Predicting the alloying element yield in a ladle furnace using principal component analysis and deep neural network

The composition control of molten steel is one of the main functions in the ladle furnace(LF)refining process.In this study,a feasible model was established to predict the alloying element yield using principal component analysis(PCA)and deep neural network(DNN).The PCA was used to eliminate collinearity and reduce the dimension of the input variables,and then the data processed by PCA were used to establish the DNN model.The prediction hit ratios for the Si element yield in the error ranges of±1%,±3%,and±5%are 54.0%,93.8%,and98.8%,respectively,whereas those of the Mn element yield in the error ranges of±1%,±2%,and±3%are 77.0%,96.3%,and 99.5%,respectively,in the PCA-DNN model.The results demonstrate that the PCA-DNN model performs better than the known models,such as the reference heat method,multiple linear regression,modified backpropagation,and DNN model.Meanwhile,the accurate prediction of the alloying element yield can greatly contribute to realizing a“narrow window”control of composition in molten steel.The construction of the prediction model for the element yield can also provide a reference for the development of an alloying control model in LF intelligent refining in the modern iron and steel industry.

Steady State Heat Transfer of Ladle Furnace During Steel Production Process

The heat transfer analysis was performed for an industrial ladle furnace （LF） with a capacity of 55-57 t in Turkey. The heat losses by conduction, convection and radiation from outer and bottom surfaces, top and electrodes of LF were determined in detail. Finally, some suggestions about decreasing heat losses were presented.

Ladle Furnace Temperature Prediction Model Based on Large-scale Data With Random Forest

In ladle furnace, the prediction of the liquid steel temperature is always a hot topic for the researchers. The most of the existing temperature prediction models use small sample set. Today, the precision of them can not satisfy practical production. Fortunately, the large sample set is accumulated from the practical production process. However, a large sample set makes it difficult to build a liquid steel temperature model. To deal with the issue, the random forest method is preferred in this paper, which is a powerful regression method with low complexity and can be designed very quickly. It is with the parallel ensemble structure,uses sample subsets,and employs a simple learning algorithm of sub-models. Then, the random forest method is applied to establish a temperature model by using the data sampled from the production process. The experiments show that the random forest temperature model is more precise than other temperature models.

Mass Balance Modeling for Electric Arc Furnace and Ladle Furnace System in Steelmaking Facility in Turkey

In the electric arc furnace （EAF） steel production processes, scrap steel is principally used as a raw material instead of iron ore. In the steelmaking process with EAF, scrap is first melted in the furnace and then the desired chemical composition of the steel can be obtained in a special furnace such as ladle furnace （LF）. This kind of furnace process is used for the secondary refining of alloy steel. LF furnace offers strong heating fluxes and enables precise temperature control, thereby allowing for the addition of desired amounts of various alloying elements. It also provides outstanding desulfurization at high-temperature treatment by reducing molten steel fluxes and removing deoxidation products. Elemental analysis with mass balance modeling is important to know the precise amount of required alloys for the LF input with respect to scrap composition. In present study, chemical reactions with mass conservation law in EAF and LF were modeled altogether as a whole system and chemical compositions of the final steel alloy output can be obtained precisely according to different scrap compositions, alloying elements ratios, and other input amounts. Besides, it was found that the mass efficiency for iron element in the system is 95.93%. These efficiencies are calculated for all input elements as 8. 45% for C, 30.31% for Si, 46.36% for Mn, 30.64% for P, 41.96% for S, and 69.79% for Cr, etc. These efficiencies provide valuable ideas about the amount of the input materials that are vanished or combusted for 100 kg of each of the input materials in the EAF and LF system.

Corrosion Mechanism of Ladle Furnace Refining Slag to Fired MgO-CaO Bricks

Corrosion effect of ladle furnace （LF） refining slag on fired MgO-CaO bricks with about 34% CaO was studied by static crucible method,and corrosion mechanism was analyzed by techniques of scan electron micrograph,energy dispersive spectrometer,and X-ray diffraction. The results show that：MgO-CaO bricks exhibit excellent corrosion resistance but poor penetration resistance to LF refining slag; oxidation of （Mg·Fe）O in reaction zone results in volume expansion forming cracks; penetration of 2CaO·Fe2O3 （C2F） from slag to MgO-CaO bricks increases liquid phases which accelerates corrosion of the bricks; a protective layer of 2CaO·SiO2 formed on reaction interface prevents penetration of C2F to the bricks.

