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A mathematical model was developed to investigate the refining process through using slot-porous matched dual tuyeres. In this model, the bubble expansion is considered through the ideal gas state equation. The density variation of bubbles is calculated through the mass conservation equation. The coalescence and breakup of bubbles are tracked using the discrete particle model (DPM). The transient flow is computed through the k-ε model with three continuous phases (air–slag–steel). Comparisons were made between traditional porous–porous and the new slot–porous tuyeres, mainly focusing on the mixing behavior and inclusion removement ratio. The results show that, for traditional porous–porous matched tuyeres (P-P mode), the inclusion removement ratio is 34.14%; by comparison, after employing the slot–porous matched tuyeres (S-P mode), the inclusion removements ratio rises to 36.34%. The mixing time is also shortened by 18.74% by using the S-P mode. The reason for this phenomenon is because the slot tuyere produces a strong asymmetry that drives more liquid at the bottom of the ladle. The new tuyere match takes advantage of porous and slot tuyeres, and the mixing behavior and inclusion removements are improved. The result is beneficial for future refining.

The influence of Ca treatment, Mg treatment and Ca–Mg combined treatment on the inclusions in 45MnVS non-quenched and tempered steel were studied in the present work. After the melting experiment, a hot rolling test was carried out on the steel ingot. Additionally, the composition, quantity and morphology of inclusions in the test steel samples were analyzed by automatic scanning electron microscopy (ASPEX) and an energy dispersive X-ray spectrometer connected to scanning electron microscope (SEM-EDS). The results indicated that the inclusions in 45MnVS steel mainly consisted of a large amount of sulfides and a small amount of oxides. Sulfide inclusions could be nucleated and precipitated using oxides as a core during solidification. The proportion of spindle-shaped inclusions in sulfide with smaller sizes was higher. The sizes of MnS–oxide inclusions were larger than those of MnS. After hot rolling, the proportion of spindle-shaped MnS and complex sulfides with oxide cores in the samples was increased significantly. Compared with Ca treatment and Ca–Mg treatment, more oxides were formed in the steel with Mg treatment, which can in turn become the cores for sulfide nucleation and precipitation. Thus, the proportion of MnS–oxide inclusions in steel increased. Compared with Ca treatment and Mg treatment, steel with Ca–Mg treatment was more conducive to the formation of complex sulfides, and increased the proportion of spindle-shaped sulfides in 45MnVS steel. After Ca treatment, Mg treatment and Ca–Mg combined treatment, the proportions of spindle-shaped sulfides in steel were 23.31%, 19.39% and 43.24%, respectively.

Utilization of CO2 in steelmaking process has attracted extensive attention in recent years, not only because of its social benefits, but also its better metallurgical performance. Mixing CO2 with O2 blown by converter oxygen lance is gradually being adopted by steelmaking plants, due to its potential of reducing consumption and improving steel quality. In the present research, effect of mixing CO2 on the jet characteristics of a four-nozzle oxygen lance was studied in detail by numerical simulation, taking the combustion behavior between supersonic jets and ambient atmosphere into consideration innovatively. The simulated results showed that the combustion flame is mainly distributed in the region between multiple jets, and the high temperature flame has a noticeable influence on the low-velocity region of the jet. Due to the dilution effect of CO2, mixing CO2 into the oxygen jets will reduce the maximum temperature of the flame and slow down the combustion rate. With the increase of CO2 mixing ratio, the high-temperature zone of combustion flame moves away from the lance tip significantly. At the same distance from the nozzle, although mixing CO2 can hardly increase the velocity magnitude of the jet, but it can achieve higher dynamic pressure, indicating stronger impacting power. Then the industrial experiment of top blowing O2-CO2 was carried out in a 120-ton converter. During the blowing time of 120~300 s, the mixing ratio of CO2 was 15 vol.% for better dephosphorization, and no CO2 was mixed in the rest time of blowing. Due to the stronger stirring and better thermodynamics, the average [P] content in the final molten steel was decreased from 0.0155 wt.% to 0.0129 wt.%, achieving higher dephosphorization efficiency.

