Study of particle trajectories, residence times and flow behavior in kneading discs of intermeshing co‐rotating twin‐screw extruders
Bibliographic record
Abstract
Abstract A three‐dimensional finite element model was implemented for the solution of mass and momentum conservation equations in the kneading disc section of an intermeshing co‐rotating twin‐screw extruder. The polymer melt was modeled with a Carreau constitutive equation. The particle tracking technique was used to obtain residence times and analyze distributive mixing for different length to diameter ratios (L/D) of kneading discs. Previous studies from Kalyon et al. (1) and Cheng and Manas‐Zloczower (2) have shown that the mixing performance of intermeshing co‐rotating twin‐screw extruders is highly dependent on the combination of screw configuration and operating conditions. The complexity of the geometry and the transient character of the flow demand powerful computational tools to characterize the flow and to develop a prediction tool for the analysis of relative performance between different configurations. Difficulties arise in the particle tracking technique because of the time discretization and the presence of moving boundaries. Results show the importance of particle history on the evaluation of the relative performance of different configurations of kneading blocks and suggest a reevaluation of the use of average flow characteristics for the analysis of mixing. Results also confirm the importance of an accurate description of the geometry and clearances in order to obtain information about relative mixing performance. Polym. Eng. Sci. 44:779–793, 2004. © 2004 Society of Plastics Engineers.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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 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".