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Abstract

Determining the boundary conditions of heat transfer in steel manufacturing is a very important issue. The heat transfer effect during contact of two solid bodies occurs in the continuous casting steel process. The temperature fields of solids taking part in heat transfer are described by the Fourier equation. The boundary conditions of heat transfer must be determined to get an accurate solution to the heat conduction equation. The heat flux between the tool and the object processed depends mainly on temperature, pressure and time. It is very difficult and complicated to accomplish direct identification and determination of the boundary conditions in this process. The solution to this problem may be the construction of a process model, performing measurements at a test stand, and using numerical methods. The proposed model must be verified on the basis of parameters which can easily be measured in industrial processes. One of them is temperature, which may be used in inverse methods to determine the heat transfer coefficient. This work presents the methodology for determining the heat flux between two solid bodies staying in contact. It consists of two stages – the experiment and the numerical computation. The problem was solved by using the finite element method (FEM) and a numerical program developed at AGH University of Science and Technology in Krakow. The findings of the conducted research are relationships describing the value of the heat flux versus the contact time and surface temperature.
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Abstract

The paper evaluates two approaches of numerical modelling of solidification of continuously cast steel billets by finite element method, namely by the numerical modelling under the Steady-State Thermal Conditions, and by the numerical modelling with the Traveling Boundary Conditions. In the paper, the 3D drawing of the geometry, the preparation of computational mesh, the definition of boundary conditions and also the definition of thermo-physical properties of materials in relation to the expected results are discussed. The effect of thermo-physical properties on the computation of central porosity in billet is also mentioned. In conclusion, the advantages and disadvantages of two described approaches are listed and the direction of the next research in the prediction of temperature field in continuously cast billets is also outlined.
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Abstract

In this work, the authors proposed a modification of the working space one-strand tundish adapted for slab casting process. Numerical simulations of liquid steel flow in the considered flow reactor were performed. The tundish is equipped with a dam with a multi-hole filter. Two variants of the filter hole arrangement were tested and their effect on the liquid steel flow hydrodynamic structure in the tundish was examined. The computer calculations results were verified by performing experiments on the water model. The result of numerical and physical simulations an RTD (Residence Time Distribution) type F curve was generated, which define the transition zone between the cast steel grades during the sequential casting process. The results of the researches showed that the modification of a dam with a multi-hole filter affects on the formation of the liquid steel flow hydrodynamic structure and the transition zone. Furthermore, examinations of the liquid steel refining ability in the considered tundish were carried out. The influence of the filter holes arrangement on the non-metallic inclusions flotation process to the slag phase and liquid steel filtration processes was checked. Numerical simulations were performed in the Ansys-Fluent computer program.
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Abstract

The purpose of this paper was testing suitability of the time-series analysis for quality control of the continuous steel casting process in production conditions. The analysis was carried out on industrial data collected in one of Polish steel plants. The production data concerned defective fractions of billets obtained in the process. The procedure of the industrial data preparation is presented. The computations for the time-series analysis were carried out in two ways, both using the authors’ own software. The first one, applied to the real numbers type of the data has a wide range of capabilities, including not only prediction of the future values but also detection of important periodicity in data. In the second approach the data were assumed in a binary (categorical) form, i.e. the every heat(melt) was labeled as ‘Good’ or ‘Defective’. The naïve Bayesian classifier was used for predicting the successive values. The most interesting results of the analysis include good prediction accuracies obtained by both methodologies, the crucial influence of the last preceding point on the predicted result for the real data time-series analysis as well as obtaining an information about the type of misclassification for binary data. The possibility of prediction of the future values can be used by engineering or operational staff with an expert knowledge to decrease fraction of defective products by taking appropriate action when the forthcoming period is identified as critical.
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