Damage created by abrasive waterjet and conventional drilling in open-hole and assembled 3D interlock woven carbon fiber-reinforced plastic composites examined by fatigue testing and linear regression analysis
Bibliographic record
Abstract
• Assessing the influence of secondary machining processes on the fatigue behavior. • Fatigue damage description by thermal imaging and acoustic emission. • Modelling of the minimal strain for both open-hole and assembled samples. • Prediction of the model parameters with hole characteristics. With the advent of 3D woven composites, delamination is no longer a major concern when drilling holes in composite structures, but the effects of the other hole characteristics must be assessed. Here, the abrasive waterjet is compared with a conventional cutting tool to reveal their damage characteristics and assess their influence on the mechanical properties of the composites. Tensile failure is observed in open-hole samples and shear failure is preceded by bearing damage in assembled samples. The magnitude of the damage is estimated using acoustic emission and thermal imaging. The results show that roughness plays an important role in damage initiation for both open-hole and assembled loading. Thus, the proposed model helps identify the differences in the degradation of mechanical properties between the two drilling methods.
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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 | 0.000 | 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".