Sensitivity Analysis of Fiber-Matrix Interface Parameters in an SMC Composite Damage Model
Bibliographic record
Abstract
This contribution shortly introduces the anisotropic, micromechanical damage model for sheet molding compound (SMC) composites presented in the authors’ previous publication [1]. As the considered material is a thermoset matrix reinforced with long (≈25 mm) glass fibers, the leading damage mechanisms are matrix micro-cracking and fiber-matrix interface debonding. Those mechanisms are modeled on the microscale and within a Mori-Tanaka homogenization framework. The model can account for arbitrary fiber orientation distributions. Matrix damage is considered as an isotropic stiffness degradation. Interface debonding is modeled via a Weibull interface strength distribution and the inhomogeneous stress distribution on the lateral fiber surface. Hereby, three independent parameters are introduced, that describe the interface strength and damage behavior, respectively. Due to the high non-linearity of the model, the influence of these parameters is not entirely clear. Therefore, the focus of this contribution lies on the variation and discussion of the above mentioned interface parameters.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".