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During continuous casting process, the internal molten steel flow pattern of the mold is one of the important factors affecting the quality of slab products. The application of electromagnetic braking (EMBr) technology in the slab caster provides an effective solution to improve the molten steel flow pattern in the mold. In the current research, one of the commonly used EMBr technology is studied, namely the Ruler-EMBr technology. In detail, the effect of magnetic flux density on the behavior of the molten steel jet flow, heat transfer, and solidification in a 1450 mm × 230 mm slab mold is numerically simulated through a Reynolds-averaged Navier-Stokes (RANS) turbulence model together with an enthalpy-porosity approach. The simulation results indicate that the electromagnetic force generated by the Ruler-EMBr can significantly suppress the diffusion of the impinging jet to the narrow face of the mold with the increase of magnetic flux density. By that, the impact of the upward backflow on the meniscus region in the mold is suppressed. Correspondingly, the uniformity of the temperature distribution in the mold is effectively improved. The parametric studies suggest that the optimized magnetic flux density is 0.3 T to ensure the improvement of steel quality with a casting speed of 1.6 m/min. By applying the magnetic flux density of 0.3 T, the Ruler-EMBr has a better capability to reduce the maximum amplitude of the surface velocity by 24.5% and increase the average surface temperature of the molten steel by 0.25% when compared to the case of No-EMBr. With this electromagnetic parameter, the Ruler-EMBr technology can well prevent the mold flux entrapment and promote solidified shell uniform growth along the casting direction.

Text sentiment analysis is an important natural language processing (NLP) task and has received considerable attention in recent years. Numerous deep-learning based methods have been proposed in previous literature in terms of new deep neural networks (DNN) including new embedding strategies, new attention mechanisms, and new encoding layers. In this study, an alternative technical path is investigated to further improve the state-of-the-art performance of text sentiment analysis. An new effective learning framework is proposed that combines knowledge distillation and sample selection. A dually-born-again network (DBAN) is presented in which the teacher network and the student network are simultaneously trained through an iterative approach. A selection gate is defined to deal with training samples which are useless or even harmful for model training. Moreover, both the DBAN and sample selection are further improved by ensemble. The proposed framework can improve the existing state-of-the-art DNN models in sentiment analysis. Experimental results indicate that the proposed framework enhances the performances of existing networks. In addition, DBAN outperforms existing born-again network.

Electromagnetic braking (EMBr) technology, as one of the most effective technologies in the continuous casting process, provides an effective tool for improving the internal and external defects of steel products. Specifically, the EMBr technology takes the benefit of the generation of Lorentz force to decrease flow instability, mold powder entrapment, and surface defects, if applied properly. For this purpose, to gain a clear understanding of the effect of EMBr technology on the continuous casting process, a commonly used EMBr technology, namely ruler EMBr technology, is applied in the current work to investigate the dynamic behaviors of molten steel flow and steel–slag interface fluctuation inside a slab mold. Furthermore, to obtain a desirable braking effect of the ruler EMBr technology, operational parameters including the magnetic flux density, submerged entry nozzle (SEN) depth, and magnetic pole location are numerically investigated. The results demonstrate that the braking effect exerted by the ruler EMBr device is favorable for suppressing the impact of upward stream on the steel–slag interface with the magnetic flux density exceeding 0.3 T. For the influence of the SEN depth and magnetic pole location on the effect of ruler EMBr mold, the results show that a steady jet flow pattern can be obtained through the adjustment of a location between the ruler EMBr device and the SEN depth. For instance, when the ruler EMBr device installation position of 225 mm corresponds to the SEN depth of 150 mm, the upward deflection of jet stream is suppressed and a stable interface fluctuation profile is formed. With this adjustment, the possibility of mold flux entrapment is decreased.

For the purpose of studying compact strip production (CSP) funnel-shaped mold and flexible thin-slab rolling (FTSR) funnel-shaped mold, a three-dimensional (3D) multi-field coupling mathematical model was established to describe the electromagnetic braking (EMBr) continuous casting process. To investigate the metallurgical effect of EMBr in the CSP and FTSR funnel-shaped thin-slab molds, a Reynolds-averaged Navier–Stokes (RANS) turbulence model, together with an enthalpy–porosity approach, was established to numerically simulate the effect of ruler EMBr on the behaviors of melt flow, heat transfer, solidification, and inclusion movement in high-speed casting. The simulation results indicate that the application of ruler EMBr in the CSP and FTSR molds shows great potential to improve the surface temperature of molten steel and reduce the penetration depth of downward backflow. This contributes to the melting of the slag rim near the meniscus region and facilitates the floating removal of the inclusions in the molten pool. In addition, in comparison with the case of no EMBr, the parametric study shows that the braking effect of ruler EMBr with an electromagnetic parameter of 0.5 T can enhance the upward backflow in the two high-speed thin-slab molds. The enhanced upward backflow can successfully entrain the inclusions to the top of the mold and improve the activity of surface fluctuations to avoid the formation of the slag rim. For instance, for the ruler EMBr applied to the FTSR mold, the maximum amplitude of surface fluctuation and the floatation removal quantity of inclusions with a diameter of 100 mm are increased by 4.6 percent and 51 percent, respectively.