Phase field modeling on elastomers considering the nonlinear materialviscosity based on staggered algorithm
Bibliographic record
Abstract
With inevitable flaws, elastomers are susceptible to rupture leading to the reduction in stretchability and loss of functionality. Numerical study on the rupture of viscoelastic elastomers is still at a tentative stage with challenges stemming from the extreme large deformation and the highly nonlinear material properties. In the present work, a finite element (FE) framework is proposed with the incorporation of polymer dynamics into the phase field modeling (PFM) based on the staggered algorithm in Abaqus. The driving force to the fracture of viscoelastic elastomers is identified and the micro-mechanism of material viscosity is further adjusted with the consideration of polymer chain breakage to capture the disentanglement due to the material damage. The rateinsensitive fracture behavior is also accurately captured in the highly rate-dependent visco-elastomeric materials. The FE model is validated in comparison with existing experimental data, and is expected to provide guidance for the design of elastomer-based transducers.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".