A macroscale damage model for the tensile and bending failure of C/C-SiC structural laminates
Bibliographic record
Abstract
This work presents a Finite Element approach to model the in-plane mechanical behavior of C/C-SiC fabrics at the lamina level, including the non-linear response of diverse lay-ups and the bending-to-tensile strength ratio at failure. The material model employs a decomposition into two idealized phases, which can be exploited to capture matrix- and fiber-dominated responses at an high level of abstraction. The constitutive law of the matrix phase adopts a Continuum Damage approach driven by two Tsai-Wu surfaces, while a quasi-brittle behavior is attributed to the fibers phase. This decomposition effectively represents the influence of matrix degradation on the response and failure of the laminates. Moreover, simulations reveal that a statistical distribution of the strength is required to represent some of the experimental outcomes. The correlation with experimental data that was achieved points out that the technique is a promising tool for supporting the early design phase of CMC structures.
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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 | 0.000 |
| 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".