Evaluation of Two Low-Constraint Toughness Test Methods in a Single Specimen
Bibliographic record
Abstract
In previous studies, the single- and double-clip gauge methods were successfully consolidated in a single-edge notched tension (SE(T)) single specimen so that crack tip opening displacement (CTOD) values obtained from both SE(T) methods could be compared under identical test conditions. The current study investigated the effect of unloading compliance crack size equations on resistance curves obtained from both gauging methods combined in a single specimen. It was found that the unloading compliance crack size equations of Cravero and Ruggieri and the single clip gauge method predict crack sizes well within approximately 2% error in average. Two CTOD-resistance curves obtained from both gauging methods produce approximately the same results until peak loads, and thereafter the curves deviate. The results obtained from the double clip gauge method are consistently higher than those from the single clip gauge, although the difference between two resistance curves is reduced when the same unloading compliance crack size prediction procedure is used. This observation is very important within the framework of engineering critical assessment (ECA) and defect assessment procedures. An “apparent” higher resistance curve will generate larger tolerable defects thereby reducing the conservatism of an ECA analysis.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".