CFD study on the effect of the oxygen lance inclination angle on the decarburization kinetics of liquid steel in the EAF

In Electric Arc Furnace (EAF) steelmaking the main chemical reaction is the decarburization reaction. This reaction is promoted by the injection of oxygen using supersonic or coherent jets and further chemical reaction with dissolved carbon in liquid steel at high temperatures. A 3D mathematical model to describe the effect of the injection angle, oxygen gas flow rate and number of lances on the decarburization kinetics of molten steel, in the absence of the top slag layer has been developed. The model has been validated using experimental data reported in the literature. The model shows that the decarburization kinetics is promoted by decreasing the injection angle from the horizontal, condition that improves both bath movement and reaction kinetics. These findings suggest that current injection angles in industrial EAF’s can be decreased in order to improve the decarburization rate. The main mechanism is the effect of the gas jet on the motion of the liquid. Taking into consideration that decreasing the injection angle from the horizontal promotes splashing, the numerical model predictions are employed to suggest alternative solutions in order to reach high decarburization rates.

3D Integrated Modeling of Supersonic Coherent Jet Penetration and Decarburization in EAF Refining Process

The present study proposes a complete 3D integrated model to simulate the top-blown supersonic coherent jet decarburization in the electric arc furnace (EAF) refining process. The 3D integrated model avoids the direct simulation of the supersonic coherent jet interacting with the liquid steel bath and provides a feasible way to simulate the decarburization in the liquid steel-oxygen two-phase reacting flow system with acceptable computational time. The model can be used to dynamically predict the details of the molten bath, including 3D distribution of in-bath substances, flow characteristics and bath temperature and provide a basis for optimizing the decarburization rate or other required parameters during the refining process.

Machine Learning-Based Prediction of a BOS Reactor Performance from Operating Parameters

A machine learning-based analysis was applied to process data obtained from a Basic Oxygen Steelmaking (BOS) pilot plant. The first purpose was to identify correlations between operating parameters and reactor performance, defined as rate of decarburization (dc/dt). Correlation analysis showed, as expected a strong positive correlation between the rate of decarburization (dc/dt) and total oxygen flow. On the other hand, the decarburization rate exhibited a negative correlation with lance height. Less obviously, the decarburization rate, also showed a positive correlation with temperature of the waste gas and CO2 content in the waste gas. The second purpose was to train the pilot-plant dataset and develop a neural network based regression to predict the decarburization rate. This was used to predict the decarburization rate in a BOS furnace in an actual manufacturing plant based on lance height and total oxygen flow. The performance was satisfactory with a coefficient of determination of 0.98, confirming that the trained model can adequately predict the variation in the decarburization rate (dc/dt) within BOS reactors.

An Improved Dynamic Model of the Vanadium Extraction Process in Steelmaking Converters

The production process from iron ore to steel can be divided into several stages, among which the processes of vanadium extraction and steelmaking are two key technological sections. The products of vanadium extraction are important strategic resources for modern industrial countries, and the remaining molten iron after vanadium extraction provides the material used in the subsequent steelmaking processes. In some mechanism models of vanadium extraction and the steelmaking process, the contact area of the reactions is considered to be constant in the empirical formula; furthermore, even the masses of the molten steel and slag are taken to be constants. This paper presents an important improvement to the existing models, in which the contact areas of the slag–metal interface and the emulsion system are considered to be non-constant. The improved model is simple and easy to analyze theoretically. Theoretical analysis of the model equations can be used to explain the competitive oxidation between each element, as well as the oxygen conservation of the system. The numerical simulations are consistent with existing production data, showing that the mass fraction of vanadium can be reduced to the specified threshold after about 3.5 min of blowing, which provides an important reference for production control. Furthermore, it is shown that the model captures the “trapezoid” structure of the decarburization rate. This paper also considers the relationship between FeO and O, the numerical simulation partly reflecting the dependence between the concentrations of FeO and O. The improved model can be used to describe and predict the change of the molten steel and slag composition in the process of vanadium extraction, which provides a mathematical foundation for the automatic control of the vanadium extraction process.

Study on Indirect Measuring Technology of EAF Steelmaking Decarburization Rate by Off-gas Analysis Technique in Hot State Experiment

In this paper, measurement method of EAF Steelmaking decarburization rate is studied. Because of the fuel gas blown and air mixed, the composition of hot temperature off-gas is measurand unreally, and the flow rate is unknown too, the direct measurement of EAF decarburization rate by furnace gas analysis is unrealized. Firstly, the off-gas generation process is discussed. After that, dynamic concentration of CO