MgO addition plays an essential role in the blast furnace smelting process, including softening-melting characteristics and metallurgical properties of slag. In the present study, the effect of MgO distribution on the softening-melting characteristics and slag system of vanadium-titanium magnetite burden were explored by simulating BF conditions. The results show that the MgO flux addition significantly affects the crystallization temperature of slag-phase, the precipitated phase components, and slag viscosity. This indicates that appropriate MgO addition can improve the metallurgical properties of blast furnace slag effectively, thereby improving the softening-melting-dripping performance of the mixed burden. The V-Ti pellets with a MgO content higher than 2.40 wt% exhibit optimum metallurgical properties. With a constant MgO content in mixed burden, the softening-melting properties of composite burden could be improved effectively as the MgO partitioning scheme includes 1.90 wt% MgO in sinter and 3.02 wt% MgO in pellet.

The cleanness of steel has always been a big problem for secondary refining. In this work, a new method, which is coupled with slot and porous plugs, is proposed to improve the cleanness in steel. Water experiments and numerical simulations were performed to study this effect. Results revealed that when using slot-porous plugs, the flow field was obviously asymmetrical, and the circulation flow was pushed towards the porous side. Then, the removement of inclusions was increased to about 22.7% percent, comparing with traditional two-slot bottom stirring and reducing the dead zone area near the bottom of the ladle; however, the mixing time delay was 16%, comparing with traditional plugs. Then, in order to explain the reason for these phenomena, we established a mathematical model through large eddy simulation and discrete particle modeling (DPM). Results shows that the asymmetry flow field awoke the recirculation flow downwards after using slot-porous plugs, which would homogenize the flow at the bottom, promoting floating in steel. What is more, the velocity near the free surface was lowered; therefore, it could also stabilize the surface velocity as well, which is also beneficial for removing inclusions as well.

Considering solidification, a large eddy simulation (LES) model of two-phase flow was established to simulate the thermal–magnetic flow coupled fields inside a jumbo bloom. The magnetic field was calculated based on Maxwell’s equations, constitutive equations, and Ohm’s law. An enthalpy–porosity technique was used to model the solidification of the steel. The movement of the free surface was described by the volume of fluid (VOF) approach. With the effect of electromagnetic stirring (MEMS), the vortices in the bloom tended to be strip-like; large vortices mostly appeared in the injection zone, while small ones were found near the surface of the bloom. It is newly found that even though the submerged entry nozzle (SEN) is asymmetrical about the bloom, a biased flow can also be found under the effect of MEMS. The reason for this phenomenon is because the magnetic force is asymmetrical and transient. A high frequency will reduce the period of biased flow; however, the frequency should not be too high because it could also intensify meniscus fluctuations and thus entrap slag droplets in the mold. The velocity near the solidification front can also be increased with a higher frequency.

Secondary aluminum dross is a byproduct of the electrolytic aluminum industry, whose main components are Al2O3, AlN and Na3AlF6. Secondary aluminum dross is a type of hazardous waste, with a tremendous yield every year. Realizing the harmless treatment or resource utilization of secondary aluminum dross has important economic and social benefits. In the present research, the process of preparing premelted calcium aluminate slag used for molten steel refining from secondary aluminum dross was studied in detail. Firstly, the chemical composition and phase component of secondary aluminum dross were analyzed systematically. Then, according to phase diagram analysis and melting point measurement, the appropriate mixing ratio of CaO and secondary aluminum dross and the appropriate calcination temperature were determined. On this basis, an experiment of premelted calcium aluminate slag preparation was carried out in a tubular resistance furnace. The phase component and micromorphology of the premelted slag were analyzed by XRD and SEM. The results show that the main component of the premelted calcium aluminate slag is 11CaO·7Al2O3·CaF2 phase with a low melting point. The original Na3AlF6 phase, which is the cause of leachable fluoride in secondary aluminum dross, disappears totally, and there is no water-soluble fluoride detected in the leaching toxicity detection. The research indicates that the process of preparing premelted calcium slag from secondary aluminum dross is feasible, which provides a helpful reference for the resource utilization of secondary aluminum dross.

