Modeling of complex parison formation in extrusion blow molding: Effect of medium to large die heads and fuel tank geometry
Bibliographic record
Abstract
Abstract This work presents the effect of die geometry and die gap opening on the extrudate swell phenomenon, in complex parison formation using the vertical wall distribution system (VWDS) and partial wall distribution system (PWDS). The BlowParison © software from IMI is used to predict the parison formation for a combined VWDS/PWDS system, accounting for swell, sag, and nonisothermal effects. This software couples a fluid mechanics approach to represent the die flow, with a solid mechanics approach to represent the parison behavior outside the die, and a mathematical swell model to account for the pronounced elongational and shear stresses at high Weissenberg numbers. The emphasis is placed on experimental validation of the predicted parison dimensions using four diverging die geometries and different sets of VWDS/PWDS profiles. The experimental and predicted weight profiles for a dissected fuel tank are also presented. Both experimental and simulation results suggest a strong dependence of extrudate swell to the die geometry in the die land zone. The results also demonstrate the validity of the numerical predictions for part design purposes given the multitude of experimental validations presented in this work. POLYM. ENG. SCI., 2009. Published by the Society of Plastics Engineers
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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 | 0.001 | 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".