Estimating Porosity of Agglomerated Products Using Optimized Sphere Packing

Author:

Marmolejo-Saucedo Jose Antonio1ORCID,Litvinchev Igor2ORCID,Bizhanov Aitber3ORCID,Yaskov Georgiy4,Romanova Tetyana5

Affiliation:

1. National Autonomous University of Mexico, Mexico

2. Nuevo Leon State University, Mexico

3. J.C. Steele and Sons, Inc., USA

4. Institute for Mechanical Engineering Problems, Ukraine

5. University of Leeds, UK

Abstract

The article presents the results of studying the dynamics of changes in the porosity of two-component briquettes and pellets depending on the size of particles and the proportions of components in the mixture using an optimized packing of spheres. Knowing the patterns of change in the porosity allows to optimize the strength of the briquette and pellets as well as to improve their behavior in the reduction processes in blast furnaces, steel making furnaces and in direct reduction reactors. A computation experiment based on heuristic simulation model was designed to study the change of the estimated porosity under increasing/substituting the number of larger spherical particles in the mixture of spheres. The results obtained made it possible for the first time to reveal the extreme nature of the change in the porosity of the briquette/pellet with the addition of larger particles, depending on the fractional composition of the briquette. The results obtained open up new opportunities for optimizing the placement of fine-grained materials in the charge of metallurgical furnaces.

Publisher

IGI Global

Reference35 articles.

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5. Chagas, Machado, & Conti, & Frigini. (2015). Use of artificial neural network in determination of bed permeability during drying stage of iron ore pellets. AISTech - Iron and Steel Technology Conference Proceedings, 1, 1029-1036.

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