EXPERIENCES IN PHYSICOCHEMICAL MODELLING OF OXYGEN CONVERTER PROCESS (BOF)
Oxygen converting of hot metal (LD/BOF) is contemplated as an object of simulation. Oxygen converting is a highly complex thermo-chemical process comprising a series of matter and energy transformation and transportation steps that makes the simulation very challenging. The basic principles of CONSIM 5 oxygen converter simulator are presented. Simulator is a comprehensive combination of a physical model with several empirical submodels describing all properties and processes that affect the final result of a converter blow, final mass and composition of steel, slag, dust and converter gas as well as the end temperature of steel. CONSIM simulator is used for simulation of series of high and low carbon steel blows. Simulated steel temperatures, oxygen consumption, blow time and iron oxide content of slag are compared with measured values. Problems of simulation and requirements for quantitative simulation of oxygen converter process are discussed.
Comparison of Different Approaches to the Creation of a Mathematical Model of Melt Temperature in an LD Converter
In the steel production process in the LD converter, it is important to have information about the melt temperature. The temperature and chemical composition of the steel are important parameters in this process in terms of its completion. During the process, continuous measurement of the melt temperature and thus also information about the end of the process are missing. This paper describes three approaches to creating a mathematical model of melt temperature. The first approach is a regression model, which predicts an immeasurable melt temperature based on other directly measured process variables. The second approach to creating a mathematical model is based on the machine learning method. Simple and efficient learning algorithms characterize the machine learning methods. We used support vector regression (SVR) method and the adaptive neuro-fuzzy inference system (ANFIS) to create a mathematical model of the melt temperature. The third approach is the deterministic approach, which is based on the decomposition of the process and its heat balance. The mathematical models that were compiled based on the mentioned approaches were verified and compared to real process data.
Inhibition of Mild Steel Corrosion Using L-tryptophan and Synergistic Surfactant Additives
The corrosion inhibition characteristics of nitrogen containing amino acid L-tryptophan on mild steel in 0.1 M HCl solution, in the temperature range of 30-50 o C, was studied by weight loss and potentiodynamic polarization measurements. L-tryptophan significantly reduces the corrosion rates of mild steel; the maximum inhibition efficiency being 83% at 50 o C in presence of inhibitor concentration of 500 ppm. The effect of the addition of very small concentrations of anionic surfactant, sodium dodecyl sulfate (SDS), and of cationic surfactant, cetyl trimethyl ammonium bromide (CTAB), on the corrosion inhibition behavior of L-tryptophan was also studied. The inhibition efficiency (IE) of L-tryptophan significantly improved in presence of both surfactants. The effect of SDS and CTAB on the corrosion inhibition behavior of L-tryptophan appears to be synergistic in nature, the values of synergism parameter being greater than unity. The adsorption of inhibitors on mild steel surface obeyed Langmuir’s adsorption isotherm. The calculated thermodynamic parameters for adsorption reveal a strong interaction between the inhibitors and the mild steel surface. The results obtained by electrochemical studies are consistent with the results of the weight loss measurements. L-tryptophan acts more anodic than cathodic inhibitor.