Development of a synergistic damage mechanics model to predict evolution of ply cracking and stiffness changes in multidirectional composite laminates under creep
Bibliographic record
Abstract
A physics-based multi-scale model that couples viscoelasticity and time-dependent damage evolution for general multidirectional laminates subjected to long-term creep loading is developed. The viscoelastic ply behavior is evaluated using a nonlinear Schapery-type viscoelastic model, while a methodology employed within the framework of classical laminate theory is used to predict the corresponding laminate time-dependent response. The evolution of microscopic ply cracks in multiple plies with different orientations during creep loading is predicted using an energy-based approach, and the corresponding laminate stiffness degradation is evaluated using a synergistic damage mechanics-based model that relies on computational micromechanics in lieu of costly experimental data. The developed model is used to predict the evolution of ply cracks and the viscoelastic stress–strain response of various cross-ply and multidirectional laminates under quasi-static and creep loading. Predicted strains, compliance changes and crack density evolutions show excellent agreement with available experimental creep data for different laminate stacking sequences, providing validation for the model. Predictions are also made for two additional multidirectional laminates in order to investigate the effect of off-axis ply angle on the creep response, which demonstrates the versatility of the model and its usefulness in assessing the long-term durability of general multidirectional composite laminates.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".