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Hot Metal (hot + metal)
Selected AbstractsA chaos-based iterated multistep predictor for blast furnace ironmaking processAICHE JOURNAL, Issue 4 2009Chuanhou Gao Abstract The prediction and control of the inner thermal state of a blast furnace, represented as silicon content in blast furnace hot metal, pose a great challenge because of complex chemical reactions and transfer phenomena taking place in blast furnace ironmaking process. In this article, a chaos-based iterated multistep predictor is designed for predicting the silicon content in blast furnace hot metal collected from a pint-sized blast furnace. The reasonable agreement between the predicted values and the observed values indicates that the established high dimensional chaotic predictor can predict the evolvement of silicon series well, which conversely render the strong indication of existing deterministic mechanism ruling the dynamics of complex blast furnace ironmaking process, i.e., a high-dimensional chaotic system is suitable for representing the blast furnace system. The results may serve as guidelines for characterizing blast furnace ironmaking process, an extremely complex but fascinating field, with chaos in the future investigation. © 2009 American Institute of Chemical Engineers AIChE J, 2009 [source] Thermomechanical modeling and simulation of aluminum alloys during extrusion processPROCEEDINGS IN APPLIED MATHEMATICS & MECHANICS, Issue 1 2008Farhad Parvizian The purpose of this work is to simulate the microstructure development of aluminum alloys during hot metal forming processes such as extrusion with the help of the Finite Element Method (FEM). To model the thermomechanical coupled behavior of the material during the extrusion process an appropriate material model is required. In the current work a Johnson,Cook like thermoelastic viscoplastic material model is used. To overcome the numerical difficulties during simulation of extrusion such as contact problem and element distortion an adaptive meshing system is developed and applied. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Using non-linear GARCH model to predict silicon content in blast furnace hot metalASIAN JOURNAL OF CONTROL, Issue 6 2008Jiu-sun Zeng Abstract Forecasting of silicon content in blast furnace (BF) hot metal has always been an important tool in the control of iron-making process. To get an accurate prediction of silicon content is an urgent task for BF operators. The approach based on generalized autoregressive conditional heteroskedastic (GARCH) has been introduced to predict step-ahead silicon content in BF hot metal. The algorithm has been explained in detail and simulation results have been analyzed from different criteria. It is shown that the algorithm gives good results and is helpful for practical production. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] Metallurgical Characteristics and Effectiveness of Metallic Charges in Electric Arc FurnaceASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, Issue 3-4 2006Cheng-Wu Du The use of direct reduced iron (DRI), hot metal, cold pig iron, decarburized granular iron, iron carbide, and complex metal charges to replace scrap metal as the feedstock to an electric arc furnace not only resolves the lack of scrap supply, but is also very helpful in diluting the residual elements in the scrap, thus improving the quality of the steel. It has now become possible to produce high-quality steel in an electric arc furnace. In this paper, the characteristics and effectiveness of various metallic charges for use in an electric arc furnace (EAF) are discussed. [source] | |||||||||||||