Impact of Manufacturing Flaw on Fatigue Damage Development and on Stiffness Variation in Woven Composite Plates
Bibliographic record
Abstract
Abstract Under dynamic loading conditions, damage in a plain weave carbon fiber reinforced polymer (CFRP) composite is a complex and multiscale process, especially in the presence of a manufacturing flaw. In this context, this paper investigates the impact of an inserted flaw on the damage scenario and stiffness degradation over fatigue life. To achieve this objective, a full three-dimensional finite element model (FEM) is developed to evaluate the stress distribution induced by the local defect. Fatigue tests are then performed on two configurations with and without inserted flaws with continuous monitoring by using non-destructive testing (NDT) techniques. The acoustic emission (AE) method is used for damage quantification and source localization while digital image correlation (DIC) and air-coupled ultrasonics (ACU) are applied to evaluate the stiffness degradation. The cross results obtained using these three monitoring techniques provide an insight into the damage process and stiffness degradation in woven composite with a simulated manufacturing flaw.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| 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".