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Tetsu-to-Hagané Vol. 102 (2016), No. 1

ISIJ International
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ONLINE ISSN: 1883-2954
PRINT ISSN: 0021-1575
Publisher: The Iron and Steel Institute of Japan

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Tetsu-to-Hagané Vol. 102 (2016), No. 1

Evaluating the Effect of Coke Layer Thickness on Permeability by Pressure Drop Estimating Model

Kazuhira Ichikawa, Yusuke Kashihara, Nobuyuki Oyama, Toshiyuki Hirosawa, Jun Ishii, Michitaka Sato, Hidetoshi Matsuno

pp. 1-8

Abstract

Recently, the price of coke has increased, so low coke rate operation has been required in the blast furnace. On the other hand, coke layer thickness decreases in low coke rate operation. It is known that gas permeability of the blast furnace becomes worse in thin coke layer thickness. So it is important to know minimum coke layer thickness. But minimum coke layer thickness has not been clear. That’s because there were no equipment to measure the effect of coke layer thickness on permeability.
In this study, to clarify the minimum coke layer thickness, new experiment equipment called cohesive zone simulator was developed. In a cohesive zone, gas flow along with coke layer, horizontally. To measure the effect of coke layer thickness on permeability, horizontal gas flow should be simulated. Therefore this simulator simulates horizontal gas flow.
Next, the effect of coke layer thickness was quantified by using the cohesive zone simulator. By the results, melting ore was penetrating into coke layer and closed part of layer. These phenomena caused increasing permeability in thin coke layer thickness condition.
Finally, pressure drop estimation model considering melting ore penetration was developed for the aim of quantifying minimum coke slit thickness.

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Evaluating the Effect of Coke Layer Thickness on Permeability by Pressure Drop Estimating Model

Development of New Charging Technique for Mixing Coke in Ore Layer at Blast Furnace with Center Feed Type Bell-less Top

Yusuke Kashihara, Yuki Iwai, Natsuo Ishiwata, Nobuyuki Oyama, Hidetoshi Matsuno, Hiroyuki Horikoshi, Koji Yamamoto, Minoru Kuwabara

pp. 9-16

Abstract

Improved permeability and increased gas utilization have been desired in order to achieve low coke rate operation of blast furnace. Coke mixed charging in the ore layer is one of the effective measures for realizing these improvements. A new charging technique for mixing small coke in the ore layer at a blast furnace with a center feed type bell-less top was developed and investigated in an experiment with a 1/18.8 scale model of an actual blast furnace at JFE Steel. By the new charging technique that small coke was charged in the determined port of the upper bunker before ore was charged in the upper bunker, discharge pattern of the mixed small coke discharged from the bell-less top was improved, and the radial distribution of mixed small coke ratio at the furnace top after the mixed materials were charged in the blast furnace was also improved. The new charging technique was applied to an actual blast furnace at JFE Steel, and improvement of gas permeability and decrease in coke rate were confirmed.

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Development of New Charging Technique for Mixing Coke in Ore Layer at Blast Furnace with Center Feed Type Bell-less Top

Fundamental Study of Sn Removal from Hot Metal by NH3 Gas Blowing

Naotaka Sasaki, Yu-Ichi Uchida, Yu-Ji Miki, Hidetoshi Matsuno

pp. 17-23

Abstract

Development of a practical method of Sn removal in the steelmaking process is necessary from the viewpoints of promoting use of scrap procured in the market and reducing energy consumption. It is well known that Sn promotes surface cracks of billets in hot rolling by coexisting with Cu. Although various methods of Sn removal have been investigated in laboratory experiments, enough Sn removal efficiency for commercially use has not been obtained. In the present study, Sn removal from high-S hot metal by NH3 gas blowing was investigated in laboratory experiments as a new method of Sn removal. The laboratory experiment on Sn removal from hot metal was carried out using up to a 10 kg-scale vacuum induction melting furnace. Sn removal was accelerated while blowing NH3 gas, and the evolution of gas bubbles were observed at the hot metal surface. Within the ranges of these experiments, higher temperature and higher concentrations of S and N were advantageous for Sn removal. The mechanism of the acceleration of Sn removal by NH3 gas blowing could be estimated that oversaturated N or H in hot metal made small bubbles to increase the hot metal surface for SnS evaporation. In the estimation of Sn removal ratio in plant-scale operation, it could reach 40%. For further rapid Sn removal, it was necessary to maximize [N] of hot metal by optimizing the lance height or flow rate of NH3 gas.

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Fundamental Study of Sn Removal from Hot Metal by NH3 Gas Blowing

Development of Analytical Methods for Free-MgO in Steelmaking Slag

Kazutoshi Hanada, Masao Inose, Sakae Sato, Keiji Watanabe, Kyoko Fujimoto

pp. 24-28

Abstract

Steelmaking slags have been widely used as aggregate for road and civil engineering. The slags sometimes expand as a result of hydration, which may cause evolution of cracks at surfaces of roads when used as aggregate. Free magnesium oxide (free-MgO) in the slags is a potential cause of the expansion as well as free calcium oxide is. Thus, analytical methods to determine the free-MgO in the slag have been required for the accurate evaluation of the expansion. We present an accurate method to determine the free-MgO in steelmaking slags based on the combination of chemical extraction and thermogravimetry (TG). Free-MgO and magnesium hydroxide (Mg(OH)2) in steelmaking slags are dissolved into an ethyleneglycol solution containing iodine and ethanol when heated. The amount of the magnesium species dissolved in the solution is determined by inductively coupled plasma atomic emission spectrometry. The amount of Mg(OH)2 in the slags determined by TG independently is subtracted from that of the dissolved in ethyleneglycol to yield the amount of free-MgO. The established method can quantify less than 0.1 wt% free-MgO in steelmaking slags.

