Membrane inflation of polymeric materials: Experiments and finite element simulations
Bibliographic record
Abstract
Abstract A high‐speed optical measurement system, which is capable of measuring transient surface shape, is used in the polymer membrane inflation experiments. The accurate measurement data, which is an array of points, with known Cartesian coordinates and with respect to a fixed coordinate system, provides a source for further bubble shape analysis. Inflation pressure is correlated with each bubble shape measurement. The measured results reveal the importance of the thermal warpage and temperature gradient in the bubble inflation tests. Potential errors in the material parameter calculation, which are caused by assuming uniform temperature and zero thermal warpage, are pointed out. Consequently, a finite element analysis has been carried out to simulate the membrane inflation with/without thermal warpage and the temperature gradient. The material parameters obtained considering the thermal warpage and temperature gradient yield improved agreement with the experimental data. Although in this paper the measurement data is mainly used for the determination of the material parameters in the bubble inflation tests, they are also a source of validating other computer‐aided simulations as well as in the study of the thermal shrinkage of polymer products.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".