Rational argon stirring for a 150-t ladle furnace

Based on the principle of similarity, water modeling experiments were carried out for a 150-t ladle furnace. The rational parameters of argon stirring were determined as the optimized positions of nozzles, top area of the porous brick, and gas flow rate. The following results are obtained： 1） the optimized positions of two nozzles are at 0.333R （R refers to the radius of the ladle at bottom） with an angle of 135°; 2） the top diameter of the porous brick should be 130 mm; 3） the flow rate of gas should be 25.0-30.6 m^3/h. The plant trial shows that the improved process is effective in enhancing the cleanliness of round billets. The total oxygen content, microinclusions, and macroinclusions in round billets are reduced by 12.5%, 8.2%, and 20%, respectively.

Improvement of the Structure and the Electromagnetic Characteristics of an Induction Ladle Furnace

Based on a numerical analysis of the alternating electromagnetic field in the process of Steel refining with an induction ladle furnace (ILF), the optimization of the structure of ILF and the electromagnetic field for melting is realized in the present work. The optimization of the ILF by outward extension of inner yokes can decrease the magnitic flux leakage obviously, reduce the eddy current energy loss dramatically and then, decrease the total power consumption.

Numerical modeling of blow refining process of a 300t ladle furnace at Baosteel

Targeting the single tuyere and double tuyere methods of argon blowing for Baosteel＇ s 300 t ladle furnace, the 3D continuity equation, the N-S equation and the turbulent k-ε double-equation were used to model the form of the molten steel flow and the dead areas under six different argon blowing conditions. The different flow field forms and the degree of mixing under different argon blowing methods were compared. The results demonstrate that when large ladles are operated via different methods of argon blowing, the spray from the centre of a single tuyere forms a symmetrical vortex, while when a double tuyere sprays, there is basically no clear vortex. In regards to the amount of argon blowing that will produce the best blend of molten steel, the amount of dead area reduction will not be clearly noticeable if there is an excessive argon blowing amount.

Direct Current Electric Arc-Electroslag Ladle Furnace

In order to solve the high consumption problem of small capacity ladle furnace (LF), the operation principle and control method of the DC are and electroslag heating ladle furnace are introduced. With only one arcing electrode, the distance between the are and the wall of ladle is enlarged, and consequently the consumption of the ladle refractory is decreased. In the invention, a signal electrode is embedded in the refractory lining of the ladle, which contacts directly with the liquid steel and the ladle shell. Two graphite anode ends are submerged in the slag layer. The signal electrode is used as voltage reference during refining process. The electroslag voltage between anode end and liquid steel is applied to control the depth of anode end in the slag layer during the refining process with this ladle furnace.

Research on Refining Technology of Clean Steel in a Plasma Ladle Furnace

The clean steel refining tests carried out in a 100 kg plasma ladle furnace(PLF)were to show the metallurgical effects of the different plasma gases such as Ar-H_2 and Ar-CO_2.The variations of carbon,nitrogen contents in steels and the mechanism of denitrogenation were studied.Compared with the conventional ladle furnace,when the plasma gases were injected into the ladle furnace,there was a decarburization process,the carburetion rates were reduced obviously. The carburetion rate is 3.6×10^(-6) per minute for the steel heated by conventional LF,and is 2.20 and 1.35 times of the heats blown 85%Ar-15%H_2 and 85%Ar-15%CO_2,respectively.When the plasma ladle furnace operated with Ar-H_2 plasma gas, the denitrogenation of the molten steel occurs.The lowest denitrogenation rate is 0.30×10^(-6)per minute when Ar-H_2 gas mixtures were used.The main reactant gas is monatomic hydrogen and the main product of denitrogenation is NH_3 for Ar-H_2 injection.

