ORALS

SESSION: IronTuePM2-R2	Assis International Symposium (9th Intl. Symp. on Advanced Sustainable Iron & Steel Making)
Tue. 28 Nov. 2023 / Room: Dreams 2
Session Chairs: Giovanni Felice Salierno; Session Monitor: TBA

16:00: [IronTuePM209] OS
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;
Paper Id: 338 [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.

References:
[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.

SESSION: IronWedAM-R2	Assis International Symposium (9th Intl. Symp. on Advanced Sustainable Iron & Steel Making)
Wed. 29 Nov. 2023 / Room: Dreams 2
Session Chairs: Alexandro Uliana; Mauricio Cota Fonseca; Session Monitor: TBA

12:50: [IronWedAM04] OL Plenary
SOFTWARE SYSTEM FOR MODEL BASED PROCESS CONTROL OF STEEL REHEATING IN BATCH AND CONTINUOUS FURNACE FOR OPTIMIZING HEATING TIME, ENERGY EFFICIENCY AND THERMAL HOMOGENIZATION
Niloy Kumar Nath¹ ; Paulo Assis² ; ¹JSPM's Rajarshi Shahu College of Engineering, Pune, India, Pune, India; ²UFOP, Ouro Preto, Ouro Preto, Brazil;
Paper Id: 340 [Abstract]

Reheating of steel ingots in batch furnace such as soaking pit and box furnace, and Concast steel products like bar, billets and slabs in continuous furnace such as walking beam, and pusher type furnace is an important step for further thermo-mechanical processing like forging and rolling operations.  Concast Steel and ingots are heated up to 1100 – 1250 C, and since this is a high temperature and energy intensive process, excess heating time will cause productivity and energy loss, as well as oxidation or scale loss. On the other hand, if it is heated very fast causing high thermal variation between the surface and core temperature, will lead to thermal stress, distortion and crack formation. Furthermore, rapid heating without thermal homogenization can cause problems during hot rolling or forging operations, which may lead to, roll stuck, cracking and forging problems. Therefore, the aim of the heating process is to avoid any excessive thermal stress, particularly in the vulnerable ferrite to austenite phase transformation range, and also to achieve thermal homogenization with optimum time and energy efficiency. To numerically simulate the process, a detailed two dimensional finite difference model is developed by using generalized axisymmetric equation, and Crank-Nicholson technique. To accurately simulate the process. The model also has to consider all the complexities of the process like anomalous behaviour of thermal conductivity of steel and latent heat of phase transformation. The model has been validated with limited number of Lab-experiments in a muffle furnace. Model based Process Control system have been developed for both batch and continuous reheating process, with Graphical User Interface (GUI) for plant application.  

References:
[1] N.K Nath, Arunava Chowdhury and Paulo S. Assis. ‘Numerical simulation of ingot and concast steel reheating in batch and continuous type furnace to optimize energy efficiency, quality and productivity’, STIS (2013), Jamshedpur, Dec. 16-18, P75.
[2] N.K. Nath and Sachin L. Borse. Process Model based Software System for Steel Reheating Furnace for Energy Efficiency, Quality and Productivity; Advances in Computational Science and Technology, Vol. 5, No. 2, (2012), pp 819-824.
[3] Priyamvada Praharaj and N.K. Nath. Numerical simulation and experimental study of ingot heating process for time and energy efficiency for quality and productivity of the process, 3rd STIS conf., (2017), IIT Kanpur, pp 435-438.
[4] Arunava Chowdhury and N.K. Nath. Mathematical model based software system for optimization of steel slab and ingot reheating in walking beam furnace; ISOR Journal of Mechanical and Civil Engineering (IOSR-JMCE), (2015), pp 12-20.