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Development of Analytical Methods for Free-MgO in Steelmaking Slag

An Identification Method of Multi-point Heat Transfer Coefficient

Takayuki Otsuka, Seiji Ito

pp. 29-33

Abstract

A heat transfer coefficient identification model has been developed which considers multiple boundary with different conditions using influence coefficient matrix derived from a mathematically and numerically obtained Jacobian matrix. The model was applied to a top surface and bottom surface heat transfer estimation problem, i.e. two unknown quantities problem, for an infinite flat steel plate which is subject to different boundary conditions. The method yields thus fast and accurate heat transfer coefficient results as well as the temperature distribution which is in excellent agreement with measured one. Further application of the model was two-dimensional problem of a work roll temperature and boundary condition estimation while rolling a hot strip. The two-dimensional temperature distribution of a cross section of the roll was calculated by using heat transfer coefficient as input values which are inversely identified by the already calculated temperature distribution. The identified heat transfer coefficient directly confronted with the input value exhibiting the method’s capacity for multiple-point identification of heat transfer coefficient.

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An Identification Method of Multi-point Heat Transfer Coefficient

Reduction of Diffusion Bonding Temperature with Recrystallization at Austenitic Stainless Steel

Masahito Katoh, Naoko Sato, Tomomi Shiratori, Yohei Suzuki

pp. 34-39

Abstract

Diffusion bonding at low temperature is a necessary process for the manufacturing of metal MEMS (Micro-Electronic-Mechanical Systems) such as, in the case of metal micro-pump that requires a high proof strength. Metals with severe plastic deformation having high mobility grain boundaries are known to bond at low temperatures. We then simultaneously carried out recrystallization and solid phase diffusion bonding of the metals. In this paper, we have confirmed a reduction in the diffusion bonding temperature in severe plastic-deformed SUS304 and SUS316L as compared to the case of heat treated solutions. Especially the bonding temperature was decreased considerably in SUS304 having strain-induced martensite.

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Reduction of Diffusion Bonding Temperature with Recrystallization at Austenitic Stainless Steel

Effect of Cold Rolling Reduction on r-value of Nb and B-added Extra Low-carbon Steel for Welded Cans

Masaki Tada, Yusuke Nakagawa, Katsumi Kojima, Hiroki Nakamaru

pp. 40-46

Abstract

When the welding body is expanded, it shrinks in the direction of can height. The change of height of can is influenced by r-value.
The effect of cold rolling reduction on the r-value of niobium (Nb) and boron (B) combined added extra low-carbon steel was investigated by using commercial steels.
Ferrite grain size of annealed sheet decreased with the increase of cold rolling reduction. At the same time, the intensity of {001} <110> increased and the r90°-value decreased.
The behavior of the decrease of r-value was dependent on the ferrite grain size of hot-rolled sheet. The intensity of {001} <110> of annealed sheet was large for the hot-rolled sheet of grain size of 8.4 μm comparing with 10.8 μm and the r90°-value decreased.

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Effect of Cold Rolling Reduction on r-value of Nb and B-added Extra Low-carbon Steel for Welded Cans

High Dimensional Microstructure Data-driven Prediction of Stress-strain Curve of DP Steels by Primary Artificial Intelligence

Yoshitaka Adachi, Keisuke Shinkawata, Akihiro Okuno, Shogo Hirokawa, Shigeki Taguchi, Sunao Sadamatsu

pp. 47-55

Abstract

Prediction of a stress-strain curve of ferrite-martensite DP steels was studied by a combined technique of Bayesian inference and artificial neural network. To screen a descriptor to be used for neural network analysis, material genomes such as volume fraction, micro-hardness, handle, and void of martensite phase, and micro-hardness of ferrite phase were examined by Bayesian inference. In a case of small data set, a machine learning method to predict mechanical properties reliably was proposed.

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High Dimensional Microstructure Data-driven Prediction of Stress-strain Curve of DP Steels by Primary Artificial Intelligence

Capture Characteristics of Gaseous Elemental Mercury by Carbonized Waste in Air and Reducing Atmospheres

Yasuaki Ueki, Ryo Yoshiie, Hiroaki Sawa, Ichiro Naruse

pp. 56-60

Abstract

Coal contains harmful trace elements. Especially, mercury has high volatility. Mercury of approximately 27% in coals used in coal fired power plants is released as gaseous elemental mercury in a flue gas to the atmosphere. In an ironmaking system, since large amounts of coal are used as a reducing agent and heat source, there is a possibility that the gaseous elemental mercury emits from some processes. Therefore, an objective in this work is to develop adsorbents that are able to capture the gaseous elemental mercury in an air atmosphere and a reducing atmosphere. In this work, carbonized wastes (sewage sludge, paper sludge, woody biomass and municipal solid waste) were used as experimental samples. As a result, the municipal solid waste char has the highest property to capture the elemental mercury in the air atmosphere at 423 K. From results of X-ray Absorption Near Edge Structure (XANES) analyses, the mercury captured in the municipal solid waste char was mainly captured as mercury sulfide (HgS) on the char. On the other hand, a mercury capture ratio of the municipal solid waste char in the reducing atmosphere was lower than that in the air atmosphere.

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Capture Characteristics of Gaseous Elemental Mercury by Carbonized Waste in Air and Reducing Atmospheres

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