Dynamic finite element analysis of nonlinear isotropic hyperelastic and viscoelastic materials for thermoforming applications
Bibliographic record
Abstract
Abstract In this work, a dynamic finite element method is used in modeling and numerical simulation of the viscoelastic and hyperelastic behavior of a thin, isotropic, and incompressible thermoplastic membrane. The viscoelastic behavior (Lodge, Christensen) and hyperelastic behavior (Ogden and Mooney‐Rivlin), are considered. The thermoforming of the sheet is performed under the action of perfect gas flows. The pressure load used in modeling is thus deduced from the thermodynamic law of perfect gases. The Lagrangian formulation together with the assumption of the membrane theory is used in the finite element implementation. The numerical validation is performed by comparing the obtained results with measured experimental data for the polymeric acrylonitrile‐butadiene‐styrene (ABS) membrane inflation. Moreover, the influence of the Lodge, the Christensen, the Mooney‐Rivlin, and the Ogden constitutive models on the thickness and on the stress distribution in the thermoforming sheet are analyzed. POLYM. ENG. SCI. 45:125–134, 2005. © 2004 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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".