Non Isothermal Hybrid Approach Using the Perfect Gas Law and Explicit Dynamic Finite Element Method for Modeling of Thermoforming and Blow Molding Processes
Bibliographic record
Abstract
Thermoforming of cut sheets is extensively used in the industry for various commercial applications. In this process, the sheet is heated to a softened state and subsequently deformed into the mould due to an applied pressure, a vacuum, a moving plug or a combination of these media. The thermoforming-process market is expanding to complex geometries and to a list of potential materials. In this work, I use a no isothermal hybrid approach which combines the dynamic finite element method and the thermodynamic law of perfect gases to study the effect of the temperature of the air flow on the blowing of a thin, isotropic and incompressible thermoplastic membrane. The viscoelastic behaviour of the K-BKZ model is considered. The Lagrangian formulation together with the assumption of the membrane shell theory is used. The numerical validation is performed by comparing the obtained results with the theoretical results for the HDPE grade. Moreover, the effect of the temperature on the thickness and stresses distribution 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) | 0.000 | 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 | 0.000 |
| 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".