September 10, 2025Applied SciencesOpen Access

Comparative Study to Evaluate Mixing Efficiency of Very Fine Particles

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CGM significantly reduced computational time by over 90%, maintaining acceptable accuracy in LMI values.
The Lacey mixing index effectively quantified mixing uniformity across various CGM scaling factors.
Mixing behaviors were consistent under various CGM conditions, with final LMI errors below 5% in most scenarios.
Practical guidelines were provided for optimizing industrial-scale particle-mixing processes and doing scalable DEM simulations.

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This comparative study shows that coarse-grain modeling improves mixing efficiency in industrial mixers, suggesting reduced computational costs.

Lee et al. (2025) studied this question.

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This comparative study shows that coarse-grain modeling improves mixing efficiency in industrial mixers, suggesting reduced computational costs.