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Mathematical Models for Gas Distribution in the Ironmaking Blast Furnace

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The Application of Mathematics in Industry

Abstract

The distribution of gas flow through the ironmaking blast furnace is of fundamental importance in the control of furnace productivity, fuel rate and campaign life. Mathematical models which describe the flow distribution of gases have been developed for use in both fundamental and applied analysis of the blast furnace gas flow problem.

The gas flow distribution through the furnace softening-melting zone, which consists of a series of interconnected packed beds of coke particles separated by impervious ferrous layers, has been predicted by solution of a series of non-linear compressible flow pressure loss equations based on an empirical relationship by Ergun. A further model, which employs the vectorial form of the Ergun equation, has been developed for prediction of the two-dimensional flow of gas exiting from the softening-melting zone and its subsequent distribution through the stack of the furnace.

This paper describes the solution procedures employed in the above models and their application to actual blast furnace conditions. As well as providing fundamental understanding of blast furnace operations, the practical applications of these models include prediction of the softening-melting zone shape using blast furnace shell pressure tapping information; interpretations of furnace gas temperature and composition measurement probes located in the shaft; and determination of optimum conditions for improved gas distribution within the furnace.

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References

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© 1982 Springer Science+Business Media Dordrecht

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Burgess, J.M., Jenkins, D.R., de Hoog, F.R. (1982). Mathematical Models for Gas Distribution in the Ironmaking Blast Furnace. In: Anderssen, R.S., de Hoog, F.R. (eds) The Application of Mathematics in Industry. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-7834-1_3

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  • DOI: https://doi.org/10.1007/978-94-011-7834-1_3

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-011-7836-5

  • Online ISBN: 978-94-011-7834-1

  • eBook Packages: Springer Book Archive

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