A Robust Static Model of Basic Oxygen Furnace for Analyzing Emerging Steelmaking Scenarios

Abstract

A robust static model, which incorporates emerging steelmaking scenarios in terms of solid charge mix with the given hot metal in basic oxygen furnace process, is developed. It employs mass and enthalpy balances to comprehend nonequilibrium conditions, considering four key empirical parameters: iron loss, post‐combustion ratio, heat loss, and undissolved lime content in slag, which are fine‐tuned using plant data through a multivariate approach, ensuring the reliability. The model is validated in a basic oxygen furnace (BOF) shop using data from over 4000 heats, achieving a strike rate of ≈77% for input lime prediction within ±1 ton and ≈80% for input oxygen prediction within ±600 Nm3. Model implementation in BOF shop provides valuable guidance to the operators, resulting in the reduction of average oxygen and lime consumption by 139 Nm3 and 652 kg heat−1, respectively. The model also enables the determination of the maximum scrap utilization of ≈16% for 0.8% silicon and ≈14% for 0.6% silicon in hot metal, respectively. The model aids in calculating the maximum tap temperature for varying hot metal silicon and iron ore addition. Overall, the model optimizes primary steelmaking, enhancing efficiency, reducing resource consumption, and offering insights into alternative iron sources like direct reduced iron.