A coupled level set‐arbitrary Lagrangian–Eulerian method applied to numerical simulation of parison pinch‐off in extrusion‐blow molding
Bibliographic record
Abstract
Abstract An outstanding problem in extrusion blow‐molding process of polymers is the precise prediction of the parison shape inside the part along the pinch‐off weld. Such a prediction is highly relevant for producing components with an accurate wall thickness distribution along the parting line as blow‐molded parts often fail at the parison pinch‐off weld of the mold parting line. In this paper, we report on the numerical study of the parison pinch‐off modeling in extrusion‐blow molding using a coupled level set (LS)‐arbitrary Lagrangian–Eulerian (ALE) method. The deformation of the parison‐free surface during the mold closing stage is approximated by means of the level set technique on a deforming mesh domain caused by the simultaneous mold halves displacement. The multi‐mode Phan‐Thien and Tanner (mPTT) constitutive equation is employed to model the parison deformation in the pressure zone, the flash pocket, and along the pinching edge. The developed LS–ALE approach is first validated on a benchmark squeeze flow problem between two parallel coaxial disks for both Newtonian and viscoelastic fluids before the numerical simulation results for the pinch‐off problem are discussed. We report numerical experiments related to the mold closing velocity effects on the parison shape behavior and parison wall thickness distribution along the pinch‐off weld for a high‐density polyethylene (HDPE). For this viscoelastic polymer, the parison exhibits a rounded shape along the pinch‐off weld line inside the part, and this rounding becomes more pronounced as the mold closing velocity increases, in accordance with experimental observations. Whereas, for a Newtonian fluid, the parison displays an angular V‐shape along the pinch‐off weld inside the part and does not depend on the mold closing speed. The parison thickness along the weld line is increased by 126% for the HDPE studied while it only increases by 72% for a Newtonian fluid with the same zero shear‐rate viscosity. The predicted parison wall thickness distribution around the pinching zone represents an important step in optimizing both processing conditions and the mold pinch‐off design. Highlights A coupled LS–ALE method was developed to simulate parison pinch‐off. The method successfully validated on squeeze flow for Oldroyd‐B fluid. Viscoelastic fluids exhibit a rounded shape at pinch‐off weld inside part. Newtonian fluids exhibit a V‐shape along pinch‐off weld inside part. Material rounded shape inside part increases with mold closing speed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".