IN SITU MEASUREMENT OF LOW CONCENTRATIONS OF CHROMIUM IN CARBON STEEL PIPING FOR FLOW-ACCELERATED CORROSION MANAGEMENT
Bibliographic record
Abstract
Low concentrations of chromium in carbon steel piping need to be measured with sufficient accuracy as these data are used to determine flow-accelerated corrosion (FAC) inspection locations in nuclear power plant (NPP) piping. The FAC wall thinning rate is very sensitive to chromium between 0.03 and 0.1 wt% according to NPP industry models used to guide inspections. Hand-held portable X-ray fluorescence (XRF) instruments are used as a nondestructive, in-field, method to determine the concentration of chromium in NPP carbon steel piping. However, measuring such low chromium concentrations involves applying this XRF technology at, or close to, its capability limits. Furthermore, this technology is being applied to the outer surface of an installed pipe, and may not yield a representative measurement of the chromium in the bare metal without adequate surface preparation.The present work provides a quantitative assessment of the performance of commercially available XRF analyzers to yield measurements that are...
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".