Temperature Prediction Model for Controlling Casting Superheat Temperature

Abstract

A temperature prediction model has been developed for controlling the casting superheat temperature. For ease of implementation, the model is intentionally made simpler having a combination of a one dimensional heat transfer model and a simple regression model. The model is based on the fact that the BOF temperature of the liquid steel along with the bath cooling behaviours controls the aimed casting superheat temperature. Starting with the steel liquidus temperature and calculating the required steel temperature backwards throughout the process line gives the targeted BOF tap temperature. The on-line picking up of actual data helps the model to predict for the next stage more accurately in forward direction. Based on the predicted steel temperature, plant operators can take any necessary corrective action like additional ladle heating and extra/reduced argon stirring to ensure the aim final ladle/tundish temperatures at the casting are achieved.