Effect of Interface Resistance on Gas Flow in Blast Furnace

Guha, Mriganshu; Nag, Samik; Swamy, Pailola Kumar; Ramna, R. V.

doi:10.2355/isijinternational.51.1795

Cited by 9 publications

(9 citation statements)

References 5 publications

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“…It was found that the increase in flow rate usually results in the increase of relative pressure drop along the vertical direction, and one of the reasons may be the strong mixing and filling of interstitial voids at the interface due to intensive interactions between particles and gas flow because the mixed layer porosities (corresponding to Figure A) would have a gradual decrease from 0.457 to 0.432, 0.423 when the flow rate increases from 3.6 to 8.1, 12.6 m 3 /s. Therefore, it is revealed that gas flow rate can significantly affect the mixed layer properties, such as the mixed ratio and layer porosity, which is consistent with the previous work …”

Section: Resultssupporting

confidence: 91%

“…In particular, the pressure drop across layered burden structure greatly depends on the number of alternate layers because the “interface resistance” caused by mixed layer has significant contributions to it. Furthermore, the gas flow resistance primarily relies on bed porosity or permeability distribution, while there exist local porosity minima in the interfacial region due to the presence of layers with different size particles …”

Section: Resultsmentioning

confidence: 99%

“…It is affected by the distribution of burden materials composed of alternating coke and ferrous ore layers. Flow distribution and hence pressure drop of gas in the granular zone of BF is dependent on permeability distribution, number, and thickness of alternating layers of coke and ore burden …”

Section: Introductionmentioning

confidence: 99%

“…The formation of mixed layers is a significant phenomenon in a BF because the porosity at the interface regions is of major importance in the definition of nonuniform flow through the stack region of a BF. Laboratory‐scale experiments, scaled burden descent models as well as industrial measurements have been conducted to examine mixed layer formation. These studies revealed that the mixed layer usually has much lower gas permeability compared with the individual layers.…”

Section: Introductionmentioning

confidence: 99%

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Numerical investigation of mixed layer effect on permeability in a dynamic blast furnace

Dianyu

2020

Engineering Reports

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Gas flow distribution in a blast furnace (BF) plays a significant role in BF smooth operation, productivity, and thermal efficiency. It is affected by the distribution of burden materials composed of alternating coke and ferrous ore layers. While moving downward coke and ferrous layers of different sizes can mix and form the so-called mixed layers. Generally, the porosity is lower and hence the pressure drop is higher in the mixed layers. These variations can change the gas flow distribution and BF performance. Previous work tried to quantify the effect of material properties and process conditions on the formation of mixed layers and the resulting local porosity variation. However, these studies were often conducted under simplified conditions. Few were dedicated to the formation of mixed layers in a BF and its effect on BF performance. This work studies the formation of mixed layers in an experimental BF by using a combined computational fluid dynamics and discrete element method approach. The effect on BF performance was evaluated under different operational conditions including different size ratios of coke to iron ore particles, burden distribution, batch weight, and discharge rate.The results obtained were helpful to optimize burden charge for improving BF performance. K E Y W O R D Sblast furnace, computational fluid dynamics, discrete element method, mixed layer, permeability

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Section: Resultssupporting

confidence: 91%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Numerical investigation of mixed layer effect on permeability in a dynamic blast furnace

Dianyu

2020

Engineering Reports

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“…1/3 scale model of Muroran No. 1 blast furnace 30) Effects of factors on burden distribution gas flow has impact on the particle size distribution; coke layer collapse affects the burden profile 1/10 scale half section model of Aceralia #B blast furnace 6) Effects of gas flow on burden distribution A narrow window in the center connects the successive coke layers 1/30 scale 2-dimensional slot type model 31) Pressure drop in blast furnace across layered burden…”

Section: Flow Valve Opening Modelmentioning

confidence: 99%

Development of Blast Furnace Burden Distribution Process Modeling and Control

et al. 2017

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The burden distribution process is an important and efficient measure to maintain the stable operation of the blast furnace. An accurate burden distribution model will reveal the impact on the internal furnace state and help to optimize the blast furnace production index. This article reviews the recent development of the modeling and control techniques in the burden distribution process. The current modeling methods of the blast furnace burden distribution can mainly be divided into the following types: the mechanismbased method, the physical scale model-based experiments and the data-driven method. However, most of the existing modeling methods are not applicable to general blast furnaces because it depends on the specific furnace structure and parameters. Furthermore, with the advancement in measurement technology, sensors now provide rich amount of online measurement of the blast furnace iron-making process. This makes the data analysis more challenging. It is imperative to establish new modeling methods for the burden distribution process. Therefore, this paper points out the new trends in modeling and control of the blast furnace burden distribution process. First, a dynamic clustering method based on dynamic time warping and adaptive resonance theory is introduced. Second, the inverse dynamic model-based burden distribution control is developed. Furthermore, a multi-model-based switch for modeling the fluctuating blast furnace process is formulated. Finally, the reinforcement learning method for the dynamic optimization of the production index is recommended.

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Observation of the Effect of Various Operating Factors on the Cohesive Zone Using the Blast Furnace Irregularity Simulator

Park

Min

Kim

et al. 2020

steel research int.

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The blast furnace (BF) process is highly complex, involving multiple phases (gases, granular solids, liquids, and powders) undergoing various chemical and physical phenomena. Any improvement in BF productivity under a given set of operating conditions necessitates a better gas flow distribution through a layered burden structure in the BF. However, it is extremely difficult to directly measure or predict the internal flows in a BF. The main zone of unstable motion in a BF is generally the cohesive zone. Herein, the cause of unstable behavior in a BF is investigated by directly observing the behavior of the cohesive zone using a BF irregularity simulator. It is found that the shape of the cohesive zone is directly influenced by the blast conditions and the height of the deadman, as well as varied change. As the blast volume increased, the height of the top level of the cohesive zone increased and the change in the temperature profile of the cohesive zone according to the difference in blast volume. Thus, it is possible to understand and estimate the unstable motion in a BF under operation by observing the real‐time behavior of the burden, using a BF irregularity simulator.

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Effect of Interface Resistance on Gas Flow in Blast Furnace

Cited by 9 publications

References 5 publications

Numerical investigation of mixed layer effect on permeability in a dynamic blast furnace

Numerical investigation of mixed layer effect on permeability in a dynamic blast furnace

Development of Blast Furnace Burden Distribution Process Modeling and Control

Observation of the Effect of Various Operating Factors on the Cohesive Zone Using the Blast Furnace Irregularity Simulator

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