A Container Based on Polymer Composite Materials for the Ultimate Disposal of Spent Nuclear Fuel and Radioactive Waste
Bibliographic record
Abstract
This work demonstrates the feasibility of fabricating containers for the ultimate disposal of spent nuclear reactor fuel and high-level radioactive waste using polymer-based composite materials. The study has identified three engineering polymers suitable for this demanding application: polyetheretherketone (PEEK), polyetherimide (PEI), and polysulfone (PSU). PEEK and PEI are used as composite materials components, with 30% carbon and glass fiber, respectively, whereas PSU is used as a virgin (nonreinforced) material. The rationale for the choice of polymer composites comes from their superior physical, mechanical, and chemical performance, in addition to their economical advantage. In particular, they display better resistance to corrosion and to structural weakening from irradiation.Scaled-down containers were fabricated using these materials. They were subjected to a battery of tests under conditions similar to those expected for the disposal environment of actual radioactive waste–filled containers. In particular, the container models were irradiated in the pool of a SLOWPOKE-2 nuclear research reactor, accumulating doses from a mixed-radiation field that were comparable to total doses accumulated over 500 yr at a deep underground waste repository site. Mechanical compression tests mimicked the large hydrostatic pressures incurred from granite rock at depths of some 1000 m within the Canadian Shield.Several composite materials were tested, and for the three engineering materials listed above, some of the results are as follows:1. variation in elastic modulus following a 28.9-kGy radiation dose—PEEK, −6.66% ± 0.47%; PEI, +5.63% ± 0.23%; PSU, +3.16% ± 0.13%2. compression results for the irradiated container models and load at break and strain—PEEK, 2.152 MPa and 1178 μmm-1; PEI, 1.236 MPa and 1171 μmm-1; PSU, 1.190 MPa and 2576 μmm-1, respectively3. cost analysis—costs for the fabrication of the prototype containers based on PEEK, $273610; PEI, $145920; PSU, $257460.The work also provided insight into potential problems in the fabrication of full-sized containers and into the best fabrication methods to adopt. The method of filament winding would be more appropriate for the PEEK- and the PEI-based composite materials, while blow forming would be the preferred method for the PSU material. In particular, this research could determine the best way to design the container lids.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".