Simulation of Microstructure of As-cast Steels in Continuous Casting

Louhenkilpi, Seppo; Miettinen, Jyrki; Holappa, Lauri

doi:10.2355/isijinternational.46.914

Cited by 37 publications

(41 citation statements)

References 5 publications

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“…Within the plateau, the scatter of the experimental measurements is higher than in the columnar region (the scatter bars are not reported to avoid undue confusion in the graphs), because λ1 and λ2 are more difficult to define there. 8) As already observed, 7,8) this behaviour can be attributed to the transition from columnar to equiaxed growth (CET). This result is in agreement with the experimental measurements of the position of the CET listed in Table 2 ( Fig.…”

Section: Heat Transfer Modelmentioning

confidence: 69%

“…Two sections for each product were investigated with the aim of revealing their dendritic microstructures. For this, the samples were etched with the following solution: 8) 4 g FeCl3, 0.3 g CuCl2, 0.4 ml HCl, 50 ml H2O. The etching duration was in the range of 30 to 60 s. Figure 1 shows an example of the dendritic morphology in the case of the round with a diameter of 280 mm.…”

Section: Materials and Experimental Methodsmentioning

confidence: 99%

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Modeling Solidification Microstructures of Steel Round Billets Obtained by Continuous Casting

et al. 2011

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The knowledge of the position of the columnar to equaxial transition (CET) is of paramount importance to evaluate the internal quality of continuous casting (CC) products. One way to control the operational CC conditions with the objective of assuring a given quality level is to develop a numerical program able to calculate the local solidification rate (R), the local thermal gradient (G) and the local time of solidification (tf) and to relate these parameters to the CET by means of a predictive model. In the present investigation, the dendritic morphology and the CET transition of three round billets made of a low carbon steel (0.14%C) and produced by CC are characterized, and a computer model is developed to evaluate the R, G and tf-parameters. Referencing the well-known CET transition model developed by Hunt, a simple prediction equation is thus obtained for the steel under study and it is used to propose guidelines for the optimization of the CC operational parameters.

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Section: Heat Transfer Modelmentioning

confidence: 69%

Section: Materials and Experimental Methodsmentioning

confidence: 99%

Modeling Solidification Microstructures of Steel Round Billets Obtained by Continuous Casting

et al. 2011

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“…Louhenkilpi reported a similar variation trend of shell thickness. 20) Differentiation of the liquidus temperature line and solidus temperature line were illustrated in Fig. 4.…”

Section: Solidus Temperature Line and Liquidus Tempera-mentioning

confidence: 99%

A Simple Model to Calculate Dendrite Growth Rate during Steel Continuous Casting Process

Long

Zhang

2010

ISIJ Int.

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“…15) Therefore, heat conduction equation reduces to the following form For metallic alloys at the range of temperatures where solidification occurs, the physical properties will be evaluated using following equations Usually to consider of the liquid flow effect on the thermal field, an effective thermal conductivity is employed in the liquid zone. 12,[17][18][19] the effective thermal conductivity depend on the some operational parameters such as electromagnetic mold stirrer conditions, geometrical shape and size of submerged entry nozzle and the amount of superheat. In the present semi-analytical model the simple suggestion of Louhenkilpi et al 19) was used which is an increase of two times for the conductivity of the liquid for bloom with electromagnetic stirrer.…”

Section: Numerical Simulation Of Solidificationmentioning

confidence: 99%

“…12,[17][18][19] the effective thermal conductivity depend on the some operational parameters such as electromagnetic mold stirrer conditions, geometrical shape and size of submerged entry nozzle and the amount of superheat. In the present semi-analytical model the simple suggestion of Louhenkilpi et al 19) was used which is an increase of two times for the conductivity of the liquid for bloom with electromagnetic stirrer.…”

Section: Numerical Simulation Of Solidificationmentioning

confidence: 99%

A New Semi-analytical Model for Prediction of the Strand Surface Temperature in the Continuous Casting of Steel in the Mold Region

2008

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In this research, a new semi-analytical model is presented for the strand surface temperature in the continuous casting of steel. Firstly with a dimensional analysis approach a general relation between the strand surface temperature and the other effective variables such as conductivity of the steel, pouring temperature, casting velocity, distance from the meniscus, volume rate of cooling water, solidus temperature and heat flux density at the meniscus is deduced. The constants appeared as coefficients or powers of variables in presented relation were computed by a numerical simulation of continuous casting for a breakout bloom. The resulted semi-analytical model for strand surface temperature was extended to predict the solidified shell thickness. The resulted semi-analytical model was validated with comparison to experimental, analytical and numerical results of slab, billet and bloom and good agreement was seen. The new presented model at this research is in versus of controllable parameters and specifications of the mold and it can be used for design of a process control system for continuous casting of slab, billet and bloom.

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Simulation of Microstructure of As-cast Steels in Continuous Casting

Cited by 37 publications

References 5 publications

Modeling Solidification Microstructures of Steel Round Billets Obtained by Continuous Casting

Modeling Solidification Microstructures of Steel Round Billets Obtained by Continuous Casting

A Simple Model to Calculate Dendrite Growth Rate during Steel Continuous Casting Process

A New Semi-analytical Model for Prediction of the Strand Surface Temperature in the Continuous Casting of Steel in the Mold Region

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