2단 유동층 철광석 환원공정의 수치 모사

한윤봉, 장근수*

전북대학교 화학공학부, 포항공대 지능자동화 연구센터*

Mathematical Modeling of Reduction Process Of Iron Ores

in a Two-Stage Fluidized Bed System

Yoon-Bong Hahn and Kun Soo Chang*

School of Chemical Engineering & Technology, Chonbuk National University

Chonju 561-756, Korea

* Automation Research Center and Department of Chemical Engineering, Pohang University of Science and Technology, Pohang 790-784, Korea

INTRODUCTION

In recent years, various smelting reduction processes have been under development to replace the conventional ironmaking process, i.e., the blast furnace process.[1,2] The smelting reduction process that combines a smelting furnace and a fluidized bed prereduction reactor has been highlighted as one of promising processes that meet the above requirements. The fluidized bed reactors have several advantages of no agglomeration of the feed, excellent heat and mass transfer, temperature uniformity through the whole reactor circuit, excellent thermal efficiency, low investment cost, and efficient pollution control. The understanding of the overall phenomena occurring in a fluidized bed is of great importance for the design of an efficient reactor, but very little work has been done due to the complexity of the system.

In this work, a mathematical model has been developed to analyze and predict the reduction process of iron ore particles in a two-stage bubbling fluidized bed system. This model includes the degradation of particles to elucidate its effect on reduction of iron oxides. The performance of the two-stage fluidized bed system has been intensively tested in terms of various operation conditions.

MATHEMATICAL MODELS

The two-stage fluidized bed (TFB) system is schematically shown in Figure 1. The specified iron ore particles are charged into the first reactor R1 and reduced with reduction gas blown into the reactor. In R1, fine particles are carried over to the second bed R2, and coarse solids are remained to be reduced with reduction gases. The fines carried over from R1 are reduced in R2, and no particles are entrained from R2 due to the geometry of an enlarged upper part of the bed. The reduced coarse and fine particles from R1 and R2 are discharged and collected to be fed into a smelting-reduction furnace for ironmaking.

It was observed that ore particles were broken into small pieces in the bed and the particles discharged from the bed were finer than feed particles. The reduction of iron oxides was then affected by this particle degradation. However, it is very difficult to quantitatively explain such a phenomenon, and to include its effect on the reduction performance of the fluidized bed. Little work has been done on this problem.

In this work, a comprehensive mathematical model has been developed to study the various subprocesses occurring in the two-stage fluidized bed system. The model includes fluidizing behavior of ore particles, particle degradation, and reduction kinetics of multi particles.

Reduction Kinetics of Iron Oxides

The iron ore particles are reduced by two major reducing agents, i.e., CO and H2. The reduction involves the following steps:

[eqn: rm 3Fe_2 O_3 ~+~ CO`("or"~ H_2 ) ~~rarrow~~2Fe_3 O_4 ~+~ CO_2` ("or"~H_2 O)]	(17)

[eqn: rm Fe_3 O_4 ~+~ CO`("or"~ H_2 ) ~~rarrow~~3Fe O ~+~ CO_2` ("or"~H_2 O) ``]	(18)

[eqn: rm Fe O ~+~ CO`("or"~ H_2 ) ~~rarrow~~Fe ~+~ CO_2` ("or"~H_2 O) ~]	(19)

Since the powdered iron ores are nonporous, the reduction kinetics of iron oxides can be described with a chemical reaction control scheme using the shrinking unreacted core model.[3] The reduction degree of a single particle is then given by:

[eqn: rm t^* ~=~ t``/``tau ~=~g(X_B ) ~=~ 1``-```(1`-`X_B )^1/3]

The reduction degree of individual particles depends on the residence times in the bed, and thus the reduction level varies from particle to particle due to different lengths of stay. The ore feed also consists of a size distribution of solid particles. Hence, the mean reduction degree of the exit stream has to account for both size and residence time of particles in the bed. On accounting for this, the mean reduction degree of the outlet stream of particles is given by:[4]

[eqn: rm 1``-`` {bar bar X}_B ~=~ int left＿ int left{(1`-`X_B (d_p , t) right} `E(t,d_p )`` dt rightａP_b (d_p ) ```d`d_p]

Integrating the above equation yileds the mean reduction degree of iron ore particles in the bed.

RESULTS AND DISCUSSION

Particle Degradation

Cold ore particles are charged into the bed R1 maintaining at a high temperature,and they are under thermal stress due to rapid heat transfer from the bed at the initial step of the prereduction stage. Furthermore, iron oxides undergo phase shifts in order of Fe2O3 → Fe3O4 → w□stite □ Fe depending on reduction degree during reduction process. The phase shifts cause considerable volume expansion and contraction. The particles are then stressed and broken off into pieces. In order to account for such a particle degradation phenomena, it is assumed that the broken particles undergo linear shrinkage mainly due to attrition, abrasion, and collision during the final reduction stage. Figure 2 shows the particle size distribution in R1 after the pre- and final reduction stages. It is seen that the weight fraction of large feed particles is decreased, but new small particles are formed and show wide size distribution after prereduction. Then, the particles discharged from the prereduction stage are further shrunk during the final reduction stage.

Reduction Behavior of Iron Ores

The effect of bed temperature on the reduction of iron oxides was predicted varying the bed temperature from 973 to 1033K for prereduction, and from 1073 to 1133K for final reduction, respectively. The model predictions are shown in Figures 3 and 4 in terms of reduction degree, gas utilization degree, and gas oxidation degree. It is seen from Figure 3 that for the prereduction stage, the reduction degree (R.D) is much affected by the bed temperature, and the R.D in R2 is about 6 - 10% greater than that in R1. This is explained by the fact that the fines in R2 has faster reduction rate than the coarse in R1. It is also seen that the gas oxidation degree(GOD) and the gas utilization degree(GUD) are dependent on the bed temperature, but the dependency is mot much compared to the reduction degree. Figure 4 shows that for the final reduction stage, the reduction is also influenced by the temperature, but the dependency is much less than that in the prereduction stage. Figure 5 shows the overall performance of the TFB system by comparing the predicted results with measured data. It is seen that overall agreement is quite satisfactory in spite of complex nature of the TFB system.

REFERNECES

1. F. Capel and M. Hirsch, Metallurgical Plant and Technology International,     3, 28 (1991).

2. S. Hayashi, S. Sayama, and Y. Iguchi, ISIJ Int., 30, 722(1990).

3. J. Szekely, J. W. Evans and H. Y. Sohn, Gas-Solid Reactions, Academic       Press, N.Y., (1976).

4. D. Kunii and O. Levenspiel, Fluidization Engineering, 2nd ed., Butterworth-

Heinemann (1991).