Scaling-up a Reactive Extrusion Operation: A One-dimensional Simulation Analysis
Bibliographic record
Abstract
Abstract The peroxide-initiated degradation of polypropylene is simulated by means of a one-dimensional (1D) reactive extrusion (REX) model. Two scale-up rules, namely, constant thermal time and specific energy consumption (SEC) are evaluated for co-rotating intermeshing twin screw extruders (COITSEs) of various sizes. The weight-average molecular weight (Mw) and the polydispersity index (PDI) are selected as the evaluation parameters for testing the scale-up procedures being analyzed. The results for the simulated operating conditions show that when the REX operation is scaled-up under constant thermal time, very good agreement is obtained between the Mw and PDI of the larger extruders and the values of these parameters corresponding to the reference extruder. For the constant SEC approach, more significant variations are observed for both of the aforementioned parameters. In the case of the constant thermal time scale-up approach, the effect of operating conditions of the reference extruder on the scaled-up operation is further analyzed. For a constant screw speed, when the reference mass throughput increases the predicted time of extrusion increases. Regarding the temperature of reaction, the higher increase of this parameter corresponds, in general terms, to the lower mass throughputs and higher screw speeds specified for the reference extruder.
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 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".