Computer Simulation of Continuous Casting Processes: A Review
Nitin Amratav,
Kulyant Kumar,
Megad Pillai
Issue:
Volume 10, Issue 3, September 2021
Pages:
31-41
Received:
28 August 2021
Accepted:
13 September 2021
Published:
29 September 2021
Abstract: Steelmaking is the second step in producing steel from iron ore. In this stage, impurities such as sulfur, phosphorus, and excess carbon are removed from the raw iron, and alloying elements such as manganese, nickel, chromium, and vanadium are added to produce the exact steel required. Modern steelmaking processes are broken into two categories: primary and secondary steelmaking. Primary steelmaking uses mostly new iron as the feedstock, usually from a blast furnace. Secondary steelmaking uses scrap steel as the primary raw material. Gases created during the production of steel can be used as a power source. Steelmaking is presently a grounded innovation driven by plant, exploratory and computational examination. The continuous casting process comprises many complicated phenomena in terms of fluid flow, heat transfer, and structural deformation. The important numerical modeling method of the continuous casting process has been discussed in reference in this work. With the recent advancement in metallurgical methods, the continuous casting process now becomes the main method for steel production. To achieve efficient and effective production, the manufacturers of steel keep on searching for new methods which increase productivity. The present work describes molten steel flow, heat transfer, solidification, electromagnetic applications, formation of the shell by solidification and coupling, etc.
Abstract: Steelmaking is the second step in producing steel from iron ore. In this stage, impurities such as sulfur, phosphorus, and excess carbon are removed from the raw iron, and alloying elements such as manganese, nickel, chromium, and vanadium are added to produce the exact steel required. Modern steelmaking processes are broken into two categories: pr...
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Prediction and Optimization of Internal Return Fines Generation in Iron Ore Sintering Using Machine Learning
Srijith Mohanan,
Prajna Mohapatra,
Arun Kumar C.,
Rama Krishna Adepu,
Vipul Mohan Koranne,
Y. G. S. Prasad,
A. S. Reddy,
R. V. Ramna
Issue:
Volume 10, Issue 3, September 2021
Pages:
42-47
Received:
3 August 2021
Accepted:
13 August 2021
Published:
28 October 2021
Abstract: Prior to dispatch of sinter to the blast furnace for hot metal production, the sinter product from the sinter cooler is screened to remove smaller/finer particles. The undersize so generated is called internal return fines, which are generally recirculated into the sintering machine. A very high level of internal return fines generation limits the use of virgin ore for sintering which may hamper sinter productivity. Recently, the sinter plant at Tata Steel’s Kalinganagar works has faced issues of high internal return fines generation. As the sinter plant begins to increase its productivity levels, it becomes critical to control the generation of internal return fines to allow fresh material consumption. Limited literature is available on factors affecting the internal return fines generation in sinter plant. Given the current computational capabilities, a machine learning model was developed to ascertain the factors affecting the internal return fines generation. The development of the machine learning model and the optimization carried out based on model output is described in this work. The key parameters affecting the internal return fines generation were the sintering rate, sinter basicity, charge density and temperature in the ignition hood. In Kalinganagar, the increase in ignition hood temperature was limited by the furnace refractory condition. Further, the sinter basicity is determined by the percentage of sinter in blast furnace burden. Incorporating these constraints, the model was used to optimize the process parameters to generate the lowest possible return fines. The understanding generated from this machine learning framework has resulted in a reduction of 2-3% in internal return fines generation, which implied higher net sinter production.
Abstract: Prior to dispatch of sinter to the blast furnace for hot metal production, the sinter product from the sinter cooler is screened to remove smaller/finer particles. The undersize so generated is called internal return fines, which are generally recirculated into the sintering machine. A very high level of internal return fines generation limits the ...
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