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A dimensionless criterion system for energy efficiency evaluation in steel rolling reheating furnaces

Year: 2025
Type: article
Abstract: As a key high-energy-consuming equipment in steel production, the energy efficiency optimization of steel rolling reheating furnaces (SRRF) has long been constrained by three core contradictions: "energy consumption-temperature matching, rolling rhythm-quality coordination, and billet shape-energy efficiency differentiation". In this study, a "general-subdivision" two-layer criterion system is established. The general criterion ( N E ) quantifies global energy consumption redundancy by means of the ratio of actual energy consumption to theoretical heat demand. The shape-corrected criterion ( N E, M ), meanwhile, incorporates a correction term for the width-to-thickness ratio ( W / H ) to distinguish between shape-induced inherent losses and operationally controllable losses. Verification using 1515 sets of industrial data demonstrates that N E can effectively assess the energy consumption-temperature matching degree for SRRF—exhibiting a negative correlation coefficient of -0.61 with temperature difference, while N E, M enables accurate identification of the heat transfer characteristics of wide billets, with a negative correlation coefficient of -0.45 with W / H , confirming that wider billets exhibit lower shape-corrected energy redundancy. Analysis of the high-gradient region reveals that although wide billets in SRRF experience higher energy consumption due to extended heat conduction paths, their thermal efficiency outperforms that of narrow billets; optimization in this regard can be achieved through regulating rolling rhythm and furnace temperature. This system serves as a quantitative tool for SRRF to transition from empirical regulation to data-driven optimization. Theoretically, it breaks through the single-factor limitation of traditional methods; practically, it provides support for energy efficiency benchmarking and dynamic regulation of SRRF.
Authors: Yi Duan, Guang Chen, Xiangjun Bao, Lu Zhang, Xiaojing Yang
Language: English
Field: Energy
Open Access status: gold
Estimated APC paid: $2,150
OpenAlex ID: W7106659542
FWCI:
Cites: 39
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