Experimental and numerical investigation of the effect of gaps on fatigue behavior of unidirectional carbon/epoxy automated fiber placement laminates
Bibliographic record
Abstract
Automated fiber placement (AFP) process provides high potential to repeatability and flexibility required for manufacturing of complex parts in many industries. Performance of such parts can be influenced by AFP manufacturing induced defects such as gaps and overlaps. In this work, the effect of gaps on fatigue behavior of unidirectional carbon/epoxy laminates was investigated. Tension–tension fatigue tests were conducted on defected samples and compared to reference samples free from defects. Infrared thermography technique was used for monitoring of damage propagation during fatigue loading. Moreover, a fatigue progressive damage model (FPDM) was developed and applied to laminates containing gaps to predict fatigue damage progression and failure. The experimental results revealed that the effect of gaps depends on the maximum applied stress during fatigue. The higher is the applied stress, the higher is the reduction in fatigue life. Good agreement was found between the results of fatigue life prediction from the FPDM and the experimental results for defected specimens.
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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".