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 ele...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.展开更多
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...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.展开更多
Clean steel encompasses a multitude of concepts that are based on fulfilling customer requirements and can be produced in many ways depending on the existing equipment and detailed customer demands.A common feature of...Clean steel encompasses a multitude of concepts that are based on fulfilling customer requirements and can be produced in many ways depending on the existing equipment and detailed customer demands.A common feature of all clean steel production is tight process control along with continuous monitoring.To meet an increasing demand for cold-rolled(CR)steel sheets of improved mechanical properties,and to cope with the change of the annealing process from a batch-type to a continuous process,it is necessary to establish a technique for making ultralow carbon(ULC)steel with a C-concentration lower than 20 ppm for the steelmaking process associated with a major challenge to guarantee the competitiveness with observance of environmental requirements.Steel ladle lining plays an important role on the energy consumption during the production and the refractory lining design contributes to minimize thermal bath loss,carbon pick up and shell temperature.A new generation of unfired zero carbon refractories was developed with two specific approaches:(1)replacement of firing bricks reducing CO_(2) footprint and(2)replacement of carbon containing with performance increasing.Bricks can be used in working and safety linings with a unique microstructure with better heat scattering and similar thermomechanical properties.This work presents customers’performance compared to traditional products highlighting energy savings.展开更多
In the prediction of the end-point molten steel temperature of the ladle furnace, the influence of some factors is nonlinear. The prediction accuracy will be affected by directly inputting these nonlinear factors into...In the prediction of the end-point molten steel temperature of the ladle furnace, the influence of some factors is nonlinear. The prediction accuracy will be affected by directly inputting these nonlinear factors into the data-driven model. To solve this problem, an improved case-based reasoning model based on heat transfer calculation(CBR-HTC) was established through the nonlinear processing of these factors with software Ansys. The results showed that the CBR-HTC model improves the prediction accuracy of end-point molten steel temperature by5.33% and 7.00% compared with the original CBR model and 6.66% and 5.33% compared with the back propagation neural network(BPNN)model in the ranges of [-3, 3] and [-7, 7], respectively. It was found that the mean absolute error(MAE) and root-mean-square error(RMSE)values of the CBR-HTC model are also lower. It was verified that the prediction accuracy of the data-driven model can be improved by combining the mechanism model with the data-driven model.展开更多
文摘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.
文摘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.
文摘Clean steel encompasses a multitude of concepts that are based on fulfilling customer requirements and can be produced in many ways depending on the existing equipment and detailed customer demands.A common feature of all clean steel production is tight process control along with continuous monitoring.To meet an increasing demand for cold-rolled(CR)steel sheets of improved mechanical properties,and to cope with the change of the annealing process from a batch-type to a continuous process,it is necessary to establish a technique for making ultralow carbon(ULC)steel with a C-concentration lower than 20 ppm for the steelmaking process associated with a major challenge to guarantee the competitiveness with observance of environmental requirements.Steel ladle lining plays an important role on the energy consumption during the production and the refractory lining design contributes to minimize thermal bath loss,carbon pick up and shell temperature.A new generation of unfired zero carbon refractories was developed with two specific approaches:(1)replacement of firing bricks reducing CO_(2) footprint and(2)replacement of carbon containing with performance increasing.Bricks can be used in working and safety linings with a unique microstructure with better heat scattering and similar thermomechanical properties.This work presents customers’performance compared to traditional products highlighting energy savings.
基金financially supported by the National Natural Science Foundation of China (No.51674030)the Fundamental Research Funds for the Central Universities (Nos.FRF-TP-18-097A1 and FRF-BD-19-022A)。
文摘In the prediction of the end-point molten steel temperature of the ladle furnace, the influence of some factors is nonlinear. The prediction accuracy will be affected by directly inputting these nonlinear factors into the data-driven model. To solve this problem, an improved case-based reasoning model based on heat transfer calculation(CBR-HTC) was established through the nonlinear processing of these factors with software Ansys. The results showed that the CBR-HTC model improves the prediction accuracy of end-point molten steel temperature by5.33% and 7.00% compared with the original CBR model and 6.66% and 5.33% compared with the back propagation neural network(BPNN)model in the ranges of [-3, 3] and [-7, 7], respectively. It was found that the mean absolute error(MAE) and root-mean-square error(RMSE)values of the CBR-HTC model are also lower. It was verified that the prediction accuracy of the data-driven model can be improved by combining the mechanism model with the data-driven model.
