2023-Sustainable Industrial Processing Summit
SIPS2023 Volume 1. Assis Intl. Symp/ Advanced Iron & Steel Making
| Editors: | F. Kongoli, T. Usui, R.A. Vilela, J. A. de Castro, W. F. Santos, J. Poveromo, GS. Mahobia, B. Deo |
| Publisher: | Flogen Star OUTREACH |
| Publication Year: | 2023 |
| Pages: | 441 pages |
| ISBN: | 978-1-989820-72-8 (CD) |
| ISSN: | 2291-1227 (Metals and Materials Processing in a Clean Environment Series) |
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MATHEMATICAL MODELING, SIMULATION AND OPTIMIZATION OF IRON ORE SINTERING PROCESS FOR QUALITY, FUEL EFFICIENCY AND POLLUTION CONTROL
Niloy Kumar Nath1; Paulo Assis2; Jose Adilson de Castro3;1JSPM'S RAJARSHI SHAHU COLLEGE OF ENGINEERING, PUNE, INDIA, Pune, India; 2UFOP, OURO PRETO, Ouro Preto, Brazil; 3UFF - FEDERAL FLUMINENSE UNIVERSITY, Volta Redonda, Brazil;
Type of Paper: Regular
Id Paper: 338
Topic: 2
Abstract:
Iron ore sintering is a high temperature, high volume process for producing raw material for blast furnace, and the quality requirements for sinter is high strength and Tumbler index, good reducibility and reduction degradation index (RDI). The process involves high temperature gas-solid reaction, drying and condensation, and melting and solidification phenomena. Simulation of the iron ore sintering process reveals considerable variation in thermal and melting profile in the sinter bed [1,2]. Melting is very low in the top critical zone just below the ignition hood, giving rise to low sinter strength and high return fines, where as in the bottom layers melting is much higher, producing glassy phase with low reducibility.
Suction pressure applied in the wind boxes for gas velocity in the sinter bed is one of the important process parameter for the sintering process, which is optimized here in three locations, top, middle and lower zones by optimization technique such as Genetic Algorithm (GA), for better melting and sinter quality in the three zones representing the total sinter strand [3].
Sinter quality which is combination of high strength and good reducibility, can be attributed to partial melting of about 30%, in the sinter bed. However due to non-uniform combustion zone in the sinter bed, melting is very low in the top critical zone, whereas melting is much higher in the lower regions. Therefore, to overcome this non-uniform melting along the sinter bed height, two-layer sintering process is envisaged with higher coke rate in the top layer, and lower coke rate in the bottom layer. The two-layer sintering process have been optimized by using Multi-Objective Genetic Algorithm, with different coke rates in the top and bottom layers. The thickness of the top and bottom layers are also varied for optimization. The two objectives for optimization are uniform 30% melting throughout the sinter bed, along with minimum overall coke rate, giving rise to two conflicting objectives for Pareto optimization [4]. The lower coke rate in the bottom layer up to the Burn through point (BTP), gives additional benefit of reducing pollution and greenhouse gases [2,5] like CO, CO2, SOx, and toxic gases such as NOx, dioxin and furan.
Keywords:
Iron Ore Sintering; Two-layer Sintering; Gas-Solid reaction; Ergun's equation; Genetic Algorithm; Pareto front; NOx; DioxinReferences:
[1] N. K. Nath, A. J. D. Silva and N. Chakraborti: Dynamic Process Modeling of Iron Ore Sintering: Steel Research: (1997); Vol. 68, No. 7, 285-292.[2] J.A.D. Castro, N.K. Nath, A.B. Franca, V.S. Guilherme and Y. Sasaki. Analysis of iron ore sintering process based on alternative gaseous fuels from steelworks by multiphase multicomponent model; Ironmaking and Steelmaking, (2012), Vol. 39, No. 8, pp 605-613
[3] N. K. Nath and Kishalay Mitra. Optimization of Suction Pressure for Iron Ore Sintering by Genetic Algorithm. Ironmaking and Steelmaking, 2004, Vol. 31, No 3, pp 199-206.
[4] N. K. Nath and K. Mitra. Mathematical modeling and optimization of two-layer sintering process for sinter quality and fuel efficiency by genetic algorithm; Materials and Manufacturing Processes, (2005), Vol. 20, No. 3, pp 335-349.
[5] C.F.C.D. Assis, J.A.S. Tenorio, P.S. Assis and N.K. Nath. Experimental Simulation and Analysis of Agricultural Waste Injection as an Alternative Fuel for Blast Furnace; Energy & Fuels, ACS Pub. 2014, Vol. 28, pp7268-7273.