Modeling flow and cell formation in foam sheet extrusion of polystyrene with <scp>CO<sub>2</sub></scp> and co‐blowing agents. Part <scp>II</scp>: Process model
Bibliographic record
Abstract
Abstract In foam extrusion, process parameters, material properties, and the blowing agent have an influence on the resulting foam properties. For safety and environmental reasons, carbon dioxide (CO2) has gained importance as physical blowing agent for the production of low‐density polystyrene foam sheets. The sole use of CO2 often leads to corrugation, open cell structures, or surface defects on the foam sheet. As an alternative, blowing agent mixtures based on CO2 and organic solvents such as ethanol, acetone, or ethyl acetate can be used, changing solubility and flow behavior of the gas‐loaded melt. A model approach for describing foam extrusion of polystyrene with various blowing agent mixtures in an annular gap die is developed. Part I of the paper describes the modeling of material properties. In Part II, the process model including nucleation and cell formation in the flow field is developed and applied to a foam sheet extrusion process. Based on the material model, melt flow and formation of cells are modeled by a step‐wise calculation along the die, showing good agreement with experimental data. Dimensionless numbers are used to describe the foaming process and a parameter study based on these dimensionless numbers is presented.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".