Decarburization is the most important reaction in the primary refining process via Oxygen Converter, since it can govern the productivity of an entire melt shop. Thus, the control of the main variables of this process such as the end time of oxygen blowing and the final carbon content of the bath is of utmost importance. For that, this book deals with the development of a mathematical model, using tools of artificial intelligence such as artificial neural nets (RNAs), to predict these variables from the analysis of the oxygen converter outlet gases. The model calculates the end blow time and the final carbon content in the liquid steel and it showed good correlation with real data from a steel mill.
| Autorius: | Felipe Farage David |
| Leidėjas: | Sciencia Scripts |
| Išleidimo metai: | 2020 |
| Knygos puslapių skaičius: | 60 |
| ISBN-10: | 6200928231 |
| ISBN-13: | 9786200928238 |
| Formatas: | 220 x 150 x 4 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Use of Artificial Neural Networks in Steelmaking Oxygen Converters: Prediction of the end of blow and the final carbon content of liquid steel.“