Multifunctional Refractory-lined Vessel: Ladle Aggregate

A ladle primarily is a container used to transport molten steel from the steelmaking unit to the casting facility.The essential requirements are heat resistant,insulative and strong enough to hold molten steel up to 300 t,with a structure of multilayered refractory lining in a steel shell vessel.When a ladle is assembled with three-phase graphite electrodes,a ladle furnace forms,starting steel refining process with/without the vacuum tank degasser and RH circulating degasser,in order to meet the growing demand on high purity and higher quality steel.The working lining is under aggressive conditions that comprise the chemical reaction with molten steel,the severe corrosion of liquid slag,the disaggregation through oxidation,and the strong stress due to the impacting of the melts and gases and the effects of thermomechanical behaviors.Magnesiacarbon brick is one of the major materials,being indispensable for the slagline of a ladle furnace.Alumina-magnesiacarbon brick has played an important role to substantially increase the service life in the metal zone,from the early lining materials of high alumina and doloma bricks.The permanent lining must assume sufficient responsibility to allow finishing the process of the engaged charge in case of a failure in the working lining.The insulation layer must be as thin as possible in order to maximize the ladle’s capacity,and reduce the shell temperature for saving energy.In this issue,several integrant refractories are reviewed or investigated in order to compile a lining overview,and to contribute a prolonged service life under aggressive working conditions of the ladle furnace.

Application of the sulphide capacity theory on refining slags during LF treatment

Sulphur has been reduced from 0.02wt% to 0.002wt% in 38 min average during 200 t ladle treatment in 2^# steel plant of Capital Steel. The sulphide capacity and equilibrium sulphur distribution of slags are calculated and compared with the measured values. The results show that the KTH model is a useful tool for the prediction of sulphide capacity and sulphur distribution during ladle treatment; the desulphurization reactions are completed nearly in thermo-equilibrium.

Hybrid Modeling for Soft Sensing of Molten Steel Temperature in LF

Aiming at the limitations of traditional thermal model and intelligent model, a new hybrid model is established for soft sensing of the molten steel temperature in LF. Firstly, a thermal model based on energy conservation is described; and then, an improved intelligent model based on process data is presented by ensemble ELM （extreme learning machine） for predicting the molten steel temperature in LF. Secondly, the self-adaptive data fusion is pro- posed as a hybrid modeling method to combine the thermal model with the intelligent model. The new hybrid model could complement mutual advantage of two models by combination. It can overcome the shortcoming of parameters obtained on-line hardly in a thermal model and the disadvantage of lacking the analysis of ladle furnace metallurgical process in an intelligent model. The new hybrid model is applied to a 300 t LF in Baoshan Iron and Steel Co Ltd for predicting the molten steel temperature. The experiments demonstrate that the hybrid model has good generalization performance and high accuracy.

Influence of refining process and utilization of different slags on inclusions, titanium yield and total oxygen content of Ti-stabilized 321 stainless steel

Ti-stabilized 321 stainless steel was prepared using an electric arc furnace, argon oxygen decarburization (AOD) furnace, ladle furnace (LF), and continuous casting processes. In addition, the effect of refining process and utilization of different slags on the evolution of inclusions, titanium yield, and oxygen content was systematically investigated by experimental and thermodynamic analysis. The results reveal that the total oxygen content (TO) and inclusion density decreased during the refining process. The spherical CaO–SiO2–Al2O3–MgO inclusions existed in the 321 stainless steel after the AOD process. Moreover, prior to the Ti addition, the spherical CaO–Al2O3–MgO–SiO2 inclusions were observed during LF refining pro-cess. However, Ti addition resulted in multilayer CaO–Al2O3–MgO–TiOx inclusions. Two different samples were prepared by conventional CaO–Al2O3-based slag (Heat-1) and -TiO2-rich CaO–Al2O3-based slag (Heat-2). The statistical analysis revealed that the density of inclusions and the -TiOx content in CaO–Al2O3–MgO–TiOx inclusions found in Heat-2 sample are much lower than those in the Heat-1 sample. Furthermore, the TO content and Ti yield during the LF refining process were controlled by using -TiO2-rich calcium aluminate synthetic slag. These results were consistent with the ion–molecule coexist-ence theory and FactSage?7.2 software calculations. When -TiO2-rich CaO–Al2O3-based slag was used, the -TiO2 activity of the slag increased, and the equilibrium oxygen content significantly decreased from the AOD to LF processes. Therefore, the higher -TiO2 activity of slag and lower equilibrium oxygen content suppressed the undesirable reactions between Ti and O.

Level 2 Automatic Control System of LF

Research on level 2 control system of 100 tons LF furnace was carried out. According to the principle of energy conservation and principle of mass conservation, the LF temperature prediction model and the composition prediction model were established. At the same time, the set value calculated by heating model and addition model could be sent to PLC. The results show that the technical indexes of LF furnace level 2 control system reach the demand and the system realizes automatic control.