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Record W4210636205 · doi:10.1080/00295639.2021.2003651

A Study of Gamma Heating, Neutron Flux, and Gamma Flux Under Several Reactor Core Conditions in the McMaster Nuclear Reactor

2022· article· en· W4210636205 on OpenAlex

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.

Bibliographic record

VenueNuclear Science and Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNuclear engineeringNeutron fluxBurnupNuclear reactor coreResearch reactorNuclear reactorCore (optical fiber)NeutronMaterials scienceNuclear physicsPhysicsEngineering

Abstract

fetched live from OpenAlex

Changes in the thermal power of a nuclear research reactor will lead to changes in experimental, irradiation, and testing conditions. Consequently, reactor core parameters are inevitably susceptible to changes. One such parameter is gamma heating (GH), which results from gamma interaction with materials. In this work, a gamma thermometer was used to measure GH over the course of 7 operational days and nights. In addition, the Monte Carlo reactor physics code Serpent-2 was used to evaluate the sensitivity of common detection methods for monitoring reactor core parameters such as neutron fluxes, GH, and gamma flux under the following conditions: reactor core power variation, reactor core fuel shuffling, and detector vicinity fuel assembly shuffling. The GH values obtained through measurements and calculations were linearly proportional to the reactor power. In addition, the Serpent-2 code for the McMaster nuclear reactor showed that despite maintaining the reactor power core at the same level, the fuel burnup distribution could alter the studied parameters.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.745

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.217
Teacher spread0.200 · 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