Bibliographic record
Abstract
Abstract In this research, granular mixing in vertical ribbon mixers was studied by means of discrete element method (DEM) simulations. Time‐averaged velocity distributions, granular mixing, mean square displacement of tracer particles, diffusion coefficients, and Peclet number in axial and azimuthal directions were used to find the flow pattern of particles and the dominant mixing mechanisms. Strong azimuthal motion of particles was observed, and it was found that by decreasing the height in the mixer, this azimuthal motion becomes stronger. The effects of rotating speed, fill level, and filling method were studied on the quality of mixing, where the quality of mixing was assessed using relative SD mixing index. It was found that by increasing the rotation speed from ω s = 60 rpm‐120 rpm, the mixing quality improves in a linear trend. Decreasing the fill level from 12 cm‐11 cm did not change the mixing quality, while with further decrease of the fill level to 10 cm, the mixing quality was improved. The mixing quality was also much better when the powder was inserted side‐to‐side instead of in axial layers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".