Abstract The continuous steel rolling reheating furnace, as a key thermal device in the rolling process, is a major energy-consuming component in steel production. The design of its heating system directly determines the heating quality of billets and overall energy efficiency. Traditional methods, which rely on experience-driven system design or empirical model-based fuel optimization strategies, often face the issue of excessive energy consumption. To address this challenge, this study proposes a quantitative correlation model based on the Principle of Terminal Concentrated Heating (PCHT), linking sectional fuel inputs to the temperature fields within the furnace, thereby providing a theoretical basis for optimizing fuel distribution. Additionally, a parallel optimization strategy is introduced, significantly enhancing computational efficiency through multi-objective collaborative optimization. The developed parallel heating system optimization model aims to minimize total fuel consumption while maximizing computational speed. Validation results demonstrate a high consistency between model predictions and experimental data trends, with an average error of less than 26°C. The computational speed improves by 98% compared to traditional methods. In four practical industrial scenarios, the optimized systems strictly adhere to the Principle of Terminal Concentrated Heating, achieving a 22.54% reduction in specific energy consumption compared to conventional designs and actual operations. This model not only provides an efficient framework for furnace design but also significantly enhances the energy-saving potential of continuous steel rolling reheating furnaces, offering practical technological support for industry emission reduction goals.
Tong et al. (Thu,) studied this question.