By analysing the factors that affect oxygen consumption during the basic oxygen furnace steelmaking process, a multiple linear regression model for predicting the oxygen blowing quantity was obtained on the basis of actual production data. Additionally, an oxygen balance model for prediction of the oxygen blowing quantity was established on the basis of oxygen balance. These two models were amalgamated to establish an integrated model for prediction of the oxygen blowing quantity. The average relative error of the integrated model is ,1%, and the hit rate of the integrated model is 97?14% when the relative errors of the model are within 5%.Relative to the multiple linear regression and the oxygen balance models, the integrated model may provide a more accurate prediction of the oxygen blowing quantity, and thus represents a good reference point for actual production.

The liquidus temperature of steel is greatly affected by its chemical composition; therefore, the value of the liquidus temperature can vary among different types of steel. In this study, on the basis of the concept of differentiation, the Fe-i binary phase diagram is analyzed using Photoshop image processing software. The effects of eleven common alloying elements (C, Si, Mn, P, S, Ca, Ni, Cu, Cr, Nb, and Mo, whose content is between 0%～4%) on the melting point of pure iron are analyzed. This analysis proves the following assumption to be incorrect: the relationship between the change in liquidus temperature and the content of element i is a linear relationship; this assumption is the basis of traditional liquidus calculation models. A new model for calculating the liquidus temperature of steel is established in this study. As compared to data from other literature, the model proposed in this paper has good generality and the calculation error of the liquidus temperature of steel is between ?3 and 4 °C, which is acceptable. A statistical analysis of the experimental data for different steel grades (obtained from Laiwu Special Steel) using the developed model showed that 87.2% of the absolute deviation values of the temperature are within 4°C. This result shows the model to be both reasonable and credible.

The process model for BOF process can be applied to predict the liquid steel composition and bath temperature during the whole steelmaking process. On the basis of the traditional three-stage decarburization theory, the concept of mixing degree was put forward, which was used to indicate the effect of oxygen jet on decarburization. Furthermore, a more practical process model for BOF steelmaking was developed by analyzing the effect of silicon, manganese, oxygen injection rate, oxygen lance height, and bath temperature on decarburization.Process verification and end-point verification for the process model have been carried out, and the verification results show that the prediction accuracy of carbon content reaches 82.6% (the range of carbon content at the end-point is less than 0.1wt%) and 85.7% (the range of carbon content at end-point is 0.1wt%-0.7wt%) when the absolute error is less than 0.02wt% and 0.05wt%, respectively.

Secondary cooling control is an important factor in the continuous steel casting process. This paper reviews popular control models and analyzes their principles and characteristics. On the basis of the review, this paper pro poses a new concept called ‘‘effective-superheat’’ and a new control model called ‘‘synthetical model dynamic control method based on online temperature measurement.’’ The model, which combines the advantages of the popular models reviewed, not only allows steady, accurate and dynamic control of slab surface temperature, but also provides the temperature profile and the end of the liquid pool. In addition, this paper also discusses the current problems with secondary cooling control and the related development trends, which may be helpful for further development of secondary cooling control technology and informationization of the continuous casting process.