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Record W4285493457 · doi:10.1115/1.4055009

Physics Evaluation of Alternative Uranium-Based Oxy-Carbide Annular Fuel Concepts for Potential Use in Compact High-Temperature Gas-Cooled Reactors

2022· article· en· W4285493457 on OpenAlexafffund
Daniel Wojtaszek, Blair P. Bromley

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2022
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsCanadian Nuclear Laboratories
FundersAtomic Energy of Canada Limited
KeywordsNuclear engineeringMaterials scienceBurnupSilicon carbidePelletsEnriched uraniumNeutron transportGraphiteCoolantNeutronUraniumNuclear physicsPhysicsComposite materialMetallurgy

Abstract

fetched live from OpenAlex

Abstract Lattice physics calculations have been carried out to evaluate the performance and safety characteristics of a modified high temperature gas-cooled reactor (HTGR) prismatic fuel block concept, based on the MHTGR-350 benchmark problem. Key changes were to replace the conventional tri-structural isotropic (TRISO)-filled fuel compacts with heterogeneous, multilayer annular fuel pellets made with UCO, ThCO, or (U,Th)CO. These fuel pellets have multiple protective cladding layers of pyrolytic carbon and silicon carbide, which will give it robust qualities. With the increased loading of U-235 in the fuel block, it was necessary to replace up to 78 fuel holes and 42 coolant holes with a hydrogen-based moderator (7LiH), in order to ensure a thermal neutron energy spectrum in the lattice. Calculation results demonstrate that the modified fuel concept has several advantages and some challenges relative to the conventional MHTGR-350 design concept. With the increased uranium loading and the reduced neutron leakage due the use of 7LiH moderator rods, higher burnup levels and lower natural uranium consumption levels can be achieved with the same level of uranium enrichment. In addition, the expected fuel residence time increased by a factor of 20 or more, making such a concept very attractive for use in small, modular, “nuclear battery” HTGRs that would only need to be fueled once. Calculation results for the current concept indicate positive graphite and hydrogen moderator temperature coefficients, and further modifications will be required to ensure a negative power coefficient of reactivity.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.246
Teacher spread0.232 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2022
Admission routes2
Has abstractyes

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