Scale-up of High-Shear Mixer Granulators
Bibliographic record
Abstract
The mechanics of particle interactions and the prevailing level of compressive stresses and shear strains are affected by the scale of operation, which in turn affects the granule structure, strength and functional properties. This may be the main reason why the current scaling relationships are ineffective from a viewpoint of product engineering.In a research programme supported by the EPSRC and four industrial organizations, i.e. Borax Europe, Hosokawa Micron BV, Pfizer Global Research and Development, and Procter and Gamble, we have addressed the following topics: Development of methodologies for quantifying the structure of granules in terms of internal voidage and composition distributions, strength, shape, size and density. Identification of the parameters that affect the structure of granules by using fundamental theories of microscopic contact mechanics of particles using DEM, macroscopic granular flow dynamics and kinetics of wetting. Experimental work across several length scales (1 L, 5 L, 50 L and 250 L) to aid the analysis of the process. In this paper, an overview of findings and their implications for granulation practice is presented.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".