Recent Progress on Advanced Blast Furnace Mathematical Model Based on Discrete Method
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- Ariyama Tatsuro
- Professor Emeritus, Tohoku University
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- Natsui Shungo
- Division of Material Science and Engineering, Faculty of Engineering, Hokkaido University
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- Kon Tatsuya
- Institute of Multidisciplinary Research for Advanced Materials Tohoku University
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- Ueda Shigeru
- Institute of Multidisciplinary Research for Advanced Materials Tohoku University
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- Kikuchi Shin
- Institute of Multidisciplinary Research for Advanced Materials Tohoku University
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- Nogami Hiroshi
- Institute of Multidisciplinary Research for Advanced Materials Tohoku University
Bibliographic Information
- Other Title
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- 離散的手法に基づく高炉数式モデルの研究開発動向
Abstract
From the backgrounds of the recent trend towards low reducing agent operation of large blast furnace and application of diversified charging modes of various burdens, an advanced mathematical model of blast furnace is required. Although conventional models based on the continuum model have been widely used, these models are not suitable for the recent demands. The discrete models such as discrete element model (DEM) and particle method are expected to precisely simulate the discontinuous and inhomogeneous phenomena in the recent operation conditions. With the discrete model, the microscopic information on each particle in the packed bed can be obtained besides the overall phenomena in blast furnace. The visual information can be obtained to understand the in-furnace phenomena with high spatial resolution. The liquid dripping and movement of fines in the lower part of blast furnace can be well simulated with DEM and particle method such as Moving Particle Semi-implicit Method (MPS). Moreover, the optimum bed structure for low reducing agent operation is being clarified by application of Eulerian-Lagrangian method. This review summarizes the recent progress on the mathematical model based on the discrete model.
Journal
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- Tetsu-to-Hagane
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Tetsu-to-Hagane 100 (2), 198-210, 2014
The Iron and Steel Institute of Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390001205127968768
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- NII Article ID
- 130003395098
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- COI
- 1:CAS:528:DC%2BC2cXnvFWmsrg%3D
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- ISSN
- 18832954
- 00211575
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed