A <scp>CFD‐DEM</scp> approach to study the breakup of fractal agglomerates in an internal mixer
Bibliographic record
Abstract
Abstract In this work we present a method to investigate the breakup of filler agglomerates in an internal mixer during a compounding operation. The method employs computational fluid dynamics (CFD) simulations along with discrete element method (DEM) simulations. CFD simulations are performed to compute the flow field inside a 2D section of a typical batch internal mixer with two tangential rotors. During the CFD simulation, we assume the filler agglomerates to behave as tracer particles, carried passively by the flow. The trajectory of the tracers, together with the experienced velocity gradients, are fed to a DEM code, built in the framework of Stokesian dynamics. The code computes the mechanical response of the agglomerates along the trajectory, from which it is finally possible to ascertain the occurrence of breakup. Simulations are performed to evaluate the robustness of the method on two different rotor speed ratio conditions and varying agglomerate strength.
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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 | 0.001 | 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".