Effects of die geometry on cell nucleation of PS foams blown with CO<sub>2</sub>
Bibliographic record
Abstract
Abstract This paper investigates the effect of varying the geometry of the die on the cell nucleation behavior of extruded PS foams blown with CO2. Three interchangeable groups of carefully calibrated filamentary dies have been used in the experimental study. The dies were deliberately designed to have either different pressure drop rates while having identical die pressures and flow rates, or different die pressures while having identical pressure drop rates and flow rates. The experimental results revealed that the geometry of the die governs the cell density of extruded PS foams, especially because of its significant effect on the pressure drop rate across the die. However, the effect of the die back pressure on the cell density was found to be marginal, whereas its effect on the cell morphology was found to be predominant. In addition, regardless of die geometry, the CO2 content proved to be a very sensitive parameter with respect to the cell nucleation behavior of extruded PS foams. On the other hand, the cell density was slightly improved by an increase of the tale content, especially at reduced concentrations of CO2.
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) | 0.000 | 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".