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An Attempt to Visualize the Scrap Behavior in the Converter for Steel Manufacturing Process Using Physical and Mathematical Methods
Lingling CaoQing LiuYannan WangWenhui LinJiankun SunLefei SunWeida Guo
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2018 Volume 59 Issue 11 Pages 1829-1836

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Abstract

The behavior of the scrap is an important factor affecting the transport phenomena in the converter for steel manufacturing process, especially for the performance of a certain heat such as temperature and chemistry composition. However, the observation and evaluation of the scrap behavior is very difficult. In this paper, a physical modeling based on the similarity principle is established for the study of the scrap behavior during converter steelmaking process. Specially-made ice pieces with different shapes and sizes are used to simulate the scrap, and its motion and melting are visualized in a transparent scaled-down model. Moreover, the dynamic melting characteristics of a given ice piece is numerically investigated. It has been indicated that the scrap behavior is closely related to the fluid characteristics in the converter. The enhancement of stirring and mixing can be of importance to the scrap controlling. The scrap with small size is more favorable for the actual production. As for the scrap melting, the shape of scrap is a crucial parameter. The large-size scrap with small specific surface area should be avoided during converter steelmaking process. In addition, more energy is needed when more scraps are charged. The obtained results can provide good references for the actual production.

1. Introduction

The Basic Oxygen Furnace (BOF) steelmaking can rapidly refine molten iron and scrap into liquid steel with a desired carbon content and temperature. Scrap is the second largest source of iron units for steel manufacturing process after hot metal treatment.1) It plays an increasingly significant role in the converter steelmaking process in many developing countries like China.2,3) The scrap has several functions, for example, as coolant to balance excess heat, and it contributes to high steel production rate and decreased CO2 emission.4,5) The behavior of scrap is directly related to the steelmaking performance. For example, unmelted scrap can cause significant problems in the performance of dynamic control,1) which may result in high temperatures or missed chemistries at turndown. Also, the effective utilization of scrap is a serious problem to be solved in the consideration of a new industry structure for optimizing material efficiency and environmental load for production and utilization of materials.6) Therefore, a systematical understanding of the behavior of the scrap in the converter is extremely important.

The behavior of the scrap inside the converter is difficult to observe and measure in unfavorable measuring conditions.7) Numerical simulation, hot model and cold model are the common methods adopted by researchers to estimate the scrap behavior.4,819) Mori et al.8) developed a mathematical model for scrap melting in the steelmaking process based on the concept of simultaneous heat and mass transfer. They predicted that scrap form and size have an effect on the rate-determining mechanism of scrap melting and on the duration of transient heat conduction in the solid scrap. Gol’dfarb et al.9) divided the scrap melting process in the oxygen-converter into four distinct periods, i.e. the freeze of the melt on the surface of the cold material, the melting of the frozen layer, the diffusive melting of the scrap and the melting of the remaining heated solid material. Guthrie et al.10) predicted the melting times of different steel scrap additions made to stagnant pig iron baths operating below the scrap melting temperature range through a mass transfer model. The turbulent natural convection currents were proved to be significant to improve the melting rates. The dissolution rate was also reported to be dependent on the mass transport of the liquid phase.11) Li et al.13,14) systemically investigated the melting kinetics under the condition of single bar, two-bar as well as multibar. A solidified shell was formed around the original bar immediately after it was immersed into the liquid steel during their measurements. This shell and an associated interfacial gap generated between it and the original bar were found to be critical to the melting kinetics. For multibar, the interbar spacing and the initial solid and liquid steel temperatures influence the final melting time by altering the degree of “steel iceberg” formation. Shukla et al.16) analyzed the melting of steel scrap in high temperature liquid iron by cold model experiments. It was found that both heat transfer and mass transfer coefficients can now be estimated by using the experimentally derived correlations for different geometries, for the case of forced convection. Guo et al.17) numerically described the melting of heavy scrap under given conditions in BOF process. The simulations showed that the location of a scrap piece relative to an oxygen jet has a significant influence on the melting time. For slab-type scrap, the thickness is the essential parameter dictating the melting time. The melting process of spherical scrap in hot metal was observed by Sun et al.18) The melting rate of the scrap was found to be increased with increasing carbon in the scrap, carbon in the bath and the bath temperature. Kruskopf19) calculated a melting curve for the scrap piece and the heat and carbon mass exchange between the melt and the scrap by introducing a theoretical basis for scrap melting model. Also a heat transfer correlation for dimensionless Nusselt number was determined by the numerical results. This can be an important part of the process model for BOF. Wang et al.4) presented the possible solutions with simultaneous considerations of steel quality, energy consumption and production cost by the statistical analysis technique. The statistical model can be used for choice of scrap mix, showing the average liquid steel composition in BOF and margin between chosen confidence level and customer allowed upper limit for certain impurities. Moreover, the studies on the solid melting in electric arc furnace,2023) circle furnace24) and rotary furnace2528) can also provide theoretical reference for the scrap melting behavior in BOF steelmaking process. These studies can dramatically propagate our understanding of the melting process of scrap. However, a great deal of detailed work is still desperately needed to fulfill a symmetric description of the dynamic melting of scrap under given conditions during a heat in converter. It is an indispensable component of the accurate dynamic controlling of BOF steelmaking process towards stable and efficient production.

