Optimisation of the ladle furnace differential flow bottom blowing model using response surface methodology

Abstract

This study investigates the mixing time variations within a 130-ton ladle furnace (LF) using hydraulic experiments to compare the dual-plug equal flow bottom blowing model (Model-EF) and the dual-plug differential flow bottom blowing model (Model-DF). Single-factor analysis was conducted to obtain the optimal porous plug arrangement. Response surface methodology (RSM) was employed to construct a mixing time prediction model based on three factors: high gas flow, low gas flow, and liquid depth, analysing the interaction effects of these factors on mixing time. The results show that the Model-DF with a flow ratio of 2:1 outperformed Model-EF across various porous plug arrangements. The best mixing effect was achieved when the radial position of the porous plugs was 0.57R and the separation angle was 120°, representing an optimisation improvement of 21.05% over the current production Model-EF. The constructed mixing time prediction model exhibited excellent fit, with an R² value as high as 0.9597. Single-factor analysis revealed that the interaction between high gas flow and low gas flow significantly influenced mixing time. Based on this model, three different liquid depths were optimised, yielding corresponding optimal process parameters, which were validated through hydraulic experiments. Experimental results showed that under different operating conditions, the errors between experimental mixing times and predicted values were 2.17%, 1.54%, and 3.77%, respectively. These findings confirmed the effectiveness and reliability of the predictive model, providing new insights and technical support for optimising the LF refining process.