Squeeze flow in multilayer polymeric films: Effect of material characteristics and process conditions
Bibliographic record
Abstract
Abstract In this work, effects of sealing temperature, time, pressure, as well as sealant thickness and viscosity on squeeze out flow (SOF) in heat sealing were examined. A new image analysis approach is presented to quantify SOF in heat sealing. It was found that increasing temperature or pressure could improve SOF but only in thick 130 μm sealants and reducing the sealant thickness to 50 μm suppressed SOF. Reducing viscosity in 50 μm sealant films was also found to improve SOF only at high‐sealing pressure and long sealing times. Three approaches were used to model SOF: analytical one‐dimensional model, numerical one‐dimensional model using finite difference method (FDM), (iii) Numerical two‐dimensional model using finite element analysis. Heat transfer was modeled, and it was shown that heat transfer induces a delay in SOF. When the FDM and the heat transfer models were combined, a good agreement between experimental and model prediction could be obtained. In addition, modeling results showed that SOF occurred in shear rates within the transition region between the Newtonian and Power‐law regions. This indicates the importance of considering the Carreau‐Yasuda fluid behavior in modeling of SOF.
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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 | 0.000 |
| 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) | 0.000 | 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".