期刊
POWDER TECHNOLOGY
卷 398, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.powtec.2021.117055
关键词
Mathematical model; Discrete element method; Burden flow; Segregation; Burden distribution
资金
- National Natural Science Foundation of China [U1960205]
This study reviews the progress in the research of burden distribution in blast furnaces, including charging measurements, physical model experiments, mathematical models for macroscopic burden distribution, and particle behavior simulations. The advantages, disadvantages, and applicable conditions of these approaches are analyzed, aiming to provide a comprehensive understanding of blast furnace charging and guidance for future technical developments.
The burden distribution has an important influence on the heat transfer, mass transfer, momentum transfer and chemical reactions of blast furnaces. Since the 1970s, metallurgical scholars have been studying the rules of burden movements and distribution during the charging process. In past decades, physical experiments are applied to investigate the burden distribution from a simple two-dimensional slot model according to a similarity principle to a three-dimensional 1:1 model using a real burden, or even by using direct detection technique in a practical blast furnace via laser or radio. Meanwhile, numerical simulations have made great progress with the rapid developments of computer technology, and mathematical models with different methods are established, which provide flexible methods for revealing the macro-and micro-properties of the burden distribution in detail. This study reviews the progress in charging measurements, physical model experiments, mathematical models for macroscopic burden distribution, and particle behavior simulations based on the discrete element method (DEM) at the particle-scale. The advantages, disadvantages, and applicable conditions of these approaches are analyzed as well, aiming at providing a comprehensive understanding for the blast furnace charging and guidance for future technical developments.(c) 2021 Elsevier B.V. All rights reserved.
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