A 3D Simulation Analysis of Reactive Flow in Screw Elements of Closely Intermeshing Twin Screw Extruders
Bibliographic record
Abstract
Abstract The peroxide-initiated degradation of polypropylene in conventional screw elements of closely intermeshing twin-screw extruders is analyzed by means of a three-dimensional (3D) simulation approach. The 3D simulations of the reacting flow are implemented under the assumption of steady-state flow conditions, and scale-up considerations are addressed by simulating screw elements of two different size extruders. The effects of the initial peroxide concentration and reference mass throughputs on processing parameters are analyzed in terms of the specified extruder size. In this study, the scaled-up mass throughput is determined under the assumption of constant residence time. For the implemented processing conditions, the final values of the weigh-average molecular weight (Mw) and polidispersity index (PDI) for both the reference and scaled-up screw elements are similar when the flow rate is close to that corresponding to the maximum conveying capacity of the screw elements. For more restricted flow conditions, however, lower values of both the Mw and PDI are obtained for the larger screw element. Additionally, a previously proposed scale-up procedure from one-dimensional (1D) simulations is evaluated by means of a 3D simulation analysis. The results of this evaluation show a good agreement between the trend of the 3D and 1D simulation results.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".