Identification of nonstationary parameters of electric arc furnace model using Monte Carlo approach

Abstract

This paper describes Monte Carlo analysis of an electric arc furnace (EAF) model based on measurements. In this research long-time samples have been analyzed in terms of incidence of occurring of particular values of EAF model coefficients. Their occurrence has been investigated through finding best fitted ones, which was measured by different indicators. These distributions have been approximated by continuous probability density functions that later allowed to develop a probabilistic EAF model.