Effect of the Chemical and Morphological Conditions of the Die Wall on the Extrusion of Linear Polyolefins
Bibliographic record
Abstract
Abstract This study examines the effects of average surface roughness and composition of the die wall surface on the critical shear stress for the onset of instabilities in die extrusion. Increasing the average surface roughness of the die wall from 0.1 to 15m produced an increase of the critical shear stress for the onset of flow instabilities by as much as 20% during the extrusion of HDPE. The surface of the extrudates obtained with dies having an average surface roughness greater than 5lm showed lines and grooves along the direction of extrusion. Chrome-plated and nickel-plated dies showed an average 28% increase in the critical shear stress as compared to conventional steel dies. The chemical composition of uncoated steel dies wall surfaces, including the presence of iron oxide, did not affect the critical shear stress for the onset of sharkskin significantly regardless of the type of resin used.
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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) | 0.001 | 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".