Rotary hearth furnace for steel solid waste recycling: Mathematical modeling and surrogate-based optimization using industrial-scale yearly operational data

Abstract

The presence of zinc in byproduct dust produced during steel production poses a challenge to resource management and can have adverse environmental effects. This study investigates the dezincification behavior of a commercial-scale rotary hearth furnace used to recycle the byproduct dust. A mathematical model of iron-ore/carbon-composite pellets was developed, incorporating a one-dimensional dynamic model to examine the non-uniform distribution of temperature and solid weight fraction. The Arrhenius kinetics of the ZnO reduction reaction (ZnO + CO → Zn + CO2) was fitted using operational data yielding estimated parameters of 163.6 kJ mol−1 and 868.6 m s−1. The simulation results of our study showed good agreement with the operational data from the furnace, with a relative error of 10%. Six factors were identified as having an impact on the dezincification ratio, with the most significant being operational time, particle size, temperature, C/O ratio, porosity, and emissivity in descending order. The mathematical model was used to examine two scenarios of environmental problems and derive optimal solutions for each. Our results show that extreme gradient boosting using operating temperature, operating duration, and C/O ratio as trained variables was the most accurate in predicting dezincification and metallization, resulting in a 33% increase in waste recycling through surrogate-based optimization. The Pareto front analysis highlights the importance of considering the net impact of carbon emissions, total production cost, and solid waste penalties together.