Capillary Extrusion and Swell of a HDPE Melt Exhibiting Slip
Bibliographic record
Abstract
Abstract The extrudate (die) swell of a high‐density polyethylene (HDPE) melt was studied both experimentally and numerically under slip conditions. The excess pressure drop due to entry (entrance pressure drop), the effect of pressure and temperature on viscosity, and the slip effects on the capillary data analysis have been examined. Using a series of capillary dies having different diameters,D, and length‐to‐diameterL/Dratios, a full rheological characterization has been carried out and the experimental data have been fitted both with a viscous model (Carreau–Yasuda) and a viscoelastic one (the Kaye‐Bernstein, Kearsley, Zapas/Papanastasiou, Scriven, Macosko or K‐BKZ/PSM model). Particular emphasis has been placed on the effects of wall slip (significant for HDPE). It was found that viscous modeling underestimates the pressures drops (especially at the higher apparent shear rates andL/Dratios) and predicts virtually no extrudate swell. On the other hand, the viscoelastic simulations were capable of reproducing the experimental data well, and this was particularly true for the pressure drop. The prediction of viscoelastic extrudate swell presented a problem, since the simulations grossly overpredict it due to the highly elastic nature of the melt. This occurs despite the presence of severe slip at the wall, which brings the swell down considerably. At this point it is not clear whether this is due to the viscoelastic model used or other phenomena, such as sagging and/or cooling, when simply extruding in the atmosphere. © 2012 Wiley Periodicals, Inc. Adv Polym Techn 32: E369–E385, 2013; View this article online at wileyonlinelibrary.com . DOI 10.1002/adv.21285
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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 | 0.000 |
| 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 | 0.000 | 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".