Systematic Study on the Thermal Performance of Casting Slab Under Varying Environmental Conditions

Accurate prediction of slab temperature during the continuous casting and rolling process is essential for optimizing reheating furnace scheduling and achieving energy savings and emission reductions in steel production. However, because of the dynamic boundary conditions caused by the complex transport processes, obtaining precise temperature data for slabs remains challenging. These difficulties lead to issues such as low hot charging rates, mixing of hot and cold slabs in reheating furnaces, and excessive heat loss from slabs after cutting. To address these challenges, this study develops a mathematical model to calculate slab temperatures during the continuous casting and rolling process, providing a foundation for production scheduling optimization. The model accounts for the coupled heat transfer effects induced by dynamic slab stacking and the stacking heat transfer effects resulting from slabs with varying cross-sectional dimensions. Validation against experimental data demonstrated the model’s accuracy and reliability. Key findings highlighted that neglecting dynamic stacking effects or simplifying slab dimensions introduces errors. These results enhance slab temperature tracking in complex processes and advance related theoretical understanding.