During the process of electroslag remelting (ESR) of steel containing titanium and aluminum, the activity ratio between titania and alumina in CaF2-CaO-MgO-Al2O3-TiO2 slag must be fixed in order to guarantee the titanium and aluminum contents in the ESR ingots. Under the condition of fixed activity ratio between titania and alumina in the slag, the melting temperature of slag should be investigated to improve the surface quality of ESR ingots. Therefore, this paper focuses on finding a kind of slag with low melting temperature that can be used for producing steel containing titanium. In the current study, the thermodynamic equilibrium of 3[Ti] + 2(Al2O3) = 4[Al] + 3(TiO2) between SUS321 steel and the two slag systems (CaF2:MgO:CaO:Al2O3:TiO2 = 46:4:25:(25 − x):x and CaF2:MgO:CaO:Al2O3:TiO2 = 46:4:(25 − 0.5 x):(25 − 0.5 x):x) are studied in an electrical resistance furnace based on Factsage software. After obtaining the equilibrium slag with fixed activity ratio between titania and alumina, the melting temperatures of the two slag systems are studied using slag melting experimental measurements and phase diagrams. The results show that the slag systems CaF2:MgO:CaO:Al2O3:TiO2 = 46:4:25:(25 − x):x, which consists of pre-melted slag S0 (CaF2:MgO:CaO:Al2O3 = 46:4:25:25) and pre-melted slag F1 (CaF2:MgO:CaO:TiO2 = 46:4:25:25), can not only control the aluminum and titanium contents in steel, but also have the desired low melting temperature property.

Concentrating the chromium in chromium slag and improving the chromium–iron ratio is beneficial for the further utilization of chromium slag. In this paper, chromium slag obtained from a chromite lime-free roasting plant was used as the raw material. Pellets made of the chromium slag and pulverized coal were reduced at different pre-reduction temperatures and then separated by a melting separation process or magnetic separation process, respectively. The mass and composition of the metallized pellets before separation, along with the alloy and tail slag after separation, were comprehensively analyzed. The experimental results showed that the output yield of alloy, iron recovery rate, and chromium content in the alloy were all higher when using melting separation than when using magnetic separation, because of the further reduction during the melting stage. More importantly, a relatively low pre-reduction temperature and selection of magnetic separation process were found to be more beneficial for chromium enrichment in slag; the highest chromium–iron ratio in tail slag can reach 2.88.

Silicon-based anode materials are considered one of the highly promising anode materials due to their high theoretical energy density; however, problems such as volume effects and solid electrolyte interface film (SEI) instability limit the practical applications. Herein, silicon nanoparticles (SiNPs) are used as the nucleus and anatase titanium dioxide (TiO2) is used as the buffer layer to form a core-shell structure to adapt to the volume change of the silicon-based material and improve the overall interfacial stability of the electrode. In addition, silver nanowires (AgNWs) doping makes it possible to form a conductive network structure to improve the conductivity of the material. We used the core-shell structure SiNPs@TiO2/AgNWs composite as an anode material for high-efficiency Li-ion batteries. Compared with the pure SiNPs electrode, the SiNPs@TiO2/AgNWs electrode exhibits excellent electrochemical performance with a first discharge specific capacity of 3524.2 mAh·g−1 at a current density of 400 mA·g−1, which provides a new idea for the preparation of silicon-based anode materials for high-performance lithium-ion batteries.

RGBD salient object detection, based on the convolutional neural network, has achieved rapid development in recent years. However, existing models often focus on detecting salient object edges, instead of objects. Importantly, detecting objects can more intuitively display the complete information of the detection target. To take care of this issue, we propose a RGBD salient object detection method, based on specific object imaging, which can quickly capture and process important information on object features, and effectively screen out the salient objects in the scene. The screened target objects include not only the edge of the object, but also the complete feature information of the object, which realizes the detection and imaging of the salient objects. We conduct experiments on benchmark datasets and validate with two common metrics, and the results show that our method reduces the error by 0.003 and 0.201 (MAE) on D3Net and JLDCF, respectively. In addition, our method can still achieve a very good detection and imaging performance in the case of the greatly reduced training data.