The objective of the present study is giving an attempt to visualize the scrap behavior during the steel manufacturing in an 80 t BOF converter. A physical modeling, based on the similarity principle, was established and the modeling experiments were performed in a transparent model with a size ratio of 1:6 at room temperature. Moreover, the dynamic melting characteristics of a given ice piece was numerically investigated. Both the melting behavior of different ices and mixing behavior in the liquid bath are all illustrated.

2. Model Description

The attempt to visualize the scrap behavior in the converter was implemented by means of physical and mathematical methods. Detailed information can be illustrated as follows.

2.1 Physical model

The motion and melting of steel scrap in high temperature liquid iron were studied by conducting cold model experiments of the motion and melting of different shaped and sized ice pieces ice in a transparent scaled-down model containing water. The concept of model design can be described as follows.

Similarity of fluid flow dynamic: The motion and melting process of the scrap in the converter bath is influenced by the fluid flow behavior around the scrap. Experiments were conducted in a 1/6th scaled 80 t converter model made of Plexiglas. Besides, compressed air was used to simulate the top and bottom blown gas. The following modified Froude number (Fr′) was used to provide the dynamic similitude between the model converter and the prototype one.   

\begin{equation} F_{r}' = \frac{u^{2}\rho_{g}}{gd(\rho_{l} - \rho_{g})} \end{equation} (1)
where u is the velocity of the gas injected into the bath, m/s; d is the characteristic length, m; ρl is the density of the liquid, kg/m3; ρg is the density of the gas, kg/m3; g is the gravity acceleration, m/s2.

The relative parameters for the hydrodynamic model experiments, listed in Table 1, can be obtained based on the similarity theory.

Table 1 Geometrical and operating parameters of the prototype and the model.

Similarity of melting behavior: The melting of the scrap is influenced by the heat transfer between the scrap and the liquid bath. For the cold model experiments, the Phase Transformation number (Ph) was assumed as one of the similarity criteria.16) The Ph number can be expressed as:   

\begin{equation} \text{Ph} = \frac{\Delta H}{C_{\textit{PS}}\cdot \Delta T} \end{equation} (2)
where ΔH is the latent heat of melting, J/kg; CPS is the specific heat of solid, J/(kg·K); ΔT is the superheat, K.

For the ice dimension, the Nusslt number (Nu) similitude is commonly applied to provide the size of the ice.29) The Nu is given by:   

\begin{equation} \mathit{Nu} = \frac{hL}{\lambda} \end{equation} (3)
where h is the heat transfer coefficient, W/(m2·K); L is the characteristic length of the solid, m; λ is the thermal conductivity of the liquid, W/(m·K).

Since pure ice mostly float on the surface of liquid water, ice adopted in the experiments were specially-made with a tailored density by the addition of chemically stable quartz powder. Certain amounts of quartz powder with a particle size of about 600–700 µm were charged during ice-making process. The density of the specially-made ice was controlled around 1.143 g/cm3. Figure 1 displays the geometry of the ice, namely plate, chunk, and cylinder. Moreover, different ices with large, medium and small size were investigated. The detailed geometrical parameters of ice in the experiments can be seen in Table 2.

Fig. 1

Geometry of the ices (a) Plate; (b) Chunk; (c) Cylinder.

Table 2 Geometrical dimension of the specially-made ices.

Figure 2 shows the schematic of the experimental set-up. The dimensions of the converter can be seen in Table 1. The main components of experimental apparatus consist of a 1/6th scaled converter made of plexiglas, a lance with converging-diverging nozzles, removable bottom nozzles, an air compressor, conductivity electrodes, a data collector, etc. The compressed air was injected into the converter model through the top lance and bottom nozzles. The specially-made ice pieces were charged into the room-temperature liquid water at the initial stage. The motion and melting of the ice were observed using a camera. The mixing behavior in the converter bath was estimated by mixing time. In the physical model, two electrical conductivity probes were used to measure the concentration change of the charged saturated KCL solution tracer. The mixing time was defined when the instantaneous tracer concentration was within ±2% of the final tracer concentration in the bath.30)

Fig. 2

Main experimental set-up.

