X-ray Computed Tomography for Nuclear Power Plant Maintenance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As part of the scheduled maintenance of nuclear power plants, specialist tools are deployed into the reactor core, for example to inspect the moderator. It is imperative that these tools operate correctly, and that no element of the tool remains in the reactor when the reactor resumes operation. The current processes for ensuring this are hugely labour intensive, and hence costly, involving a full teardown before and after deployment. This paper describes the development of a novel X-ray Computed Tomography (CT) system and workflow for ensuring the integrity of specialist reactor tools without the need for disassembly. The system hardware must be able to deal with the challenge of tools that are up to 6 metres in length and contain a significant amount of dense componentry. On the other hand, the system software must be able to confirm the correct and comprehensive assembly of the tool based on the obtained CT scan, and despite numerous potential, but benign, differences in the tool appearance. The presented approach overcomes both challenges: the hardware uses a gantry design with a high-powered X-ray source (see Fig. 1), the software employs a machine learning implementation.
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.
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 | 0.001 |
| 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 it