Evolution of the Numerical Model Describing the Distribution of Non-Metallic Inclusions in the Tundish

Merder, T.; Pieprzyca, J.; Warzecha, M.; Warzecha, P.; Hutny, A.

doi:10.3390/ma14092229

Cited by 10 publications

(10 citation statements)

References 39 publications

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“…These compounds are a consequence of the introduction of metals and ferroalloys in the form of complex deoxidants, resulting in the formation of a liquid or solid-liquid non-metallic phase. The function of the deoxidant in steel is usually played by silicon, manganese, and aluminium, and therefore it is possible to form a liquid phase containing their oxides and also iron oxide [ 23 , 24 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ].…”

Section: Methodsmentioning

confidence: 99%

Evolution of Chemical Composition and Modeling of Growth Nonmetallic Inclusions in Steel Containing Yttrium

et al. 2021

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The programs WYK_Stal and Bi-Growth, developed at AGH-UST, Kraków, Poland, were used for simulating the refining process, the formation of non-metallic inclusions, and their growth. The Fe-Y-Al-O-S-Ca system in pre-oxidized steel was analyzed, where yttrium formed precipitates from both O and S. When first Al and second Y were added to steel, the proportion of Al2O3 inclusions remained constant. This resulted in higher yttrium losses for oxide formation, whereas the sulfur content promoted sulfide phase formation. The introduction of yttrium at the end of refining contributed to reducing the consumption of this element in the non-metallic phase formation. The addition of aluminum and then calcium were sufficient to achieve a high degree of deoxidation and desulfurization. Calculations performed with WYK_Stal for both (a) and (c) versions of the model showed that the sulfide phase was constituted by CaS and FeS (model c) and CaS (model (a)). The participation of the calcium sulfide phase turned out to be dominant in the inclusions. Their presence was also identified in the slag phase. Simulations of the growth of complex oxide and oxo-sulfide inclusions using the Bi_Growth program showed that the yttrium content of the steel has a decisive role in the formation of complex oxide inclusions and the final oxygen content of the steel. In contrast, for the growth of oxide-sulfide inclusions, the character of growth is determined by the sulfur content of steel.

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Section: Methodsmentioning

confidence: 99%

Evolution of Chemical Composition and Modeling of Growth Nonmetallic Inclusions in Steel Containing Yttrium

et al. 2021

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“…Coefficient Aij is a quantity dependent on the supersaturation defined by the difference between the current and equilibrium yttrium concentration in steel and the reaction rate constant kij. An assumption was made that Aij>0, which means that a deficiency in any of the components terminates the growth process of a given precipitate, but neither terminates the growth process of the entire precipitate, nor the dissolution of the particles [5]:…”

Section: Bicomponent Nucleus Growth Model (Bi-growth)mentioning

confidence: 99%

Rem-O-S Compound inclusions growth model

Gerasin

Kalisz

2022

METAL 2022 Conference Proeedings

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The program Bi-Growth were used for simulating the formation of non-metallic inclusions (REM-O-S), and their growth. In the process of refining, the non-metallic inclusions are heterogeneous and create a mixture of different oxides or oxides and sulfides. These compounds are a consequence of the introduction of metals and ferroalloys in the form of complex deoxidants. The current work proposes a solution to the bi-growth of oxide and sulfide precipitates by focusing on the formation of precipitates after introducing REM to steel. Because high mixing energies are used during refining, the role of reactant diffusion into the reaction zone was neglected, and the system was treated as perfectly homogeneous in terms of chemical composition. Each precipitate was assumed to grow only on its surface, e.g REMxOy. In this case, the particle growth rate was found to depend solely on the concentration of all three components (REM,O,S).

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“…In addition, their distribution characteristics and local concentrations can be reflected with a high accuracy. Sheng et al [ 21 ] applied a CFD model to study the effect of thermal buoyancy on fluid flow and residence time distribution in a single-strand tundish. The results showed that thermal buoyancy has a significant impact on the flow pattern and temperature distributions of molten steel in the tundish.…”

Section: Introductionmentioning

confidence: 99%

Effect of Flow Field Optimization of an Asymmetric Multi-Strand Tundish on the Quality Consistency of Cracking Con-Rod Steel

et al. 2022

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Cracking con-rod is an advanced high-precision connecting structure based on brittle expansion, breaking and reconnection of steel, to solve the problem of assembly circle missing. High carbon micro-alloyed steel C70S6, as a dominant material for the production of cracking con-rod, has extremely strict requirements on non-metallic inclusions in steel and microstructure stability. Continuous casting tundish plays an important role in removing large-sized inclusions and stabilizing casting quality. Aiming at the inconsistent casting quality of C70S6 steel produced by a three-strand asymmetric tundish and the frequent occurrence of slag entrapment problems in Xining Special Steel, the tundish structure was optimized by means of physical modelling combined with numerical simulation, and the quality of the bloom castings and subsequent hot-rolled products before and after optimization were compared based on volume production. The results show that a new flow control design to the tundish can effectively improve the consistency of its metallurgical effect for each of the three strands and the following overall product quality, in which the flow field and temperature field in the tundish are more uniform. This is due to the adoption of a vortex inhibitor and an optimized wall structure according to the measured RTD curve, ink trajectory and numerical simulation on the 3-D streamline contours and temperature distribution in the tundish. The peak concentration of outlet 1 is decreased from 6.5 before optimization to less than 2.0 after optimization, which means the elimination or alleviation of the local short-circuit flow. The maximum temperature difference of C70S6 molten steel measured at the outlets of the tundish three strands is decreased from 2–5 °C to 1–3 °C, which is in good agreement with the numerical simulation results. The difference in columnar crystal ratio of the corresponding bloom castings is decreased from 2.27–3.17% to 1.26–1.85%, and the consistency of central carbon segregation index is also significantly improved. In addition, the difference in oxygen content among the three strand blooms is decreased from 1.7–3.5 ppm to 0.8–1.9 ppm. As a result, the overall mechanical properties and microstructure stability of the hot-rolled products are improved statistically, in which the hardness fluctuation is decreased from 84 HBW to 60 HBW, the inclusion grade of types B + C + D + Ds is reduced to 1.105, and the occurrence rate of Ds dropped to 0.118%. Accordingly, the failure rate of the cracking con-rod is controlled stably within 4‰, and the fracture is generally smoother than that before tundish optimization. In summary, the flow field optimization to a multi-strand asymmetric tundish has a clear effect on improving the overall quality of its bloom castings and rolled products, which should be paid more attention industrially. Meanwhile, the present study provides a reliable theoretical and experimental reference for the improvement of metallurgical effects of an asymmetric-typed tundish commonly used in special steel production.

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Evolution of the Numerical Model Describing the Distribution of Non-Metallic Inclusions in the Tundish

Cited by 10 publications

References 39 publications

Evolution of Chemical Composition and Modeling of Growth Nonmetallic Inclusions in Steel Containing Yttrium

Evolution of Chemical Composition and Modeling of Growth Nonmetallic Inclusions in Steel Containing Yttrium

Rem-O-S Compound inclusions growth model

Effect of Flow Field Optimization of an Asymmetric Multi-Strand Tundish on the Quality Consistency of Cracking Con-Rod Steel

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