2.2 Mathematical model

The melting process of a specific ice piece was numerically simulated so as to evaluate the dissolution of ice piece under given conditions. An enthalpy-porosity technique3133) was used for modeling the melting process. In this technique, the melt interface is not tracked explicitly. Instead, a quantity called the liquid fraction, which indicates the fraction of the cell volume that is in liquid form, is associated with each cell in the domain. The liquid fraction is computed at each iteration, based on an enthalpy balance. The mushy zone is a region in which the liquid fraction lies between 0 and 1. The mushy zone is modeled as a “pseudo” porous medium in which the porosity decreases from 1 to 0 as the material solidifies. When the material has fully solidified in a cell, the porosity becomes zero and hence the velocities also drop to zero.34) The melting process of small plate shaped ice piece in liquid temperature was simulated in the investigation. Figure 3 presents the computational domain. A cubic volume is selected as the computation zone, and the geometrical dimension is 200 mm × 200 mm × 200 mm.

Fig. 3

Schematic of model geometry.

The enthalpy of the ice piece (H) is computed as the sum of the sensible enthalpy (h) and the latent heat (ΔH):   

\begin{equation} H = h + \Delta H \end{equation} (4)
where $h = h_{\textit{ref}} + \int_{T_{\textit{ref}}}^{T}C_{p} dT$ and href is reference enthalpy, J/kg; Tref is reference temperature, K; Cp is specific heat at constant temperature, J/(kg·K).

The liquid fraction (β) can be defined as:   

\begin{align} \beta = 0\quad & \text{if}\quad T < T_{\textit{solidus}}\\ \beta = 1\quad & \text{if}\quad T > T_{\textit{liquidus}}\\ \beta = \frac{T - T_{\textit{solidus}}}{T_{\textit{liquidus}} - T_{\textit{solidus}}}\quad & \text{if}\quad T_{\textit{solidus}} < T < T_{\textit{liquidus}} \end{align} (5)
where Tsolidus is solidus temperature, K; Tliquidus is liquidus temperature, K.

The latent heat content can now be written in terms of the latent heat of the ice (L):   

\begin{equation} \Delta H = \beta L \end{equation} (6)

Thus, the energy equation of the melting process can be written as:   

\begin{equation} \frac{\partial}{\partial t}(\rho H) + \nabla (\rho\vec{v}H) = \nabla (k\nabla T) + S \end{equation} (7)
where ρ is density, kg/m3; v is fluid velocity, m/s; S is source term.

The calculations were implemented in ANSYS FLUENT 16.2 based on the aforementioned established model.

2.3 Model validation

In order to validate the simulation, the simulated melting behavior of the solid ice was estimated by experimental results of cold model investigations in a water vessel under the same condition.16) The heat transfer coefficient was selected as the parameter to describe the melting behavior. For the ice with plate geometry, the Nusselt number obtained from experiments can be expressed as:16)   

\begin{equation} N_{u} = 0.2947\cdot \textit{Re}^{0.6045}P_{r}^{1/3} \end{equation} (8)
where Nu is Reynolds number; Pr is Prandtl number.

The comparisons between the simulated and measured heat transfer coefficient are presented in Fig. 4. It can be seen that the heat transfer coefficients obtained from numerical simulations are in good agreement with the values obtained from the experiments in the reported literature.16) The heat transfer coefficient at the liquid velocity of 0.1 m/s is about 2839 W·m−2·K−1 derived from the simulation, and the corresponding value obtained from experiment is around 3025 W·m−2·K−1. The deviation may be caused by two reasons. The first one is the experimental errors. In the experiments, the averaged liquid velocity measured by particle imaging velocimetry technique was used to calculate the Re number. This average velocity is a bulk velocity, not the exact velocity in the surface layer of the ice plate which has a velocity gradient when liquid flow over the ice plate. Besides, the representative thickness of the ice plate used for the calculation of the heat transfer coefficient was monitored by a high-speed camera. The refractive issues can cause an error for the measured value. The second reason is the numerical error during the simulations. The presented result of the numerical simulation is a kind of approximate solution. It is not the exact solution of the melting process. The error is also inevitable for the numerical process. Given these two main reasons, it is reasonable to conclude that the validation in this study is satisfactory.

Fig. 4

Heat transfer coefficients obtained from simulation and experiment.

