Progress Toward Instrumented Nuclear Fuel Pellets Using Additive Manufacturing
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
Instrumented fuel pellets offer the potential to be used for the real-time measurement of fuel properties within emerging nuclear reactor designs. The use of three-dimensional (3D) printed nuclear fuel pellets is one approach to accommodate instrumentation. The 3D printing of nuclear materials requires that a printable feedstock material be developed for use with a specific additive manufacturing technology. In the present work, an iterative design process was used to formulate a filament containing yttria-stabilized zirconia, as a surrogate for uranium dioxide, that is suitable for use with fused filament fabrication 3D printers.The components of the filament and their amounts, the printing parameters, and the debinding process were varied to produce an optimized printing procedure. A final five-component formulation containing 50.0 ± 0.1 vol % organic material was developed. With this formulation, the requirement to print to a 16-mm wall thickness, consistent with CANDU pellet dimensions rather than the maximum of 4 mm reported previously, resulted in numerous production failures. Ultimately, the manipulation of specific printer parameters to form microchannels within the pellet during printing resulted in pellets consistent with the target criteria. In the final set of eight pellets, seven pellets met the density criterion of 95% theoretical density, with an average density of 96.2 ± 1.0% of theoretical density.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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