The master thesis focuses on the development of an analytical model of the electric arc furnace. The main objective is to create a simplified model for the estimation of the melt temperature in the electric arc furnace used in the steel melting process for the last part of the furnace operation, i.e. the refining phase. Due to the high temperatures within the furnace where the melting process occurs, and the manner in which temperature measurements are conducted, they are not performed continuously. We aim to overcome this limitation by developing a model that provides sufficiently accurate temperature estimation, thereby reducing the need for frequent measurements that lead to energy losses. Simultaneously, this gives furnace operators a better insight into the current state of the furnace.
The first part of this paper is devoted to modelling the refining phase, where, from the point of view of the model, the furnace is divided into different zones. The energy transfer between these zones and the chemical reactions are described mathematically in the form of equations.
In the second part of this paper, we present the simulated annealing optimization algorithm, utilized for determining the optimal parameters of the electric arc furnace model. This approach facilitates the efficient adaptation of the model to real-world conditions, thereby enhancing the accuracy of temperature estimation.
In the concluding section of this paper, we present the results and evaluation of the developed model. Furthermore, we discuss options for further work in this area of research and potential improvements and adaptations to the model arising from the obtained results.
|