3. Results and Discussions

The behavior of the scrap was investigated using various sized and shaped ice pieces based on the model established above. The transient motion, mixing and melting behavior of the ice pieces were illustrated. The charging amount was designed as 5% by considering convenient observation and energy saving when exploring the influence of dimensional characteristic of ice pieces. The melting time was defined as the time when all the solids dissolved in the liquid. Moreover, the dynamic heat transfer of a given solid ice was numerically simulated.

3.1 Transient behavior of the ice pieces

Due to the fairly sophisticated transport phenomena and the difficulties in direct observation of scrap in the high temperature liquid bath, water model experiments conducted in this study provided us an elementary visualization towards the scrap motion and melting.

The representative transient motion of the ice pieces are presented in Fig. 5. All the ice pieces in the converter bath melted in 78 s. For a specific ice right below the lance (outline was marked by solid line in Fig. 5), this ice piece was hit by the top blown jet at the beginning (t = 1 s) and then moved downward (t = 2 s, t = 3 s). The ice piece then suffered the impaction from the top lance and bottom nozzles simultaneously and gradually moved up after 10 s. The ice pieces go with the flow in the converter and the melting process is taking place at the same time. The transient behavior of the ice pieces shows great agreement with the fluid flow behavior in the liquid bath. Therefore, it can be concluded that the scrap behavior, especially the melting behavior, can be improved by optimized fluid flow behavior in the converter. Relative studies also showed that the heat convective coefficient of liquid/solid interface is dramatically decreased in a dead corner.17) The existence of dead zone in the liquid bath can be a hidden danger for unmelted scrap during actual converter steelmaking production. Enhancing the stirring and mixing performance, therefore, can be of importance to the scrap melting controlling during converter steelmaking process. The mixing characteristics of the liquid bath with different ice pieces will be discussed in the following part.

Fig. 5

Transient motion of ice pieces in the converter bath. (The filled dot represents the body-center of a specific ice; the dashed arrow indicates the moving itinerary of a specific ice)

3.2 Mixing behavior of the liquid bath with various ice pieces

The mixing behavior in the converter is of great significance to the melting of solid scrap as described above. Moreover, different types of scrap in various dimensions are charged into the furnace during steelmaking process. Thus, the mixing effects under different charging ice conditions were assessed.

The mixing behavior of the liquid bath, with different sized and shaped ice pieces, was evaluated as displayed in Fig. 6. It can be seen that the mixing time of the liquid bath decreased with the diminishing of ice sizes for both plate and chunk shaped ice pieces. The mixing time of the liquid bath with large sized plate ice pieces is 44 s, while the value for small plate ice pieces is 40 s. The converter bath with small ice pieces (SC and CYL) achieved better mixing performance. This can be attributed that large sized ice pieces provide more resistance to the fluid transportation in a large region. Besides, the liquid bath charged with chunk and cylinder shaped ice pieces had better mixing performance than that with plate shaped ice pieces. The mixing time for MP and MC charged bath are 42.5 s and 40.2 s respectively. It should be noted that a larger disparity in mixing effect could be expected during converter steelmaking process with more charged solids scrap. Therefore, small sized scraps are more favorable for converter steelmaking process from the standpoint of mixing.

Fig. 6

Mixing behavior of the liquid bath with various ice pieces.

Progressively increasing charging amount of scrap is required for BOF steelmaking process with the increase of the scrap resources.2) Therefore, the influential effect of charging amount of the scrap pieces was investigated subsequently. The mixing characteristics with the initial charging amount of 0, 4%, 5%, and 8.6%, are presented respectively in Fig. 7. It can be concluded that the mixing time in the converter bath is significantly increased with the increase of charging amount of ice pieces. The mixing time with 8.6% charged ice pieces was increased by 76.3% compared to that without ice pieces. In this context, better stirring performance is needed to improve the mixing characteristic in the bath with more charged scrap during converter steelmaking process.

Fig. 7

Mixing behavior of the liquid bath with various charging amount.

3.3 Melting behavior of different ice pieces

Concurrently, the melting behavior of different ice pieces were investigated. The melting behavior with different geometrical ice pieces is shown in Fig. 8.

Fig. 8

Melting behavior with various ice pieces.

