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Record W208918126

Criticality of a Neptunium-237 sphere surrounded with highly enriched uranium shells and an iron reflector

2024· paratext· en· W208918126 on OpenAlexaff
Rene Sanchez, David J. Loaiza, David Hayes, Robert Kimpland

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2024
Typeparatext
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsJ. D. Irving (Canada)
Fundersnot available
KeywordsNeptuniumUraniumCriticalityIsotopes of uraniumNeutronActinideRadiochemistryNuclear physicsUranium-235PhysicsChemistryFission
DOInot available

Abstract

fetched live from OpenAlex

An additional experiment has been performed using the recently cast 6-kg {sup 237}Np sphere. The experiment consisted of surrounding the neptunium sphere with highly enriched uranium and an iron reflector. The purpose of the critical experiment is to provide additional criticality data that can be used to validate criticality safety evaluations involving the deposition of neptunium. It is well known that {sup 237}Np is primarily produced by successive neutron capture events in {sup 235}U or through the (n, 2n) reaction in {sup 238}U. These nuclear reactions lead to the production of {sup 237}U, which decays by beta emission into {sup 237}Np. In addition, in the spent fuel, {sup 241}Am decays by alpha emission into {sup 237}Np. Because {sup 237}Np is a threshold fissioner, the best reflectors for critical systems containing neptunium are those materials that exhibit good neutron scattering properties such as low carbon steel (99 wt % Fe). In this experiment, the iron reflector reduced the amount of uranium used in the critical experiment and increased the importance of the neptunium sphere.

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)0.001
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.010
GPT teacher head0.228
Teacher spread0.217 · 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
GenreOther

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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)Same topicNuclear reactor physics and engineeringFrench-language works237,207