steelmaking and to produce cleaner steels. It can also help researchers to understand the process better. There have been several recent attempts to develop a kinetic model that can predict changes in steel, slag, and inclusion compositions with time. Often the models require parameters that can be difficult to measure under plant conditions, and model limitations have not been discussed in detail. In this study, a two-parameter kinetic model has been developed to predict changes in steel, slag, and inclusion compositions during ladle refining; the two parameters are the mass-transfer coefficient in steel and the inclusion flotation rate constant. The model was based on FactSage macro-processing. Examples of results show that the model can be used to diagnose effects of steel and slag sampling practices and to estimate alloy dissolution time. The model results demonstrate that the presence of solids in slag can significantly reduce the rate of steel–slag reaction while maintaining a high inclusion flotation rate. Some limitations of the model are discussed: the overprediction of calcium transfer to alumina inclusions and the absence of information on inclusions originating from entrained slag.

Development of a Reliable Kinetic Model for Ladle Refining

The advancement in computational thermodynamics can help researchers to test their hypotheses regarding complex steelmaking operations in a more quantified manner. The main aim of the current work was to use develop a kinetic model that can predict changes in steel, slag and inclusions during ladle refining and use this model as a tool to develop better understanding of the steelmaking process itself. The important reactions during ladle refining are: steel-refractory reaction, slag-refractory reaction, flotation of inclusions to slag, steel-inclusion reaction, steel-slag reaction and inclusions originating from slag. The chemical reactions between two phases were considered to be mass transfer controlled. The macro-processing feature in FactSage was used to do multiple equilibrium calculations and calculate the change in steel, slag and inclusion composition. Targeted experiments and industrial trials were conducted to find model parameters. For laboratory experiments, the rate of magnesium-transfer to oxide inclusions in steel due to steel-crucible and steel-slag reaction was studied. It was concluded that the presence of spinel layer on MgO crucible at the steel-crucible reaction can help in significantly reduce the rate of Mg pick-up due to steel-crucible reaction. For industrial trials, a comparison between the rate of steel-slag reaction and inclusion flotation rate showed that the steel-slag reaction could be significantly slowed due to slag inhomogeneity. The kinetic model was also used to identify artifacts in steel and slag sampling during ladle refining. One of the main limitations of the kinetic model was the over-prediction of calcium pick-up in steel due to steel-slag reaction. Induction furnace experiments were conducted using MgO, ZrO2 and CaO crucible with different slag composition and silicon concentration to study the extent of calcium pick-up due to steel-slag and steel-crucible reactions. The steel-CaO crucible equilibrium experiment was used to estimate Ca-O interaction parameter. The equilibrated steel was reoxidized with known amount of oxygen to allow all the dissolved calcium to precipitate as oxide inclusions. Inclusion analysis of sample taken after reoxidation was used to estimate dissolved calcium in steel. The measured dissolved calcium was used to estimate Ca-O interaction parameter. A private database for liquid steel was created in FactSage and used for kinetic modeling of laboratory scale steel-slag-crucible experiments. The use of private database for kinetic model helped in avoiding excess calcium pick-up in steel due to steel-slag reaction. However, the model and database should be tested for conditions where significant calcium pick-up is experimentally observed. In the present work, the inclusion removal was assumed to be first order reaction with fixed rate constant. In practice, the inclusion removal is expected to be a more complicated process of agglomeration and flotation. Similarly, the steel-inclusion reactions were considered in equilibrium for each time step of calculation. Sometimes, the composition difference inside single inclusions was found. Some characterization tools were used that could be useful in future to study the agglomeration of inclusions and composition differences inside single inclusion. The agglomeration behavior of inclusions at the steel-argon interface inside confocal laser scanning microscope was compared to the agglomeration in bulk samples from laboratory and industrial steel samples. The size and morphology of inclusion clusters were studied using X-ray micro CT. The composition and morphology of single inclusion was studied using focused ion beam methods: Ga-FIB instrument and plasma-FIB instrument.

Deepoo Kumar

Papers

Modeling Manganese Silicate Inclusion Composition Changes during Ladle Treatment Using FactSage Macros

Calcium Modification of Inclusions via Slag/Metal Reactions

Rate of MgO Pickup in Alumina Inclusions in Aluminum-Killed Steel

Development of a Reliable Kinetic Model for Ladle Refining

Development of a Reliable Kinetic Model for Ladle Refining of Steel