Effects of pellet-sinter interaction parameters on component segregation and bed porosity considering flow velocity and mixture composition

A DEM study

Journal Article (2024)
Author(s)

Raïsa Roeplal (TU Delft - Mechanical Engineering)

Yusong Pang (TU Delft - Mechanical Engineering)

Dingena Schott (TU Delft - Mechanical Engineering)

Research Group
Transport Engineering and Logistics
DOI related publication
https://doi.org/10.1016/j.apt.2023.104322 Final published version
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Publication Year
2024
Language
English
Research Group
Transport Engineering and Logistics
Issue number
2
Volume number
35
Article number
104322
Page Views
295
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Abstract

Bed permeability is a crucial factor in blast furnace performance which depends on the material distribution achieved through charging. Since a homogeneous bed of pellet and sinter is recommended, it is crucial to understand whether segregation of the pellet-sinter mixture occurs during charging. The Discrete Element Method is useful in this regard; however, simulations of pellet-sinter mixture charging currently lack credibility since pellet-sinter interaction parameters have not yet been calibrated and validated. Determining pellet-sinter interaction parameters will require significant efforts, so it is useful to know whether mixture segregation and the resulting bed permeability are sensitive to these parameters. In this work, we investigate to what extent the restitution coefficient, sliding friction coefficient and rolling friction coefficient between pellet and sinter affect segregation during bed formation and the resulting permeability in terms of porosity using a simplified charging setup. The investigation is done for different mixture compositions and flow velocities, and analysis settings including sample size and sampling directions. We conclude that all parameters affect segregation and porosity, regardless of the composition and velocity. Hence, all mixture parameters including the interaction parameters between the components must be carefully calibrated when developing a model for predicting permeability.