How to Optimize the Blast Furnace Profiles for Maximum Energy Efficiency

Abstract While the inner profile of a blast furnace (BF) follows general standardization, its specific design remains largely experience-based. BF process modeling and optimization offer a systematic and cost-effective approach to studying the effects of key variables, including material properties, BF geometry, and operational conditions, providing valuable insights for BF design and control. In this work, a 3D BF process model was employed to investigate the design rules for BF geometry in the 1000 to 5000 m 3 volume range. First, under fixed operating conditions, the optimal BF geometry for each volume was identified by minimizing total energy consumption. The results show that the method employed in this study can quantitatively replicate well-established industrial trends related to BF volume. Secondly, an analysis of transport phenomena within a furnace provided a rationale for these geometric trends. Lastly, it is shown that the optimum BF profile is also affected by the preset geometric constraints, even under the same operating conditions. Therefore, customized BF design may be required to better align with varying production needs.

Authors

Institutions

Publication Details

Journal
Metallurgical and Materials Transactions B
Published
2025-06-13
DOI
https://doi.org/10.1007/s11663-025-03620-w
Primary Topic
Iron and Steelmaking Processes
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

How to Optimize the Blast Furnace Profiles for Maximum Energy Efficiency

Ruiping Zou, Wenqi Zhong, Lulu Jiao, Junjie Li et al.
Metallurgical and Materials Transactions B
Iron and Steelmaking Processes
article

How to Optimize the Blast Furnace Profiles for Maximum Energy Efficiency

Ruiping Zou, Wenqi Zhong, Lulu Jiao, Junjie Li, Shibo Kuang, Aibing Yu
article en

Abstract

Abstract While the inner profile of a blast furnace (BF) follows general standardization, its specific design remains largely experience-based. BF process modeling and optimization offer a systematic and cost-effective approach to studying the effects of key variables, including material properties, BF geometry, and operational conditions, providing valuable insights for BF design and control. In this work, a 3D BF process model was employed to investigate the design rules for BF geometry in the 1000 to 5000 m 3 volume range. First, under fixed operating conditions, the optimal BF geometry for each volume was identified by minimizing total energy consumption. The results show that the method employed in this study can quantitatively replicate well-established industrial trends related to BF volume. Secondly, an analysis of transport phenomena within a furnace provided a rationale for these geometric trends. Lastly, it is shown that the optimum BF profile is also affected by the preset geometric constraints, even under the same operating conditions. Therefore, customized BF design may be required to better align with varying production needs.

Metallurgical and Materials Transactions BVol. 56(4)
Monash University (AU), Southeast University (CN)
Monash University, National Natural Science Foundation of China, Baosteel Group Corporation, National Supercomputing Center, Korea Institute of Science and Technology Information
Openalex Percentile: Top 87%
Iron and Steelmaking Processes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

How to Optimize the Blast Furnace Profiles for Maximum Energy Efficiency — Ruiping Zou, Wenqi Zhong, et al. · Metallurgical and Materials Transactions B (2025) | TGRS Research Map | TGRS