A Novel Technique for Addition of Hydrogen to Zirconium Alloys: Mechanical Hydrogen Ingress and Its Applications
Bibliographic record
Abstract
This thesis outlines the development of the Mechanical Hydrogen Ingress (MHI) technique, which is a novel method of adding hydrogen to zirconium. The method was shown to have an uncertainty of 2% of the predicted hydrogen concentration plus 1.4 ppm (i.e. a sample with 50 ppm would have an uncertainty of 0.02(50) + 1.4 = 2.4 ppm). The MHI technique was used to add a known amount of hydrogen to a low-hydrogen zirconium sample in order to determine the initial hydrogen concentration using the differential scanning calorimetry technique, to determine the hydrogen solubility in copper, and to add hydrogen to zirconium at temperatures below 350 C to support life-extension experiments on irradiated ex-service CANDU pressure tubes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".