Figure 8 shows that smaller sized ice pieces with larger specific surface area have shorter melting time. The melting time of large sized chunk ice pieces is 130 s, which is 50 s longer than that of small sized chunk ice pieces. In addition, the melting time of chunk-shaped ice pieces is distinctly extended compared to that of plate and cylinder shaped ice pieces. The difference can be ascribed to the variation of specific surface area. Taken the large sized plate and chunk for example, the specific surface area of LP ice piece (0.108 m2/m3) was 1.35 times of the LC ice piece (0.080 m2/m3). Consequently, it can be deduced that the shape of the scrap is a crucial parameter affecting the melting time. The shape of the charged scrap should be carefully considered, especially for those heats with the presence the unmelted scrap. Unmelted scrap at tapping may cause serious problems such as slopping in actual production. As observed from the modeling work, large sized scrap with small specific surface area should be avoided to stable production during BOF steel manufacturing process.

The melting behavior under different charging amount of ice pieces is presented in Fig. 9. The melting time under different conditions were 0 s, 85 s, 95 s and 234 s, respectively. The melting time almost tripled when the charging amount of ice increased from 4% to 8.6%. Large temperature drop, of course, took place at the same time. This may increase the possibility of unmelt scrap during actual production. It provides useful references for actual BOF production, especially for the current steelmaking production with increasing scrap amount. Therefore, more energy is required to improve the mixing effect and to compensate for temperature losses when increasing the charging amount of scrap during converter steelmaking process.

Fig. 9

Melting behavior with various charging amount.

3.4 Dynamic melting process of solid ices

The motion, mixing and melting behavior with various charged ice pieces were studied as described above. The melting process of a specific ice piece in liquid water was then numerically simulated to explore the dynamic melting characteristics under given conditions. The ice with plate geometry was studied as an example in this investigation.

The dynamic melting characteristics of a small plate shaped ice were simulated at different liquid temperatures and velocities. The melting process of the ice in still water with different temperatures is shown in Table 3. The melting process was accelerated by increasing the temperature of the surrounded water. The melting process lasted about 33.69 s (T = 293 K), and the value was 17.30 s when the liquid temperature increased to 333 K which was almost reduced by half. The melting process was almost uniform in different directions. Therefore, increasing the heat of liquid can be an effective way to improve the solid melting characteristics during converter steelmaking process. Thermal compensation technology, in this context, should be taken into consideration for BOF steel manufacturing process.

Table 3 Dynamic melting characteristics at different liquid temperatures (v = 0 m·s−1).

So as to investigate the influence of surrounded water on the melting process of the solid ice, different initial velocities were imposed on the liquid water in Y direction ranging from 0.1 m·s−1 to 0.5 m·s−1. The dynamic melting characteristics at different liquid velocities are presented in Table 4. Moreover, the melting process was prominently accelerated by improving the fluid status, especially in Y direction. The melting time declined by approximately 90% when the fluid velocity increased from 0.1 m·s−1 to 0.5 m·s−1. This can be another persuasive evidence to the close relation between the mixing and melting behavior in the converter bath. Favourable transport condition in the liquid bath is a prerequisite to obtain a satisfactory scrap melting effect in the converter. Reducing the dead zone can be a practical method in scrap controlling during BOF steel manufacturing.

Table 4 Dynamic melting characteristics at different liquid velocities (T = 300 K).

4. Conclusions

An attempt to visualize the scrap behavior in an 80 t converter for the steel manufacturing process was implemented by means of physical and mathematical methods. Specially-made ice pieces with different shapes and sizes were used to simulate the scrap, and their motion and melting behavior were visualized in a transparent 1/6th scaled-down model. The dynamic melting characteristics of a given solid ice was also numerically investigated. The main conclusions are summarized as follows:

  1. (1)    The scrap behavior is closely related to the fluid characteristics in the converter. The melting time of a small plate ice piece declines by approximate 90% when the fluid velocity increases from 0.1 m·s−1 to 0.5 m·s−1. Enhancing the stirring and mixing performance can be an important part for the scrap controlling.
  2. (2)    Small-sized scraps are more favorable for the actual converter steelmaking process from the standpoint of mixing. The mixing effect is also greatly influenced by the charging amount. The mixing time increases by 76.3% when increasing the charged ice pieces by 8.6%. Better stirring performance is needed to improve the mixing effect in the heats with more charged scraps.
  3. (3)    The scrap shape is a crucial parameter affecting the melting time. Large sized scrap with small specific surface area should be avoided during BOF steel manufacturing. The melting time almost triples when the charging amount of ices increase by 4.6%. More energy is required to improve the mixing effect and to compensate for temperature losses.

Acknowledgments

The financial support from Doctoral Fund of Ministry of Educations of China (No. 20120006110036) and Jiangxi Provincial Department of Science and Technology (20171ACE50020) are highly acknowledged. Lingling Cao and Yannan Wang also want to thank the support of the China Scholarship Council (CSC).

REFERENCES
 
© 2018 The Japan Institute of Metals and Materials
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