Analysis reveals dynamic models improve heating uniformity in industrial reheating furnaces, suggesting better operational efficiency.
With increasing demands for precision in reheating furnace operations, traditional simulations using constant boundary conditions fail to capture dynamic thermal conditions. To overcome these challenges, an air‐fuel dynamic control numerical model in an industrial‐scale reheating furnace is developed. The predictions made by the model show strong agreement with on‐site industrial data, validating its accuracy and reliability. The study underscores the importance of integrating the proportional integral derivative (PID) control algorithm into the simulation model of reheating furnaces. Using this model, differences in the heating process with and without dynamic adjustment of air and fuel volumes are compared and analyzed. The flame area fluctuation range of the whole working period is reduced by 420.2 m 2 (90.3%) compared with the constant condition. The average temperature deviation of each heating zone decreased by more than 28.17 K (76.9%). The simulation model effectively regulates slab temperature, ensuring uniformity and meeting target requirements, enabling the prediction of unknown production conditions. This study expands the scope of numerical simulations of reheating furnaces.
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XU et al. (2025) studied this question.
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