Validation of a population balance model for iron ore dry grinding at the IJmuiden pelletizing plant
[Display omitted] •Description of flowsheet of dry iron ore mills.•Application of batch test data on individual ores•Breakage rate/selection function vs. cumulative rate models•Population Balance Model of grinding an ore mixture•Sampling campaign results from 3 parallel process lines The dry closed...
Gespeichert in:
Veröffentlicht in: | Minerals engineering 2024-11, Vol.218, p.109019, Article 109019 |
---|---|
1. Verfasser: | |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | [Display omitted]
•Description of flowsheet of dry iron ore mills.•Application of batch test data on individual ores•Breakage rate/selection function vs. cumulative rate models•Population Balance Model of grinding an ore mixture•Sampling campaign results from 3 parallel process lines
The dry closed circuit ball mill circuits of Tata Steel’s pelletizing plant in IJmuiden receive a variable mixture of ores to produce a dry ground iron ore mixture. A population balance model was developed to help study circuit unit performance, the impact of installation modifications and influence of input materials on the performance of the circuits. Batch grinding tests were done on input materials, measuring size distribution as function of time using high resolution laser diffraction measurements. Data from the tests were fitted to a breakage and selection function model as well as a cumulative rate model. A population mass balance model of the circuit was developed based on the breakage and selection function model, as it showed a better fit to the batch data for the majority of materials. The circuit model also incorporates a mill model and model for the various classifier stages. The circuits were sampled at various locations in the flow sheet, showing fair overall agreement with model calculations. Differences between model and observations are highlighted and improvements in the modelling technique as well as the sampling discussed. |
---|---|
ISSN: | 0892-6875 |
DOI: | 10.1016/j.mineng.2024.109019 |