2019
DOI: 10.1016/j.mineng.2019.105876
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Pressing iron ore concentrate in a pilot-scale HPGR. Part 2: Modeling and simulation

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Cited by 14 publications
(12 citation statements)
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“…The model consists of linking outputs from DEM simulations to the population balance model (PBM). This later is represented by the energy-specific selection function proposed by Herbst and Fuerstenau (1980), a nonnormalizable breakage distribution function used by Campos et al (2019a) and selected expressions proposed by Torres and Casali (2009). Following this approach, DEM simulations allow to capture the effect of design and operating variables on the HPGR performance, while the PBM model allows dealing with the entire range of particle sizes fed to the machine.…”
Section: Proposed Hybrid Modelmentioning
confidence: 99%
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“…The model consists of linking outputs from DEM simulations to the population balance model (PBM). This later is represented by the energy-specific selection function proposed by Herbst and Fuerstenau (1980), a nonnormalizable breakage distribution function used by Campos et al (2019a) and selected expressions proposed by Torres and Casali (2009). Following this approach, DEM simulations allow to capture the effect of design and operating variables on the HPGR performance, while the PBM model allows dealing with the entire range of particle sizes fed to the machine.…”
Section: Proposed Hybrid Modelmentioning
confidence: 99%
“…Two functions must be known in order to solve the resulting system of differential equations: b ij and S i,k . Campos et al (2019a) and Faria et al (2019) observed that, for some Brazilian iron ores, the non-normalizable breakage function proposed by King (2001) was required to describe their response, being given by:   1 for…”
Section: Proposed Hybrid Modelmentioning
confidence: 99%
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“…The scaling-up procedure was performed based on a particular mechanical property of the HPGR (the ratio of the roll gap to the diameter), which was assumed to remain constant at any operating scale. Similarly, Campos et al [32] also cast the calibration problem as a least squares optimization problem. The objective function was designed to consider the logarithms of the measured and estimated values of the cumulative PSD, and the resulting problem was solved using a direct search algorithm from fminsearch in MathWorks MATLAB ® .…”
Section: Literature Reviewmentioning
confidence: 99%