A comparison of the effect of riveting and cold expansion on the strain distribution and fatigue performance of fiber metal laminates
Bibliographic record
Abstract
Fatigue tests carried out on three configurations (unexpanded, cold expanded and riveted) of fiber metal laminate material clearly demonstrated the beneficial effect of riveting compared to cold expansion in zero load transfer joints, for an approximately equivalent level of interference. Digital image correlation was used to measure the in-plane surface strain on cold expanded and riveted coupons during fatigue loading, and for the first time, digital image correlation was combined with pressure sensitive films to measure the strains resulting from the application of the rivet, including those under the rivet head. A comparison of the resultant strain field showed that the application of a rivet significantly reduces the stress concentration at the central hole and is effective in extending fatigue life. Some rivet heads were removed by milling, and the results from subsequent fatigue tests were used together with closed-form calculations to explain the findings of this study. It was concluded that the beneficial effect of riveting was less as a result of interference hole filling on the part of the rivet shank, but more a combination of the effect of interference and compression through the joint thickness.
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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".