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Spark plasma sintering of fuel meats for U3O8 based dispersion fuels

2024· article· en· W4399797864 on OpenAlex
Anil Prasad, Jayangani I. Ranasinghe, Linu Malakkal, Lukas Bichler, Jerzy A. Szpunar, Charles Liu

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNuclear Engineering and Design · 2024
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsUniversity of SaskatchewanOkanagan University CollegeUniversity of British Columbia, Okanagan CampusCanadian Nuclear Laboratories
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpark plasma sinteringMaterials scienceSPARK (programming language)Nuclear engineeringSinteringDispersion (optics)PlasmaWaste managementMetallurgyEngineeringNuclear physicsComputer sciencePhysics

Abstract

fetched live from OpenAlex

• Dispersion fuels created from spark plasma sintering obey the Master Sintering Curve theory. • Increasing Mo loadings and temperatures increase reduction rate of U 3 O 8 to UO 2. • Relative density increased in Al-U 3 O 8 as Al loading increased. • Mo-U 3 O 8 fuels densified but additional Mo did not affect density. Research and test reactors often use dispersion-type fuel due to its increased thermal conductivity and burn-up capabilities compared to conventional fuel. Al-U 3 O 8 (aluminumtriuranium octaoxide) dispersion fuels have several advantages over their competitors, such as higher service temperature and better stability of oxygen stoichiometry. However, the two-step fabrication of dispersion fuel causes undesirable porosity in cold-pressed fuel meats that is preserved in co-extruded fuel plates. To combat this, spark plasma sintering (SPS) was used for the fabrication of Al-15, 20, and 30 vol% U 3 O 8 and 8 and 12 vol% Mo-U 3 O 8 fuel meats for the Al-U 3 O 8 time. The in situ SPS data was used to construct and validate Master Sintering Curves (MSCs) with accuracies in Al fuels at 0.02 g/cm 3 , and Mo fuels at 0.07 and 0.17 g/cm 3 . The as-sintered fuel meats were characterised using x-ray diffraction (XRD) and scanning electron microscopy (SEM) to understand chemical and physical changes following the SPS process. The pellets exhibited very high relative densities, the U 3 O 8 was observed to undergo reduction to UO 2 .

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.211
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it