A pulsed eddy current probe for inspection of support plates from within Alloy-800 steam generator tubes
Bibliographic record
Abstract
Support plate degradation and fouling in nuclear steam generators (SGs) can lead to SG tube corrosion and loss of efficiency. Inspection and monitoring of these conditions can be integrated with preventive maintenance programs, thereby advancing station-life management processes. A prototype pulsed eddy current (PEC) probe, targeting inspection issues associated with SG tubes in SS410 tube support plate structures, has been developed using commercial finite element (FE) software. FE modeling was used to identify appropriate driver and pickup coil configurations for optimum sensitivity to changes in gap and offset for Alloy-800 SG tubes passing through 25 mm thick SS410 support plates. Experimental measurements using a probe that was manufactured based on the modeled configuration, were used to confirm the sensitivity of differential PEC signals to changes in relative position of the tube within the tube support plate holes. Models investigated the effect of shift and tilt of tube with respect to hole centers. Near hole centers and for small shifts, modeled signal amplitudes from the differentially connected coil pairs were observed to change linearly with tube shift. This was in agreement with experimentally measured TEC coil response. The work paves the way for development of a system targeting the inspection and evaluation of support plate structures in steam generators.
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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 | 0.001 | 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".